1. Introduction¶
Bike sharing companies are on the rise since years and are very popular in the metropolitan areas around the world. Reliability, availability and user-friendly processes are important aspects of the business. To provide constant quality and availabilty to the customer it is crucial to understand the significant factors of demand. Since every bike needs maintenance from time to time you better know when you can spare some of your capacity and when it is highly demanded.
The following notebook provides:
- a general analysis of the Bike Sharing Dataset from this website: https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset
- a prediction model for the utilization of bikes per hour with insights about the factors and main effects
- an operative function to predict the utilization for future days.
With the help of the tool provided, managers are able to plan their maintenance phases and investments more efficiently.
The problem with regression models which estimate mean values is that approximately half of all cases you will be above the estimates. To provide a high level of availability and reliability for the customer it is benificial to use upper bounds of estimated utilization hence the chosen regression method is a quantile regression model. This product allows the company to prepare for upcoming demands with respect to a desired level of reliability (e.g. 90%).
It will turn out that the most significant effect comes from customers using bikes in the morning and afterwork hours on workdays. It is recommended to plan with respect to these critical moments to obtain a high level of customer satisfaction. Ending up with no bike in the morning hours can put customers into difficult situations with a high risk of bad reputation for the company - a good ground for competitors.
2. Import libraries, load and transform data¶
In [1]:
import numpy as np
import pandas as pd
import math as ma
import matplotlib.pyplot as plt
% matplotlib inline
from matplotlib import mlab
import datetime
The data and attribute info from the website¶
Attribute Information:
Both hour.csv and day.csv have the following fields, except hr which is not available in day.csv
- instant: record index
- dteday : date
- season : season (1:springer, 2:summer, 3:fall, 4:winter)
- yr : year (0: 2011, 1:2012)
- mnth : month ( 1 to 12)
- hr : hour (0 to 23)
- holiday : weather day is holiday or not (extracted from [Web Link])
- weekday : day of the week
- workingday : if day is neither weekend nor holiday is 1, otherwise is 0.
- weathersit :
- Clear, Few clouds, Partly cloudy, Partly cloudy
- Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist
- Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds
- Heavy Rain + Ice Pallets + Thunderstorm + Mist, Snow + Fog
- temp : Normalized temperature in Celsius. The values are derived via (t-t_min)/(t_max-t_min), t_min=-8, t_max=+39 (only in hourly scale)
- atemp: Normalized feeling temperature in Celsius. The values are derived via (t-t_min)/(t_max-t_min), t_min=-16, t_max=+50 (only in hourly scale)
- hum: Normalized humidity. The values are divided to 100 (max)
- windspeed: Normalized wind speed. The values are divided to 67 (max)
- casual: count of casual users
- registered: count of registered users
- cnt: count of total rental bikes including both casual and registered
In [ ]:
In [2]:
day = pd.read_csv("day.csv", sep = ',')
hour = pd.read_csv("hour.csv", sep = ',')
day['dteday'] = pd.to_datetime(day['dteday'])
hour['dteday'] = pd.to_datetime(hour['dteday'])
hour['timestamp'] = pd.to_datetime(hour['dteday']) + hour['hr'].astype('timedelta64[h]')
hour['time'] = hour['dteday'] - hour['dteday'].min() # prepare timestamp and count days for prediction
hour['days'] = hour['time'].dt.days
3. A look into the data¶
First thoughts¶
The dataset contains no missing values, appears to be very clean, has standardized measures and no obvious outliers. I had no doubt that it is a ready to use data set.
Let us have a look at the time series of the utilization ('cnt' variable) per day and per hour.
In [3]:
count_by_day = day[['dteday','cnt']].set_index('dteday')
plt.figure()
count_by_day.plot(figsize=(15,5))
plt.legend(loc='best')
Out[3]:
<matplotlib.legend.Legend at 0x1130d7358>
<matplotlib.figure.Figure at 0x10a7cd7f0>
In [4]:
count_by_hour = hour[['timestamp','cnt']].set_index('timestamp')
plt.figure()
count_by_hour.plot(figsize=(18,10))
plt.legend(loc='best')
Out[4]:
<matplotlib.legend.Legend at 0x11bf871d0>
<matplotlib.figure.Figure at 0x1222352e8>
Thoughts on the time series¶
Both resolutions of the utilization time series show similar behaviour. There is periodicity over the year. In summer time more bikes are used than in winter time. It is an increasing and then decreasing progress. Very important here is that the level of Jan 2011 is almost the same as in Dec 2011, Jan 2012 and Dec 2012. The plateau during summer 2012 is higher than in 2011. I conclude that there might have been an investment in beginning of 2012 and the capacity has been scaled up by a certain factor. I would rather not speak of a significant increasing trend over time, and the linear models I tried did not show a high regression coefficient for the time aspect. So let us further assume that changes of the system like investments explain the difference between time periods. Since there is no information in the data about the total amount of bikes available we can only speculate about this. The absolute maximum values per year could give us some estimate which supports the theory. All changes of the system should be taken into account when forecasting and should be tracked by (categorical) indicators in the data to estimate a proper mean for the new time period.
The top 20 days¶
- All top 20 days are from year 2012
- Top days can occur in every season but half of the top 20 days are from autumn.
- No holiday is under the top 20 days.
- Top days can be working days and not.
- Top 20 days are never with bad weather conditions.
In [5]:
day.sort_values(by = ['cnt'], ascending = False).head(20)
Out[5]:
| instant | dteday | season | yr | mnth | holiday | weekday | workingday | weathersit | temp | atemp | hum | windspeed | casual | registered | cnt | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 623 | 624 | 2012-09-15 | 3 | 1 | 9 | 0 | 6 | 0 | 1 | 0.608333 | 0.585867 | 0.501667 | 0.247521 | 3160 | 5554 | 8714 |
| 637 | 638 | 2012-09-29 | 4 | 1 | 9 | 0 | 6 | 0 | 1 | 0.542500 | 0.530296 | 0.542917 | 0.227604 | 2589 | 5966 | 8555 |
| 630 | 631 | 2012-09-22 | 3 | 1 | 9 | 0 | 6 | 0 | 1 | 0.650000 | 0.610488 | 0.646667 | 0.283583 | 2512 | 5883 | 8395 |
| 447 | 448 | 2012-03-23 | 2 | 1 | 3 | 0 | 5 | 1 | 2 | 0.601667 | 0.570067 | 0.694167 | 0.116300 | 2469 | 5893 | 8362 |
| 504 | 505 | 2012-05-19 | 2 | 1 | 5 | 0 | 6 | 0 | 1 | 0.600000 | 0.566908 | 0.456250 | 0.083975 | 3410 | 4884 | 8294 |
| 617 | 618 | 2012-09-09 | 3 | 1 | 9 | 0 | 0 | 0 | 1 | 0.610000 | 0.578925 | 0.547500 | 0.224496 | 2570 | 5657 | 8227 |
| 571 | 572 | 2012-07-25 | 3 | 1 | 7 | 0 | 3 | 1 | 1 | 0.724167 | 0.654054 | 0.450000 | 0.164800 | 1383 | 6790 | 8173 |
| 629 | 630 | 2012-09-21 | 3 | 1 | 9 | 0 | 5 | 1 | 1 | 0.599167 | 0.571971 | 0.668750 | 0.154229 | 1250 | 6917 | 8167 |
| 643 | 644 | 2012-10-05 | 4 | 1 | 10 | 0 | 5 | 1 | 1 | 0.615000 | 0.580187 | 0.627500 | 0.106350 | 1516 | 6640 | 8156 |
| 518 | 519 | 2012-06-02 | 2 | 1 | 6 | 0 | 6 | 0 | 1 | 0.583333 | 0.566288 | 0.549167 | 0.186562 | 2795 | 5325 | 8120 |
| 658 | 659 | 2012-10-20 | 4 | 1 | 10 | 0 | 6 | 0 | 1 | 0.484167 | 0.472842 | 0.572917 | 0.117537 | 2806 | 5284 | 8090 |
| 622 | 623 | 2012-09-14 | 3 | 1 | 9 | 0 | 5 | 1 | 1 | 0.633333 | 0.594083 | 0.672500 | 0.103863 | 1379 | 6630 | 8009 |
| 644 | 645 | 2012-10-06 | 4 | 1 | 10 | 0 | 6 | 0 | 1 | 0.554167 | 0.538521 | 0.664167 | 0.268025 | 3031 | 4934 | 7965 |
| 631 | 632 | 2012-09-23 | 4 | 1 | 9 | 0 | 0 | 0 | 1 | 0.529167 | 0.518933 | 0.467083 | 0.223258 | 2454 | 5453 | 7907 |
| 620 | 621 | 2012-09-12 | 3 | 1 | 9 | 0 | 3 | 1 | 1 | 0.599167 | 0.570075 | 0.577083 | 0.131846 | 1050 | 6820 | 7870 |
| 595 | 596 | 2012-08-18 | 3 | 1 | 8 | 0 | 6 | 0 | 1 | 0.678333 | 0.618071 | 0.603333 | 0.177867 | 2827 | 5038 | 7865 |
| 665 | 666 | 2012-10-27 | 4 | 1 | 10 | 0 | 6 | 0 | 2 | 0.530000 | 0.515133 | 0.720000 | 0.235692 | 2643 | 5209 | 7852 |
| 441 | 442 | 2012-03-17 | 1 | 1 | 3 | 0 | 6 | 0 | 2 | 0.514167 | 0.505046 | 0.755833 | 0.110704 | 3155 | 4681 | 7836 |
| 621 | 622 | 2012-09-13 | 3 | 1 | 9 | 0 | 4 | 1 | 1 | 0.612500 | 0.579558 | 0.637083 | 0.082721 | 1054 | 6750 | 7804 |
| 619 | 620 | 2012-09-11 | 3 | 1 | 9 | 0 | 2 | 1 | 1 | 0.577500 | 0.554292 | 0.520000 | 0.092054 | 1070 | 6697 | 7767 |
Lets consider the distribution of utilization (per day and per hour) over the years and some categorical variables.¶
In [6]:
fig, axes = plt.subplots(2,3, figsize=(15,10)) # create figure and axes
day.boxplot(column='cnt',by=['yr','season'], ax=axes.flatten()[0] )
day.boxplot(column='cnt',by=['yr','mnth'], ax=axes.flatten()[1])
day.boxplot(column='cnt',by=['yr','weekday'], ax=axes.flatten()[2])
day.boxplot(column='cnt',by=['yr','workingday'], ax=axes.flatten()[3])
day.boxplot(column='cnt',by=['yr','holiday'], ax=axes.flatten()[4])
day.boxplot(column='cnt',by=['yr','weathersit'], ax=axes.flatten()[5])
#fig.delaxes(axes[1,1]) # remove empty subplot
plt.tight_layout()
plt.show()
thoughts¶
Boxplots from left to right row-wise:
spring is the season with the lowest daily counts for each year and summer is the highest. The relations between the seasons is alike for both years.
The month seems to give a better information than the season. (This graph looks like there is a positive trend over time, but the linear models did not confirm it)
- The days of the week could play a role, especially in year 2012. But it is not strong.
- Workingday information is weak with respect of daily total utilization.
- Holidays tend to have a slightly lower daily utilization compared to non-holidays.
- The worse the weather situation the lower the daily utilization.
Next step: Have a look at the data per hour and focus on the year 2012 only since the overall behaviour is very similar.¶
Top 20 hours¶
- All of them are form 2012
- Season is most likely autumn or early winter
- Top 20 hours are always on working days with good weather conditions during early after work.
In [7]:
hour.sort_values(by = ['cnt'], ascending = False).head(20)
Out[7]:
| instant | dteday | season | yr | mnth | hr | holiday | weekday | workingday | weathersit | temp | atemp | hum | windspeed | casual | registered | cnt | timestamp | time | days | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 14773 | 14774 | 2012-09-12 | 3 | 1 | 9 | 18 | 0 | 3 | 1 | 1 | 0.66 | 0.6212 | 0.44 | 0.2537 | 91 | 886 | 977 | 2012-09-12 18:00:00 | 620 days | 620 |
| 14964 | 14965 | 2012-09-20 | 3 | 1 | 9 | 17 | 0 | 4 | 1 | 1 | 0.64 | 0.6212 | 0.50 | 0.2239 | 91 | 885 | 976 | 2012-09-20 17:00:00 | 628 days | 628 |
| 14748 | 14749 | 2012-09-11 | 3 | 1 | 9 | 17 | 0 | 2 | 1 | 1 | 0.70 | 0.6364 | 0.28 | 0.0000 | 168 | 802 | 970 | 2012-09-11 17:00:00 | 619 days | 619 |
| 14725 | 14726 | 2012-09-10 | 3 | 1 | 9 | 18 | 0 | 1 | 1 | 1 | 0.62 | 0.6212 | 0.35 | 0.2985 | 111 | 857 | 968 | 2012-09-10 18:00:00 | 618 days | 618 |
| 15084 | 15085 | 2012-09-25 | 4 | 1 | 9 | 17 | 0 | 2 | 1 | 1 | 0.66 | 0.6212 | 0.39 | 0.2836 | 107 | 860 | 967 | 2012-09-25 17:00:00 | 633 days | 633 |
| 15780 | 15781 | 2012-10-24 | 4 | 1 | 10 | 17 | 0 | 3 | 1 | 1 | 0.66 | 0.6212 | 0.47 | 0.0000 | 87 | 876 | 963 | 2012-10-24 17:00:00 | 662 days | 662 |
| 10622 | 10623 | 2012-03-23 | 2 | 1 | 3 | 17 | 0 | 5 | 1 | 2 | 0.72 | 0.6515 | 0.42 | 0.1642 | 264 | 693 | 957 | 2012-03-23 17:00:00 | 447 days | 447 |
| 15108 | 15109 | 2012-09-26 | 4 | 1 | 9 | 17 | 0 | 3 | 1 | 1 | 0.74 | 0.6667 | 0.48 | 0.2985 | 77 | 876 | 953 | 2012-09-26 17:00:00 | 634 days | 634 |
| 15444 | 15445 | 2012-10-10 | 4 | 1 | 10 | 17 | 0 | 3 | 1 | 1 | 0.58 | 0.5455 | 0.43 | 0.2239 | 91 | 857 | 948 | 2012-10-10 17:00:00 | 648 days | 648 |
| 15588 | 15589 | 2012-10-16 | 4 | 1 | 10 | 17 | 0 | 2 | 1 | 1 | 0.52 | 0.5000 | 0.39 | 0.1940 | 104 | 839 | 943 | 2012-10-16 17:00:00 | 654 days | 654 |
| 14293 | 14294 | 2012-08-23 | 3 | 1 | 8 | 18 | 0 | 4 | 1 | 1 | 0.74 | 0.6667 | 0.48 | 0.2239 | 130 | 811 | 941 | 2012-08-23 18:00:00 | 600 days | 600 |
| 15756 | 15757 | 2012-10-23 | 4 | 1 | 10 | 17 | 0 | 2 | 1 | 1 | 0.68 | 0.6364 | 0.41 | 0.0000 | 67 | 871 | 938 | 2012-10-23 17:00:00 | 661 days | 661 |
| 14772 | 14773 | 2012-09-12 | 3 | 1 | 9 | 17 | 0 | 3 | 1 | 1 | 0.70 | 0.6364 | 0.41 | 0.2985 | 114 | 811 | 925 | 2012-09-12 17:00:00 | 620 days | 620 |
| 15732 | 15733 | 2012-10-22 | 4 | 1 | 10 | 17 | 0 | 1 | 1 | 1 | 0.62 | 0.6212 | 0.33 | 0.1045 | 84 | 838 | 922 | 2012-10-22 17:00:00 | 660 days | 660 |
| 15276 | 15277 | 2012-10-03 | 4 | 1 | 10 | 17 | 0 | 3 | 1 | 1 | 0.70 | 0.6515 | 0.65 | 0.0000 | 84 | 833 | 917 | 2012-10-03 17:00:00 | 641 days | 641 |
| 13596 | 13597 | 2012-07-25 | 3 | 1 | 7 | 17 | 0 | 3 | 1 | 1 | 0.80 | 0.6970 | 0.31 | 0.0000 | 130 | 783 | 913 | 2012-07-25 17:00:00 | 571 days | 571 |
| 15132 | 15133 | 2012-09-27 | 4 | 1 | 9 | 17 | 0 | 4 | 1 | 2 | 0.66 | 0.6212 | 0.69 | 0.2985 | 87 | 818 | 905 | 2012-09-27 17:00:00 | 635 days | 635 |
| 15300 | 15301 | 2012-10-04 | 4 | 1 | 10 | 17 | 0 | 4 | 1 | 1 | 0.70 | 0.6515 | 0.51 | 0.2239 | 112 | 789 | 901 | 2012-10-04 17:00:00 | 642 days | 642 |
| 15324 | 15325 | 2012-10-05 | 4 | 1 | 10 | 17 | 0 | 5 | 1 | 1 | 0.70 | 0.6364 | 0.42 | 0.1642 | 158 | 742 | 900 | 2012-10-05 17:00:00 | 643 days | 643 |
| 14965 | 14966 | 2012-09-20 | 3 | 1 | 9 | 18 | 0 | 4 | 1 | 1 | 0.60 | 0.6212 | 0.56 | 0.2537 | 119 | 781 | 900 | 2012-09-20 18:00:00 | 628 days | 628 |
In [8]:
fig, axes = plt.subplots(2,2, figsize=(15,10)) # create figure and axes
hour[hour['yr']==1].boxplot(column='cnt',by=['hr'], ax=axes.flatten()[0])
hour[hour['yr']==1].boxplot(column='cnt',by=['season','hr'], ax=axes.flatten()[1])
hour[hour['yr']==1].boxplot(column='cnt',by=['weekday','hr'], ax=axes.flatten()[2])
hour[hour['yr']==1].boxplot(column='cnt',by=['workingday','hr'], ax=axes.flatten()[3])
#hour.boxplot(column='cnt',by=['yr','holiday'], ax=axes.flatten()[4])
#hour.boxplot(column='cnt',by=['yr','weathersit'], ax=axes.flatten()[5])
#fig.delaxes(axes[1,1]) # remove empty subplot
plt.tight_layout()
plt.show()
thoughts¶
Boxplots from left to right row-wise:
Morning and afternoon hours have significant peaks over the day. Night and afternoon hours have an interesting ammount of outliers.
The peaks remain for every season of the year. This is a characteristic profile.
- The weekday has some impact on the hourly profile. On Saturdays and Sundays people use bikes around noon. This also explains the outliers in the first figure. Eureka!
- The comparison of working days and non-working days is consistent with the former observations and supports the theory that people tend to use bikes more frequently at noon and in the late night on free days.
In [12]:
# Split utilization into regsitered and casual users
fig, axes = plt.subplots(1,2 , figsize=(15,5)) # create figure and axes
hour[hour['yr']==1].boxplot(column='registered',by=['workingday','hr'] , figsize=(7,5), ax=axes.flatten()[0])
hour[hour['yr']==1].boxplot(column='casual',by=['workingday','hr'] , figsize=(7,5), ax=axes.flatten()[1] )
#fig.delaxes(axes[1,1]) # remove empty subplot
plt.tight_layout()
plt.show()
conclusions¶
On workingdays people use bikes to get to and from work where on weekends (and holidays) people use them more during noon and late night hours. Other factors like weather and time of the year affect the baseline of the utilization since a proportion of people might avoid biking in winter and bad weather in general.
Now let us have a look at the remeining variables and their pairwise relation¶
In [9]:
from pandas.tools.plotting import scatter_matrix
scatter_matrix(day[['cnt','temp','atemp','windspeed','hum','mnth','season']],
alpha=0.2, figsize=(15, 15), diagonal='kde')
Out[9]:
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Discussion of the plots above¶
Some variables are redundant:
If you know which month you are then you exactly know which season it is, you have a good idea about the temperature, you know nothing about windspeed or humidity but it has some impact on the utilization.
There is also a high correlation between the temperature and the felt-temperature, so you definetly need only one of them. Since the temperature is easier to get from weather apps, we drop the 'atmep' variable.
To make it short: The linear OLS regression showed evidence of multicollinearity when combining the mentioned variables into one model and in the end the simplest predictos already gave you a good model fit. Using more precise information only had marginal effect on explaining the response. Hence the following model will only respect the most significant variables.
4. Prediction model and interpretation¶
The choice of a model¶
- After peeking into the data I first tryed a linear OLS regression on the daily dataset and was surprised by the high value of R-squared which was around 0.96 . Since the model had evidence of multicollinearity I removed predictors obviously being redundant as seen in the former section.
- The OLS model based on the daily data had a lower R-squared so at this point I had to decide whether I try to tune it with the help of different machine learning techniques or rather find a good business need first and then make use out of the linear regression.
- A further observation of the effects in the linear OLS model convinced me to keep it simple since the most significant factors were easy to understand and easy to provide as data in terms of forecasting. (e.g. it is more likely to predict the weathersituation for the next week instead of the correct weather parameters as temperature, humidity and windspeed) Further a parametric model is easy to interpret and gives you quantified results which directly lead to business insights.
- From my own experience with bike sharing products I concluded that a quantile regression might finally be a worthy tool to fulfill customer needs and help planers provide high availability standards on the market.
A lot of different combinations of the predictors have been considered and this is somehow the best compromise I found in terms of R-squared and multicollinearity. Especially the presence of the number of days from 2011-01-01 had very little contribution to R-squared and lead to multicollinearity within the predictors. The combination of workingday and hr has good explanation and is adjusted by mnth for high peaks during main season. I find the following model very easy to interpret and beneficial for a business case. The "formula" representation in the statsmodels module makes it very easy to work with models and categorical data.
In [10]:
import statsmodels.api as sm
import statsmodels.formula.api as smf
mod = smf.ols(formula='cnt ~ C(hr) + C(yr) + C(mnth) + C(workingday) + C(weathersit) + C(mnth):C(workingday):C(hr)', data=hour)
OLS_model = mod.fit()
hour['cnt_OLS'] = OLS_model.predict(hour) # writing the predicted values into the dataset
print(OLS_model.summary())
OLS Regression Results
==============================================================================
Dep. Variable: cnt R-squared: 0.849
Model: OLS Adj. R-squared: 0.844
Method: Least Squares F-statistic: 163.0
Date: Fri, 28 Sep 2018 Prob (F-statistic): 0.00
Time: 11:50:42 Log-Likelihood: -98622.
No. Observations: 17379 AIC: 1.984e+05
Df Residuals: 16799 BIC: 2.029e+05
Df Model: 579
Covariance Type: nonrobust
==============================================================================================================
coef std err t P>|t| [95.0% Conf. Int.]
--------------------------------------------------------------------------------------------------------------
Intercept 1.6439 15.303 0.107 0.914 -28.351 31.639
C(hr)[T.1] -1.8438 21.711 -0.085 0.932 -44.400 40.712
C(hr)[T.2] -9.2437 21.626 -0.427 0.669 -51.634 33.146
C(hr)[T.3] -16.0037 21.882 -0.731 0.465 -58.895 26.888
C(hr)[T.4] -27.3949 21.883 -1.252 0.211 -70.287 15.497
C(hr)[T.5] -33.5820 22.465 -1.495 0.135 -77.616 10.453
C(hr)[T.6] -28.5326 21.884 -1.304 0.192 -71.427 14.362
C(hr)[T.7] -25.3873 21.626 -1.174 0.240 -67.776 17.002
C(hr)[T.8] 2.0242 21.625 0.094 0.925 -40.364 44.412
C(hr)[T.9] 21.7418 21.625 1.005 0.315 -20.646 64.130
C(hr)[T.10] 62.6272 21.627 2.896 0.004 20.236 105.019
C(hr)[T.11] 94.6127 21.626 4.375 0.000 52.224 137.002
C(hr)[T.12] 123.0121 21.626 5.688 0.000 80.622 165.402
C(hr)[T.13] 131.5121 21.626 6.081 0.000 89.122 173.902
C(hr)[T.14] 137.9787 21.625 6.380 0.000 95.591 180.367
C(hr)[T.15] 143.6605 21.625 6.643 0.000 101.272 186.049
C(hr)[T.16] 131.3018 21.626 6.071 0.000 88.912 173.692
C(hr)[T.17] 86.8685 21.626 4.017 0.000 44.479 129.258
C(hr)[T.18] 81.1320 21.626 3.752 0.000 38.743 123.522
C(hr)[T.19] 63.2398 21.627 2.924 0.003 20.848 105.631
C(hr)[T.20] 35.5769 21.626 1.645 0.100 -6.812 77.966
C(hr)[T.21] 21.5314 21.626 0.996 0.319 -20.857 63.920
C(hr)[T.22] 8.5818 21.627 0.397 0.692 -33.810 50.973
C(hr)[T.23] 1.7133 21.626 0.079 0.937 -40.676 44.102
C(yr)[T.1] 91.4260 1.090 83.890 0.000 89.290 93.562
C(mnth)[T.2] 11.2726 22.796 0.494 0.621 -33.411 55.956
C(mnth)[T.3] 28.8747 23.165 1.246 0.213 -16.531 74.280
C(mnth)[T.4] 36.1416 22.164 1.631 0.103 -7.303 79.586
C(mnth)[T.5] 70.0385 22.463 3.118 0.002 26.008 114.069
C(mnth)[T.6] 81.2795 23.161 3.509 0.000 35.882 126.677
C(mnth)[T.7] 102.7176 21.881 4.694 0.000 59.828 145.607
C(mnth)[T.8] 88.3297 24.017 3.678 0.000 41.254 135.405
C(mnth)[T.9] 86.5197 22.160 3.904 0.000 43.083 129.956
C(mnth)[T.10] 80.6702 22.161 3.640 0.000 37.233 124.107
C(mnth)[T.11] 27.2591 22.159 1.230 0.219 -16.176 70.694
C(mnth)[T.12] 25.7906 21.884 1.178 0.239 -17.105 68.686
C(workingday)[T.1] -22.5942 19.220 -1.176 0.240 -60.268 15.079
C(weathersit)[T.2] -19.1598 1.296 -14.784 0.000 -21.700 -16.620
C(weathersit)[T.3] -95.3722 2.059 -46.321 0.000 -99.408 -91.336
C(weathersit)[T.4] -94.1692 42.091 -2.237 0.025 -176.671 -11.667
C(mnth)[T.2]:C(hr)[T.1] -5.8666 32.295 -0.182 0.856 -69.169 57.436
C(mnth)[T.3]:C(hr)[T.1] -6.5679 32.811 -0.200 0.841 -70.881 57.745
C(mnth)[T.4]:C(hr)[T.1] -22.2828 31.398 -0.710 0.478 -83.826 39.260
C(mnth)[T.5]:C(hr)[T.1] -25.6215 31.825 -0.805 0.421 -88.002 36.759
C(mnth)[T.6]:C(hr)[T.1] -22.7162 32.810 -0.692 0.489 -87.028 41.595
C(mnth)[T.7]:C(hr)[T.1] -41.0558 31.004 -1.324 0.185 -101.826 19.715
C(mnth)[T.8]:C(hr)[T.1] -27.2087 34.020 -0.800 0.424 -93.891 39.473
C(mnth)[T.9]:C(hr)[T.1] -34.2902 31.396 -1.092 0.275 -95.831 27.250
C(mnth)[T.10]:C(hr)[T.1] -27.8088 31.396 -0.886 0.376 -89.349 33.731
C(mnth)[T.11]:C(hr)[T.1] -6.6062 31.397 -0.210 0.833 -68.148 54.936
C(mnth)[T.12]:C(hr)[T.1] -5.7600 31.004 -0.186 0.853 -66.531 55.011
C(mnth)[T.2]:C(hr)[T.2] -9.0252 32.237 -0.280 0.780 -72.214 54.163
C(mnth)[T.3]:C(hr)[T.2] -2.1531 33.366 -0.065 0.949 -67.554 63.248
C(mnth)[T.4]:C(hr)[T.2] -20.2803 31.341 -0.647 0.518 -81.711 41.151
C(mnth)[T.5]:C(hr)[T.2] -40.0805 31.768 -1.262 0.207 -102.350 22.189
C(mnth)[T.6]:C(hr)[T.2] -43.4959 32.755 -1.328 0.184 -107.698 20.707
C(mnth)[T.7]:C(hr)[T.2] -53.8516 30.945 -1.740 0.082 -114.508 6.805
C(mnth)[T.8]:C(hr)[T.2] -28.6400 33.965 -0.843 0.399 -95.215 37.935
C(mnth)[T.9]:C(hr)[T.2] -42.0877 31.339 -1.343 0.179 -103.515 19.340
C(mnth)[T.10]:C(hr)[T.2] -42.8590 31.338 -1.368 0.171 -104.285 18.567
C(mnth)[T.11]:C(hr)[T.2] -25.9643 31.339 -0.828 0.407 -87.393 35.464
C(mnth)[T.12]:C(hr)[T.2] -12.2750 30.945 -0.397 0.692 -72.930 48.380
C(mnth)[T.2]:C(hr)[T.3] -13.3089 32.410 -0.411 0.681 -76.835 50.217
C(mnth)[T.3]:C(hr)[T.3] -23.8073 32.925 -0.723 0.470 -88.343 40.729
C(mnth)[T.4]:C(hr)[T.3] -30.6516 31.517 -0.973 0.331 -92.429 31.126
C(mnth)[T.5]:C(hr)[T.3] -65.6889 31.943 -2.056 0.040 -128.301 -3.077
C(mnth)[T.6]:C(hr)[T.3] -76.2159 32.925 -2.315 0.021 -140.751 -11.680
C(mnth)[T.7]:C(hr)[T.3] -83.9309 31.125 -2.697 0.007 -144.938 -22.924
C(mnth)[T.8]:C(hr)[T.3] -70.3083 34.127 -2.060 0.039 -137.202 -3.415
C(mnth)[T.9]:C(hr)[T.3] -74.0936 31.517 -2.351 0.019 -135.870 -12.318
C(mnth)[T.10]:C(hr)[T.3] -67.3489 31.516 -2.137 0.033 -129.123 -5.575
C(mnth)[T.11]:C(hr)[T.3] -36.6803 31.515 -1.164 0.244 -98.453 25.093
C(mnth)[T.12]:C(hr)[T.3] -28.4572 31.536 -0.902 0.367 -90.271 33.357
C(mnth)[T.2]:C(hr)[T.4] -7.9843 32.668 -0.244 0.807 -72.017 56.049
C(mnth)[T.3]:C(hr)[T.4] -31.1439 32.925 -0.946 0.344 -95.681 33.393
C(mnth)[T.4]:C(hr)[T.4] -33.4605 31.517 -1.062 0.288 -95.237 28.316
C(mnth)[T.5]:C(hr)[T.4] -69.3392 31.943 -2.171 0.030 -131.951 -6.727
C(mnth)[T.6]:C(hr)[T.4] -85.4718 32.925 -2.596 0.009 -150.009 -20.934
C(mnth)[T.7]:C(hr)[T.4] -93.8154 31.125 -3.014 0.003 -154.823 -32.808
C(mnth)[T.8]:C(hr)[T.4] -85.3732 34.128 -2.502 0.012 -152.267 -18.479
C(mnth)[T.9]:C(hr)[T.4] -93.3605 31.517 -2.962 0.003 -155.137 -31.584
C(mnth)[T.10]:C(hr)[T.4] -76.8104 31.518 -2.437 0.015 -138.588 -15.033
C(mnth)[T.11]:C(hr)[T.4] -36.4892 31.516 -1.158 0.247 -98.263 25.285
C(mnth)[T.12]:C(hr)[T.4] -34.4940 31.322 -1.101 0.271 -95.888 26.900
C(mnth)[T.2]:C(hr)[T.5] -4.9291 33.666 -0.146 0.884 -70.918 61.060
C(mnth)[T.3]:C(hr)[T.5] -37.5177 33.916 -1.106 0.269 -103.996 28.961
C(mnth)[T.4]:C(hr)[T.5] -30.9000 31.927 -0.968 0.333 -93.480 31.681
C(mnth)[T.5]:C(hr)[T.5] -58.6062 32.346 -1.812 0.070 -122.007 4.795
C(mnth)[T.6]:C(hr)[T.5] -81.5388 33.315 -2.448 0.014 -146.839 -16.239
C(mnth)[T.7]:C(hr)[T.5] -91.7337 31.537 -2.909 0.004 -153.550 -29.918
C(mnth)[T.8]:C(hr)[T.5] -88.4429 34.506 -2.563 0.010 -156.078 -20.808
C(mnth)[T.9]:C(hr)[T.5] -88.2420 31.926 -2.764 0.006 -150.820 -25.664
C(mnth)[T.10]:C(hr)[T.5] -70.9233 31.923 -2.222 0.026 -133.497 -8.350
C(mnth)[T.11]:C(hr)[T.5] -30.6101 31.923 -0.959 0.338 -93.182 31.962
C(mnth)[T.12]:C(hr)[T.5] -26.3729 31.537 -0.836 0.403 -88.189 35.443
C(mnth)[T.2]:C(hr)[T.6] -9.8533 32.412 -0.304 0.761 -73.385 53.678
C(mnth)[T.3]:C(hr)[T.6] -23.9286 32.925 -0.727 0.467 -88.465 40.608
C(mnth)[T.4]:C(hr)[T.6] -16.2493 31.521 -0.516 0.606 -78.033 45.535
C(mnth)[T.5]:C(hr)[T.6] -52.4310 31.942 -1.641 0.101 -115.041 10.179
C(mnth)[T.6]:C(hr)[T.6] -66.2352 32.925 -2.012 0.044 -130.772 -1.698
C(mnth)[T.7]:C(hr)[T.6] -85.5474 31.125 -2.749 0.006 -146.555 -24.539
C(mnth)[T.8]:C(hr)[T.6] -80.6042 34.129 -2.362 0.018 -147.500 -13.709
C(mnth)[T.9]:C(hr)[T.6] -81.6174 31.517 -2.590 0.010 -143.394 -19.841
C(mnth)[T.10]:C(hr)[T.6] -62.9306 31.517 -1.997 0.046 -124.707 -1.154
C(mnth)[T.11]:C(hr)[T.6] -23.3514 31.516 -0.741 0.459 -85.126 38.423
C(mnth)[T.12]:C(hr)[T.6] -23.2693 31.125 -0.748 0.455 -84.278 37.740
C(mnth)[T.2]:C(hr)[T.7] 2.0747 32.237 0.064 0.949 -61.114 65.263
C(mnth)[T.3]:C(hr)[T.7] 0.8923 32.756 0.027 0.978 -63.312 65.097
C(mnth)[T.4]:C(hr)[T.7] 18.9320 31.340 0.604 0.546 -42.498 80.362
C(mnth)[T.5]:C(hr)[T.7] -22.3546 31.768 -0.704 0.482 -84.623 39.913
C(mnth)[T.6]:C(hr)[T.7] -40.5075 32.755 -1.237 0.216 -104.710 23.695
C(mnth)[T.7]:C(hr)[T.7] -70.1542 30.945 -2.267 0.023 -130.810 -9.498
C(mnth)[T.8]:C(hr)[T.7] -51.4136 33.647 -1.528 0.127 -117.365 14.538
C(mnth)[T.9]:C(hr)[T.7] -55.5287 31.339 -1.772 0.076 -116.957 5.900
C(mnth)[T.10]:C(hr)[T.7] -23.1467 31.338 -0.739 0.460 -84.572 38.279
C(mnth)[T.11]:C(hr)[T.7] 10.1953 31.338 0.325 0.745 -51.231 71.621
C(mnth)[T.12]:C(hr)[T.7] -10.4597 30.945 -0.338 0.735 -71.116 50.197
C(mnth)[T.2]:C(hr)[T.8] 9.9876 32.237 0.310 0.757 -53.201 73.176
C(mnth)[T.3]:C(hr)[T.8] 9.3194 32.755 0.285 0.776 -54.883 73.522
C(mnth)[T.4]:C(hr)[T.8] 55.5545 31.340 1.773 0.076 -5.875 116.984
C(mnth)[T.5]:C(hr)[T.8] 18.7323 31.767 0.590 0.555 -43.534 80.999
C(mnth)[T.6]:C(hr)[T.8] 19.9758 32.754 0.610 0.542 -44.226 84.178
C(mnth)[T.7]:C(hr)[T.8] -17.9467 30.945 -0.580 0.562 -78.603 42.709
C(mnth)[T.8]:C(hr)[T.8] -9.7625 33.647 -0.290 0.772 -75.714 56.189
C(mnth)[T.9]:C(hr)[T.8] 3.4258 31.338 0.109 0.913 -58.000 64.852
C(mnth)[T.10]:C(hr)[T.8] 28.5892 31.339 0.912 0.362 -32.838 90.017
C(mnth)[T.11]:C(hr)[T.8] 52.7998 31.338 1.685 0.092 -8.626 114.226
C(mnth)[T.12]:C(hr)[T.8] -6.3651 30.945 -0.206 0.837 -67.021 54.290
C(mnth)[T.2]:C(hr)[T.9] 19.0129 32.238 0.590 0.555 -44.177 82.203
C(mnth)[T.3]:C(hr)[T.9] 35.0135 32.755 1.069 0.285 -29.189 99.216
C(mnth)[T.4]:C(hr)[T.9] 83.5449 31.340 2.666 0.008 22.115 144.975
C(mnth)[T.5]:C(hr)[T.9] 82.1972 31.767 2.587 0.010 19.930 144.465
C(mnth)[T.6]:C(hr)[T.9] 101.9516 32.754 3.113 0.002 37.749 166.154
C(mnth)[T.7]:C(hr)[T.9] 53.2481 30.945 1.721 0.085 -7.407 113.903
C(mnth)[T.8]:C(hr)[T.9] 68.8224 33.647 2.045 0.041 2.871 134.774
C(mnth)[T.9]:C(hr)[T.9] 95.0848 31.338 3.034 0.002 33.659 156.511
C(mnth)[T.10]:C(hr)[T.9] 88.6322 31.338 2.828 0.005 27.207 150.058
C(mnth)[T.11]:C(hr)[T.9] 83.2742 31.338 2.657 0.008 21.849 144.700
C(mnth)[T.12]:C(hr)[T.9] 15.2329 30.945 0.492 0.623 -45.423 75.889
C(mnth)[T.2]:C(hr)[T.10] 24.1068 32.239 0.748 0.455 -39.085 87.298
C(mnth)[T.3]:C(hr)[T.10] 66.4873 32.755 2.030 0.042 2.284 130.690
C(mnth)[T.4]:C(hr)[T.10] 119.0594 31.343 3.799 0.000 57.625 180.494
C(mnth)[T.5]:C(hr)[T.10] 155.7854 31.769 4.904 0.000 93.515 218.056
C(mnth)[T.6]:C(hr)[T.10] 176.6544 32.755 5.393 0.000 112.451 240.858
C(mnth)[T.7]:C(hr)[T.10] 109.8490 30.946 3.550 0.000 49.192 170.506
C(mnth)[T.8]:C(hr)[T.10] 129.7362 33.648 3.856 0.000 63.783 195.690
C(mnth)[T.9]:C(hr)[T.10] 183.1494 31.339 5.844 0.000 121.722 244.577
C(mnth)[T.10]:C(hr)[T.10] 143.0441 31.338 4.565 0.000 81.618 204.470
C(mnth)[T.11]:C(hr)[T.10] 108.5228 31.339 3.463 0.001 47.095 169.951
C(mnth)[T.12]:C(hr)[T.10] 33.7309 30.948 1.090 0.276 -26.931 94.393
C(mnth)[T.2]:C(hr)[T.11] 20.2118 32.238 0.627 0.531 -42.978 83.401
C(mnth)[T.3]:C(hr)[T.11] 85.5419 32.755 2.612 0.009 21.339 149.745
C(mnth)[T.4]:C(hr)[T.11] 150.8240 31.341 4.812 0.000 89.393 212.255
C(mnth)[T.5]:C(hr)[T.11] 210.2568 31.769 6.618 0.000 147.986 272.528
C(mnth)[T.6]:C(hr)[T.11] 220.7277 32.755 6.739 0.000 156.525 284.930
C(mnth)[T.7]:C(hr)[T.11] 132.3296 30.945 4.276 0.000 71.674 192.985
C(mnth)[T.8]:C(hr)[T.11] 140.7673 33.649 4.183 0.000 74.813 206.722
C(mnth)[T.9]:C(hr)[T.11] 241.9639 31.338 7.721 0.000 180.538 303.390
C(mnth)[T.10]:C(hr)[T.11] 182.1086 31.338 5.811 0.000 120.682 243.535
C(mnth)[T.11]:C(hr)[T.11] 134.3533 31.338 4.287 0.000 72.928 195.779
C(mnth)[T.12]:C(hr)[T.11] 54.8007 30.946 1.771 0.077 -5.857 115.458
C(mnth)[T.2]:C(hr)[T.12] 31.2657 32.238 0.970 0.332 -31.924 94.455
C(mnth)[T.3]:C(hr)[T.12] 114.3220 32.756 3.490 0.000 50.116 178.528
C(mnth)[T.4]:C(hr)[T.12] 175.4165 31.343 5.597 0.000 113.981 236.852
C(mnth)[T.5]:C(hr)[T.12] 234.3675 31.769 7.377 0.000 172.098 296.637
C(mnth)[T.6]:C(hr)[T.12] 242.3283 32.755 7.398 0.000 178.126 306.531
C(mnth)[T.7]:C(hr)[T.12] 146.0355 30.945 4.719 0.000 85.379 206.692
C(mnth)[T.8]:C(hr)[T.12] 196.9144 33.651 5.852 0.000 130.954 262.875
C(mnth)[T.9]:C(hr)[T.12] 279.7565 31.339 8.927 0.000 218.329 341.184
C(mnth)[T.10]:C(hr)[T.12] 209.6986 31.338 6.691 0.000 148.272 271.125
C(mnth)[T.11]:C(hr)[T.12] 161.9618 31.338 5.168 0.000 100.536 223.388
C(mnth)[T.12]:C(hr)[T.12] 75.8698 30.947 2.452 0.014 15.210 136.530
C(mnth)[T.2]:C(hr)[T.13] 40.7686 32.239 1.265 0.206 -22.424 103.961
C(mnth)[T.3]:C(hr)[T.13] 124.2738 32.759 3.794 0.000 60.064 188.484
C(mnth)[T.4]:C(hr)[T.13] 181.1506 31.345 5.779 0.000 119.711 242.590
C(mnth)[T.5]:C(hr)[T.13] 245.0170 31.769 7.712 0.000 182.746 307.288
C(mnth)[T.6]:C(hr)[T.13] 228.6424 32.755 6.980 0.000 164.439 292.846
C(mnth)[T.7]:C(hr)[T.13] 145.3050 30.945 4.696 0.000 84.649 205.961
C(mnth)[T.8]:C(hr)[T.13] 159.4636 33.649 4.739 0.000 93.507 225.420
C(mnth)[T.9]:C(hr)[T.13] 264.6565 31.339 8.445 0.000 203.229 326.084
C(mnth)[T.10]:C(hr)[T.13] 202.3592 31.338 6.457 0.000 140.934 263.785
C(mnth)[T.11]:C(hr)[T.13] 172.8038 31.338 5.514 0.000 111.378 234.230
C(mnth)[T.12]:C(hr)[T.13] 69.9813 30.948 2.261 0.024 9.320 130.643
C(mnth)[T.2]:C(hr)[T.14] 29.5768 32.237 0.917 0.359 -33.611 92.765
C(mnth)[T.3]:C(hr)[T.14] 133.1914 32.755 4.066 0.000 68.987 197.396
C(mnth)[T.4]:C(hr)[T.14] 188.4526 31.342 6.013 0.000 127.019 249.886
C(mnth)[T.5]:C(hr)[T.14] 208.7474 31.768 6.571 0.000 146.479 271.016
C(mnth)[T.6]:C(hr)[T.14] 216.8448 32.754 6.620 0.000 152.643 281.047
C(mnth)[T.7]:C(hr)[T.14] 125.6626 30.945 4.061 0.000 65.006 186.319
C(mnth)[T.8]:C(hr)[T.14] 133.4278 33.650 3.965 0.000 67.471 199.385
C(mnth)[T.9]:C(hr)[T.14] 230.6899 31.338 7.361 0.000 169.264 292.115
C(mnth)[T.10]:C(hr)[T.14] 192.8006 31.340 6.152 0.000 131.371 254.230
C(mnth)[T.11]:C(hr)[T.14] 168.8872 31.338 5.389 0.000 107.461 230.313
C(mnth)[T.12]:C(hr)[T.14] 51.4017 30.947 1.661 0.097 -9.258 112.061
C(mnth)[T.2]:C(hr)[T.15] 27.7928 32.237 0.862 0.389 -35.395 90.981
C(mnth)[T.3]:C(hr)[T.15] 138.1967 32.757 4.219 0.000 73.989 202.404
C(mnth)[T.4]:C(hr)[T.15] 176.5708 31.342 5.634 0.000 115.137 238.004
C(mnth)[T.5]:C(hr)[T.15] 200.6748 31.767 6.317 0.000 138.408 262.941
C(mnth)[T.6]:C(hr)[T.15] 191.6305 32.755 5.850 0.000 127.427 255.834
C(mnth)[T.7]:C(hr)[T.15] 104.7629 30.945 3.385 0.001 44.107 165.419
C(mnth)[T.8]:C(hr)[T.15] 117.3384 33.648 3.487 0.000 51.385 183.292
C(mnth)[T.9]:C(hr)[T.15] 234.6847 31.338 7.489 0.000 173.259 296.111
C(mnth)[T.10]:C(hr)[T.15] 174.2400 31.338 5.560 0.000 112.813 235.667
C(mnth)[T.11]:C(hr)[T.15] 149.1054 31.338 4.758 0.000 87.680 210.531
C(mnth)[T.12]:C(hr)[T.15] 41.6748 30.948 1.347 0.178 -18.986 102.336
C(mnth)[T.2]:C(hr)[T.16] 20.7130 32.240 0.642 0.521 -42.481 83.907
C(mnth)[T.3]:C(hr)[T.16] 140.2520 32.761 4.281 0.000 76.036 204.468
C(mnth)[T.4]:C(hr)[T.16] 181.6269 31.343 5.795 0.000 120.192 243.062
C(mnth)[T.5]:C(hr)[T.16] 204.8119 31.767 6.447 0.000 142.545 267.079
C(mnth)[T.6]:C(hr)[T.16] 225.6770 32.754 6.890 0.000 161.475 289.879
C(mnth)[T.7]:C(hr)[T.16] 116.7859 30.946 3.774 0.000 56.129 177.443
C(mnth)[T.8]:C(hr)[T.16] 121.3222 33.650 3.605 0.000 55.365 187.279
C(mnth)[T.9]:C(hr)[T.16] 233.1589 31.339 7.440 0.000 171.731 294.587
C(mnth)[T.10]:C(hr)[T.16] 199.0094 31.338 6.350 0.000 137.583 260.436
C(mnth)[T.11]:C(hr)[T.16] 141.5222 31.338 4.516 0.000 80.097 202.948
C(mnth)[T.12]:C(hr)[T.16] 48.0888 30.949 1.554 0.120 -12.575 108.753
C(mnth)[T.2]:C(hr)[T.17] 35.4033 32.239 1.098 0.272 -27.789 98.596
C(mnth)[T.3]:C(hr)[T.17] 156.8523 32.762 4.788 0.000 92.636 221.069
C(mnth)[T.4]:C(hr)[T.17] 225.4261 31.340 7.193 0.000 163.996 286.856
C(mnth)[T.5]:C(hr)[T.17] 234.9243 31.768 7.395 0.000 172.655 297.194
C(mnth)[T.6]:C(hr)[T.17] 250.6397 32.755 7.652 0.000 186.437 314.842
C(mnth)[T.7]:C(hr)[T.17] 154.8584 30.947 5.004 0.000 94.198 215.519
C(mnth)[T.8]:C(hr)[T.17] 149.4430 33.650 4.441 0.000 83.485 215.401
C(mnth)[T.9]:C(hr)[T.17] 257.8841 31.340 8.229 0.000 196.455 319.313
C(mnth)[T.10]:C(hr)[T.17] 211.5427 31.339 6.750 0.000 150.114 272.971
C(mnth)[T.11]:C(hr)[T.17] 129.2975 31.338 4.126 0.000 67.872 190.723
C(mnth)[T.12]:C(hr)[T.17] 27.3417 30.949 0.883 0.377 -33.322 88.006
C(mnth)[T.2]:C(hr)[T.18] -1.8076 32.238 -0.056 0.955 -64.997 61.382
C(mnth)[T.3]:C(hr)[T.18] 106.9605 32.757 3.265 0.001 42.753 171.168
C(mnth)[T.4]:C(hr)[T.18] 165.1547 31.340 5.270 0.000 103.726 226.584
C(mnth)[T.5]:C(hr)[T.18] 195.5248 31.768 6.155 0.000 133.257 257.793
C(mnth)[T.6]:C(hr)[T.18] 206.0107 32.757 6.289 0.000 141.804 270.217
C(mnth)[T.7]:C(hr)[T.18] 122.2991 30.945 3.952 0.000 61.643 182.955
C(mnth)[T.8]:C(hr)[T.18] 144.4786 33.964 4.254 0.000 77.905 211.052
C(mnth)[T.9]:C(hr)[T.18] 204.9206 31.339 6.539 0.000 143.494 266.348
C(mnth)[T.10]:C(hr)[T.18] 151.4186 31.338 4.832 0.000 89.992 212.845
C(mnth)[T.11]:C(hr)[T.18] 72.3760 31.338 2.309 0.021 10.949 133.802
C(mnth)[T.12]:C(hr)[T.18] 3.5143 30.947 0.114 0.910 -57.145 64.174
C(mnth)[T.2]:C(hr)[T.19] -20.1376 32.239 -0.625 0.532 -83.329 43.053
C(mnth)[T.3]:C(hr)[T.19] 56.4316 32.759 1.723 0.085 -7.780 120.643
C(mnth)[T.4]:C(hr)[T.19] 121.4181 31.341 3.874 0.000 59.986 182.850
C(mnth)[T.5]:C(hr)[T.19] 156.9018 31.767 4.939 0.000 94.634 219.169
C(mnth)[T.6]:C(hr)[T.19] 178.9429 32.757 5.463 0.000 114.736 243.150
C(mnth)[T.7]:C(hr)[T.19] 120.0834 30.947 3.880 0.000 59.424 180.742
C(mnth)[T.8]:C(hr)[T.19] 120.9041 33.965 3.560 0.000 54.330 187.479
C(mnth)[T.9]:C(hr)[T.19] 158.3527 31.339 5.053 0.000 96.924 219.781
C(mnth)[T.10]:C(hr)[T.19] 59.2709 31.342 1.891 0.059 -2.164 120.705
C(mnth)[T.11]:C(hr)[T.19] 46.5182 31.339 1.484 0.138 -14.910 107.946
C(mnth)[T.12]:C(hr)[T.19] -4.1173 30.948 -0.133 0.894 -64.778 56.543
C(mnth)[T.2]:C(hr)[T.20] -10.0828 32.239 -0.313 0.754 -73.274 53.108
C(mnth)[T.3]:C(hr)[T.20] 25.8098 32.758 0.788 0.431 -38.399 90.019
C(mnth)[T.4]:C(hr)[T.20] 72.0156 31.341 2.298 0.022 10.584 133.447
C(mnth)[T.5]:C(hr)[T.20] 102.1101 31.768 3.214 0.001 39.842 164.378
C(mnth)[T.6]:C(hr)[T.20] 131.9588 32.755 4.029 0.000 67.756 196.162
C(mnth)[T.7]:C(hr)[T.20] 113.6161 30.945 3.671 0.000 52.960 174.272
C(mnth)[T.8]:C(hr)[T.20] 72.0514 33.965 2.121 0.034 5.476 138.627
C(mnth)[T.9]:C(hr)[T.20] 75.5550 31.340 2.411 0.016 14.126 136.984
C(mnth)[T.10]:C(hr)[T.20] 30.5891 31.338 0.976 0.329 -30.837 92.015
C(mnth)[T.11]:C(hr)[T.20] 32.6471 31.338 1.042 0.298 -28.779 94.073
C(mnth)[T.12]:C(hr)[T.20] -1.3616 30.946 -0.044 0.965 -62.020 59.296
C(mnth)[T.2]:C(hr)[T.21] -2.7011 32.240 -0.084 0.933 -65.896 60.493
C(mnth)[T.3]:C(hr)[T.21] 17.0411 32.757 0.520 0.603 -47.166 81.248
C(mnth)[T.4]:C(hr)[T.21] 44.9004 31.340 1.433 0.152 -16.529 106.330
C(mnth)[T.5]:C(hr)[T.21] 66.4551 31.767 2.092 0.036 4.188 128.722
C(mnth)[T.6]:C(hr)[T.21] 81.0631 32.755 2.475 0.013 16.860 145.266
C(mnth)[T.7]:C(hr)[T.21] 84.5937 30.945 2.734 0.006 23.937 145.250
C(mnth)[T.8]:C(hr)[T.21] 47.4827 33.964 1.398 0.162 -19.091 114.056
C(mnth)[T.9]:C(hr)[T.21] 34.6292 31.338 1.105 0.269 -26.797 96.056
C(mnth)[T.10]:C(hr)[T.21] 12.9659 31.338 0.414 0.679 -48.461 74.393
C(mnth)[T.11]:C(hr)[T.21] 20.3531 31.338 0.649 0.516 -41.072 81.779
C(mnth)[T.12]:C(hr)[T.21] -6.7473 30.946 -0.218 0.827 -67.404 53.910
C(mnth)[T.2]:C(hr)[T.22] 11.6989 32.240 0.363 0.717 -51.494 74.892
C(mnth)[T.3]:C(hr)[T.22] 7.6842 32.758 0.235 0.815 -56.526 71.894
C(mnth)[T.4]:C(hr)[T.22] 32.1841 31.344 1.027 0.305 -29.254 93.622
C(mnth)[T.5]:C(hr)[T.22] 43.3353 31.770 1.364 0.173 -18.937 105.608
C(mnth)[T.6]:C(hr)[T.22] 45.9846 32.756 1.404 0.160 -18.221 110.190
C(mnth)[T.7]:C(hr)[T.22] 46.0849 30.946 1.489 0.136 -14.572 106.742
C(mnth)[T.8]:C(hr)[T.22] 17.3062 33.964 0.510 0.610 -49.267 83.879
C(mnth)[T.9]:C(hr)[T.22] 15.3448 31.339 0.490 0.624 -46.082 76.772
C(mnth)[T.10]:C(hr)[T.22] 5.8422 31.338 0.186 0.852 -55.584 67.268
C(mnth)[T.11]:C(hr)[T.22] 14.8528 31.338 0.474 0.636 -46.574 76.279
C(mnth)[T.12]:C(hr)[T.22] -2.5494 30.947 -0.082 0.934 -63.209 58.111
C(mnth)[T.2]:C(hr)[T.23] -1.4237 32.237 -0.044 0.965 -64.612 61.765
C(mnth)[T.3]:C(hr)[T.23] -7.9767 32.756 -0.244 0.808 -72.183 56.229
C(mnth)[T.4]:C(hr)[T.23] 9.9500 31.339 0.317 0.751 -51.478 71.378
C(mnth)[T.5]:C(hr)[T.23] 11.9076 31.768 0.375 0.708 -50.362 74.177
C(mnth)[T.6]:C(hr)[T.23] 12.3425 32.755 0.377 0.706 -51.861 76.545
C(mnth)[T.7]:C(hr)[T.23] -4.5851 30.945 -0.148 0.882 -65.240 56.069
C(mnth)[T.8]:C(hr)[T.23] -2.9303 33.964 -0.086 0.931 -69.504 63.643
C(mnth)[T.9]:C(hr)[T.23] -6.1494 31.339 -0.196 0.844 -67.576 55.277
C(mnth)[T.10]:C(hr)[T.23] -20.5499 31.339 -0.656 0.512 -81.977 40.877
C(mnth)[T.11]:C(hr)[T.23] 4.5133 31.338 0.144 0.885 -56.912 65.939
C(mnth)[T.12]:C(hr)[T.23] -11.4428 30.946 -0.370 0.712 -72.100 49.214
C(workingday)[T.1]:C(hr)[T.1] -6.5095 27.244 -0.239 0.811 -59.910 46.891
C(workingday)[T.1]:C(hr)[T.2] 1.1834 27.318 0.043 0.965 -52.363 54.729
C(workingday)[T.1]:C(hr)[T.3] -11.6600 28.502 -0.409 0.682 -67.526 44.206
C(workingday)[T.1]:C(hr)[T.4] 11.5345 27.754 0.416 0.678 -42.865 65.934
C(workingday)[T.1]:C(hr)[T.5] 36.0556 27.850 1.295 0.195 -18.533 90.644
C(workingday)[T.1]:C(hr)[T.6] 69.9259 27.382 2.554 0.011 16.255 123.597
C(workingday)[T.1]:C(hr)[T.7] 157.9606 27.176 5.813 0.000 104.693 211.228
C(workingday)[T.1]:C(hr)[T.8] 292.2610 27.175 10.755 0.000 238.995 345.527
C(workingday)[T.1]:C(hr)[T.9] 131.3981 27.175 4.835 0.000 78.132 184.664
C(workingday)[T.1]:C(hr)[T.10] 4.1485 27.177 0.153 0.879 -49.121 57.418
C(workingday)[T.1]:C(hr)[T.11] -29.3703 27.174 -1.081 0.280 -82.634 23.894
C(workingday)[T.1]:C(hr)[T.12] -34.8743 27.112 -1.286 0.198 -88.016 18.267
C(workingday)[T.1]:C(hr)[T.13] -37.7955 27.114 -1.394 0.163 -90.942 15.351
C(workingday)[T.1]:C(hr)[T.14] -56.3336 27.112 -2.078 0.038 -109.475 -3.192
C(workingday)[T.1]:C(hr)[T.15] -57.9292 27.111 -2.137 0.033 -111.069 -4.790
C(workingday)[T.1]:C(hr)[T.16] -4.1070 27.074 -0.152 0.879 -57.175 48.961
C(workingday)[T.1]:C(hr)[T.17] 171.7407 27.053 6.348 0.000 118.715 224.767
C(workingday)[T.1]:C(hr)[T.18] 156.4294 27.135 5.765 0.000 103.243 209.616
C(workingday)[T.1]:C(hr)[T.19] 102.6385 27.113 3.786 0.000 49.494 155.783
C(workingday)[T.1]:C(hr)[T.20] 73.7333 27.113 2.719 0.007 20.588 126.878
C(workingday)[T.1]:C(hr)[T.21] 53.0095 27.113 1.955 0.051 -0.136 106.155
C(workingday)[T.1]:C(hr)[T.22] 41.0901 27.115 1.515 0.130 -12.058 94.238
C(workingday)[T.1]:C(hr)[T.23] 25.4851 27.111 0.940 0.347 -27.656 78.626
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[0] -4.5761 28.118 -0.163 0.871 -59.690 50.538
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[0] -12.3622 28.049 -0.441 0.659 -67.342 42.617
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[0] -14.2088 27.492 -0.517 0.605 -68.097 39.679
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[0] -30.0871 27.563 -1.092 0.275 -84.114 23.939
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[0] -48.4939 28.134 -1.724 0.085 -103.640 6.652
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[0] -65.4932 27.198 -2.408 0.016 -118.805 -12.181
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[0] -57.1205 28.712 -1.989 0.047 -113.399 -0.842
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[0] -51.7183 27.484 -1.882 0.060 -105.591 2.154
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[0] -51.9334 27.421 -1.894 0.058 -105.681 1.814
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[0] -6.6012 27.478 -0.240 0.810 -60.461 47.259
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[0] -4.4720 27.204 -0.164 0.869 -57.795 48.851
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[1] -2.8562 28.179 -0.101 0.919 -58.090 52.377
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[1] -5.8386 28.107 -0.208 0.835 -60.932 49.255
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[1] -0.5477 27.547 -0.020 0.984 -54.543 53.448
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[1] -19.9520 27.627 -0.722 0.470 -74.104 34.200
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[1] -43.3338 28.199 -1.537 0.124 -98.606 11.938
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[1] -51.4668 27.264 -1.888 0.059 -104.907 1.974
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[1] -50.6318 28.771 -1.760 0.078 -107.026 5.763
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[1] -32.4334 27.605 -1.175 0.240 -86.543 21.676
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[1] -38.8699 27.545 -1.411 0.158 -92.861 15.121
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[1] -5.3218 27.545 -0.193 0.847 -59.313 48.669
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[1] -9.8441 27.267 -0.361 0.718 -63.289 43.601
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[2] -6.2870 28.380 -0.222 0.825 -61.914 49.340
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[2] -22.1571 28.975 -0.765 0.444 -78.950 34.636
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[2] -10.7236 27.614 -0.388 0.698 -64.851 43.403
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[2] -14.2853 27.698 -0.516 0.606 -68.577 40.006
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[2] -34.3784 28.266 -1.216 0.224 -89.784 21.027
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[2] -48.3749 27.335 -1.770 0.077 -101.955 5.205
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[2] -60.4684 28.841 -2.097 0.036 -117.000 -3.936
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[2] -34.5201 27.674 -1.247 0.212 -88.764 19.724
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[2] -36.1722 27.617 -1.310 0.190 -90.305 17.961
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[2] 6.6739 27.679 0.241 0.809 -47.580 60.928
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[2] -9.5168 27.335 -0.348 0.728 -63.097 44.063
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[3] 20.7539 29.741 0.698 0.485 -37.541 79.049
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[3] 9.0808 29.413 0.309 0.758 -48.572 66.734
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[3] 12.6085 28.904 0.436 0.663 -44.047 69.264
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[3] 23.7526 28.869 0.823 0.411 -32.833 80.338
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[3] 18.1853 29.414 0.618 0.536 -39.469 75.839
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[3] -4.5008 28.518 -0.158 0.875 -60.400 51.398
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[3] -2.0639 29.963 -0.069 0.945 -60.794 56.667
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[3] 13.8182 28.847 0.479 0.632 -42.725 70.361
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[3] 6.5582 28.845 0.227 0.820 -49.981 63.098
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[3] 38.3055 28.907 1.325 0.185 -18.356 94.967
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[3] 26.3588 28.969 0.910 0.363 -30.423 83.140
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[4] -13.1626 29.786 -0.442 0.659 -71.546 45.221
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[4] -0.3640 28.963 -0.013 0.990 -57.134 56.406
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[4] 5.9660 28.106 0.212 0.832 -49.126 61.058
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[4] 17.3292 28.131 0.616 0.538 -37.810 72.469
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[4] 15.1641 28.690 0.529 0.597 -41.071 71.400
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[4] -7.3504 27.772 -0.265 0.791 -61.787 47.086
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[4] 0.7858 29.254 0.027 0.979 -56.555 58.126
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[4] 24.5896 28.049 0.877 0.381 -30.390 79.569
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[4] 9.2480 28.048 0.330 0.742 -45.729 64.225
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[4] 23.1459 28.049 0.825 0.409 -31.834 78.126
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[4] 22.6329 28.108 0.805 0.421 -32.461 77.727
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[5] -10.5501 29.741 -0.355 0.723 -68.845 47.744
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[5] 12.9871 29.384 0.442 0.659 -44.609 70.583
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[5] 0.7742 28.141 0.028 0.978 -54.386 55.934
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[5] 3.9267 28.224 0.139 0.889 -51.395 59.248
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[5] 16.6155 28.782 0.577 0.564 -39.800 73.031
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[5] -2.2797 27.867 -0.082 0.935 -56.903 52.343
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[5] 10.0284 29.341 0.342 0.733 -47.483 67.540
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[5] 25.6384 28.145 0.911 0.362 -29.528 80.805
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[5] 9.7876 28.144 0.348 0.728 -45.377 64.952
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[5] 18.9855 28.145 0.675 0.500 -36.182 74.153
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[5] 10.5672 27.867 0.379 0.705 -44.055 65.190
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[6] 7.6787 28.249 0.272 0.786 -47.693 63.051
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[6] 16.7485 28.237 0.593 0.553 -38.599 72.096
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[6] 9.3973 27.679 0.340 0.734 -44.857 63.652
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[6] 50.6838 27.764 1.826 0.068 -3.736 105.104
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[6] 65.0508 28.331 2.296 0.022 9.520 120.582
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[6] 59.4157 27.400 2.168 0.030 5.709 113.122
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[6] 66.0906 28.899 2.287 0.022 9.445 122.736
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[6] 82.5111 27.680 2.981 0.003 28.255 136.767
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[6] 59.3015 27.681 2.142 0.032 5.044 113.559
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[6] 45.1728 27.682 1.632 0.103 -9.086 99.432
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[6] 25.6606 27.400 0.937 0.349 -28.047 79.368
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[7] 24.2118 28.052 0.863 0.388 -30.773 79.196
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[7] 40.2051 28.040 1.434 0.152 -14.756 95.166
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[7] 64.4179 27.478 2.344 0.019 10.559 118.277
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[7] 128.2488 27.561 4.653 0.000 74.227 182.271
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[7] 190.1469 28.133 6.759 0.000 135.004 245.290
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[7] 191.5859 27.196 7.045 0.000 138.278 244.894
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[7] 182.4249 28.329 6.439 0.000 126.896 237.953
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[7] 215.4610 27.479 7.841 0.000 161.600 269.322
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[7] 145.3639 27.478 5.290 0.000 91.504 199.224
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[7] 119.6661 27.479 4.355 0.000 65.804 173.528
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[7] 77.3321 27.197 2.843 0.004 24.023 130.642
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[8] 22.6382 28.052 0.807 0.420 -32.346 77.622
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[8] 59.1559 28.039 2.110 0.035 4.196 114.116
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[8] 70.3308 27.478 2.560 0.010 16.472 124.190
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[8] 116.2908 27.560 4.219 0.000 62.269 170.312
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[8] 138.8977 28.134 4.937 0.000 83.753 194.043
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[8] 154.6125 27.196 5.685 0.000 101.305 207.920
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[8] 159.9304 28.329 5.645 0.000 104.402 215.459
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[8] 167.1446 27.481 6.082 0.000 113.279 221.010
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[8] 141.9268 27.478 5.165 0.000 88.067 195.786
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[8] 113.3827 27.479 4.126 0.000 59.522 167.244
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[8] 110.8892 27.196 4.077 0.000 57.582 164.196
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[9] -8.7642 28.053 -0.312 0.755 -63.752 46.223
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[9] -7.5203 28.039 -0.268 0.789 -62.480 47.439
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[9] -34.5470 27.478 -1.257 0.209 -88.406 19.312
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[9] -62.8366 27.561 -2.280 0.023 -116.859 -8.814
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[9] -87.5572 28.133 -3.112 0.002 -142.700 -32.414
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[9] -59.1226 27.196 -2.174 0.030 -112.430 -5.815
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[9] -47.9475 28.330 -1.692 0.091 -103.477 7.582
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[9] -80.4084 27.479 -2.926 0.003 -134.270 -26.547
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[9] -49.7799 27.480 -1.812 0.070 -103.643 4.083
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[9] -22.7255 27.478 -0.827 0.408 -76.585 31.134
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[9] 32.8511 27.196 1.208 0.227 -20.456 86.158
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[10] -29.0566 28.052 -1.036 0.300 -84.041 25.928
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[10] -61.1188 28.039 -2.180 0.029 -116.079 -6.158
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[10] -95.3516 27.478 -3.470 0.001 -149.211 -41.492
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[10] -150.8895 27.561 -5.475 0.000 -204.912 -96.867
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[10] -186.1687 28.133 -6.618 0.000 -241.311 -131.026
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[10] -136.2412 27.197 -5.009 0.000 -189.549 -82.933
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[10] -131.2170 28.330 -4.632 0.000 -186.747 -75.688
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[10] -183.1178 27.478 -6.664 0.000 -236.977 -129.258
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[10] -136.1173 27.478 -4.954 0.000 -189.977 -82.258
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[10] -71.3335 27.480 -2.596 0.009 -125.197 -17.470
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[10] -13.6242 27.197 -0.501 0.616 -66.933 39.684
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[11] -16.5110 28.053 -0.589 0.556 -71.497 38.475
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[11] -57.2294 28.039 -2.041 0.041 -112.189 -2.270
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[11] -103.8118 27.478 -3.778 0.000 -157.672 -49.952
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[11] -178.6135 27.561 -6.481 0.000 -232.635 -124.592
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[11] -201.3097 28.132 -7.156 0.000 -256.452 -146.167
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[11] -133.2616 27.196 -4.900 0.000 -186.569 -79.954
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[11] -106.4389 28.330 -3.757 0.000 -161.969 -50.909
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[11] -210.7387 27.478 -7.669 0.000 -264.599 -156.878
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[11] -143.6605 27.478 -5.228 0.000 -197.520 -89.801
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[11] -81.4387 27.479 -2.964 0.003 -135.300 -27.577
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[11] -6.4839 27.196 -0.238 0.812 -59.792 46.824
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[12] -19.5844 27.990 -0.700 0.484 -74.449 35.280
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[12] -69.1681 27.976 -2.472 0.013 -124.005 -14.332
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[12] -110.7932 27.415 -4.041 0.000 -164.529 -57.058
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[12] -173.7114 27.498 -6.317 0.000 -227.610 -119.813
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[12] -193.2671 28.071 -6.885 0.000 -248.288 -138.246
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[12] -131.3303 27.133 -4.840 0.000 -184.514 -78.147
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[12] -134.5032 28.274 -4.757 0.000 -189.923 -79.084
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[12] -229.0320 27.414 -8.354 0.000 -282.767 -175.297
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[12] -132.0206 27.414 -4.816 0.000 -185.755 -78.286
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[12] -82.7310 27.414 -3.018 0.003 -136.466 -28.996
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[12] -10.6859 27.132 -0.394 0.694 -63.868 42.496
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[13] -36.0292 27.991 -1.287 0.198 -90.894 18.836
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[13] -82.5408 27.977 -2.950 0.003 -137.378 -27.704
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[13] -123.4060 27.415 -4.501 0.000 -177.142 -69.670
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[13] -180.2356 27.499 -6.554 0.000 -234.137 -126.335
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[13] -192.0403 28.072 -6.841 0.000 -247.063 -137.017
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[13] -143.5188 27.133 -5.289 0.000 -196.702 -90.336
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[13] -111.8682 28.274 -3.957 0.000 -167.288 -56.449
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[13] -219.0991 27.415 -7.992 0.000 -272.836 -165.363
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[13] -153.9319 27.359 -5.626 0.000 -207.558 -100.306
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[13] -99.4675 27.415 -3.628 0.000 -153.203 -45.732
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[13] -10.4659 27.134 -0.386 0.700 -63.651 42.719
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[14] -32.7741 27.991 -1.171 0.242 -87.639 22.091
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[14] -98.8734 27.976 -3.534 0.000 -153.710 -44.037
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[14] -129.9709 27.415 -4.741 0.000 -183.707 -76.235
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[14] -165.6244 27.498 -6.023 0.000 -219.524 -111.725
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[14] -182.3448 28.071 -6.496 0.000 -237.367 -127.323
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[14] -124.3698 27.132 -4.584 0.000 -177.552 -71.188
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[14] -84.9236 28.274 -3.004 0.003 -140.343 -29.504
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[14] -183.6044 27.414 -6.697 0.000 -237.340 -129.869
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[14] -140.6612 27.357 -5.142 0.000 -194.284 -87.039
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[14] -103.0480 27.414 -3.759 0.000 -156.783 -49.313
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[14] 6.4225 27.134 0.237 0.813 -46.763 59.608
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[15] -18.3475 27.994 -0.655 0.512 -73.219 36.524
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[15] -96.5404 27.976 -3.451 0.001 -151.376 -41.705
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[15] -107.5543 27.414 -3.923 0.000 -161.289 -53.819
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[15] -132.8681 27.497 -4.832 0.000 -186.766 -78.970
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[15] -151.3907 28.072 -5.393 0.000 -206.414 -96.367
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[15] -95.6617 27.132 -3.526 0.000 -148.844 -42.480
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[15] -55.2019 28.273 -1.952 0.051 -110.620 0.216
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[15] -171.4933 27.416 -6.255 0.000 -225.231 -117.755
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[15] -97.9920 27.357 -3.582 0.000 -151.615 -44.369
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[15] -60.9221 27.416 -2.222 0.026 -114.661 -7.183
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[15] 31.9426 27.135 1.177 0.239 -21.244 85.129
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[16] 6.6077 27.950 0.236 0.813 -48.178 61.393
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[16] -81.8907 27.937 -2.931 0.003 -136.651 -27.130
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[16] -73.2794 27.374 -2.677 0.007 -126.936 -19.623
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[16] -68.8726 27.458 -2.508 0.012 -122.694 -15.051
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[16] -106.4662 28.032 -3.798 0.000 -161.412 -51.520
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[16] -28.6306 27.092 -1.057 0.291 -81.734 24.472
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[16] 22.2115 28.231 0.787 0.431 -33.125 77.548
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[16] -94.2653 27.375 -3.443 0.001 -147.923 -40.607
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[16] -40.0105 27.319 -1.465 0.143 -93.558 13.537
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[16] -13.7353 27.376 -0.502 0.616 -67.395 39.924
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[16] 44.4180 27.095 1.639 0.101 -8.690 97.526
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[17] 5.5744 27.931 0.200 0.842 -49.173 60.322
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[17] -30.8038 27.919 -1.103 0.270 -85.527 23.920
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[17] -4.0811 27.357 -0.149 0.881 -57.703 49.541
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[17] 28.3066 27.440 1.032 0.302 -25.479 82.092
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[17] 38.8792 28.012 1.388 0.165 -16.028 93.787
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[17] 90.2109 27.073 3.332 0.001 37.144 143.278
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[17] 165.4259 28.215 5.863 0.000 110.122 220.729
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[17] 48.2714 27.354 1.765 0.078 -5.345 101.888
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[17] 102.2847 27.298 3.747 0.000 48.777 155.793
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[17] 51.4831 27.354 1.882 0.060 -2.134 105.100
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[17] 70.3937 27.072 2.600 0.009 17.329 123.459
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[18] 39.5080 28.012 1.410 0.158 -15.399 94.415
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[18] 34.4703 27.997 1.231 0.218 -20.407 89.347
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[18] 53.4555 27.438 1.948 0.051 -0.326 107.236
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[18] 56.7161 27.524 2.061 0.039 2.766 110.666
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[18] 66.2781 28.096 2.359 0.018 11.207 121.349
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[18] 129.7885 27.154 4.780 0.000 76.565 183.012
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[18] 165.7826 28.666 5.783 0.000 109.594 221.971
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[18] 83.0577 27.437 3.027 0.002 29.277 136.838
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[18] 92.7493 27.378 3.388 0.001 39.085 146.414
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[18] 76.1167 27.438 2.774 0.006 22.336 129.898
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[18] 78.6409 27.154 2.896 0.004 25.416 131.866
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[19] 32.7679 27.991 1.171 0.242 -22.098 87.634
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[19] 16.9990 27.976 0.608 0.543 -37.837 71.835
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[19] 13.7418 27.415 0.501 0.616 -39.994 67.478
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[19] 2.7430 27.502 0.100 0.921 -51.163 56.649
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[19] 3.4327 28.072 0.122 0.903 -51.592 58.457
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[19] 50.2367 27.134 1.851 0.064 -2.949 103.423
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[19] 78.1120 28.646 2.727 0.006 21.962 134.262
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[19] 25.2454 27.414 0.921 0.357 -28.490 78.980
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[19] 62.3693 27.359 2.280 0.023 8.744 115.995
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[19] 39.1786 27.417 1.429 0.153 -14.561 92.918
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[19] 45.6476 27.133 1.682 0.093 -7.537 98.832
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[20] 22.4054 27.989 0.800 0.423 -32.457 77.268
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[20] 15.7715 27.976 0.564 0.573 -39.064 70.607
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[20] 0.6572 27.419 0.024 0.981 -53.086 54.400
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[20] -2.3364 27.498 -0.085 0.932 -56.234 51.562
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[20] 7.0669 28.071 0.252 0.801 -47.955 62.089
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[20] 6.3275 27.132 0.233 0.816 -46.854 59.509
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[20] 53.1518 28.646 1.855 0.064 -2.997 109.301
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[20] 27.6916 27.414 1.010 0.312 -26.043 81.427
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[20] 47.6990 27.358 1.744 0.081 -5.925 101.323
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[20] 20.7585 27.414 0.757 0.449 -32.977 74.494
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[20] 27.8171 27.134 1.025 0.305 -25.367 81.002
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[21] 16.6241 27.991 0.594 0.553 -38.241 71.489
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[21] 9.3983 27.976 0.336 0.737 -45.437 64.234
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[21] 5.5339 27.416 0.202 0.840 -48.205 59.273
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[21] -10.0555 27.498 -0.366 0.715 -63.954 43.843
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[21] 9.6487 28.072 0.344 0.731 -45.375 64.673
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[21] -18.0568 27.133 -0.665 0.506 -71.240 35.126
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[21] 21.9770 28.645 0.767 0.443 -34.171 78.125
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[21] 27.9552 27.416 1.020 0.308 -25.782 81.693
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[21] 16.8846 27.359 0.617 0.537 -36.742 70.511
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[21] 19.2177 27.414 0.701 0.483 -34.517 72.952
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[21] 26.2813 27.133 0.969 0.333 -26.902 79.465
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[22] -3.2724 27.990 -0.117 0.907 -58.135 51.590
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[22] 1.8383 27.976 0.066 0.948 -52.997 56.673
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[22] -7.6111 27.417 -0.278 0.781 -61.350 46.128
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[22] -11.8462 27.498 -0.431 0.667 -65.745 42.052
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[22] -1.4673 28.072 -0.052 0.958 -56.491 53.556
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[22] -21.2708 27.132 -0.784 0.433 -74.453 31.911
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[22] 18.0970 28.646 0.632 0.528 -38.052 74.246
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[22] 12.7493 27.415 0.465 0.642 -40.987 66.486
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[22] 6.5242 27.358 0.238 0.812 -47.101 60.149
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[22] 8.3514 27.414 0.305 0.761 -45.383 62.086
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[22] 11.1449 27.133 0.411 0.681 -42.038 64.328
C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[23] -0.8099 27.990 -0.029 0.977 -55.673 54.053
C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[23] 1.9039 27.977 0.068 0.946 -52.933 56.741
C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[23] -8.4731 27.417 -0.309 0.757 -62.213 45.266
C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[23] -13.7184 27.497 -0.499 0.618 -67.616 40.179
C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[23] -13.9697 28.072 -0.498 0.619 -68.994 41.055
C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[23] -11.2080 27.133 -0.413 0.680 -64.391 41.975
C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[23] -7.9584 28.648 -0.278 0.781 -64.112 48.195
C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[23] -5.3922 27.416 -0.197 0.844 -59.131 48.347
C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[23] 2.9586 27.357 0.108 0.914 -50.664 56.581
C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[23] 4.5514 27.414 0.166 0.868 -49.183 58.286
C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[23] 15.3308 27.134 0.565 0.572 -37.856 68.517
==============================================================================
Omnibus: 1577.513 Durbin-Watson: 0.486
Prob(Omnibus): 0.000 Jarque-Bera (JB): 10878.178
Skew: -0.099 Prob(JB): 0.00
Kurtosis: 6.871 Cond. No. 766.
==============================================================================
Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
The final model¶
In [13]:
desired_reliability = 0.5
from statsmodels.regression.quantile_regression import QuantReg
qr = QuantReg.from_formula(formula='cnt ~ C(hr) + C(yr) + C(mnth) + C(workingday) + C(weathersit) + C(mnth):C(workingday):C(hr)', data=hour)
q50 = qr.fit(q = desired_reliability)
hour['cnt_q50'] = q50.predict(hour)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:193: IterationLimitWarning: Maximum number of iterations (1000) reached.
IterationLimitWarning)
In [14]:
desired_reliability = 0.9
qr = QuantReg.from_formula(formula='cnt ~ C(hr) + C(yr) + C(mnth) + C(workingday) + C(weathersit) + C(mnth):C(workingday):C(hr)', data=hour)
q90 = qr.fit(q = desired_reliability)
hour['cnt_q90'] = q90.predict(hour)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:193: IterationLimitWarning: Maximum number of iterations (1000) reached.
IterationLimitWarning)
Compare the different predictions to the original values of July 2012¶
In [15]:
count_by_hour = hour[['timestamp','cnt','cnt_q50','cnt_q90']].set_index('timestamp')
plt.figure( )
count_by_hour.plot(figsize=(30,20), linewidth=2)
plt.xlim(datetime.date(2012, 7, 1), datetime.date(2012, 8, 1))
plt.ylim(0,1000)
plt.legend(loc='best')
plt.show()
<matplotlib.figure.Figure at 0x122231940>
Discussion¶
With the predictions of the q90-model only a few hours would have lead to shortage issues.
Now consider the mean absolute deviance of the predictions from the observed values.
In [16]:
hour['abs_dev_OLS'] = np.abs(hour['cnt']-hour['cnt_OLS'])
hour['abs_dev_q50'] = np.abs(hour['cnt']-hour['cnt_q50'])
hour['abs_dev_q90'] = np.abs(hour['cnt']-hour['cnt_q90'])
print("mean absolute deviance for q50:" , hour['abs_dev_q50'].mean() , "for q90: ", hour['abs_dev_q90'].mean(), "and for OLS:", hour['abs_dev_OLS'].mean() )
mean absolute deviance for q50: 48.68053411650068 for q90: 79.64946908131675 and for OLS: 51.09465833840732
In [17]:
q50.summary()
Out[17]:
| Dep. Variable: | cnt | Pseudo R-squared: | 0.6462 |
|---|---|---|---|
| Model: | QuantReg | Bandwidth: | 8.994 |
| Method: | Least Squares | Sparsity: | 83.35 |
| Date: | Fri, 28 Sep 2018 | No. Observations: | 17379 |
| Time: | 12:28:41 | Df Residuals: | 16799 |
| Df Model: | 579 |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] | |
|---|---|---|---|---|---|
| Intercept | 23.9999 | 8.892 | 2.699 | 0.007 | 6.571 41.429 |
| C(hr)[T.1] | -8.0359 | 12.616 | -0.637 | 0.524 | -32.764 16.692 |
| C(hr)[T.2] | -12.9999 | 12.567 | -1.034 | 0.301 | -37.632 11.632 |
| C(hr)[T.3] | -18.9999 | 12.715 | -1.494 | 0.135 | -43.923 5.923 |
| C(hr)[T.4] | -22.9999 | 12.715 | -1.809 | 0.070 | -47.923 1.924 |
| C(hr)[T.5] | -22.9999 | 13.054 | -1.762 | 0.078 | -48.587 2.587 |
| C(hr)[T.6] | -22.9999 | 12.716 | -1.809 | 0.071 | -47.925 1.925 |
| C(hr)[T.7] | -21.8982 | 12.566 | -1.743 | 0.081 | -46.529 2.733 |
| C(hr)[T.8] | -9.8099 | 12.566 | -0.781 | 0.435 | -34.441 14.821 |
| C(hr)[T.9] | 8.6222 | 12.566 | 0.686 | 0.493 | -16.008 33.253 |
| C(hr)[T.10] | 45.5594 | 12.567 | 3.625 | 0.000 | 20.927 70.192 |
| C(hr)[T.11] | 68.9986 | 12.566 | 5.491 | 0.000 | 44.367 93.630 |
| C(hr)[T.12] | 90.4502 | 12.567 | 7.198 | 0.000 | 65.818 115.082 |
| C(hr)[T.13] | 83.1195 | 12.567 | 6.614 | 0.000 | 58.488 107.751 |
| C(hr)[T.14] | 94.0584 | 12.566 | 7.485 | 0.000 | 69.428 118.689 |
| C(hr)[T.15] | 99.2239 | 12.566 | 7.896 | 0.000 | 74.593 123.855 |
| C(hr)[T.16] | 90.4161 | 12.567 | 7.195 | 0.000 | 65.784 115.048 |
| C(hr)[T.17] | 55.0003 | 12.566 | 4.377 | 0.000 | 30.369 79.631 |
| C(hr)[T.18] | 51.7992 | 12.566 | 4.122 | 0.000 | 27.168 76.431 |
| C(hr)[T.19] | 36.9972 | 12.567 | 2.944 | 0.003 | 12.365 61.630 |
| C(hr)[T.20] | 20.9193 | 12.566 | 1.665 | 0.096 | -3.712 45.550 |
| C(hr)[T.21] | 5.5882 | 12.566 | 0.445 | 0.657 | -19.043 30.219 |
| C(hr)[T.22] | -4.5165 | 12.567 | -0.359 | 0.719 | -29.149 20.116 |
| C(hr)[T.23] | -3.9998 | 12.566 | -0.318 | 0.750 | -28.631 20.631 |
| C(yr)[T.1] | 65.0000 | 0.633 | 102.642 | 0.000 | 63.759 66.241 |
| C(mnth)[T.2] | -2.6280 | 13.246 | -0.198 | 0.843 | -28.592 23.336 |
| C(mnth)[T.3] | 14.0001 | 13.461 | 1.040 | 0.298 | -12.384 40.384 |
| C(mnth)[T.4] | 15.2190 | 12.879 | 1.182 | 0.237 | -10.025 40.463 |
| C(mnth)[T.5] | 62.0001 | 13.053 | 4.750 | 0.000 | 36.415 87.585 |
| C(mnth)[T.6] | 74.0001 | 13.458 | 5.499 | 0.000 | 47.621 100.380 |
| C(mnth)[T.7] | 95.0001 | 12.715 | 7.472 | 0.000 | 70.078 119.922 |
| C(mnth)[T.8] | 69.0001 | 13.955 | 4.944 | 0.000 | 41.646 96.354 |
| C(mnth)[T.9] | 82.9788 | 12.877 | 6.444 | 0.000 | 57.739 108.219 |
| C(mnth)[T.10] | 65.0001 | 12.877 | 5.048 | 0.000 | 39.760 90.240 |
| C(mnth)[T.11] | 26.5777 | 12.876 | 2.064 | 0.039 | 1.339 51.817 |
| C(mnth)[T.12] | 27.0001 | 12.716 | 2.123 | 0.034 | 2.075 51.926 |
| C(workingday)[T.1] | -33.3900 | 11.168 | -2.990 | 0.003 | -55.281 -11.499 |
| C(weathersit)[T.2] | -13.0000 | 0.753 | -17.263 | 0.000 | -14.476 -11.524 |
| C(weathersit)[T.3] | -65.0000 | 1.196 | -54.329 | 0.000 | -67.345 -62.655 |
| C(weathersit)[T.4] | -63.0000 | 24.458 | -2.576 | 0.010 | -110.940 -15.060 |
| C(mnth)[T.2]:C(hr)[T.1] | 10.6641 | 18.766 | 0.568 | 0.570 | -26.119 47.447 |
| C(mnth)[T.3]:C(hr)[T.1] | 3.0359 | 19.066 | 0.159 | 0.873 | -34.335 40.407 |
| C(mnth)[T.4]:C(hr)[T.1] | -7.4872 | 18.244 | -0.410 | 0.682 | -43.248 28.274 |
| C(mnth)[T.5]:C(hr)[T.1] | -18.9641 | 18.493 | -1.025 | 0.305 | -55.212 17.283 |
| C(mnth)[T.6]:C(hr)[T.1] | -14.9641 | 19.065 | -0.785 | 0.433 | -52.334 22.406 |
| C(mnth)[T.7]:C(hr)[T.1] | -32.9641 | 18.015 | -1.830 | 0.067 | -68.276 2.348 |
| C(mnth)[T.8]:C(hr)[T.1] | -18.9641 | 19.768 | -0.959 | 0.337 | -57.711 19.783 |
| C(mnth)[T.9]:C(hr)[T.1] | -32.5719 | 18.244 | -1.785 | 0.074 | -68.331 3.188 |
| C(mnth)[T.10]:C(hr)[T.1] | -9.9651 | 18.244 | -0.546 | 0.585 | -45.724 25.794 |
| C(mnth)[T.11]:C(hr)[T.1] | -9.4519 | 18.244 | -0.518 | 0.604 | -45.212 26.308 |
| C(mnth)[T.12]:C(hr)[T.1] | 0.0359 | 18.016 | 0.002 | 0.998 | -35.276 35.348 |
| C(mnth)[T.2]:C(hr)[T.2] | 3.9336 | 18.732 | 0.210 | 0.834 | -32.783 40.651 |
| C(mnth)[T.3]:C(hr)[T.2] | 2.9999 | 19.388 | 0.155 | 0.877 | -35.003 41.003 |
| C(mnth)[T.4]:C(hr)[T.2] | -4.9842 | 18.211 | -0.274 | 0.784 | -40.680 30.712 |
| C(mnth)[T.5]:C(hr)[T.2] | -32.0001 | 18.460 | -1.734 | 0.083 | -68.183 4.183 |
| C(mnth)[T.6]:C(hr)[T.2] | -32.0001 | 19.033 | -1.681 | 0.093 | -69.306 5.306 |
| C(mnth)[T.7]:C(hr)[T.2] | -48.0001 | 17.982 | -2.669 | 0.008 | -83.246 -12.754 |
| C(mnth)[T.8]:C(hr)[T.2] | -16.0001 | 19.736 | -0.811 | 0.418 | -54.685 22.685 |
| C(mnth)[T.9]:C(hr)[T.2] | -54.5139 | 18.210 | -2.994 | 0.003 | -90.208 -18.820 |
| C(mnth)[T.10]:C(hr)[T.2] | -30.3806 | 18.210 | -1.668 | 0.095 | -66.074 5.313 |
| C(mnth)[T.11]:C(hr)[T.2] | -28.8690 | 18.210 | -1.585 | 0.113 | -64.563 6.825 |
| C(mnth)[T.12]:C(hr)[T.2] | -16.0001 | 17.981 | -0.890 | 0.374 | -51.245 19.245 |
| C(mnth)[T.2]:C(hr)[T.3] | 5.6535 | 18.832 | 0.300 | 0.764 | -31.260 42.567 |
| C(mnth)[T.3]:C(hr)[T.3] | -12.0001 | 19.132 | -0.627 | 0.531 | -49.500 25.500 |
| C(mnth)[T.4]:C(hr)[T.3] | -20.9992 | 18.314 | -1.147 | 0.252 | -56.896 14.898 |
| C(mnth)[T.5]:C(hr)[T.3] | -52.0001 | 18.561 | -2.802 | 0.005 | -88.382 -15.618 |
| C(mnth)[T.6]:C(hr)[T.3] | -71.0001 | 19.132 | -3.711 | 0.000 | -108.500 -33.500 |
| C(mnth)[T.7]:C(hr)[T.3] | -75.0001 | 18.086 | -4.147 | 0.000 | -110.450 -39.550 |
| C(mnth)[T.8]:C(hr)[T.3] | -53.0001 | 19.830 | -2.673 | 0.008 | -91.870 -14.130 |
| C(mnth)[T.9]:C(hr)[T.3] | -95.5563 | 18.313 | -5.218 | 0.000 | -131.453 -59.660 |
| C(mnth)[T.10]:C(hr)[T.3] | -50.0001 | 18.313 | -2.730 | 0.006 | -85.895 -14.105 |
| C(mnth)[T.11]:C(hr)[T.3] | -37.5650 | 18.313 | -2.051 | 0.040 | -73.460 -1.670 |
| C(mnth)[T.12]:C(hr)[T.3] | -36.0001 | 18.325 | -1.965 | 0.049 | -71.919 -0.082 |
| C(mnth)[T.2]:C(hr)[T.4] | 2.6280 | 18.983 | 0.138 | 0.890 | -34.580 39.836 |
| C(mnth)[T.3]:C(hr)[T.4] | -53.0001 | 19.132 | -2.770 | 0.006 | -90.501 -15.499 |
| C(mnth)[T.4]:C(hr)[T.4] | -31.1082 | 18.314 | -1.699 | 0.089 | -67.005 4.789 |
| C(mnth)[T.5]:C(hr)[T.4] | -58.0001 | 18.561 | -3.125 | 0.002 | -94.382 -21.618 |
| C(mnth)[T.6]:C(hr)[T.4] | -108.0001 | 19.132 | -5.645 | 0.000 | -145.501 -70.499 |
| C(mnth)[T.7]:C(hr)[T.4] | -90.0001 | 18.086 | -4.976 | 0.000 | -125.450 -54.550 |
| C(mnth)[T.8]:C(hr)[T.4] | -96.0001 | 19.831 | -4.841 | 0.000 | -134.871 -57.130 |
| C(mnth)[T.9]:C(hr)[T.4] | -121.3832 | 18.314 | -6.628 | 0.000 | -157.280 -85.486 |
| C(mnth)[T.10]:C(hr)[T.4] | -60.0001 | 18.314 | -3.276 | 0.001 | -95.897 -24.103 |
| C(mnth)[T.11]:C(hr)[T.4] | -50.4165 | 18.313 | -2.753 | 0.006 | -86.312 -14.521 |
| C(mnth)[T.12]:C(hr)[T.4] | -68.0001 | 18.200 | -3.736 | 0.000 | -103.674 -32.326 |
| C(mnth)[T.2]:C(hr)[T.5] | 2.6280 | 19.562 | 0.134 | 0.893 | -35.716 40.972 |
| C(mnth)[T.3]:C(hr)[T.5] | -61.0001 | 19.708 | -3.095 | 0.002 | -99.629 -22.371 |
| C(mnth)[T.4]:C(hr)[T.5] | -32.3742 | 18.552 | -1.745 | 0.081 | -68.738 3.990 |
| C(mnth)[T.5]:C(hr)[T.5] | -57.0001 | 18.795 | -3.033 | 0.002 | -93.841 -20.159 |
| C(mnth)[T.6]:C(hr)[T.5] | -115.0001 | 19.358 | -5.941 | 0.000 | -152.944 -77.056 |
| C(mnth)[T.7]:C(hr)[T.5] | -88.0001 | 18.325 | -4.802 | 0.000 | -123.920 -52.081 |
| C(mnth)[T.8]:C(hr)[T.5] | -108.0001 | 20.050 | -5.386 | 0.000 | -147.301 -68.699 |
| C(mnth)[T.9]:C(hr)[T.5] | -101.6992 | 18.551 | -5.482 | 0.000 | -138.062 -65.337 |
| C(mnth)[T.10]:C(hr)[T.5] | -62.9580 | 18.550 | -3.394 | 0.001 | -99.318 -26.598 |
| C(mnth)[T.11]:C(hr)[T.5] | -50.5196 | 18.550 | -2.724 | 0.006 | -86.879 -14.161 |
| C(mnth)[T.12]:C(hr)[T.5] | -71.0001 | 18.325 | -3.874 | 0.000 | -106.920 -35.080 |
| C(mnth)[T.2]:C(hr)[T.6] | 2.6434 | 18.834 | 0.140 | 0.888 | -34.273 39.560 |
| C(mnth)[T.3]:C(hr)[T.6] | -37.0001 | 19.132 | -1.934 | 0.053 | -74.500 0.500 |
| C(mnth)[T.4]:C(hr)[T.6] | -4.0837 | 18.316 | -0.223 | 0.824 | -39.985 31.817 |
| C(mnth)[T.5]:C(hr)[T.6] | -46.0001 | 18.561 | -2.478 | 0.013 | -82.381 -9.619 |
| C(mnth)[T.6]:C(hr)[T.6] | -61.0001 | 19.132 | -3.188 | 0.001 | -98.501 -23.500 |
| C(mnth)[T.7]:C(hr)[T.6] | -81.0001 | 18.086 | -4.479 | 0.000 | -116.450 -45.550 |
| C(mnth)[T.8]:C(hr)[T.6] | -86.0001 | 19.831 | -4.337 | 0.000 | -124.871 -47.129 |
| C(mnth)[T.9]:C(hr)[T.6] | -102.0070 | 18.314 | -5.570 | 0.000 | -137.904 -66.110 |
| C(mnth)[T.10]:C(hr)[T.6] | -56.0001 | 18.314 | -3.058 | 0.002 | -91.897 -20.103 |
| C(mnth)[T.11]:C(hr)[T.6] | -21.5777 | 18.313 | -1.178 | 0.239 | -57.473 14.318 |
| C(mnth)[T.12]:C(hr)[T.6] | -27.0001 | 18.086 | -1.493 | 0.135 | -62.451 8.451 |
| C(mnth)[T.2]:C(hr)[T.7] | 3.2666 | 18.732 | 0.174 | 0.862 | -33.451 39.984 |
| C(mnth)[T.3]:C(hr)[T.7] | -2.1018 | 19.033 | -0.110 | 0.912 | -39.409 35.206 |
| C(mnth)[T.4]:C(hr)[T.7] | 9.5862 | 18.211 | 0.526 | 0.599 | -26.109 45.281 |
| C(mnth)[T.5]:C(hr)[T.7] | -28.1018 | 18.459 | -1.522 | 0.128 | -64.284 8.080 |
| C(mnth)[T.6]:C(hr)[T.7] | -49.1018 | 19.033 | -2.580 | 0.010 | -86.408 -11.795 |
| C(mnth)[T.7]:C(hr)[T.7] | -62.1018 | 17.981 | -3.454 | 0.001 | -97.347 -26.856 |
| C(mnth)[T.8]:C(hr)[T.7] | -39.3626 | 19.551 | -2.013 | 0.044 | -77.685 -1.040 |
| C(mnth)[T.9]:C(hr)[T.7] | -70.1323 | 18.210 | -3.851 | 0.000 | -105.827 -34.438 |
| C(mnth)[T.10]:C(hr)[T.7] | -32.2592 | 18.210 | -1.772 | 0.076 | -67.952 3.433 |
| C(mnth)[T.11]:C(hr)[T.7] | -8.6980 | 18.210 | -0.478 | 0.633 | -44.391 26.995 |
| C(mnth)[T.12]:C(hr)[T.7] | -19.1018 | 17.982 | -1.062 | 0.288 | -54.348 16.144 |
| C(mnth)[T.2]:C(hr)[T.8] | 18.1143 | 18.732 | 0.967 | 0.334 | -18.603 54.831 |
| C(mnth)[T.3]:C(hr)[T.8] | 17.8099 | 19.033 | 0.936 | 0.349 | -19.496 55.116 |
| C(mnth)[T.4]:C(hr)[T.8] | 38.5909 | 18.211 | 2.119 | 0.034 | 2.896 74.286 |
| C(mnth)[T.5]:C(hr)[T.8] | 25.8099 | 18.459 | 1.398 | 0.162 | -10.371 61.991 |
| C(mnth)[T.6]:C(hr)[T.8] | 27.8099 | 19.033 | 1.461 | 0.144 | -9.496 65.116 |
| C(mnth)[T.7]:C(hr)[T.8] | -17.1901 | 17.981 | -0.956 | 0.339 | -52.436 18.055 |
| C(mnth)[T.8]:C(hr)[T.8] | 8.7346 | 19.551 | 0.447 | 0.655 | -29.588 47.057 |
| C(mnth)[T.9]:C(hr)[T.8] | 10.2392 | 18.210 | 0.562 | 0.574 | -25.454 45.932 |
| C(mnth)[T.10]:C(hr)[T.8] | 26.0027 | 18.210 | 1.428 | 0.153 | -9.691 61.697 |
| C(mnth)[T.11]:C(hr)[T.8] | 38.3079 | 18.210 | 2.104 | 0.035 | 2.615 74.001 |
| C(mnth)[T.12]:C(hr)[T.8] | -0.1901 | 17.981 | -0.011 | 0.992 | -35.435 35.055 |
| C(mnth)[T.2]:C(hr)[T.9] | 27.5039 | 18.733 | 1.468 | 0.142 | -9.214 64.222 |
| C(mnth)[T.3]:C(hr)[T.9] | 31.3778 | 19.033 | 1.649 | 0.099 | -5.929 68.684 |
| C(mnth)[T.4]:C(hr)[T.9] | 101.6528 | 18.211 | 5.582 | 0.000 | 65.958 137.348 |
| C(mnth)[T.5]:C(hr)[T.9] | 94.3778 | 18.459 | 5.113 | 0.000 | 58.196 130.560 |
| C(mnth)[T.6]:C(hr)[T.9] | 103.3778 | 19.033 | 5.432 | 0.000 | 66.072 140.684 |
| C(mnth)[T.7]:C(hr)[T.9] | 53.3778 | 17.981 | 2.969 | 0.003 | 18.133 88.623 |
| C(mnth)[T.8]:C(hr)[T.9] | 99.9853 | 19.551 | 5.114 | 0.000 | 61.663 138.308 |
| C(mnth)[T.9]:C(hr)[T.9] | 97.4020 | 18.210 | 5.349 | 0.000 | 61.709 133.095 |
| C(mnth)[T.10]:C(hr)[T.9] | 103.3771 | 18.210 | 5.677 | 0.000 | 67.684 139.070 |
| C(mnth)[T.11]:C(hr)[T.9] | 82.7724 | 18.210 | 4.546 | 0.000 | 47.080 118.465 |
| C(mnth)[T.12]:C(hr)[T.9] | 21.3778 | 17.981 | 1.189 | 0.235 | -13.868 56.623 |
| C(mnth)[T.2]:C(hr)[T.10] | 38.0094 | 18.733 | 2.029 | 0.042 | 1.290 74.728 |
| C(mnth)[T.3]:C(hr)[T.10] | 56.4406 | 19.033 | 2.965 | 0.003 | 19.134 93.747 |
| C(mnth)[T.4]:C(hr)[T.10] | 142.3693 | 18.212 | 7.817 | 0.000 | 106.671 178.067 |
| C(mnth)[T.5]:C(hr)[T.10] | 166.4406 | 18.460 | 9.016 | 0.000 | 130.257 202.624 |
| C(mnth)[T.6]:C(hr)[T.10] | 195.4406 | 19.033 | 10.268 | 0.000 | 158.133 232.748 |
| C(mnth)[T.7]:C(hr)[T.10] | 106.4406 | 17.982 | 5.919 | 0.000 | 71.194 141.687 |
| C(mnth)[T.8]:C(hr)[T.10] | 160.4492 | 19.552 | 8.206 | 0.000 | 122.125 198.773 |
| C(mnth)[T.9]:C(hr)[T.10] | 182.4802 | 18.210 | 10.021 | 0.000 | 146.786 218.174 |
| C(mnth)[T.10]:C(hr)[T.10] | 157.7657 | 18.210 | 8.664 | 0.000 | 122.073 193.459 |
| C(mnth)[T.11]:C(hr)[T.10] | 131.0214 | 18.210 | 7.195 | 0.000 | 95.327 166.716 |
| C(mnth)[T.12]:C(hr)[T.10] | 70.4406 | 17.983 | 3.917 | 0.000 | 35.192 105.690 |
| C(mnth)[T.2]:C(hr)[T.11] | 37.3107 | 18.733 | 1.992 | 0.046 | 0.593 74.028 |
| C(mnth)[T.3]:C(hr)[T.11] | 89.0014 | 19.033 | 4.676 | 0.000 | 51.695 126.308 |
| C(mnth)[T.4]:C(hr)[T.11] | 197.7819 | 18.211 | 10.860 | 0.000 | 162.086 233.478 |
| C(mnth)[T.5]:C(hr)[T.11] | 208.0014 | 18.460 | 11.268 | 0.000 | 171.817 244.185 |
| C(mnth)[T.6]:C(hr)[T.11] | 237.0014 | 19.033 | 12.452 | 0.000 | 199.695 274.308 |
| C(mnth)[T.7]:C(hr)[T.11] | 169.0014 | 17.981 | 9.399 | 0.000 | 133.756 204.247 |
| C(mnth)[T.8]:C(hr)[T.11] | 176.7568 | 19.552 | 9.040 | 0.000 | 138.432 215.081 |
| C(mnth)[T.9]:C(hr)[T.11] | 259.0882 | 18.210 | 14.228 | 0.000 | 223.395 294.781 |
| C(mnth)[T.10]:C(hr)[T.11] | 216.8205 | 18.210 | 11.907 | 0.000 | 181.127 252.514 |
| C(mnth)[T.11]:C(hr)[T.11] | 168.4818 | 18.210 | 9.252 | 0.000 | 132.789 204.175 |
| C(mnth)[T.12]:C(hr)[T.11] | 81.0014 | 17.982 | 4.505 | 0.000 | 45.755 116.248 |
| C(mnth)[T.2]:C(hr)[T.12] | 69.7855 | 18.732 | 3.725 | 0.000 | 33.068 106.503 |
| C(mnth)[T.3]:C(hr)[T.12] | 118.5498 | 19.034 | 6.228 | 0.000 | 81.241 155.858 |
| C(mnth)[T.4]:C(hr)[T.12] | 213.6897 | 18.212 | 11.733 | 0.000 | 177.991 249.388 |
| C(mnth)[T.5]:C(hr)[T.12] | 283.5498 | 18.460 | 15.360 | 0.000 | 247.367 319.733 |
| C(mnth)[T.6]:C(hr)[T.12] | 248.5498 | 19.033 | 13.059 | 0.000 | 211.243 285.856 |
| C(mnth)[T.7]:C(hr)[T.12] | 194.5498 | 17.982 | 10.819 | 0.000 | 159.304 229.796 |
| C(mnth)[T.8]:C(hr)[T.12] | 230.0631 | 19.554 | 11.766 | 0.000 | 191.735 268.391 |
| C(mnth)[T.9]:C(hr)[T.12] | 290.1920 | 18.210 | 15.936 | 0.000 | 254.498 325.886 |
| C(mnth)[T.10]:C(hr)[T.12] | 259.5508 | 18.210 | 14.253 | 0.000 | 223.858 295.244 |
| C(mnth)[T.11]:C(hr)[T.12] | 200.9828 | 18.210 | 11.037 | 0.000 | 165.290 236.676 |
| C(mnth)[T.12]:C(hr)[T.12] | 121.5498 | 17.983 | 6.759 | 0.000 | 86.302 156.798 |
| C(mnth)[T.2]:C(hr)[T.13] | 79.1437 | 18.733 | 4.225 | 0.000 | 42.424 115.863 |
| C(mnth)[T.3]:C(hr)[T.13] | 152.8805 | 19.035 | 8.032 | 0.000 | 115.570 190.191 |
| C(mnth)[T.4]:C(hr)[T.13] | 234.3512 | 18.214 | 12.867 | 0.000 | 198.650 270.052 |
| C(mnth)[T.5]:C(hr)[T.13] | 289.8805 | 18.460 | 15.703 | 0.000 | 253.697 326.065 |
| C(mnth)[T.6]:C(hr)[T.13] | 260.8806 | 19.033 | 13.707 | 0.000 | 223.574 298.187 |
| C(mnth)[T.7]:C(hr)[T.13] | 212.8805 | 17.981 | 11.839 | 0.000 | 177.635 248.126 |
| C(mnth)[T.8]:C(hr)[T.13] | 256.3670 | 19.553 | 13.112 | 0.000 | 218.041 294.693 |
| C(mnth)[T.9]:C(hr)[T.13] | 301.1953 | 18.210 | 16.540 | 0.000 | 265.501 336.889 |
| C(mnth)[T.10]:C(hr)[T.13] | 242.8178 | 18.210 | 13.335 | 0.000 | 207.125 278.511 |
| C(mnth)[T.11]:C(hr)[T.13] | 219.7581 | 18.210 | 12.068 | 0.000 | 184.065 255.451 |
| C(mnth)[T.12]:C(hr)[T.13] | 114.8805 | 17.983 | 6.388 | 0.000 | 79.632 150.129 |
| C(mnth)[T.2]:C(hr)[T.14] | 69.6140 | 18.732 | 3.716 | 0.000 | 32.897 106.331 |
| C(mnth)[T.3]:C(hr)[T.14] | 146.9416 | 19.033 | 7.720 | 0.000 | 109.634 184.249 |
| C(mnth)[T.4]:C(hr)[T.14] | 242.2353 | 18.212 | 13.301 | 0.000 | 206.538 277.933 |
| C(mnth)[T.5]:C(hr)[T.14] | 256.9416 | 18.460 | 13.919 | 0.000 | 220.759 293.124 |
| C(mnth)[T.6]:C(hr)[T.14] | 250.9416 | 19.033 | 13.185 | 0.000 | 213.635 288.248 |
| C(mnth)[T.7]:C(hr)[T.14] | 165.9416 | 17.982 | 9.228 | 0.000 | 130.696 201.187 |
| C(mnth)[T.8]:C(hr)[T.14] | 188.5331 | 19.553 | 9.642 | 0.000 | 150.207 226.859 |
| C(mnth)[T.9]:C(hr)[T.14] | 255.1234 | 18.210 | 14.010 | 0.000 | 219.431 290.816 |
| C(mnth)[T.10]:C(hr)[T.14] | 233.3809 | 18.211 | 12.816 | 0.000 | 197.686 269.076 |
| C(mnth)[T.11]:C(hr)[T.14] | 218.3640 | 18.210 | 11.992 | 0.000 | 182.671 254.057 |
| C(mnth)[T.12]:C(hr)[T.14] | 91.9416 | 17.982 | 5.113 | 0.000 | 56.694 127.189 |
| C(mnth)[T.2]:C(hr)[T.15] | 57.4040 | 18.732 | 3.064 | 0.002 | 20.687 94.121 |
| C(mnth)[T.3]:C(hr)[T.15] | 170.7761 | 19.034 | 8.972 | 0.000 | 133.467 208.085 |
| C(mnth)[T.4]:C(hr)[T.15] | 232.6624 | 18.212 | 12.775 | 0.000 | 196.965 268.360 |
| C(mnth)[T.5]:C(hr)[T.15] | 248.7761 | 18.459 | 13.477 | 0.000 | 212.595 284.957 |
| C(mnth)[T.6]:C(hr)[T.15] | 212.7761 | 19.033 | 11.179 | 0.000 | 175.469 250.083 |
| C(mnth)[T.7]:C(hr)[T.15] | 157.7761 | 17.982 | 8.774 | 0.000 | 122.530 193.022 |
| C(mnth)[T.8]:C(hr)[T.15] | 197.7910 | 19.552 | 10.116 | 0.000 | 159.467 236.115 |
| C(mnth)[T.9]:C(hr)[T.15] | 268.7621 | 18.210 | 14.759 | 0.000 | 233.069 304.455 |
| C(mnth)[T.10]:C(hr)[T.15] | 208.5532 | 18.210 | 11.453 | 0.000 | 172.860 244.247 |
| C(mnth)[T.11]:C(hr)[T.15] | 180.3344 | 18.210 | 9.903 | 0.000 | 144.641 216.027 |
| C(mnth)[T.12]:C(hr)[T.15] | 77.7761 | 17.983 | 4.325 | 0.000 | 42.528 113.025 |
| C(mnth)[T.2]:C(hr)[T.16] | 35.2120 | 18.734 | 1.880 | 0.060 | -1.509 71.932 |
| C(mnth)[T.3]:C(hr)[T.16] | 127.5838 | 19.037 | 6.702 | 0.000 | 90.270 164.898 |
| C(mnth)[T.4]:C(hr)[T.16] | 225.3545 | 18.212 | 12.374 | 0.000 | 189.656 261.053 |
| C(mnth)[T.5]:C(hr)[T.16] | 259.5839 | 18.459 | 14.063 | 0.000 | 223.402 295.766 |
| C(mnth)[T.6]:C(hr)[T.16] | 259.5839 | 19.033 | 13.639 | 0.000 | 222.278 296.890 |
| C(mnth)[T.7]:C(hr)[T.16] | 162.5839 | 17.982 | 9.042 | 0.000 | 127.338 197.830 |
| C(mnth)[T.8]:C(hr)[T.16] | 174.2274 | 19.553 | 8.911 | 0.000 | 135.902 212.553 |
| C(mnth)[T.9]:C(hr)[T.16] | 259.9633 | 18.210 | 14.276 | 0.000 | 224.269 295.658 |
| C(mnth)[T.10]:C(hr)[T.16] | 235.9643 | 18.210 | 12.958 | 0.000 | 200.271 271.658 |
| C(mnth)[T.11]:C(hr)[T.16] | 183.1954 | 18.210 | 10.060 | 0.000 | 147.503 218.888 |
| C(mnth)[T.12]:C(hr)[T.16] | 80.5839 | 17.984 | 4.481 | 0.000 | 45.334 115.834 |
| C(mnth)[T.2]:C(hr)[T.17] | 60.0806 | 18.733 | 3.207 | 0.001 | 23.361 96.800 |
| C(mnth)[T.3]:C(hr)[T.17] | 147.9997 | 19.037 | 7.774 | 0.000 | 110.685 185.314 |
| C(mnth)[T.4]:C(hr)[T.17] | 249.7811 | 18.211 | 13.716 | 0.000 | 214.086 285.476 |
| C(mnth)[T.5]:C(hr)[T.17] | 271.9997 | 18.460 | 14.735 | 0.000 | 235.817 308.183 |
| C(mnth)[T.6]:C(hr)[T.17] | 280.9997 | 19.033 | 14.764 | 0.000 | 243.693 318.306 |
| C(mnth)[T.7]:C(hr)[T.17] | 188.9997 | 17.983 | 10.510 | 0.000 | 153.752 224.248 |
| C(mnth)[T.8]:C(hr)[T.17] | 180.8557 | 19.553 | 9.249 | 0.000 | 142.529 219.182 |
| C(mnth)[T.9]:C(hr)[T.17] | 264.0486 | 18.211 | 14.500 | 0.000 | 228.354 299.743 |
| C(mnth)[T.10]:C(hr)[T.17] | 261.1794 | 18.210 | 14.342 | 0.000 | 225.485 296.874 |
| C(mnth)[T.11]:C(hr)[T.17] | 144.6360 | 18.210 | 7.943 | 0.000 | 108.943 180.329 |
| C(mnth)[T.12]:C(hr)[T.17] | 56.9997 | 17.984 | 3.169 | 0.002 | 21.750 92.250 |
| C(mnth)[T.2]:C(hr)[T.18] | 22.8263 | 18.733 | 1.219 | 0.223 | -13.891 59.544 |
| C(mnth)[T.3]:C(hr)[T.18] | 76.2008 | 19.034 | 4.003 | 0.000 | 38.891 113.510 |
| C(mnth)[T.4]:C(hr)[T.18] | 184.9832 | 18.211 | 10.158 | 0.000 | 149.288 220.678 |
| C(mnth)[T.5]:C(hr)[T.18] | 220.2008 | 18.459 | 11.929 | 0.000 | 184.019 256.383 |
| C(mnth)[T.6]:C(hr)[T.18] | 244.2008 | 19.034 | 12.830 | 0.000 | 206.892 281.510 |
| C(mnth)[T.7]:C(hr)[T.18] | 141.2008 | 17.981 | 7.853 | 0.000 | 105.955 176.446 |
| C(mnth)[T.8]:C(hr)[T.18] | 180.2008 | 19.736 | 9.131 | 0.000 | 141.517 218.885 |
| C(mnth)[T.9]:C(hr)[T.18] | 231.3732 | 18.210 | 12.706 | 0.000 | 195.680 267.067 |
| C(mnth)[T.10]:C(hr)[T.18] | 207.2009 | 18.210 | 11.378 | 0.000 | 171.507 242.894 |
| C(mnth)[T.11]:C(hr)[T.18] | 100.6219 | 18.210 | 5.526 | 0.000 | 64.929 136.315 |
| C(mnth)[T.12]:C(hr)[T.18] | 35.2008 | 17.982 | 1.958 | 0.050 | -0.047 70.448 |
| C(mnth)[T.2]:C(hr)[T.19] | 8.5749 | 18.733 | 0.458 | 0.647 | -28.144 45.294 |
| C(mnth)[T.3]:C(hr)[T.19] | 58.0028 | 19.035 | 3.047 | 0.002 | 20.691 95.314 |
| C(mnth)[T.4]:C(hr)[T.19] | 133.8035 | 18.211 | 7.347 | 0.000 | 98.107 169.500 |
| C(mnth)[T.5]:C(hr)[T.19] | 178.0028 | 18.459 | 9.643 | 0.000 | 141.821 214.185 |
| C(mnth)[T.6]:C(hr)[T.19] | 195.0028 | 19.034 | 10.245 | 0.000 | 157.694 232.312 |
| C(mnth)[T.7]:C(hr)[T.19] | 147.0028 | 17.982 | 8.175 | 0.000 | 111.755 182.250 |
| C(mnth)[T.8]:C(hr)[T.19] | 152.0028 | 19.736 | 7.702 | 0.000 | 113.318 190.688 |
| C(mnth)[T.9]:C(hr)[T.19] | 174.6231 | 18.211 | 9.589 | 0.000 | 138.929 210.318 |
| C(mnth)[T.10]:C(hr)[T.19] | 107.6903 | 18.212 | 5.913 | 0.000 | 71.992 143.388 |
| C(mnth)[T.11]:C(hr)[T.19] | 75.2118 | 18.210 | 4.130 | 0.000 | 39.518 110.906 |
| C(mnth)[T.12]:C(hr)[T.19] | 17.0028 | 17.983 | 0.946 | 0.344 | -18.245 52.251 |
| C(mnth)[T.2]:C(hr)[T.20] | 4.7181 | 18.733 | 0.252 | 0.801 | -32.000 41.437 |
| C(mnth)[T.3]:C(hr)[T.20] | 27.0807 | 19.035 | 1.423 | 0.155 | -10.229 64.391 |
| C(mnth)[T.4]:C(hr)[T.20] | 82.8730 | 18.211 | 4.551 | 0.000 | 47.177 118.569 |
| C(mnth)[T.5]:C(hr)[T.20] | 112.0807 | 18.459 | 6.072 | 0.000 | 75.898 148.263 |
| C(mnth)[T.6]:C(hr)[T.20] | 148.0807 | 19.033 | 7.780 | 0.000 | 110.774 185.387 |
| C(mnth)[T.7]:C(hr)[T.20] | 122.0807 | 17.982 | 6.789 | 0.000 | 86.835 157.326 |
| C(mnth)[T.8]:C(hr)[T.20] | 88.0807 | 19.736 | 4.463 | 0.000 | 49.396 126.766 |
| C(mnth)[T.9]:C(hr)[T.20] | 80.4255 | 18.211 | 4.416 | 0.000 | 44.731 116.120 |
| C(mnth)[T.10]:C(hr)[T.20] | 69.0807 | 18.210 | 3.794 | 0.000 | 33.388 104.773 |
| C(mnth)[T.11]:C(hr)[T.20] | 48.4967 | 18.210 | 2.663 | 0.008 | 12.804 84.190 |
| C(mnth)[T.12]:C(hr)[T.20] | 0.0807 | 17.982 | 0.004 | 0.996 | -35.166 35.327 |
| C(mnth)[T.2]:C(hr)[T.21] | 14.6617 | 18.734 | 0.783 | 0.434 | -22.059 51.382 |
| C(mnth)[T.3]:C(hr)[T.21] | 38.4118 | 19.034 | 2.018 | 0.044 | 1.103 75.721 |
| C(mnth)[T.4]:C(hr)[T.21] | 57.1793 | 18.211 | 3.140 | 0.002 | 21.484 92.874 |
| C(mnth)[T.5]:C(hr)[T.21] | 76.4118 | 18.459 | 4.140 | 0.000 | 40.230 112.594 |
| C(mnth)[T.6]:C(hr)[T.21] | 92.4118 | 19.033 | 4.855 | 0.000 | 55.105 129.719 |
| C(mnth)[T.7]:C(hr)[T.21] | 80.4118 | 17.982 | 4.472 | 0.000 | 45.166 115.658 |
| C(mnth)[T.8]:C(hr)[T.21] | 56.4118 | 19.736 | 2.858 | 0.004 | 17.728 95.096 |
| C(mnth)[T.9]:C(hr)[T.21] | 40.3403 | 18.210 | 2.215 | 0.027 | 4.647 76.034 |
| C(mnth)[T.10]:C(hr)[T.21] | 28.7218 | 18.210 | 1.577 | 0.115 | -6.972 64.415 |
| C(mnth)[T.11]:C(hr)[T.21] | 35.4219 | 18.210 | 1.945 | 0.052 | -0.271 71.115 |
| C(mnth)[T.12]:C(hr)[T.21] | -4.5882 | 17.982 | -0.255 | 0.799 | -39.834 30.658 |
| C(mnth)[T.2]:C(hr)[T.22] | 28.1447 | 18.734 | 1.502 | 0.133 | -8.575 64.865 |
| C(mnth)[T.3]:C(hr)[T.22] | 17.5165 | 19.035 | 0.920 | 0.357 | -19.794 54.827 |
| C(mnth)[T.4]:C(hr)[T.22] | 35.2896 | 18.213 | 1.938 | 0.053 | -0.410 70.990 |
| C(mnth)[T.5]:C(hr)[T.22] | 35.5165 | 18.461 | 1.924 | 0.054 | -0.668 71.701 |
| C(mnth)[T.6]:C(hr)[T.22] | 58.5165 | 19.034 | 3.074 | 0.002 | 21.209 95.824 |
| C(mnth)[T.7]:C(hr)[T.22] | 40.5165 | 17.982 | 2.253 | 0.024 | 5.270 75.763 |
| C(mnth)[T.8]:C(hr)[T.22] | 27.5165 | 19.735 | 1.394 | 0.163 | -11.167 66.200 |
| C(mnth)[T.9]:C(hr)[T.22] | 22.3440 | 18.210 | 1.227 | 0.220 | -13.350 58.038 |
| C(mnth)[T.10]:C(hr)[T.22] | 31.0231 | 18.210 | 1.704 | 0.088 | -4.670 66.716 |
| C(mnth)[T.11]:C(hr)[T.22] | 24.2837 | 18.210 | 1.334 | 0.182 | -11.410 59.977 |
| C(mnth)[T.12]:C(hr)[T.22] | -3.4835 | 17.983 | -0.194 | 0.846 | -38.731 31.764 |
| C(mnth)[T.2]:C(hr)[T.23] | 8.6941 | 18.732 | 0.464 | 0.643 | -28.023 45.411 |
| C(mnth)[T.3]:C(hr)[T.23] | 6.9998 | 19.034 | 0.368 | 0.713 | -30.309 44.308 |
| C(mnth)[T.4]:C(hr)[T.23] | 17.7809 | 18.210 | 0.976 | 0.329 | -17.914 53.475 |
| C(mnth)[T.5]:C(hr)[T.23] | 13.9998 | 18.460 | 0.758 | 0.448 | -22.183 50.183 |
| C(mnth)[T.6]:C(hr)[T.23] | 12.9998 | 19.033 | 0.683 | 0.495 | -24.307 50.306 |
| C(mnth)[T.7]:C(hr)[T.23] | -5.0002 | 17.981 | -0.278 | 0.781 | -40.245 30.245 |
| C(mnth)[T.8]:C(hr)[T.23] | 2.9998 | 19.736 | 0.152 | 0.879 | -35.684 41.684 |
| C(mnth)[T.9]:C(hr)[T.23] | -6.2563 | 18.210 | -0.344 | 0.731 | -41.950 29.437 |
| C(mnth)[T.10]:C(hr)[T.23] | -23.0007 | 18.210 | -1.263 | 0.207 | -58.694 12.693 |
| C(mnth)[T.11]:C(hr)[T.23] | 5.8535 | 18.210 | 0.321 | 0.748 | -29.839 41.546 |
| C(mnth)[T.12]:C(hr)[T.23] | -16.0002 | 17.982 | -0.890 | 0.374 | -51.246 19.246 |
| C(workingday)[T.1]:C(hr)[T.1] | -1.2833 | 15.831 | -0.081 | 0.935 | -32.313 29.746 |
| C(workingday)[T.1]:C(hr)[T.2] | 2.4993 | 15.874 | 0.157 | 0.875 | -28.615 33.613 |
| C(workingday)[T.1]:C(hr)[T.3] | -20.6158 | 16.562 | -1.245 | 0.213 | -53.078 11.847 |
| C(workingday)[T.1]:C(hr)[T.4] | -14.6100 | 16.127 | -0.906 | 0.365 | -46.220 17.000 |
| C(workingday)[T.1]:C(hr)[T.5] | 35.3900 | 16.183 | 2.187 | 0.029 | 3.670 67.110 |
| C(workingday)[T.1]:C(hr)[T.6] | 61.3899 | 15.911 | 3.858 | 0.000 | 30.203 92.577 |
| C(workingday)[T.1]:C(hr)[T.7] | 139.2883 | 15.791 | 8.821 | 0.000 | 108.336 170.241 |
| C(workingday)[T.1]:C(hr)[T.8] | 268.2508 | 15.791 | 16.988 | 0.000 | 237.299 299.202 |
| C(workingday)[T.1]:C(hr)[T.9] | 141.1403 | 15.791 | 8.938 | 0.000 | 110.189 172.092 |
| C(workingday)[T.1]:C(hr)[T.10] | 14.8307 | 15.792 | 0.939 | 0.348 | -16.123 45.784 |
| C(workingday)[T.1]:C(hr)[T.11] | -8.3629 | 15.790 | -0.530 | 0.596 | -39.313 22.587 |
| C(workingday)[T.1]:C(hr)[T.12] | -5.0601 | 15.754 | -0.321 | 0.748 | -35.939 25.819 |
| C(workingday)[T.1]:C(hr)[T.13] | -0.7294 | 15.755 | -0.046 | 0.963 | -31.611 30.153 |
| C(workingday)[T.1]:C(hr)[T.14] | -20.6684 | 15.754 | -1.312 | 0.190 | -51.547 10.211 |
| C(workingday)[T.1]:C(hr)[T.15] | -24.8339 | 15.753 | -1.576 | 0.115 | -55.712 6.044 |
| C(workingday)[T.1]:C(hr)[T.16] | 17.9739 | 15.732 | 1.143 | 0.253 | -12.862 48.810 |
| C(workingday)[T.1]:C(hr)[T.17] | 166.3414 | 15.720 | 10.582 | 0.000 | 135.529 197.153 |
| C(workingday)[T.1]:C(hr)[T.18] | 139.5909 | 15.767 | 8.853 | 0.000 | 108.686 170.496 |
| C(workingday)[T.1]:C(hr)[T.19] | 104.3929 | 15.755 | 6.626 | 0.000 | 73.512 135.274 |
| C(workingday)[T.1]:C(hr)[T.20] | 78.4708 | 15.755 | 4.981 | 0.000 | 47.590 109.352 |
| C(workingday)[T.1]:C(hr)[T.21] | 59.8019 | 15.755 | 3.796 | 0.000 | 28.921 90.683 |
| C(workingday)[T.1]:C(hr)[T.22] | 55.9066 | 15.756 | 3.548 | 0.000 | 25.024 86.789 |
| C(workingday)[T.1]:C(hr)[T.23] | 31.3899 | 15.754 | 1.993 | 0.046 | 0.511 62.269 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[0] | 5.0346 | 16.339 | 0.308 | 0.758 | -26.991 37.060 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[0] | 3.3900 | 16.299 | 0.208 | 0.835 | -28.557 35.337 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[0] | 9.4665 | 15.975 | 0.593 | 0.553 | -21.846 40.779 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[0] | -23.6100 | 16.016 | -1.474 | 0.140 | -55.003 7.783 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[0] | -36.6100 | 16.348 | -2.239 | 0.025 | -68.654 -4.566 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[0] | -50.6100 | 15.804 | -3.202 | 0.001 | -81.588 -19.632 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[0] | -34.6220 | 16.684 | -2.075 | 0.038 | -67.324 -1.920 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[0] | -47.5887 | 15.970 | -2.980 | 0.003 | -78.893 -16.285 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[0] | -29.6100 | 15.933 | -1.858 | 0.063 | -60.841 1.621 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[0] | -2.1876 | 15.967 | -0.137 | 0.891 | -33.484 29.109 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[0] | -0.6100 | 15.808 | -0.039 | 0.969 | -31.595 30.375 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[1] | -23.4036 | 16.374 | -1.429 | 0.153 | -55.498 8.691 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[1] | 4.6733 | 16.332 | 0.286 | 0.775 | -27.340 36.687 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[1] | 14.9842 | 16.007 | 0.936 | 0.349 | -16.391 46.360 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[1] | -15.3267 | 16.053 | -0.955 | 0.340 | -46.793 16.140 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[1] | -28.3267 | 16.385 | -1.729 | 0.084 | -60.444 3.790 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[1] | -33.3267 | 15.842 | -2.104 | 0.035 | -64.379 -2.274 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[1] | -37.3357 | 16.718 | -2.233 | 0.026 | -70.105 -4.566 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[1] | -21.6976 | 16.041 | -1.353 | 0.176 | -53.139 9.744 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[1] | -25.3257 | 16.006 | -1.582 | 0.114 | -56.698 6.047 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[1] | 9.6663 | 16.006 | 0.604 | 0.546 | -21.707 41.039 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[1] | -2.3267 | 15.844 | -0.147 | 0.883 | -33.382 28.729 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[2] | -21.5222 | 16.491 | -1.305 | 0.192 | -53.846 10.801 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[2] | 3.8907 | 16.836 | 0.231 | 0.817 | -29.110 36.892 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[2] | 11.6558 | 16.046 | 0.726 | 0.468 | -19.796 43.108 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[2] | -5.1093 | 16.095 | -0.317 | 0.751 | -36.657 26.438 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[2] | -19.1093 | 16.425 | -1.163 | 0.245 | -51.304 13.085 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[2] | -22.1093 | 15.884 | -1.392 | 0.164 | -53.243 9.025 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[2] | -51.2669 | 16.759 | -3.059 | 0.002 | -84.116 -18.418 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[2] | -4.5742 | 16.081 | -0.284 | 0.776 | -36.094 26.946 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[2] | -11.7288 | 16.048 | -0.731 | 0.465 | -43.184 19.726 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[2] | 24.1819 | 16.084 | 1.504 | 0.133 | -7.344 55.708 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[2] | 10.8907 | 15.884 | 0.686 | 0.493 | -20.243 42.024 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[3] | -2.0197 | 17.282 | -0.117 | 0.907 | -35.893 31.854 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[3] | 48.0058 | 17.091 | 2.809 | 0.005 | 14.505 81.507 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[3] | 34.1632 | 16.795 | 2.034 | 0.042 | 1.243 67.084 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[3] | 42.0058 | 16.775 | 2.504 | 0.012 | 9.126 74.886 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[3] | 48.0058 | 17.091 | 2.809 | 0.005 | 14.505 81.507 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[3] | 32.0058 | 16.571 | 1.931 | 0.053 | -0.476 64.487 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[3] | 34.0058 | 17.411 | 1.953 | 0.051 | -0.121 68.133 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[3] | 64.5833 | 16.762 | 3.853 | 0.000 | 31.728 97.439 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[3] | 35.0058 | 16.761 | 2.089 | 0.037 | 2.152 67.859 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[3] | 61.9931 | 16.797 | 3.691 | 0.000 | 29.068 94.918 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[3] | 60.0058 | 16.833 | 3.565 | 0.000 | 27.012 93.000 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[4] | -4.0000 | 17.308 | -0.231 | 0.817 | -37.925 29.925 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[4] | 39.9008 | 16.829 | 2.371 | 0.018 | 6.913 72.888 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[4] | 63.8891 | 16.332 | 3.912 | 0.000 | 31.877 95.901 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[4] | 46.0000 | 16.346 | 2.814 | 0.005 | 13.960 78.040 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[4] | 85.0000 | 16.671 | 5.099 | 0.000 | 52.323 117.677 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[4] | 44.0000 | 16.138 | 2.727 | 0.006 | 12.368 75.632 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[4] | 77.0304 | 16.999 | 4.532 | 0.000 | 43.711 110.349 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[4] | 89.4044 | 16.299 | 5.485 | 0.000 | 57.457 121.351 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[4] | 47.0000 | 16.298 | 2.884 | 0.004 | 15.054 78.946 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[4] | 73.8619 | 16.299 | 4.532 | 0.000 | 41.915 105.809 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[4] | 90.0000 | 16.333 | 5.510 | 0.000 | 57.986 122.014 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[5] | -15.6232 | 17.281 | -0.904 | 0.366 | -49.497 18.250 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[5] | 46.0000 | 17.074 | 2.694 | 0.007 | 12.532 79.468 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[5] | 20.3347 | 16.352 | 1.244 | 0.214 | -11.717 52.387 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[5] | 7.0000 | 16.400 | 0.427 | 0.670 | -25.146 39.146 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[5] | 59.0000 | 16.724 | 3.528 | 0.000 | 26.219 91.781 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[5] | -11.0000 | 16.193 | -0.679 | 0.497 | -42.740 20.740 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[5] | 51.0443 | 17.049 | 2.994 | 0.003 | 17.626 84.463 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[5] | 35.8819 | 16.354 | 2.194 | 0.028 | 3.826 67.938 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[5] | 13.0160 | 16.354 | 0.796 | 0.426 | -19.039 45.071 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[5] | 25.3991 | 16.354 | 1.553 | 0.120 | -6.657 57.456 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[5] | 50.0000 | 16.193 | 3.088 | 0.002 | 18.260 81.740 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[6] | 5.9847 | 16.415 | 0.365 | 0.715 | -26.190 38.160 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[6] | 41.0000 | 16.408 | 2.499 | 0.012 | 8.839 73.161 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[6] | 17.8649 | 16.084 | 1.111 | 0.267 | -13.661 49.391 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[6] | 50.0000 | 16.133 | 3.099 | 0.002 | 18.378 81.622 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[6] | 70.0000 | 16.462 | 4.252 | 0.000 | 37.732 102.268 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[6] | 70.0000 | 15.921 | 4.397 | 0.000 | 38.792 101.208 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[6] | 92.0003 | 16.793 | 5.479 | 0.000 | 59.085 124.915 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[6] | 105.0327 | 16.084 | 6.530 | 0.000 | 73.506 136.559 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[6] | 64.9595 | 16.085 | 4.039 | 0.000 | 33.432 96.487 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[6] | 48.7628 | 16.085 | 3.032 | 0.002 | 17.235 80.291 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[6] | 35.0000 | 15.922 | 2.198 | 0.028 | 3.792 66.208 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[7] | 21.3614 | 16.300 | 1.311 | 0.190 | -10.589 53.312 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[7] | 50.1017 | 16.293 | 3.075 | 0.002 | 18.165 82.038 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[7] | 102.9826 | 15.966 | 6.450 | 0.000 | 71.687 134.279 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[7] | 157.1017 | 16.015 | 9.810 | 0.000 | 125.711 188.493 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[7] | 214.1017 | 16.347 | 13.097 | 0.000 | 182.059 246.144 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[7] | 187.1017 | 15.803 | 11.840 | 0.000 | 156.126 218.077 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[7] | 199.5486 | 16.461 | 12.122 | 0.000 | 167.282 231.815 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[7] | 230.1534 | 15.967 | 14.414 | 0.000 | 198.856 261.450 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[7] | 174.4777 | 15.967 | 10.928 | 0.000 | 143.181 205.774 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[7] | 171.0638 | 15.967 | 10.713 | 0.000 | 139.766 202.361 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[7] | 126.1017 | 15.804 | 7.979 | 0.000 | 95.125 157.078 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[8] | 20.4630 | 16.300 | 1.255 | 0.209 | -11.487 52.413 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[8] | 68.1392 | 16.293 | 4.182 | 0.000 | 36.203 100.075 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[8] | 136.6070 | 15.966 | 8.556 | 0.000 | 105.311 167.903 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[8] | 165.1392 | 16.015 | 10.312 | 0.000 | 133.749 196.530 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[8] | 174.1392 | 16.348 | 10.652 | 0.000 | 142.096 206.182 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[8] | 165.1392 | 15.803 | 10.450 | 0.000 | 134.164 196.115 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[8] | 189.0300 | 16.461 | 11.483 | 0.000 | 156.764 221.296 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[8] | 155.3652 | 15.968 | 9.729 | 0.000 | 124.065 186.665 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[8] | 136.9052 | 15.967 | 8.574 | 0.000 | 105.609 168.202 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[8] | 158.1770 | 15.967 | 9.906 | 0.000 | 126.880 189.474 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[8] | 153.1392 | 15.803 | 9.691 | 0.000 | 122.164 184.115 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[9] | -13.2483 | 16.301 | -0.813 | 0.416 | -45.200 18.704 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[9] | 9.2497 | 16.293 | 0.568 | 0.570 | -22.686 41.185 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[9] | -36.2398 | 15.967 | -2.270 | 0.023 | -67.536 -4.944 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[9] | -62.7503 | 16.015 | -3.918 | 0.000 | -94.141 -31.359 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[9] | -85.7503 | 16.347 | -5.246 | 0.000 | -117.792 -53.708 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[9] | -56.7503 | 15.803 | -3.591 | 0.000 | -87.726 -25.775 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[9] | -65.3581 | 16.462 | -3.970 | 0.000 | -97.625 -33.091 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[9] | -87.6352 | 15.967 | -5.488 | 0.000 | -118.933 -56.338 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[9] | -55.8875 | 15.968 | -3.500 | 0.000 | -87.186 -24.589 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[9] | -27.7188 | 15.967 | -1.736 | 0.083 | -59.015 3.578 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[9] | 44.2497 | 15.803 | 2.800 | 0.005 | 13.274 75.225 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[10] | -31.3814 | 16.300 | -1.925 | 0.054 | -63.331 0.569 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[10] | -39.4407 | 16.293 | -2.421 | 0.016 | -71.377 -7.505 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[10] | -99.3371 | 15.967 | -6.222 | 0.000 | -130.633 -68.041 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[10] | -151.4407 | 16.015 | -9.456 | 0.000 | -182.832 -120.050 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[10] | -194.4407 | 16.347 | -11.895 | 0.000 | -226.483 -162.399 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[10] | -122.4407 | 15.803 | -7.748 | 0.000 | -153.417 -91.465 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[10] | -139.4876 | 16.462 | -8.473 | 0.000 | -171.754 -107.221 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[10] | -178.4119 | 15.967 | -11.174 | 0.000 | -209.708 -147.116 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[10] | -139.0909 | 15.967 | -8.711 | 0.000 | -170.387 -107.795 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[10] | -88.5993 | 15.968 | -5.549 | 0.000 | -119.898 -57.301 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[10] | -46.4407 | 15.803 | -2.939 | 0.003 | -77.417 -15.465 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[11] | -21.9283 | 16.301 | -1.345 | 0.179 | -53.879 10.022 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[11] | -60.2471 | 16.293 | -3.698 | 0.000 | -92.183 -28.312 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[11] | -128.2467 | 15.967 | -8.032 | 0.000 | -159.543 -96.950 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[11] | -165.2471 | 16.015 | -10.318 | 0.000 | -196.638 -133.856 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[11] | -199.2471 | 16.347 | -12.189 | 0.000 | -231.289 -167.205 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[11] | -164.2471 | 15.803 | -10.393 | 0.000 | -195.223 -133.271 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[11] | -120.1987 | 16.462 | -7.302 | 0.000 | -152.465 -87.932 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[11] | -228.2124 | 15.967 | -14.293 | 0.000 | -259.509 -196.916 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[11] | -167.0522 | 15.967 | -10.463 | 0.000 | -198.348 -135.756 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[11] | -107.7034 | 15.967 | -6.745 | 0.000 | -139.001 -76.406 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[11] | -32.2471 | 15.803 | -2.041 | 0.041 | -63.223 -1.271 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[12] | -50.1574 | 16.264 | -3.084 | 0.002 | -82.038 -18.277 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[12] | -72.5499 | 16.256 | -4.463 | 0.000 | -104.414 -40.686 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[12] | -131.9087 | 15.930 | -8.281 | 0.000 | -163.133 -100.684 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[12] | -212.5499 | 15.978 | -13.302 | 0.000 | -243.869 -181.231 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[12] | -192.5499 | 16.311 | -11.805 | 0.000 | -224.521 -160.578 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[12] | -164.5499 | 15.766 | -10.437 | 0.000 | -195.453 -133.647 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[12] | -145.0765 | 16.429 | -8.830 | 0.000 | -177.279 -112.874 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[12] | -227.1708 | 15.930 | -14.261 | 0.000 | -258.395 -195.947 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[12] | -170.9555 | 15.930 | -10.732 | 0.000 | -202.179 -139.732 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[12] | -124.5605 | 15.930 | -7.819 | 0.000 | -155.785 -93.336 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[12] | -54.5499 | 15.766 | -3.460 | 0.001 | -85.453 -23.647 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[13] | -54.5157 | 16.265 | -3.352 | 0.001 | -86.396 -22.635 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[13] | -101.8806 | 16.256 | -6.267 | 0.000 | -133.745 -70.016 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[13] | -155.0493 | 15.930 | -9.733 | 0.000 | -186.274 -123.825 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[13] | -210.8806 | 15.979 | -13.197 | 0.000 | -242.201 -179.560 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[13] | -204.8806 | 16.312 | -12.560 | 0.000 | -236.853 -172.908 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[13] | -200.8806 | 15.766 | -12.741 | 0.000 | -231.784 -169.977 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[13] | -174.8464 | 16.429 | -10.642 | 0.000 | -207.049 -142.643 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[13] | -246.5398 | 15.930 | -15.476 | 0.000 | -277.765 -215.315 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[13] | -169.8179 | 15.897 | -10.682 | 0.000 | -200.978 -138.657 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[13] | -144.4072 | 15.930 | -9.065 | 0.000 | -175.631 -113.183 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[13] | -46.8806 | 15.767 | -2.973 | 0.003 | -77.785 -15.976 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[14] | -54.9859 | 16.265 | -3.381 | 0.001 | -86.866 -23.105 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[14] | -110.9417 | 16.256 | -6.825 | 0.000 | -142.806 -79.078 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[14] | -168.4141 | 15.930 | -10.572 | 0.000 | -199.638 -137.190 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[14] | -198.9417 | 15.979 | -12.451 | 0.000 | -230.261 -167.622 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[14] | -210.9417 | 16.311 | -12.932 | 0.000 | -242.913 -178.970 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[14] | -159.9417 | 15.766 | -10.145 | 0.000 | -190.844 -129.039 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[14] | -125.5358 | 16.429 | -7.641 | 0.000 | -157.739 -93.333 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[14] | -206.1022 | 15.930 | -12.938 | 0.000 | -237.326 -174.878 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[14] | -164.3810 | 15.896 | -10.341 | 0.000 | -195.540 -133.222 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[14] | -158.9085 | 15.930 | -9.976 | 0.000 | -190.133 -127.684 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[14] | -29.9417 | 15.767 | -1.899 | 0.058 | -60.846 0.963 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[15] | -26.7760 | 16.267 | -1.646 | 0.100 | -58.660 5.108 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[15] | -124.7762 | 16.256 | -7.676 | 0.000 | -156.640 -92.913 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[15] | -152.8648 | 15.930 | -9.596 | 0.000 | -184.089 -121.641 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[15] | -171.7762 | 15.978 | -10.751 | 0.000 | -203.095 -140.458 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[15] | -157.7762 | 16.312 | -9.673 | 0.000 | -189.749 -125.803 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[15] | -145.7762 | 15.766 | -9.246 | 0.000 | -176.679 -114.874 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[15] | -116.2885 | 16.429 | -7.078 | 0.000 | -148.491 -84.086 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[15] | -198.7410 | 15.931 | -12.475 | 0.000 | -229.967 -167.515 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[15] | -110.5533 | 15.897 | -6.954 | 0.000 | -141.712 -79.394 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[15] | -98.9121 | 15.931 | -6.209 | 0.000 | -130.138 -67.686 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[15] | 6.2238 | 15.767 | 0.395 | 0.693 | -24.682 37.129 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[16] | 14.4161 | 16.241 | 0.888 | 0.375 | -17.418 46.250 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[16] | -77.5839 | 16.234 | -4.779 | 0.000 | -109.404 -45.764 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[16] | -69.6341 | 15.906 | -4.378 | 0.000 | -100.812 -38.456 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[16] | -115.5839 | 15.955 | -7.244 | 0.000 | -146.858 -84.310 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[16] | -110.5839 | 16.289 | -6.789 | 0.000 | -142.511 -78.656 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[16] | -56.5839 | 15.742 | -3.594 | 0.000 | -87.441 -25.727 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[16] | 5.8945 | 16.404 | 0.359 | 0.719 | -26.260 38.049 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[16] | -90.9419 | 15.907 | -5.717 | 0.000 | -122.121 -59.763 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[16] | -27.9644 | 15.874 | -1.762 | 0.078 | -59.079 3.151 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[16] | -27.7731 | 15.907 | -1.746 | 0.081 | -58.953 3.407 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[16] | 31.4161 | 15.744 | 1.995 | 0.046 | 0.556 62.276 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[17] | -13.4041 | 16.230 | -0.826 | 0.409 | -45.216 18.408 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[17] | -66.9514 | 16.223 | -4.127 | 0.000 | -98.750 -35.153 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[17] | 44.0483 | 15.896 | 2.771 | 0.006 | 12.890 75.207 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[17] | 52.0486 | 15.945 | 3.264 | 0.001 | 20.795 83.302 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[17] | 37.0486 | 16.277 | 2.276 | 0.023 | 5.143 68.954 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[17] | 99.0486 | 15.732 | 6.296 | 0.000 | 68.213 129.884 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[17] | 149.1601 | 16.395 | 9.098 | 0.000 | 117.025 181.295 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[17] | 42.0208 | 15.895 | 2.644 | 0.008 | 10.865 73.176 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[17] | 81.8689 | 15.862 | 5.161 | 0.000 | 50.777 112.961 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[17] | 112.8357 | 15.895 | 7.099 | 0.000 | 81.680 143.991 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[17] | 82.0486 | 15.731 | 5.216 | 0.000 | 51.214 112.883 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[18] | 21.8017 | 16.277 | 1.339 | 0.180 | -10.103 53.707 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[18] | 50.7991 | 16.268 | 3.123 | 0.002 | 18.912 82.687 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[18] | 103.2523 | 15.943 | 6.476 | 0.000 | 72.002 134.503 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[18] | 66.7991 | 15.994 | 4.177 | 0.000 | 35.450 98.148 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[18] | 85.7991 | 16.326 | 5.255 | 0.000 | 53.799 117.799 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[18] | 143.7991 | 15.778 | 9.114 | 0.000 | 112.872 174.726 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[18] | 153.7300 | 16.657 | 9.229 | 0.000 | 121.080 186.379 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[18] | 89.4803 | 15.943 | 5.612 | 0.000 | 58.230 120.730 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[18] | 97.7990 | 15.909 | 6.147 | 0.000 | 66.616 128.982 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[18] | 122.8008 | 15.943 | 7.702 | 0.000 | 91.550 154.052 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[18] | 112.7991 | 15.779 | 7.149 | 0.000 | 81.871 143.727 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[19] | 37.0531 | 16.265 | 2.278 | 0.023 | 5.172 68.934 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[19] | -14.0029 | 16.256 | -0.861 | 0.389 | -45.867 17.861 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[19] | 50.8672 | 15.930 | 3.193 | 0.001 | 19.643 82.092 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[19] | 11.9971 | 15.981 | 0.751 | 0.453 | -19.326 43.321 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[19] | 14.9971 | 16.312 | 0.919 | 0.358 | -16.976 46.970 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[19] | 25.9971 | 15.767 | 1.649 | 0.099 | -4.908 56.902 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[19] | 83.0046 | 16.646 | 4.987 | 0.000 | 50.377 115.632 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[19] | 44.9439 | 15.930 | 2.821 | 0.005 | 13.720 76.168 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[19] | 38.3096 | 15.897 | 2.410 | 0.016 | 7.149 69.470 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[19] | 51.2542 | 15.931 | 3.217 | 0.001 | 20.027 82.481 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[19] | 64.9971 | 15.766 | 4.122 | 0.000 | 34.093 95.901 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[20] | 17.9099 | 16.264 | 1.101 | 0.271 | -13.969 49.789 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[20] | 5.9192 | 16.256 | 0.364 | 0.716 | -25.944 37.783 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[20] | 23.4147 | 15.932 | 1.470 | 0.142 | -7.814 54.643 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[20] | 8.9192 | 15.978 | 0.558 | 0.577 | -22.399 40.238 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[20] | 20.9192 | 16.311 | 1.282 | 0.200 | -11.053 52.891 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[20] | 1.9192 | 15.766 | 0.122 | 0.903 | -28.983 32.822 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[20] | 54.0157 | 16.645 | 3.245 | 0.001 | 21.389 86.642 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[20] | 29.6970 | 15.930 | 1.864 | 0.062 | -1.527 60.921 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[20] | 23.9192 | 15.897 | 1.505 | 0.132 | -7.240 55.079 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[20] | 16.9480 | 15.930 | 1.064 | 0.287 | -14.276 48.172 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[20] | 47.9192 | 15.767 | 3.039 | 0.002 | 17.015 78.823 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[21] | 14.9664 | 16.265 | 0.920 | 0.357 | -16.914 46.847 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[21] | -8.4119 | 16.256 | -0.517 | 0.605 | -40.275 23.451 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[21] | 21.4429 | 15.931 | 1.346 | 0.178 | -9.783 52.669 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[21] | -1.4119 | 15.978 | -0.088 | 0.930 | -32.731 29.907 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[21] | 10.5881 | 16.312 | 0.649 | 0.516 | -21.385 42.561 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[21] | 9.5881 | 15.766 | 0.608 | 0.543 | -21.315 40.491 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[21] | 42.6056 | 16.645 | 2.560 | 0.010 | 9.979 75.232 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[21] | 29.7879 | 15.931 | 1.870 | 0.062 | -1.438 61.013 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[21] | 16.2781 | 15.898 | 1.024 | 0.306 | -14.883 47.439 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[21] | 16.0430 | 15.930 | 1.007 | 0.314 | -15.181 47.267 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[21] | 40.5881 | 15.766 | 2.574 | 0.010 | 9.684 71.492 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[22] | -17.5166 | 16.264 | -1.077 | 0.281 | -49.396 14.362 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[22] | -1.5166 | 16.256 | -0.093 | 0.926 | -33.380 30.347 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[22] | 1.4909 | 15.931 | 0.094 | 0.925 | -29.736 32.717 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[22] | 6.4834 | 15.978 | 0.406 | 0.685 | -24.836 37.802 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[22] | -3.5166 | 16.312 | -0.216 | 0.829 | -35.489 28.456 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[22] | -3.5166 | 15.766 | -0.223 | 0.823 | -34.419 27.386 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[22] | 17.3182 | 16.645 | 1.040 | 0.298 | -15.308 49.945 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[22] | 3.6772 | 15.930 | 0.231 | 0.817 | -27.548 34.902 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[22] | -10.0232 | 15.897 | -0.630 | 0.528 | -41.183 21.137 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[22] | 3.2706 | 15.930 | 0.205 | 0.837 | -27.953 34.494 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[22] | 8.4834 | 15.766 | 0.538 | 0.591 | -22.420 39.386 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[23] | -3.0660 | 16.264 | -0.189 | 0.850 | -34.946 28.814 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[23] | -7.9999 | 16.256 | -0.492 | 0.623 | -39.864 23.864 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[23] | 1.0001 | 15.931 | 0.063 | 0.950 | -30.227 32.227 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[23] | -18.9999 | 15.978 | -1.189 | 0.234 | -50.318 12.319 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[23] | -15.9999 | 16.312 | -0.981 | 0.327 | -47.973 15.973 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[23] | -7.9999 | 15.766 | -0.507 | 0.612 | -38.903 22.904 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[23] | 0.0213 | 16.647 | 0.001 | 0.999 | -32.608 32.651 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[23] | -9.7224 | 15.931 | -0.610 | 0.542 | -40.949 21.504 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[23] | 15.0006 | 15.896 | 0.944 | 0.345 | -16.158 46.159 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[23] | 3.5709 | 15.930 | 0.224 | 0.823 | -27.653 34.795 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[23] | 16.0001 | 15.767 | 1.015 | 0.310 | -14.905 46.905 |
In [18]:
q90.summary()
Out[18]:
| Dep. Variable: | cnt | Pseudo R-squared: | 0.7556 |
|---|---|---|---|
| Model: | QuantReg | Bandwidth: | 10.04 |
| Method: | Least Squares | Sparsity: | 101.6 |
| Date: | Fri, 28 Sep 2018 | No. Observations: | 17379 |
| Time: | 12:28:41 | Df Residuals: | 16799 |
| Df Model: | 579 |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] | |
|---|---|---|---|---|---|
| Intercept | 30.0000 | 7.487 | 4.007 | 0.000 | 15.325 44.675 |
| C(hr)[T.1] | -1.0000 | 10.180 | -0.098 | 0.922 | -20.953 18.953 |
| C(hr)[T.2] | -12.0000 | 10.573 | -1.135 | 0.256 | -32.725 8.725 |
| C(hr)[T.3] | -17.0000 | 9.913 | -1.715 | 0.086 | -36.431 2.431 |
| C(hr)[T.4] | -22.0000 | 9.910 | -2.220 | 0.026 | -41.424 -2.576 |
| C(hr)[T.5] | -22.0000 | 10.346 | -2.126 | 0.033 | -42.279 -1.721 |
| C(hr)[T.6] | -23.0000 | 9.912 | -2.320 | 0.020 | -42.428 -3.572 |
| C(hr)[T.7] | -20.0000 | 10.571 | -1.892 | 0.059 | -40.721 0.721 |
| C(hr)[T.8] | -3.0000 | 9.732 | -0.308 | 0.758 | -22.075 16.075 |
| C(hr)[T.9] | 13.0000 | 10.571 | 1.230 | 0.219 | -7.721 33.721 |
| C(hr)[T.10] | 66.0000 | 9.736 | 6.779 | 0.000 | 46.916 85.084 |
| C(hr)[T.11] | 131.0000 | 10.574 | 12.388 | 0.000 | 110.273 151.727 |
| C(hr)[T.12] | 189.0000 | 10.576 | 17.871 | 0.000 | 168.271 209.729 |
| C(hr)[T.13] | 218.0000 | 10.576 | 20.614 | 0.000 | 197.271 238.729 |
| C(hr)[T.14] | 203.0000 | 10.573 | 19.200 | 0.000 | 182.276 223.724 |
| C(hr)[T.15] | 205.0000 | 10.573 | 19.389 | 0.000 | 184.276 225.724 |
| C(hr)[T.16] | 197.0000 | 10.573 | 18.632 | 0.000 | 176.275 217.725 |
| C(hr)[T.17] | 109.0000 | 10.573 | 10.309 | 0.000 | 88.276 129.724 |
| C(hr)[T.18] | 67.0000 | 10.573 | 6.337 | 0.000 | 46.276 87.724 |
| C(hr)[T.19] | 49.0000 | 10.573 | 4.634 | 0.000 | 28.275 69.725 |
| C(hr)[T.20] | 16.0000 | 9.733 | 1.644 | 0.100 | -3.078 35.078 |
| C(hr)[T.21] | 9.0000 | 10.573 | 0.851 | 0.395 | -11.723 29.723 |
| C(hr)[T.22] | 2.0000 | 10.574 | 0.189 | 0.850 | -18.727 22.727 |
| C(hr)[T.23] | 3.0000 | 9.732 | 0.308 | 0.758 | -16.075 22.075 |
| C(yr)[T.1] | 95.0000 | 0.484 | 196.286 | 0.000 | 94.051 95.949 |
| C(mnth)[T.2] | 12.0000 | 10.609 | 1.131 | 0.258 | -8.795 32.795 |
| C(mnth)[T.3] | 31.0000 | 10.917 | 2.840 | 0.005 | 9.602 52.398 |
| C(mnth)[T.4] | 28.0310 | 10.121 | 2.770 | 0.006 | 8.193 47.869 |
| C(mnth)[T.5] | 77.0000 | 10.348 | 7.441 | 0.000 | 56.717 97.283 |
| C(mnth)[T.6] | 87.0000 | 10.913 | 7.972 | 0.000 | 65.609 108.391 |
| C(mnth)[T.7] | 110.0000 | 10.816 | 10.170 | 0.000 | 88.800 131.200 |
| C(mnth)[T.8] | 103.0000 | 11.672 | 8.825 | 0.000 | 80.122 125.878 |
| C(mnth)[T.9] | 82.0169 | 10.117 | 8.107 | 0.000 | 62.187 101.847 |
| C(mnth)[T.10] | 99.0014 | 10.117 | 9.786 | 0.000 | 79.171 118.832 |
| C(mnth)[T.11] | 45.0006 | 10.117 | 4.448 | 0.000 | 25.171 64.830 |
| C(mnth)[T.12] | 45.0000 | 10.820 | 4.159 | 0.000 | 23.792 66.208 |
| C(workingday)[T.1] | -16.0000 | 9.029 | -1.772 | 0.076 | -33.697 1.697 |
| C(weathersit)[T.2] | -5.0000 | 0.576 | -8.688 | 0.000 | -6.128 -3.872 |
| C(weathersit)[T.3] | -12.0000 | 0.913 | -13.142 | 0.000 | -13.790 -10.210 |
| C(weathersit)[T.4] | -101.0000 | 30.610 | -3.300 | 0.001 | -160.999 -41.001 |
| C(mnth)[T.2]:C(hr)[T.1] | -4.0000 | 14.730 | -0.272 | 0.786 | -32.872 24.872 |
| C(mnth)[T.3]:C(hr)[T.1] | -16.0000 | 15.170 | -1.055 | 0.292 | -45.735 13.735 |
| C(mnth)[T.4]:C(hr)[T.1] | -14.9487 | 14.020 | -1.066 | 0.286 | -42.430 12.532 |
| C(mnth)[T.5]:C(hr)[T.1] | -19.0000 | 14.352 | -1.324 | 0.186 | -47.131 9.131 |
| C(mnth)[T.6]:C(hr)[T.1] | -21.0000 | 16.081 | -1.306 | 0.192 | -52.520 10.520 |
| C(mnth)[T.7]:C(hr)[T.1] | -37.0000 | 15.025 | -2.463 | 0.014 | -66.451 -7.549 |
| C(mnth)[T.8]:C(hr)[T.1] | -47.0000 | 16.254 | -2.892 | 0.004 | -78.859 -15.141 |
| C(mnth)[T.9]:C(hr)[T.1] | -23.0114 | 14.018 | -1.642 | 0.101 | -50.489 4.466 |
| C(mnth)[T.10]:C(hr)[T.1] | -55.0010 | 14.017 | -3.924 | 0.000 | -82.477 -27.525 |
| C(mnth)[T.11]:C(hr)[T.1] | 2.0223 | 14.017 | 0.144 | 0.885 | -25.453 29.498 |
| C(mnth)[T.12]:C(hr)[T.1] | -3.0000 | 15.026 | -0.200 | 0.842 | -32.452 26.452 |
| C(mnth)[T.2]:C(hr)[T.2] | -8.0000 | 15.006 | -0.533 | 0.594 | -37.413 21.413 |
| C(mnth)[T.3]:C(hr)[T.2] | -16.0000 | 15.976 | -1.001 | 0.317 | -47.316 15.316 |
| C(mnth)[T.4]:C(hr)[T.2] | -3.7193 | 14.310 | -0.260 | 0.795 | -31.769 24.330 |
| C(mnth)[T.5]:C(hr)[T.2] | -34.0000 | 14.633 | -2.324 | 0.020 | -62.682 -5.318 |
| C(mnth)[T.6]:C(hr)[T.2] | -33.0000 | 15.435 | -2.138 | 0.033 | -63.253 -2.747 |
| C(mnth)[T.7]:C(hr)[T.2] | -59.0000 | 15.297 | -3.857 | 0.000 | -88.983 -29.017 |
| C(mnth)[T.8]:C(hr)[T.2] | -47.0000 | 16.505 | -2.848 | 0.004 | -79.351 -14.649 |
| C(mnth)[T.9]:C(hr)[T.2] | -19.0135 | 14.305 | -1.329 | 0.184 | -47.053 9.026 |
| C(mnth)[T.10]:C(hr)[T.2] | -59.9797 | 14.307 | -4.192 | 0.000 | -88.023 -31.937 |
| C(mnth)[T.11]:C(hr)[T.2] | -16.9994 | 14.306 | -1.188 | 0.235 | -45.041 11.042 |
| C(mnth)[T.12]:C(hr)[T.2] | -1.0000 | 15.296 | -0.065 | 0.948 | -30.982 28.982 |
| C(mnth)[T.2]:C(hr)[T.3] | -8.0000 | 14.549 | -0.550 | 0.582 | -36.518 20.518 |
| C(mnth)[T.3]:C(hr)[T.3] | -21.0000 | 14.991 | -1.401 | 0.161 | -50.384 8.384 |
| C(mnth)[T.4]:C(hr)[T.3] | -16.2842 | 13.828 | -1.178 | 0.239 | -43.389 10.821 |
| C(mnth)[T.5]:C(hr)[T.3] | -53.0000 | 14.168 | -3.741 | 0.000 | -80.771 -25.229 |
| C(mnth)[T.6]:C(hr)[T.3] | -61.0000 | 14.988 | -4.070 | 0.000 | -90.378 -31.622 |
| C(mnth)[T.7]:C(hr)[T.3] | -78.0000 | 14.849 | -5.253 | 0.000 | -107.106 -48.894 |
| C(mnth)[T.8]:C(hr)[T.3] | -65.0000 | 16.088 | -4.040 | 0.000 | -96.533 -33.467 |
| C(mnth)[T.9]:C(hr)[T.3] | -52.0169 | 13.830 | -3.761 | 0.000 | -79.125 -24.909 |
| C(mnth)[T.10]:C(hr)[T.3] | -78.6410 | 13.825 | -5.688 | 0.000 | -105.740 -51.542 |
| C(mnth)[T.11]:C(hr)[T.3] | -40.9927 | 13.826 | -2.965 | 0.003 | -68.093 -13.892 |
| C(mnth)[T.12]:C(hr)[T.3] | -28.0000 | 14.509 | -1.930 | 0.054 | -56.438 0.438 |
| C(mnth)[T.2]:C(hr)[T.4] | -13.0000 | 15.709 | -0.828 | 0.408 | -43.791 17.791 |
| C(mnth)[T.3]:C(hr)[T.4] | -26.0000 | 14.990 | -1.735 | 0.083 | -55.381 3.381 |
| C(mnth)[T.4]:C(hr)[T.4] | -24.0310 | 13.827 | -1.738 | 0.082 | -51.134 3.072 |
| C(mnth)[T.5]:C(hr)[T.4] | -67.0000 | 14.164 | -4.730 | 0.000 | -94.762 -39.238 |
| C(mnth)[T.6]:C(hr)[T.4] | -78.0000 | 14.987 | -5.204 | 0.000 | -107.376 -48.624 |
| C(mnth)[T.7]:C(hr)[T.4] | -102.0000 | 14.205 | -7.181 | 0.000 | -129.843 -74.157 |
| C(mnth)[T.8]:C(hr)[T.4] | -96.0000 | 17.191 | -5.584 | 0.000 | -129.697 -62.303 |
| C(mnth)[T.9]:C(hr)[T.4] | -81.0169 | 13.828 | -5.859 | 0.000 | -108.121 -53.913 |
| C(mnth)[T.10]:C(hr)[T.4] | -95.0014 | 13.829 | -6.870 | 0.000 | -122.107 -67.896 |
| C(mnth)[T.11]:C(hr)[T.4] | -45.0004 | 13.825 | -3.255 | 0.001 | -72.098 -17.903 |
| C(mnth)[T.12]:C(hr)[T.4] | -43.8612 | 14.344 | -3.058 | 0.002 | -71.976 -15.746 |
| C(mnth)[T.2]:C(hr)[T.5] | -5.0000 | 15.619 | -0.320 | 0.749 | -35.615 25.615 |
| C(mnth)[T.3]:C(hr)[T.5] | -31.0000 | 15.827 | -1.959 | 0.050 | -62.022 0.022 |
| C(mnth)[T.4]:C(hr)[T.5] | -24.0310 | 14.141 | -1.699 | 0.089 | -51.748 3.686 |
| C(mnth)[T.5]:C(hr)[T.5] | -66.0000 | 14.471 | -4.561 | 0.000 | -94.366 -37.634 |
| C(mnth)[T.6]:C(hr)[T.5] | -79.0000 | 15.283 | -5.169 | 0.000 | -108.956 -49.044 |
| C(mnth)[T.7]:C(hr)[T.5] | -104.0000 | 15.142 | -6.868 | 0.000 | -133.680 -74.320 |
| C(mnth)[T.8]:C(hr)[T.5] | -94.0000 | 16.363 | -5.745 | 0.000 | -126.073 -61.927 |
| C(mnth)[T.9]:C(hr)[T.5] | -78.0357 | 14.138 | -5.520 | 0.000 | -105.747 -50.324 |
| C(mnth)[T.10]:C(hr)[T.5] | -92.0015 | 14.142 | -6.506 | 0.000 | -119.721 -64.282 |
| C(mnth)[T.11]:C(hr)[T.5] | -43.8515 | 14.138 | -3.102 | 0.002 | -71.564 -16.139 |
| C(mnth)[T.12]:C(hr)[T.5] | -47.0000 | 14.512 | -3.239 | 0.001 | -75.445 -18.555 |
| C(mnth)[T.2]:C(hr)[T.6] | -6.0000 | 14.549 | -0.412 | 0.680 | -34.517 22.517 |
| C(mnth)[T.3]:C(hr)[T.6] | -28.0000 | 15.912 | -1.760 | 0.078 | -59.190 3.190 |
| C(mnth)[T.4]:C(hr)[T.6] | -2.0274 | 13.825 | -0.147 | 0.883 | -29.126 25.071 |
| C(mnth)[T.5]:C(hr)[T.6] | -62.0000 | 14.164 | -4.377 | 0.000 | -89.763 -34.237 |
| C(mnth)[T.6]:C(hr)[T.6] | -56.0000 | 14.990 | -3.736 | 0.000 | -85.382 -26.618 |
| C(mnth)[T.7]:C(hr)[T.6] | -85.0000 | 14.848 | -5.725 | 0.000 | -114.103 -55.897 |
| C(mnth)[T.8]:C(hr)[T.6] | -83.0000 | 16.088 | -5.159 | 0.000 | -114.535 -51.465 |
| C(mnth)[T.9]:C(hr)[T.6] | -66.0169 | 14.555 | -4.536 | 0.000 | -94.546 -37.488 |
| C(mnth)[T.10]:C(hr)[T.6] | -84.0014 | 13.824 | -6.077 | 0.000 | -111.098 -56.905 |
| C(mnth)[T.11]:C(hr)[T.6] | -29.0006 | 14.551 | -1.993 | 0.046 | -57.522 -0.480 |
| C(mnth)[T.12]:C(hr)[T.6] | -41.0000 | 14.205 | -2.886 | 0.004 | -68.843 -13.157 |
| C(mnth)[T.2]:C(hr)[T.7] | 4.718e-07 | 15.831 | 2.98e-08 | 1.000 | -31.031 31.031 |
| C(mnth)[T.3]:C(hr)[T.7] | -18.0000 | 15.433 | -1.166 | 0.244 | -48.251 12.251 |
| C(mnth)[T.4]:C(hr)[T.7] | 10.0606 | 14.304 | 0.703 | 0.482 | -17.977 38.098 |
| C(mnth)[T.5]:C(hr)[T.7] | -40.0000 | 14.634 | -2.733 | 0.006 | -68.684 -11.316 |
| C(mnth)[T.6]:C(hr)[T.7] | -21.0000 | 15.435 | -1.361 | 0.174 | -51.254 9.254 |
| C(mnth)[T.7]:C(hr)[T.7] | -68.0000 | 15.295 | -4.446 | 0.000 | -97.981 -38.019 |
| C(mnth)[T.8]:C(hr)[T.7] | -64.0000 | 16.219 | -3.946 | 0.000 | -95.790 -32.210 |
| C(mnth)[T.9]:C(hr)[T.7] | -48.0168 | 14.306 | -3.356 | 0.001 | -76.059 -19.975 |
| C(mnth)[T.10]:C(hr)[T.7] | -44.9988 | 14.306 | -3.145 | 0.002 | -73.040 -16.957 |
| C(mnth)[T.11]:C(hr)[T.7] | -11.9959 | 14.305 | -0.839 | 0.402 | -40.035 16.044 |
| C(mnth)[T.12]:C(hr)[T.7] | -29.0000 | 14.669 | -1.977 | 0.048 | -57.753 -0.247 |
| C(mnth)[T.2]:C(hr)[T.8] | 23.0000 | 14.427 | 1.594 | 0.111 | -5.278 51.278 |
| C(mnth)[T.3]:C(hr)[T.8] | 8.0000 | 14.871 | 0.538 | 0.591 | -21.150 37.150 |
| C(mnth)[T.4]:C(hr)[T.8] | 50.9712 | 13.699 | 3.721 | 0.000 | 24.119 77.823 |
| C(mnth)[T.5]:C(hr)[T.8] | 11.0000 | 14.038 | 0.784 | 0.433 | -16.516 38.516 |
| C(mnth)[T.6]:C(hr)[T.8] | 29.0000 | 14.871 | 1.950 | 0.051 | -0.149 58.149 |
| C(mnth)[T.7]:C(hr)[T.8] | -5.0000 | 14.078 | -0.355 | 0.722 | -32.594 22.594 |
| C(mnth)[T.8]:C(hr)[T.8] | -7.0000 | 15.683 | -0.446 | 0.655 | -37.741 23.741 |
| C(mnth)[T.9]:C(hr)[T.8] | 13.9836 | 13.697 | 1.021 | 0.307 | -12.864 40.831 |
| C(mnth)[T.10]:C(hr)[T.8] | -0.9957 | 13.697 | -0.073 | 0.942 | -27.843 25.852 |
| C(mnth)[T.11]:C(hr)[T.8] | 29.0021 | 13.698 | 2.117 | 0.034 | 2.152 55.852 |
| C(mnth)[T.12]:C(hr)[T.8] | -8.0000 | 14.077 | -0.568 | 0.570 | -35.592 19.592 |
| C(mnth)[T.2]:C(hr)[T.9] | 7.0000 | 15.833 | 0.442 | 0.658 | -24.035 38.035 |
| C(mnth)[T.3]:C(hr)[T.9] | 85.0000 | 15.435 | 5.507 | 0.000 | 54.745 115.255 |
| C(mnth)[T.4]:C(hr)[T.9] | 114.0260 | 14.304 | 7.972 | 0.000 | 85.989 142.063 |
| C(mnth)[T.5]:C(hr)[T.9] | 105.0000 | 14.631 | 7.176 | 0.000 | 76.321 133.679 |
| C(mnth)[T.6]:C(hr)[T.9] | 115.0000 | 15.434 | 7.451 | 0.000 | 84.748 145.252 |
| C(mnth)[T.7]:C(hr)[T.9] | 89.0000 | 14.671 | 6.066 | 0.000 | 60.243 117.757 |
| C(mnth)[T.8]:C(hr)[T.9] | 69.0000 | 16.218 | 4.255 | 0.000 | 37.212 100.788 |
| C(mnth)[T.9]:C(hr)[T.9] | 121.9877 | 14.306 | 8.527 | 0.000 | 93.946 150.029 |
| C(mnth)[T.10]:C(hr)[T.9] | 100.0386 | 14.307 | 6.992 | 0.000 | 71.996 128.082 |
| C(mnth)[T.11]:C(hr)[T.9] | 90.0037 | 14.306 | 6.291 | 0.000 | 61.962 118.046 |
| C(mnth)[T.12]:C(hr)[T.9] | 37.0000 | 15.294 | 2.419 | 0.016 | 7.022 66.978 |
| C(mnth)[T.2]:C(hr)[T.10] | 2.0000 | 14.425 | 0.139 | 0.890 | -26.275 30.275 |
| C(mnth)[T.3]:C(hr)[T.10] | 134.0000 | 14.874 | 9.009 | 0.000 | 104.846 163.154 |
| C(mnth)[T.4]:C(hr)[T.10] | 186.9733 | 13.702 | 13.646 | 0.000 | 160.117 213.830 |
| C(mnth)[T.5]:C(hr)[T.10] | 169.0000 | 14.040 | 12.037 | 0.000 | 141.480 196.520 |
| C(mnth)[T.6]:C(hr)[T.10] | 215.0000 | 14.874 | 14.455 | 0.000 | 185.846 244.154 |
| C(mnth)[T.7]:C(hr)[T.10] | 105.0000 | 14.732 | 7.127 | 0.000 | 76.123 133.877 |
| C(mnth)[T.8]:C(hr)[T.10] | 153.0000 | 15.688 | 9.753 | 0.000 | 122.250 183.750 |
| C(mnth)[T.9]:C(hr)[T.10] | 215.9835 | 13.698 | 15.768 | 0.000 | 189.135 242.832 |
| C(mnth)[T.10]:C(hr)[T.10] | 170.0056 | 13.697 | 12.412 | 0.000 | 143.158 196.853 |
| C(mnth)[T.11]:C(hr)[T.10] | 120.9995 | 13.698 | 8.833 | 0.000 | 94.150 147.849 |
| C(mnth)[T.12]:C(hr)[T.10] | 56.0000 | 14.085 | 3.976 | 0.000 | 28.391 83.609 |
| C(mnth)[T.2]:C(hr)[T.11] | 2.0000 | 15.005 | 0.133 | 0.894 | -27.412 31.412 |
| C(mnth)[T.3]:C(hr)[T.11] | 176.0000 | 15.436 | 11.402 | 0.000 | 145.743 206.257 |
| C(mnth)[T.4]:C(hr)[T.11] | 243.9917 | 14.310 | 17.051 | 0.000 | 215.943 272.040 |
| C(mnth)[T.5]:C(hr)[T.11] | 248.0000 | 14.636 | 16.945 | 0.000 | 219.312 276.688 |
| C(mnth)[T.6]:C(hr)[T.11] | 223.0000 | 15.435 | 14.447 | 0.000 | 192.745 253.255 |
| C(mnth)[T.7]:C(hr)[T.11] | 125.0000 | 15.298 | 8.171 | 0.000 | 95.015 154.985 |
| C(mnth)[T.8]:C(hr)[T.11] | 140.0000 | 16.223 | 8.630 | 0.000 | 108.202 171.798 |
| C(mnth)[T.9]:C(hr)[T.11] | 287.9860 | 14.307 | 20.129 | 0.000 | 259.943 316.029 |
| C(mnth)[T.10]:C(hr)[T.11] | 230.0369 | 14.306 | 16.080 | 0.000 | 201.996 258.078 |
| C(mnth)[T.11]:C(hr)[T.11] | 144.0288 | 14.306 | 10.067 | 0.000 | 115.987 172.071 |
| C(mnth)[T.12]:C(hr)[T.11] | 92.0000 | 15.301 | 6.013 | 0.000 | 62.008 121.992 |
| C(mnth)[T.2]:C(hr)[T.12] | -21.0000 | 15.833 | -1.326 | 0.185 | -52.035 10.035 |
| C(mnth)[T.3]:C(hr)[T.12] | 276.0000 | 15.436 | 17.880 | 0.000 | 245.743 306.257 |
| C(mnth)[T.4]:C(hr)[T.12] | 292.9791 | 14.312 | 20.471 | 0.000 | 264.926 321.032 |
| C(mnth)[T.5]:C(hr)[T.12] | 246.0000 | 14.635 | 16.809 | 0.000 | 217.313 274.687 |
| C(mnth)[T.6]:C(hr)[T.12] | 267.0000 | 15.436 | 17.298 | 0.000 | 236.744 297.256 |
| C(mnth)[T.7]:C(hr)[T.12] | 91.0000 | 15.300 | 5.948 | 0.000 | 61.011 120.989 |
| C(mnth)[T.8]:C(hr)[T.12] | 221.0000 | 16.221 | 13.624 | 0.000 | 189.205 252.795 |
| C(mnth)[T.9]:C(hr)[T.12] | 309.9838 | 14.308 | 21.665 | 0.000 | 281.939 338.029 |
| C(mnth)[T.10]:C(hr)[T.12] | 262.0033 | 14.306 | 18.315 | 0.000 | 233.962 290.044 |
| C(mnth)[T.11]:C(hr)[T.12] | 145.0553 | 14.307 | 10.139 | 0.000 | 117.013 173.098 |
| C(mnth)[T.12]:C(hr)[T.12] | 94.0000 | 14.681 | 6.403 | 0.000 | 65.225 122.775 |
| C(mnth)[T.2]:C(hr)[T.13] | -1.0000 | 15.006 | -0.067 | 0.947 | -30.414 28.414 |
| C(mnth)[T.3]:C(hr)[T.13] | 264.0000 | 15.439 | 17.100 | 0.000 | 233.739 294.261 |
| C(mnth)[T.4]:C(hr)[T.13] | 277.9913 | 14.315 | 19.420 | 0.000 | 249.932 306.050 |
| C(mnth)[T.5]:C(hr)[T.13] | 239.0000 | 14.636 | 16.329 | 0.000 | 210.312 267.688 |
| C(mnth)[T.6]:C(hr)[T.13] | 249.0000 | 15.437 | 16.130 | 0.000 | 218.742 279.258 |
| C(mnth)[T.7]:C(hr)[T.13] | 139.0000 | 14.675 | 9.472 | 0.000 | 110.236 167.764 |
| C(mnth)[T.8]:C(hr)[T.13] | 123.0000 | 16.223 | 7.582 | 0.000 | 91.201 154.799 |
| C(mnth)[T.9]:C(hr)[T.13] | 278.9884 | 14.308 | 19.499 | 0.000 | 250.944 307.033 |
| C(mnth)[T.10]:C(hr)[T.13] | 271.9986 | 14.305 | 19.014 | 0.000 | 243.959 300.038 |
| C(mnth)[T.11]:C(hr)[T.13] | 137.0129 | 14.307 | 9.577 | 0.000 | 108.970 165.055 |
| C(mnth)[T.12]:C(hr)[T.13] | 68.0000 | 14.682 | 4.631 | 0.000 | 39.221 96.779 |
| C(mnth)[T.2]:C(hr)[T.14] | 37.0000 | 15.006 | 2.466 | 0.014 | 7.587 66.413 |
| C(mnth)[T.3]:C(hr)[T.14] | 197.0000 | 15.437 | 12.761 | 0.000 | 166.741 227.259 |
| C(mnth)[T.4]:C(hr)[T.14] | 271.9881 | 14.314 | 19.001 | 0.000 | 243.931 300.046 |
| C(mnth)[T.5]:C(hr)[T.14] | 210.0000 | 14.635 | 14.350 | 0.000 | 181.315 238.685 |
| C(mnth)[T.6]:C(hr)[T.14] | 232.0000 | 15.435 | 15.031 | 0.000 | 201.746 262.254 |
| C(mnth)[T.7]:C(hr)[T.14] | 109.0000 | 14.673 | 7.429 | 0.000 | 80.239 137.761 |
| C(mnth)[T.8]:C(hr)[T.14] | 148.0000 | 16.224 | 9.122 | 0.000 | 116.199 179.801 |
| C(mnth)[T.9]:C(hr)[T.14] | 255.9957 | 14.306 | 17.894 | 0.000 | 227.954 284.038 |
| C(mnth)[T.10]:C(hr)[T.14] | 213.0260 | 14.307 | 14.890 | 0.000 | 184.984 241.068 |
| C(mnth)[T.11]:C(hr)[T.14] | 182.0232 | 14.307 | 12.723 | 0.000 | 153.981 210.066 |
| C(mnth)[T.12]:C(hr)[T.14] | 100.0000 | 15.303 | 6.535 | 0.000 | 70.004 129.996 |
| C(mnth)[T.2]:C(hr)[T.15] | 14.0000 | 15.006 | 0.933 | 0.351 | -15.414 43.414 |
| C(mnth)[T.3]:C(hr)[T.15] | 249.0000 | 15.440 | 16.127 | 0.000 | 218.735 279.265 |
| C(mnth)[T.4]:C(hr)[T.15] | 267.9726 | 14.314 | 18.721 | 0.000 | 239.915 296.030 |
| C(mnth)[T.5]:C(hr)[T.15] | 194.0000 | 14.633 | 13.257 | 0.000 | 165.317 222.683 |
| C(mnth)[T.6]:C(hr)[T.15] | 227.0000 | 15.435 | 14.707 | 0.000 | 196.746 257.254 |
| C(mnth)[T.7]:C(hr)[T.15] | 83.0000 | 14.674 | 5.656 | 0.000 | 54.238 111.762 |
| C(mnth)[T.8]:C(hr)[T.15] | 144.0000 | 16.220 | 8.878 | 0.000 | 112.206 175.794 |
| C(mnth)[T.9]:C(hr)[T.15] | 283.9835 | 14.307 | 19.850 | 0.000 | 255.941 312.026 |
| C(mnth)[T.10]:C(hr)[T.15] | 194.0012 | 14.304 | 13.563 | 0.000 | 165.963 222.039 |
| C(mnth)[T.11]:C(hr)[T.15] | 174.0065 | 14.307 | 12.163 | 0.000 | 145.964 202.049 |
| C(mnth)[T.12]:C(hr)[T.15] | 72.0000 | 15.303 | 4.705 | 0.000 | 42.005 101.995 |
| C(mnth)[T.2]:C(hr)[T.16] | 29.0000 | 15.004 | 1.933 | 0.053 | -0.410 58.410 |
| C(mnth)[T.3]:C(hr)[T.16] | 188.0000 | 15.438 | 12.178 | 0.000 | 157.740 218.260 |
| C(mnth)[T.4]:C(hr)[T.16] | 264.9698 | 14.308 | 18.518 | 0.000 | 236.924 293.016 |
| C(mnth)[T.5]:C(hr)[T.16] | 197.0000 | 14.634 | 13.462 | 0.000 | 168.316 225.684 |
| C(mnth)[T.6]:C(hr)[T.16] | 235.0000 | 15.434 | 15.226 | 0.000 | 204.747 265.253 |
| C(mnth)[T.7]:C(hr)[T.16] | 115.0000 | 14.675 | 7.837 | 0.000 | 86.236 143.764 |
| C(mnth)[T.8]:C(hr)[T.16] | 161.0000 | 16.222 | 9.925 | 0.000 | 129.203 192.797 |
| C(mnth)[T.9]:C(hr)[T.16] | 296.9925 | 14.308 | 20.757 | 0.000 | 268.947 325.038 |
| C(mnth)[T.10]:C(hr)[T.16] | 216.0240 | 14.307 | 15.099 | 0.000 | 187.981 244.067 |
| C(mnth)[T.11]:C(hr)[T.16] | 102.0476 | 14.306 | 7.133 | 0.000 | 74.006 130.089 |
| C(mnth)[T.12]:C(hr)[T.16] | 81.0000 | 15.305 | 5.292 | 0.000 | 51.000 111.000 |
| C(mnth)[T.2]:C(hr)[T.17] | 60.0000 | 15.004 | 3.999 | 0.000 | 30.590 89.410 |
| C(mnth)[T.3]:C(hr)[T.17] | 278.0000 | 15.438 | 18.007 | 0.000 | 247.739 308.261 |
| C(mnth)[T.4]:C(hr)[T.17] | 310.9722 | 14.307 | 21.736 | 0.000 | 282.929 339.015 |
| C(mnth)[T.5]:C(hr)[T.17] | 270.0000 | 14.635 | 18.449 | 0.000 | 241.313 298.687 |
| C(mnth)[T.6]:C(hr)[T.17] | 272.0000 | 15.433 | 17.624 | 0.000 | 241.749 302.251 |
| C(mnth)[T.7]:C(hr)[T.17] | 187.0000 | 14.674 | 12.743 | 0.000 | 158.237 215.763 |
| C(mnth)[T.8]:C(hr)[T.17] | 187.0000 | 16.217 | 11.531 | 0.000 | 155.212 218.788 |
| C(mnth)[T.9]:C(hr)[T.17] | 395.9995 | 14.309 | 27.676 | 0.000 | 367.953 424.046 |
| C(mnth)[T.10]:C(hr)[T.17] | 277.0127 | 14.308 | 19.361 | 0.000 | 248.968 305.057 |
| C(mnth)[T.11]:C(hr)[T.17] | 214.0044 | 14.306 | 14.959 | 0.000 | 185.962 242.046 |
| C(mnth)[T.12]:C(hr)[T.17] | 48.0000 | 15.299 | 3.138 | 0.002 | 18.013 77.987 |
| C(mnth)[T.2]:C(hr)[T.18] | 38.0000 | 15.005 | 2.532 | 0.011 | 8.589 67.411 |
| C(mnth)[T.3]:C(hr)[T.18] | 268.0000 | 15.435 | 17.364 | 0.000 | 237.747 298.253 |
| C(mnth)[T.4]:C(hr)[T.18] | 266.9691 | 14.306 | 18.661 | 0.000 | 238.927 295.011 |
| C(mnth)[T.5]:C(hr)[T.18] | 282.0000 | 14.634 | 19.270 | 0.000 | 253.315 310.685 |
| C(mnth)[T.6]:C(hr)[T.18] | 255.0000 | 15.435 | 16.521 | 0.000 | 224.746 285.254 |
| C(mnth)[T.7]:C(hr)[T.18] | 211.0000 | 15.297 | 13.794 | 0.000 | 181.017 240.983 |
| C(mnth)[T.8]:C(hr)[T.18] | 202.0000 | 16.504 | 12.240 | 0.000 | 169.651 234.349 |
| C(mnth)[T.9]:C(hr)[T.18] | 319.9885 | 14.307 | 22.365 | 0.000 | 291.945 348.032 |
| C(mnth)[T.10]:C(hr)[T.18] | 217.9991 | 14.306 | 15.239 | 0.000 | 189.958 246.040 |
| C(mnth)[T.11]:C(hr)[T.18] | 122.0496 | 14.307 | 8.531 | 0.000 | 94.007 150.093 |
| C(mnth)[T.12]:C(hr)[T.18] | 65.0000 | 15.299 | 4.249 | 0.000 | 35.013 94.987 |
| C(mnth)[T.2]:C(hr)[T.19] | 3.0000 | 15.005 | 0.200 | 0.842 | -26.410 32.410 |
| C(mnth)[T.3]:C(hr)[T.19] | 170.0000 | 15.433 | 11.016 | 0.000 | 139.750 200.250 |
| C(mnth)[T.4]:C(hr)[T.19] | 261.9961 | 14.304 | 18.316 | 0.000 | 233.959 290.033 |
| C(mnth)[T.5]:C(hr)[T.19] | 191.0000 | 14.634 | 13.051 | 0.000 | 162.315 219.685 |
| C(mnth)[T.6]:C(hr)[T.19] | 209.0000 | 15.438 | 13.538 | 0.000 | 178.740 239.260 |
| C(mnth)[T.7]:C(hr)[T.19] | 191.0000 | 14.673 | 13.017 | 0.000 | 162.239 219.761 |
| C(mnth)[T.8]:C(hr)[T.19] | 205.0000 | 16.504 | 12.421 | 0.000 | 172.650 237.350 |
| C(mnth)[T.9]:C(hr)[T.19] | 213.9868 | 14.304 | 14.960 | 0.000 | 185.949 242.024 |
| C(mnth)[T.10]:C(hr)[T.19] | 103.0255 | 14.311 | 7.199 | 0.000 | 74.974 131.078 |
| C(mnth)[T.11]:C(hr)[T.19] | 75.0009 | 14.307 | 5.242 | 0.000 | 46.957 103.045 |
| C(mnth)[T.12]:C(hr)[T.19] | 38.0000 | 14.670 | 2.590 | 0.010 | 9.245 66.755 |
| C(mnth)[T.2]:C(hr)[T.20] | 11.0000 | 14.425 | 0.763 | 0.446 | -17.275 39.275 |
| C(mnth)[T.3]:C(hr)[T.20] | 87.0000 | 14.874 | 5.849 | 0.000 | 57.845 116.155 |
| C(mnth)[T.4]:C(hr)[T.20] | 149.9706 | 13.703 | 10.945 | 0.000 | 123.112 176.829 |
| C(mnth)[T.5]:C(hr)[T.20] | 125.0000 | 14.039 | 8.904 | 0.000 | 97.482 152.518 |
| C(mnth)[T.6]:C(hr)[T.20] | 158.0000 | 14.872 | 10.624 | 0.000 | 128.850 187.150 |
| C(mnth)[T.7]:C(hr)[T.20] | 158.0000 | 14.081 | 11.220 | 0.000 | 130.399 185.601 |
| C(mnth)[T.8]:C(hr)[T.20] | 97.0000 | 15.981 | 6.070 | 0.000 | 65.676 128.324 |
| C(mnth)[T.9]:C(hr)[T.20] | 114.9842 | 13.699 | 8.394 | 0.000 | 88.133 141.835 |
| C(mnth)[T.10]:C(hr)[T.20] | 56.9987 | 13.697 | 4.161 | 0.000 | 30.151 83.847 |
| C(mnth)[T.11]:C(hr)[T.20] | 74.0002 | 13.696 | 5.403 | 0.000 | 47.154 100.847 |
| C(mnth)[T.12]:C(hr)[T.20] | 33.0000 | 14.729 | 2.240 | 0.025 | 4.130 61.870 |
| C(mnth)[T.2]:C(hr)[T.21] | 17.0000 | 15.004 | 1.133 | 0.257 | -12.409 46.409 |
| C(mnth)[T.3]:C(hr)[T.21] | 23.0000 | 15.434 | 1.490 | 0.136 | -7.253 53.253 |
| C(mnth)[T.4]:C(hr)[T.21] | 72.9793 | 14.307 | 5.101 | 0.000 | 44.937 101.022 |
| C(mnth)[T.5]:C(hr)[T.21] | 111.0000 | 14.633 | 7.586 | 0.000 | 82.318 139.682 |
| C(mnth)[T.6]:C(hr)[T.21] | 95.0000 | 16.335 | 5.816 | 0.000 | 62.982 127.018 |
| C(mnth)[T.7]:C(hr)[T.21] | 103.0000 | 15.298 | 6.733 | 0.000 | 73.015 132.985 |
| C(mnth)[T.8]:C(hr)[T.21] | 83.0000 | 16.504 | 5.029 | 0.000 | 50.651 115.349 |
| C(mnth)[T.9]:C(hr)[T.21] | 85.9894 | 14.306 | 6.011 | 0.000 | 57.949 114.030 |
| C(mnth)[T.10]:C(hr)[T.21] | 37.0019 | 14.307 | 2.586 | 0.010 | 8.959 65.045 |
| C(mnth)[T.11]:C(hr)[T.21] | 34.0023 | 14.306 | 2.377 | 0.017 | 5.960 62.044 |
| C(mnth)[T.12]:C(hr)[T.21] | 12.0000 | 15.299 | 0.784 | 0.433 | -17.987 41.987 |
| C(mnth)[T.2]:C(hr)[T.22] | 30.0000 | 15.007 | 1.999 | 0.046 | 0.585 59.415 |
| C(mnth)[T.3]:C(hr)[T.22] | 9.0000 | 15.435 | 0.583 | 0.560 | -21.255 39.255 |
| C(mnth)[T.4]:C(hr)[T.22] | 61.9843 | 14.314 | 4.330 | 0.000 | 33.927 90.042 |
| C(mnth)[T.5]:C(hr)[T.22] | 95.0000 | 14.634 | 6.492 | 0.000 | 66.315 123.685 |
| C(mnth)[T.6]:C(hr)[T.22] | 71.0000 | 15.436 | 4.600 | 0.000 | 40.743 101.257 |
| C(mnth)[T.7]:C(hr)[T.22] | 72.0000 | 14.675 | 4.906 | 0.000 | 43.236 100.764 |
| C(mnth)[T.8]:C(hr)[T.22] | 39.0000 | 16.504 | 2.363 | 0.018 | 6.650 71.350 |
| C(mnth)[T.9]:C(hr)[T.22] | 60.9915 | 14.308 | 4.263 | 0.000 | 32.947 89.036 |
| C(mnth)[T.10]:C(hr)[T.22] | 17.9997 | 14.307 | 1.258 | 0.208 | -10.044 46.044 |
| C(mnth)[T.11]:C(hr)[T.22] | 21.0027 | 14.307 | 1.468 | 0.142 | -7.041 49.046 |
| C(mnth)[T.12]:C(hr)[T.22] | 3.0000 | 15.299 | 0.196 | 0.845 | -26.988 32.988 |
| C(mnth)[T.2]:C(hr)[T.23] | 14.0000 | 14.426 | 0.971 | 0.332 | -14.276 42.276 |
| C(mnth)[T.3]:C(hr)[T.23] | -14.0000 | 14.870 | -0.941 | 0.346 | -43.147 15.147 |
| C(mnth)[T.4]:C(hr)[T.23] | 44.9793 | 13.699 | 3.284 | 0.001 | 18.129 71.830 |
| C(mnth)[T.5]:C(hr)[T.23] | 35.0000 | 14.038 | 2.493 | 0.013 | 7.483 62.517 |
| C(mnth)[T.6]:C(hr)[T.23] | 35.0000 | 15.803 | 2.215 | 0.027 | 4.024 65.976 |
| C(mnth)[T.7]:C(hr)[T.23] | 11.0000 | 14.077 | 0.781 | 0.435 | -16.593 38.593 |
| C(mnth)[T.8]:C(hr)[T.23] | 4.0000 | 15.978 | 0.250 | 0.802 | -27.319 35.319 |
| C(mnth)[T.9]:C(hr)[T.23] | 20.9839 | 13.698 | 1.532 | 0.126 | -5.866 47.834 |
| C(mnth)[T.10]:C(hr)[T.23] | -8.9943 | 13.698 | -0.657 | 0.511 | -35.844 17.855 |
| C(mnth)[T.11]:C(hr)[T.23] | 6.9997 | 13.697 | 0.511 | 0.609 | -19.847 33.846 |
| C(mnth)[T.12]:C(hr)[T.23] | -9.0000 | 14.079 | -0.639 | 0.523 | -36.596 18.596 |
| C(workingday)[T.1]:C(hr)[T.1] | -2.0000 | 12.445 | -0.161 | 0.872 | -26.394 22.394 |
| C(workingday)[T.1]:C(hr)[T.2] | 6.0000 | 12.874 | 0.466 | 0.641 | -19.234 31.234 |
| C(workingday)[T.1]:C(hr)[T.3] | 6.0000 | 12.832 | 0.468 | 0.640 | -19.152 31.152 |
| C(workingday)[T.1]:C(hr)[T.4] | 14.0000 | 12.547 | 1.116 | 0.265 | -10.593 38.593 |
| C(workingday)[T.1]:C(hr)[T.5] | 19.0000 | 12.579 | 1.510 | 0.131 | -5.656 43.656 |
| C(workingday)[T.1]:C(hr)[T.6] | 46.0000 | 12.228 | 3.762 | 0.000 | 22.033 69.967 |
| C(workingday)[T.1]:C(hr)[T.7] | 167.0000 | 12.761 | 13.087 | 0.000 | 141.987 192.013 |
| C(workingday)[T.1]:C(hr)[T.8] | 402.0000 | 12.077 | 33.285 | 0.000 | 378.327 425.673 |
| C(workingday)[T.1]:C(hr)[T.9] | 139.0000 | 12.763 | 10.891 | 0.000 | 113.983 164.017 |
| C(workingday)[T.1]:C(hr)[T.10] | -19.0000 | 12.081 | -1.573 | 0.116 | -42.680 4.680 |
| C(workingday)[T.1]:C(hr)[T.11] | -79.0000 | 12.769 | -6.187 | 0.000 | -104.028 -53.972 |
| C(workingday)[T.1]:C(hr)[T.12] | -107.0000 | 12.719 | -8.412 | 0.000 | -131.931 -82.069 |
| C(workingday)[T.1]:C(hr)[T.13] | -126.0000 | 12.720 | -9.905 | 0.000 | -150.933 -101.067 |
| C(workingday)[T.1]:C(hr)[T.14] | -136.0000 | 12.720 | -10.692 | 0.000 | -160.933 -111.067 |
| C(workingday)[T.1]:C(hr)[T.15] | -126.0000 | 12.718 | -9.907 | 0.000 | -150.929 -101.071 |
| C(workingday)[T.1]:C(hr)[T.16] | -38.9999 | 12.709 | -3.069 | 0.002 | -63.910 -14.090 |
| C(workingday)[T.1]:C(hr)[T.17] | 252.0085 | 12.672 | 19.888 | 0.000 | 227.171 276.846 |
| C(workingday)[T.1]:C(hr)[T.18] | 247.0000 | 12.755 | 19.365 | 0.000 | 221.999 272.001 |
| C(workingday)[T.1]:C(hr)[T.19] | 163.0000 | 12.717 | 12.818 | 0.000 | 138.074 187.926 |
| C(workingday)[T.1]:C(hr)[T.20] | 104.0000 | 12.031 | 8.644 | 0.000 | 80.418 127.582 |
| C(workingday)[T.1]:C(hr)[T.21] | 56.0000 | 12.718 | 4.403 | 0.000 | 31.072 80.928 |
| C(workingday)[T.1]:C(hr)[T.22] | 37.0000 | 12.721 | 2.909 | 0.004 | 12.065 61.935 |
| C(workingday)[T.1]:C(hr)[T.23] | 14.0000 | 12.030 | 1.164 | 0.245 | -9.579 37.579 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[0] | -5.0000 | 12.793 | -0.391 | 0.696 | -30.077 20.077 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[0] | -25.0000 | 12.938 | -1.932 | 0.053 | -50.361 0.361 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[0] | -9.0306 | 12.299 | -0.734 | 0.463 | -33.138 15.077 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[0] | -38.0000 | 12.546 | -3.029 | 0.002 | -62.591 -13.409 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[0] | -49.0000 | 13.017 | -3.764 | 0.000 | -74.515 -23.485 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[0] | -67.0000 | 13.027 | -5.143 | 0.000 | -92.535 -41.465 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[0] | -65.0000 | 13.553 | -4.796 | 0.000 | -91.565 -38.435 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[0] | -48.0168 | 12.297 | -3.905 | 0.000 | -72.120 -23.913 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[0] | -73.0014 | 12.252 | -5.958 | 0.000 | -97.016 -48.987 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[0] | -28.0009 | 12.295 | -2.277 | 0.023 | -52.101 -3.901 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[0] | -26.0000 | 12.838 | -2.025 | 0.043 | -51.163 -0.837 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[1] | -4.0000 | 12.475 | -0.321 | 0.748 | -28.453 20.453 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[1] | -10.0000 | 12.606 | -0.793 | 0.428 | -34.710 14.710 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[1] | -0.0823 | 11.953 | -0.007 | 0.995 | -23.511 23.346 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[1] | -44.0000 | 12.215 | -3.602 | 0.000 | -67.943 -20.057 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[1] | -49.0000 | 13.774 | -3.557 | 0.000 | -75.999 -22.001 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[1] | -55.0000 | 12.704 | -4.329 | 0.000 | -79.901 -30.099 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[1] | -44.0000 | 13.383 | -3.288 | 0.001 | -70.231 -17.769 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[1] | -44.0055 | 12.000 | -3.667 | 0.000 | -67.527 -20.483 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[1] | -33.0004 | 12.174 | -2.711 | 0.007 | -56.862 -9.139 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[1] | -41.0229 | 12.171 | -3.371 | 0.001 | -64.879 -17.166 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[1] | -33.0000 | 12.706 | -2.597 | 0.009 | -57.905 -8.095 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[2] | -4.0000 | 13.011 | -0.307 | 0.759 | -29.504 21.504 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[2] | -10.0000 | 13.754 | -0.727 | 0.467 | -36.960 16.960 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[2] | -13.3118 | 12.612 | -1.055 | 0.291 | -38.033 11.409 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[2] | -34.0000 | 12.832 | -2.650 | 0.008 | -59.151 -8.849 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[2] | -48.0000 | 13.123 | -3.658 | 0.000 | -73.723 -22.277 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[2] | -46.0000 | 13.496 | -3.408 | 0.001 | -72.454 -19.546 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[2] | -49.0000 | 13.648 | -3.590 | 0.000 | -75.752 -22.248 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[2] | -53.0034 | 12.450 | -4.257 | 0.000 | -77.406 -28.600 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[2] | -37.0217 | 12.610 | -2.936 | 0.003 | -61.739 -12.304 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[2] | -21.0012 | 12.459 | -1.686 | 0.092 | -45.422 3.420 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[2] | -40.0000 | 12.942 | -3.091 | 0.002 | -65.367 -14.633 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[3] | 1.0000 | 13.159 | 0.076 | 0.939 | -24.794 26.794 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[3] | -6.0000 | 13.077 | -0.459 | 0.646 | -31.633 19.633 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[3] | -1.7468 | 12.453 | -0.140 | 0.888 | -26.156 22.663 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[3] | -14.0000 | 12.605 | -1.111 | 0.267 | -38.707 10.707 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[3] | -19.0000 | 13.074 | -1.453 | 0.146 | -44.626 6.626 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[3] | -25.0000 | 13.084 | -1.911 | 0.056 | -50.646 0.646 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[3] | -32.0000 | 13.750 | -2.327 | 0.020 | -58.952 -5.048 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[3] | -19.0000 | 12.626 | -1.505 | 0.132 | -43.749 5.749 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[3] | -13.3605 | 12.405 | -1.077 | 0.281 | -37.675 10.954 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[3] | 5.9921 | 12.455 | 0.481 | 0.630 | -18.421 30.405 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[3] | -12.0000 | 12.699 | -0.945 | 0.345 | -36.891 12.891 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[4] | -1.0000 | 14.243 | -0.070 | 0.944 | -28.918 26.918 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[4] | -5.0000 | 13.272 | -0.377 | 0.706 | -31.015 21.015 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[4] | 1.0000 | 12.333 | 0.081 | 0.935 | -23.174 25.174 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[4] | -1.0000 | 12.314 | -0.081 | 0.935 | -25.137 23.137 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[4] | -4.0000 | 12.797 | -0.313 | 0.755 | -29.084 21.084 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[4] | -5.0000 | 12.053 | -0.415 | 0.678 | -28.625 18.625 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[4] | -3.0000 | 14.647 | -0.205 | 0.838 | -31.710 25.710 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[4] | 6.0000 | 12.064 | 0.497 | 0.619 | -17.647 29.647 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[4] | 7.881e-06 | 12.062 | 6.53e-07 | 1.000 | -23.643 23.643 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[4] | 4.9998 | 12.063 | 0.414 | 0.679 | -18.645 28.644 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[4] | 3.8612 | 12.107 | 0.319 | 0.750 | -19.869 27.591 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[5] | -6.0000 | 13.723 | -0.437 | 0.662 | -32.899 20.899 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[5] | 3.0000 | 13.411 | 0.224 | 0.823 | -23.287 29.287 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[5] | 7.0000 | 12.316 | 0.568 | 0.570 | -17.140 31.140 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[5] | 8.0000 | 12.360 | 0.647 | 0.517 | -16.227 32.227 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[5] | 10.0000 | 12.839 | 0.779 | 0.436 | -15.165 35.165 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[5] | 10.0000 | 12.649 | 0.791 | 0.429 | -14.794 34.794 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[5] | 10.0000 | 13.373 | 0.748 | 0.455 | -16.213 36.213 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[5] | 18.0189 | 12.310 | 1.464 | 0.143 | -6.109 42.147 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[5] | 11.0000 | 12.102 | 0.909 | 0.363 | -12.721 34.721 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[5] | 15.8509 | 11.887 | 1.333 | 0.182 | -7.449 39.150 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[5] | 17.0000 | 11.890 | 1.430 | 0.153 | -6.306 40.306 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[6] | 1.783e-06 | 12.210 | 1.46e-07 | 1.000 | -23.932 23.932 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[6] | 11.0000 | 13.513 | 0.814 | 0.416 | -15.486 37.486 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[6] | 8.0254 | 11.731 | 0.684 | 0.494 | -14.969 31.020 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[6] | 60.0000 | 12.178 | 4.927 | 0.000 | 36.129 83.871 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[6] | 55.0000 | 12.485 | 4.405 | 0.000 | 30.528 79.472 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[6] | 61.0000 | 12.496 | 4.882 | 0.000 | 36.507 85.493 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[6] | 60.0000 | 13.036 | 4.603 | 0.000 | 34.449 85.551 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[6] | 69.0000 | 12.580 | 5.485 | 0.000 | 44.341 93.659 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[6] | 62.0000 | 11.949 | 5.189 | 0.000 | 38.579 85.421 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[6] | 51.0000 | 12.781 | 3.990 | 0.000 | 25.948 76.052 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[6] | 50.0000 | 11.721 | 4.266 | 0.000 | 27.026 72.974 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[7] | 34.0000 | 13.715 | 2.479 | 0.013 | 7.116 60.884 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[7] | 98.0000 | 12.946 | 7.570 | 0.000 | 72.625 123.375 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[7] | 94.9094 | 12.297 | 7.718 | 0.000 | 70.807 119.012 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[7] | 175.0000 | 12.546 | 13.948 | 0.000 | 150.408 199.592 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[7] | 204.0000 | 13.017 | 15.672 | 0.000 | 178.485 229.515 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[7] | 214.0000 | 13.022 | 16.433 | 0.000 | 188.475 239.525 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[7] | 212.0000 | 13.200 | 16.061 | 0.000 | 186.127 237.873 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[7] | 266.0002 | 12.295 | 21.635 | 0.000 | 241.901 290.100 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[7] | 197.9977 | 12.292 | 16.108 | 0.000 | 173.905 222.090 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[7] | 129.9966 | 12.291 | 10.577 | 0.000 | 105.905 154.088 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[7] | 113.0000 | 12.290 | 9.195 | 0.000 | 88.911 137.089 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[8] | -11.0000 | 12.061 | -0.912 | 0.362 | -34.640 12.640 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[8] | 107.0000 | 12.262 | 8.726 | 0.000 | 82.966 131.034 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[8] | 86.0067 | 11.580 | 7.427 | 0.000 | 63.308 108.705 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[8] | 80.0000 | 11.846 | 6.753 | 0.000 | 56.780 103.220 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[8] | 75.0000 | 12.341 | 6.077 | 0.000 | 50.810 99.190 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[8] | 125.0000 | 11.355 | 11.008 | 0.000 | 102.743 147.257 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[8] | 136.0000 | 12.536 | 10.848 | 0.000 | 111.427 160.573 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[8] | 186.0019 | 11.582 | 16.059 | 0.000 | 163.299 208.705 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[8] | 208.0078 | 11.581 | 17.961 | 0.000 | 185.308 230.707 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[8] | 108.9989 | 11.579 | 9.413 | 0.000 | 86.302 131.696 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[8] | 148.0000 | 11.571 | 12.791 | 0.000 | 125.320 170.680 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[9] | -3.0000 | 13.716 | -0.219 | 0.827 | -29.885 23.885 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[9] | -47.0000 | 12.938 | -3.633 | 0.000 | -72.361 -21.639 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[9] | -44.0546 | 12.297 | -3.583 | 0.000 | -68.158 -19.951 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[9] | -89.0000 | 12.543 | -7.096 | 0.000 | -113.586 -64.414 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[9] | -106.0000 | 13.015 | -8.144 | 0.000 | -131.512 -80.488 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[9] | -105.0000 | 12.286 | -8.546 | 0.000 | -129.082 -80.918 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[9] | -35.0000 | 13.202 | -2.651 | 0.008 | -60.878 -9.122 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[9] | -104.0035 | 12.299 | -8.457 | 0.000 | -128.110 -79.897 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[9] | -73.0378 | 12.291 | -5.942 | 0.000 | -97.129 -48.946 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[9] | -42.0041 | 12.294 | -3.417 | 0.001 | -66.101 -17.907 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[9] | 2.02e-07 | 13.027 | 1.55e-08 | 1.000 | -25.533 25.533 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[10] | -6.0000 | 12.062 | -0.497 | 0.619 | -29.643 17.643 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[10] | -133.0000 | 12.259 | -10.849 | 0.000 | -157.029 -108.971 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[10] | -135.0005 | 11.580 | -11.658 | 0.000 | -157.698 -112.303 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[10] | -159.0000 | 11.848 | -13.420 | 0.000 | -182.223 -135.777 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[10] | -208.0000 | 12.343 | -16.851 | 0.000 | -232.195 -183.805 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[10] | -133.0000 | 12.152 | -10.945 | 0.000 | -156.819 -109.181 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[10] | -157.0000 | 12.535 | -12.525 | 0.000 | -181.570 -132.430 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[10] | -213.9948 | 11.582 | -18.477 | 0.000 | -236.696 -191.293 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[10] | -183.7992 | 11.580 | -15.872 | 0.000 | -206.497 -161.102 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[10] | -91.9954 | 11.582 | -7.943 | 0.000 | -114.696 -69.294 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[10] | -31.0000 | 11.357 | -2.730 | 0.006 | -53.260 -8.740 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[11] | 7.0000 | 12.749 | 0.549 | 0.583 | -17.988 31.988 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[11] | -144.0000 | 12.936 | -11.132 | 0.000 | -169.355 -118.645 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[11] | -177.0208 | 12.293 | -14.400 | 0.000 | -201.116 -152.926 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[11] | -206.0000 | 12.549 | -16.416 | 0.000 | -230.596 -181.404 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[11] | -205.0000 | 13.016 | -15.750 | 0.000 | -230.512 -179.488 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[11] | -129.0000 | 12.832 | -10.053 | 0.000 | -154.153 -103.847 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[11] | -122.0000 | 13.198 | -9.244 | 0.000 | -147.870 -96.130 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[11] | -235.0028 | 12.295 | -19.113 | 0.000 | -259.103 -210.903 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[11] | -199.0373 | 12.293 | -16.192 | 0.000 | -223.132 -174.943 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[11] | -103.0288 | 12.296 | -8.379 | 0.000 | -127.129 -78.928 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[11] | -53.0000 | 13.024 | -4.070 | 0.000 | -78.528 -27.472 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[12] | 40.0000 | 13.669 | 2.926 | 0.003 | 13.208 66.792 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[12] | -216.0000 | 12.891 | -16.755 | 0.000 | -241.268 -190.732 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[12] | -194.0087 | 12.244 | -15.845 | 0.000 | -218.009 -170.008 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[12] | -171.0000 | 12.497 | -13.683 | 0.000 | -195.496 -146.504 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[12] | -207.0000 | 13.141 | -15.753 | 0.000 | -232.757 -181.243 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[12] | -73.0000 | 12.978 | -5.625 | 0.000 | -98.439 -47.561 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[12] | -160.0000 | 13.150 | -12.167 | 0.000 | -185.776 -134.224 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[12] | -228.9941 | 12.245 | -18.701 | 0.000 | -252.995 -204.993 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[12] | -169.0030 | 12.244 | -13.803 | 0.000 | -193.003 -145.003 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[12] | -83.0559 | 12.245 | -6.783 | 0.000 | -107.057 -59.055 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[12] | -38.0000 | 12.235 | -3.106 | 0.002 | -61.981 -14.019 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[13] | 3.0000 | 12.703 | 0.236 | 0.813 | -21.899 27.899 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[13] | -212.0000 | 12.890 | -16.446 | 0.000 | -237.267 -186.733 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[13] | -162.0095 | 12.246 | -13.230 | 0.000 | -186.012 -138.007 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[13] | -178.0000 | 12.500 | -14.240 | 0.000 | -202.501 -153.499 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[13] | -211.0000 | 12.971 | -16.268 | 0.000 | -236.424 -185.576 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[13] | -136.0000 | 12.034 | -11.302 | 0.000 | -159.587 -112.413 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[13] | -79.0000 | 13.160 | -6.003 | 0.000 | -104.795 -53.205 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[13] | -195.9967 | 12.244 | -16.008 | 0.000 | -219.996 -171.997 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[13] | -230.0001 | 12.206 | -18.844 | 0.000 | -253.924 -206.076 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[13] | -85.0135 | 12.245 | -6.943 | 0.000 | -109.016 -61.011 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[13] | -25.0000 | 12.241 | -2.042 | 0.041 | -48.994 -1.006 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[14] | -33.0000 | 12.701 | -2.598 | 0.009 | -57.895 -8.105 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[14] | -147.0000 | 12.891 | -11.403 | 0.000 | -172.269 -121.731 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[14] | -153.0144 | 12.245 | -12.496 | 0.000 | -177.016 -129.013 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[14] | -155.0000 | 12.498 | -12.402 | 0.000 | -179.497 -130.503 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[14] | -171.0000 | 12.970 | -13.184 | 0.000 | -196.423 -145.577 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[14] | -79.0000 | 12.033 | -6.566 | 0.000 | -102.585 -55.415 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[14] | -91.0000 | 13.159 | -6.915 | 0.000 | -116.793 -65.207 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[14] | -148.0047 | 12.246 | -12.086 | 0.000 | -172.007 -124.002 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[14] | -137.0274 | 12.400 | -11.050 | 0.000 | -161.333 -112.721 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[14] | -107.0138 | 12.245 | -8.739 | 0.000 | -131.015 -83.012 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[14] | -46.0000 | 12.984 | -3.543 | 0.000 | -71.451 -20.549 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[15] | 2.0000 | 12.705 | 0.157 | 0.875 | -22.903 26.903 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[15] | -181.0000 | 12.890 | -14.042 | 0.000 | -206.266 -155.734 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[15] | -154.0005 | 12.244 | -12.578 | 0.000 | -177.999 -130.002 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[15] | -104.0000 | 12.496 | -8.322 | 0.000 | -128.494 -79.506 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[15] | -169.0000 | 12.970 | -13.030 | 0.000 | -194.422 -143.578 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[15] | -58.0000 | 12.033 | -4.820 | 0.000 | -81.586 -34.414 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[15] | -80.0000 | 13.158 | -6.080 | 0.000 | -105.791 -54.209 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[15] | -201.9974 | 12.249 | -16.492 | 0.000 | -226.006 -177.989 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[15] | -86.0026 | 12.200 | -7.049 | 0.000 | -109.916 -62.089 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[15] | -74.9986 | 12.247 | -6.124 | 0.000 | -99.004 -50.994 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[15] | 3.0000 | 12.981 | 0.231 | 0.817 | -22.444 28.444 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[16] | -1.0001 | 12.693 | -0.079 | 0.937 | -25.880 23.880 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[16] | -98.0001 | 12.882 | -7.608 | 0.000 | -123.250 -72.750 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[16] | -119.9789 | 12.237 | -9.805 | 0.000 | -143.965 -95.993 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[16] | -54.0001 | 12.490 | -4.323 | 0.000 | -78.482 -29.518 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[16] | -137.0001 | 12.964 | -10.568 | 0.000 | -162.410 -111.590 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[16] | -8.0001 | 12.227 | -0.654 | 0.513 | -31.966 15.966 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[16] | -38.0001 | 13.150 | -2.890 | 0.004 | -63.774 -12.226 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[16] | -137.0093 | 12.238 | -11.196 | 0.000 | -160.996 -113.023 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[16] | -41.0255 | 12.395 | -3.310 | 0.001 | -65.320 -16.731 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[16] | -9.0467 | 12.238 | -0.739 | 0.460 | -33.035 14.941 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[16] | -15.0001 | 12.976 | -1.156 | 0.248 | -40.434 10.434 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[17] | -13.0085 | 12.441 | -1.046 | 0.296 | -37.393 11.376 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[17] | -50.0085 | 12.846 | -3.893 | 0.000 | -75.188 -24.829 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[17] | -61.0038 | 12.203 | -4.999 | 0.000 | -84.924 -37.084 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[17] | -5.0085 | 12.273 | -0.408 | 0.683 | -29.065 19.048 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[17] | 20.9915 | 12.752 | 1.646 | 0.100 | -4.004 45.987 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[17] | 79.9915 | 12.190 | 6.562 | 0.000 | 56.097 103.886 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[17] | 109.9915 | 13.108 | 8.391 | 0.000 | 84.298 135.685 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[17] | -23.0211 | 12.199 | -1.887 | 0.059 | -46.932 0.889 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[17] | 75.9773 | 12.157 | 6.250 | 0.000 | 52.148 99.806 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[17] | -91.0135 | 11.983 | -7.595 | 0.000 | -114.502 -67.525 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[17] | 53.9915 | 12.742 | 4.237 | 0.000 | 29.016 78.967 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[18] | 49.0000 | 12.744 | 3.845 | 0.000 | 24.020 73.980 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[18] | 57.0000 | 12.929 | 4.409 | 0.000 | 31.657 82.343 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[18] | -8.9833 | 12.290 | -0.731 | 0.465 | -33.073 15.107 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[18] | 3.0000 | 12.720 | 0.236 | 0.814 | -21.932 27.932 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[18] | 48.0000 | 13.014 | 3.688 | 0.000 | 22.492 73.508 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[18] | 87.0000 | 13.016 | 6.684 | 0.000 | 61.487 112.513 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[18] | 125.0000 | 13.542 | 9.231 | 0.000 | 98.457 151.543 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[18] | 66.9977 | 12.288 | 5.452 | 0.000 | 42.912 91.083 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[18] | 97.9994 | 12.441 | 7.877 | 0.000 | 73.613 122.386 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[18] | -16.0486 | 12.285 | -1.306 | 0.191 | -40.129 8.031 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[18] | 36.0000 | 13.017 | 2.766 | 0.006 | 10.486 61.514 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[19] | -2.0000 | 12.704 | -0.157 | 0.875 | -26.902 22.902 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[19] | 27.0000 | 12.890 | 2.095 | 0.036 | 1.734 52.266 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[19] | -112.0264 | 12.246 | -9.148 | 0.000 | -136.030 -88.023 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[19] | -43.0000 | 12.501 | -3.440 | 0.001 | -67.504 -18.496 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[19] | -15.0000 | 12.973 | -1.156 | 0.248 | -40.428 10.428 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[19] | 9.0000 | 12.036 | 0.748 | 0.455 | -14.592 32.592 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[19] | 14.0000 | 13.506 | 1.037 | 0.300 | -12.473 40.473 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[19] | 9.9984 | 12.244 | 0.817 | 0.414 | -14.001 33.998 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[19] | 18.9730 | 12.203 | 1.555 | 0.120 | -4.946 42.892 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[19] | -44.0012 | 12.246 | -3.593 | 0.000 | -68.006 -19.997 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[19] | 10.0000 | 12.034 | 0.831 | 0.406 | -13.588 33.588 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[20] | -18.0000 | 12.011 | -1.499 | 0.134 | -41.543 5.543 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[20] | 15.0000 | 12.210 | 1.228 | 0.219 | -8.933 38.933 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[20] | -35.0008 | 11.529 | -3.036 | 0.002 | -57.599 -12.403 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[20] | 4.0000 | 11.604 | 0.345 | 0.730 | -18.744 26.744 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[20] | -13.0000 | 12.294 | -1.057 | 0.290 | -37.097 11.097 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[20] | -14.0000 | 11.302 | -1.239 | 0.215 | -36.152 8.152 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[20] | 45.0000 | 12.857 | 3.500 | 0.000 | 19.800 70.200 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[20] | 8.0038 | 11.527 | 0.694 | 0.487 | -14.590 30.598 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[20] | 29.9998 | 11.484 | 2.612 | 0.009 | 7.491 52.509 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[20] | -43.9996 | 11.528 | -3.817 | 0.000 | -66.595 -21.404 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[20] | -6.0000 | 12.103 | -0.496 | 0.620 | -29.723 17.723 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[21] | 16.0000 | 12.702 | 1.260 | 0.208 | -8.897 40.897 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[21] | 33.0000 | 12.890 | 2.560 | 0.010 | 7.734 58.266 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[21] | 13.9902 | 12.247 | 1.142 | 0.253 | -10.015 37.996 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[21] | -33.0000 | 12.498 | -2.640 | 0.008 | -57.497 -8.503 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[21] | -4.0000 | 14.029 | -0.285 | 0.776 | -31.499 23.499 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[21] | -25.0000 | 12.979 | -1.926 | 0.054 | -50.439 0.439 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[21] | -18.0000 | 13.503 | -1.333 | 0.183 | -44.467 8.467 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[21] | -22.0063 | 12.246 | -1.797 | 0.072 | -46.011 1.998 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[21] | -9.0034 | 12.400 | -0.726 | 0.468 | -33.309 15.303 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[21] | 9.9976 | 12.244 | 0.817 | 0.414 | -14.001 33.997 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[21] | 19.0000 | 12.979 | 1.464 | 0.143 | -6.440 44.440 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[22] | -19.0000 | 12.703 | -1.496 | 0.135 | -43.898 5.898 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[22] | 9.0000 | 12.890 | 0.698 | 0.485 | -16.266 34.266 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[22] | -6.0146 | 12.247 | -0.491 | 0.623 | -30.020 17.991 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[22] | -56.0000 | 12.498 | -4.481 | 0.000 | -80.497 -31.503 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[22] | -15.0000 | 12.972 | -1.156 | 0.248 | -40.427 10.427 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[22] | -42.0000 | 12.034 | -3.490 | 0.000 | -65.587 -18.413 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[22] | -4.0000 | 13.501 | -0.296 | 0.767 | -30.463 22.463 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[22] | -12.0060 | 12.245 | -0.980 | 0.327 | -36.008 11.996 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[22] | -20.0012 | 12.205 | -1.639 | 0.101 | -43.923 3.921 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[22] | -5.0033 | 12.244 | -0.409 | 0.683 | -29.004 18.997 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[22] | 10.0000 | 12.788 | 0.782 | 0.434 | -15.065 35.065 |
| C(mnth)[T.2]:C(workingday)[T.1]:C(hr)[23] | -7.0000 | 12.010 | -0.583 | 0.560 | -30.541 16.541 |
| C(mnth)[T.3]:C(workingday)[T.1]:C(hr)[23] | 2.0000 | 12.213 | 0.164 | 0.870 | -21.938 25.938 |
| C(mnth)[T.4]:C(workingday)[T.1]:C(hr)[23] | -11.0096 | 11.525 | -0.955 | 0.339 | -33.600 11.581 |
| C(mnth)[T.5]:C(workingday)[T.1]:C(hr)[23] | -28.0000 | 11.982 | -2.337 | 0.019 | -51.486 -4.514 |
| C(mnth)[T.6]:C(workingday)[T.1]:C(hr)[23] | -24.0000 | 13.405 | -1.790 | 0.073 | -50.274 2.274 |
| C(mnth)[T.7]:C(workingday)[T.1]:C(hr)[23] | -23.0000 | 11.301 | -2.035 | 0.042 | -45.152 -0.848 |
| C(mnth)[T.8]:C(workingday)[T.1]:C(hr)[23] | -6.0000 | 12.857 | -0.467 | 0.641 | -31.201 19.201 |
| C(mnth)[T.9]:C(workingday)[T.1]:C(hr)[23] | -7.9901 | 11.523 | -0.693 | 0.488 | -30.576 14.596 |
| C(mnth)[T.10]:C(workingday)[T.1]:C(hr)[23] | -22.0072 | 11.480 | -1.917 | 0.055 | -44.510 0.495 |
| C(mnth)[T.11]:C(workingday)[T.1]:C(hr)[23] | 2.0020 | 11.527 | 0.174 | 0.862 | -20.593 24.597 |
| C(mnth)[T.12]:C(workingday)[T.1]:C(hr)[23] | 11.0000 | 11.303 | 0.973 | 0.330 | -11.154 33.154 |
5. Prediction function for daily usage¶
In [19]:
class utilization_prediction:
def __init__(self, data):
self.data = data
import pandas as pd
import numpy as np
from statsmodels.regression.quantile_regression import QuantReg
# can be called once a day to learn model on given data
def fit_model(self, desired_reliability):
qr = QuantReg.from_formula(formula='cnt ~ C(hr) + C(yr) + C(mnth) + C(workingday) + C(weathersit) + C(mnth):C(workingday):C(hr) ', data=self.data)
self.qr_model = qr.fit(q = desired_reliability)
#qr = smf.ols(formula='cnt ~ C(hr) + C(yr) + C(mnth) + C(workingday) + C(weathersit) + C(mnth):C(workingday):C(hr) ', data=self.data)
#self.qr_model = qr.fit()
# can be called multiple times a day to produce a prediction of a specific scenario
def prediction(self,yr,mnth,workingday,weathersit):
col_names = ['hr','yr','mnth','workingday','weathersit']
X = pd.DataFrame( columns = col_names)
hours = range(0,24)
for hour in hours:
X = X.append(pd.DataFrame([[hour,yr,mnth,workingday,weathersit]], columns = col_names))
results = self.qr_model.predict(X)
return(results)
In [20]:
#define model
model = utilization_prediction(hour)
In [21]:
# fit model for specific confidence level
model.fit_model(desired_reliability=0.9)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:189: ConvergenceWarning: Convergence cycle detected
warnings.warn("Convergence cycle detected", ConvergenceWarning)
//anaconda/lib/python3.5/site-packages/statsmodels/regression/quantile_regression.py:193: IterationLimitWarning: Maximum number of iterations (1000) reached.
IterationLimitWarning)
In [22]:
# predict utilization per hour for given attributes
model.prediction(yr=1,mnth=9,workingday=0,weathersit=1)
Out[22]:
array([ 207.01685883, 183.00547201, 176.00336414, 138.00000859,
104.00000355, 106.98114753, 117.99999937, 139.00004075,
218.00044648, 342.00454898, 489.00039153, 626.00289637,
706.00063622, 704.00528977, 666.0125366 , 696.00036021,
701.0093322 , 712.0163873 , 594.00534896, 470.00366992,
338.00110268, 302.00626652, 270.00834781, 231.00080933])
In [23]:
# predict utilization per hour for given attributes
model.prediction(yr=1,mnth=9,workingday=1,weathersit=1)
Out[23]:
array([ 143.00002188, 120.99999907, 112.99999873, 108.99999915,
108.0000097 , 127.99999916, 217.00002042, 556.00021502,
790.00232596, 361.00104913, 240.00560627, 296.00012162,
354.00657189, 366.00860653, 366.00787315, 352.00292535,
509.00011482, 925.00381272, 892.00301662, 627.00208363,
434.00486594, 320.00001105, 279.00233103, 221.01075313])
6. Results¶
People use bike sharing products all over the year and characteristics can be explained by daily habits and the weather.
The most significant effect on the utilization can be measured during workingdays. Most people obviously use bikes to get to and from work. This conclusion is supported when comparing the utilization of registered against casual users. At this point a reliable service is crucial for the customer. People regsiter and rely on the service and should be respected by the company with high standards.
Since the time windows of low utilization are relatively short in the main seasons it helps taking the weather into account when planing any actions to the system like bike maintenance, software updates or investments in general.
In [24]:
hour[hour['yr']==1].boxplot(column='cnt',by=['workingday','hr'] , figsize=(17,5) )
Out[24]:
<matplotlib.axes._subplots.AxesSubplot at 0x125d4f3c8>
In [25]:
fig, axes = plt.subplots(1,2 , figsize=(15,5)) # create figure and axes
hour[hour['yr']==1].boxplot(column='registered',by=['workingday','hr'] , figsize=(7,5), ax=axes.flatten()[0])
hour[hour['yr']==1].boxplot(column='casual',by=['workingday','hr'] , figsize=(7,5), ax=axes.flatten()[1] )
#fig.delaxes(axes[1,1]) # remove empty subplot
plt.tight_layout()
plt.show()
On workingdays between afterwork and the next morning lies 10~12 hours of low utilization time. It is highly recommended to set up an agile and quick maintenance routine that frequently repairs bikes and sustains a constant availabilty. With the help of weather prediction it is possible to prepare for high levels of demand during the main season. If you want to assure high availabilty standards you can use the quantile regression with a high level of confidence and prepare for most of the upcoming rush hours. The next figure shows utilization and predicted utilization during one week of July 2012. You can easily spot the characteristic curve for weekend and workingdays.
In [26]:
count_by_hour = hour[['timestamp','cnt','cnt_q50','cnt_q90']].set_index('timestamp')
plt.figure( )
count_by_hour.plot(figsize=(30,20), linewidth=2)
plt.xlim(datetime.date(2012, 9, 21), datetime.date(2012, 9, 27))
plt.ylim(0,1000)
plt.title("Utilization and 90%-Quantile Regression for one week at the end of September 2012")
plt.legend(loc='best')
plt.show()
<matplotlib.figure.Figure at 0x127e504a8>
With a desired level of confidence of 90% the predictions would have guaranteed a high level of availability to the customer. End of September 2012 turned out to be a time with the highest hourly utilization. At this point managers can evaluate their maintenance processes and adapt to high the demand and hence sustain availability even at most critical times of the year.
The mean absolute deviations of the utilization predicted by the linear models form the observed values are:
In [27]:
print("mean absolute deviance for q50:" , hour['abs_dev_q50'].mean() , "for q90: ", hour['abs_dev_q90'].mean(), "and for OLS:", hour['abs_dev_OLS'].mean() )
mean absolute deviance for q50: 48.68053411650068 for q90: 79.64946908131675 and for OLS: 51.09465833840732
The mean absolute deviation tells us that the error of estimation is around 50 bikes each hour. In the case of the 90%-quantile regression it utilization is mostly overestimated by around 80 bikes per hour. In relation to almost 1000 bikes per hour as a maximum we have a relative mean absolut deviation of approximately 5% with the linear model.