
# Data and array manipulation
import pandas as pd
import numpy as np
import datetime as dt

# Regression analysis
import statsmodels.api as sm
from sklearn.model_selection import train_test_split
from sklearn import metrics

# Plotting and Visualization
import matplotlib.pyplot as plt
import plotly.express as px
import cufflinks as cf

# Interactive charts
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot

# Options
init_notebook_mode(connected = True)
cf.go_offline()
pd.options.display.float_format = '{:,.3f}'.format
pd.set_option('display.max_columns', None)

# Default graphic settings
default_yaxis = dict(showgrid = False,
                     zeroline = False,
                     showline = False,
                     showticklabels = True)


# Importing metadata
df_data_dictionary = pd.read_excel('E:\\Data\\HR\\data_dictionary.xlsx').fillna('')

# Main table
df_general_data = pd.read_csv('E:\\Data\\HR\\general_data.csv')

# Employee & manager tables
df_employee_survey_data = pd.read_csv('E:\\Data\\HR\\employee_survey_data.csv')
df_manager_survey_data = pd.read_csv('E:\\Data\\HR\\manager_survey_data.csv')

# Check in & check out times
df_in_time = pd.read_csv('E:\\Data\\HR\\in_time.csv', index_col = 'Unnamed: 0').applymap(pd.Timestamp)
df_out_time = pd.read_csv('E:\\Data\\HR\\out_time.csv', index_col = 'Unnamed: 0').applymap(pd.Timestamp)


df_data_dictionary


df_data_dictionary.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 52 entries, 0 to 51
Data columns (total 3 columns):
 #   Column    Non-Null Count  Dtype 
---  ------    --------------  ----- 
 0   Variable  52 non-null     object
 1   Meaning   52 non-null     object
 2   Levels    52 non-null     object
dtypes: object(3)
memory usage: 1.3+ KB


df_general_data.head()


df_general_data.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4410 entries, 0 to 4409
Data columns (total 24 columns):
 #   Column                   Non-Null Count  Dtype  
---  ------                   --------------  -----  
 0   Age                      4410 non-null   int64  
 1   Attrition                4410 non-null   object 
 2   BusinessTravel           4410 non-null   object 
 3   Department               4410 non-null   object 
 4   DistanceFromHome         4410 non-null   int64  
 5   Education                4410 non-null   int64  
 6   EducationField           4410 non-null   object 
 7   EmployeeCount            4410 non-null   int64  
 8   EmployeeID               4410 non-null   int64  
 9   Gender                   4410 non-null   object 
 10  JobLevel                 4410 non-null   int64  
 11  JobRole                  4410 non-null   object 
 12  MaritalStatus            4410 non-null   object 
 13  MonthlyIncome            4410 non-null   int64  
 14  NumCompaniesWorked       4391 non-null   float64
 15  Over18                   4410 non-null   object 
 16  PercentSalaryHike        4410 non-null   int64  
 17  StandardHours            4410 non-null   int64  
 18  StockOptionLevel         4410 non-null   int64  
 19  TotalWorkingYears        4401 non-null   float64
 20  TrainingTimesLastYear    4410 non-null   int64  
 21  YearsAtCompany           4410 non-null   int64  
 22  YearsSinceLastPromotion  4410 non-null   int64  
 23  YearsWithCurrManager     4410 non-null   int64  
dtypes: float64(2), int64(14), object(8)
memory usage: 827.0+ KB


df_employee_survey_data.head()


df_employee_survey_data.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4410 entries, 0 to 4409
Data columns (total 4 columns):
 #   Column                   Non-Null Count  Dtype  
---  ------                   --------------  -----  
 0   EmployeeID               4410 non-null   int64  
 1   EnvironmentSatisfaction  4385 non-null   float64
 2   JobSatisfaction          4390 non-null   float64
 3   WorkLifeBalance          4372 non-null   float64
dtypes: float64(3), int64(1)
memory usage: 137.9 KB


df_manager_survey_data.head()


df_manager_survey_data.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4410 entries, 0 to 4409
Data columns (total 3 columns):
 #   Column             Non-Null Count  Dtype
---  ------             --------------  -----
 0   EmployeeID         4410 non-null   int64
 1   JobInvolvement     4410 non-null   int64
 2   PerformanceRating  4410 non-null   int64
dtypes: int64(3)
memory usage: 103.5 KB


df_in_time.head()


df_in_time.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 4410 entries, 1 to 4410
Columns: 261 entries, 2015-01-01 to 2015-12-31
dtypes: datetime64[ns](261)
memory usage: 8.8 MB


df_out_time.head()


df_out_time.info()

<class 'pandas.core.frame.DataFrame'>
Int64Index: 4410 entries, 1 to 4410
Columns: 261 entries, 2015-01-01 to 2015-12-31
dtypes: datetime64[ns](261)
memory usage: 8.8 MB


# Calculating working duration by taking difference between in and out times
df_work_duration = (df_out_time - df_in_time).replace({np.nan: dt.timedelta(0)}).applymap(pd.Timedelta.total_seconds)
df_work_duration.head()


# Adding Employee ID
df_work_duration.reset_index(inplace = True)
df_work_duration.rename(columns={'index': 'EmployeeID'},inplace=True)
df_work_duration


# Calculating average working duration in seconds for each employee
df_work_duration['Avg_duration_sec'] = df_work_duration.mean(axis = 1)
df_avg_work_duration = df_work_duration[['EmployeeID', 'Avg_duration_sec']]
df_avg_work_duration.head()


# General data
df_general_data.Education = df_general_data.Education.replace({1: 'Below College', 2: 'College', 3: 'Bachelor', 4: 'Master', 5: 'Doctor'})

# Employee survey data
df_employee_survey_data.EnvironmentSatisfaction = df_employee_survey_data.EnvironmentSatisfaction.replace({1: 'Low', 2: 'Medium', 3:'High', 4: 'Very High'})
df_employee_survey_data.JobSatisfaction = df_employee_survey_data.JobSatisfaction.replace({1: 'Low', 2: 'Medium', 3:'High', 4: 'Very High'})
df_employee_survey_data.WorkLifeBalance = df_employee_survey_data.WorkLifeBalance.replace({1: 'Bad', 2: 'Good', 3:'Better', 4: 'Best'})

# Manager survey data
df_manager_survey_data.JobInvolvement = df_manager_survey_data.JobInvolvement.replace({1: 'Low', 2: 'Medium', 3:'High', 4: 'Very High'})
df_manager_survey_data.PerformanceRating = df_manager_survey_data.PerformanceRating.replace({1: 'Low', 2: 'Good', 3:'Excellent', 4: 'Outstanding'})

df_general_data.head()


df_employee_survey_data.head()


df_manager_survey_data.head()


df_master_data = df_general_data.merge(df_employee_survey_data, left_on = 'EmployeeID', right_on = 'EmployeeID')
df_master_data = df_master_data.merge(df_manager_survey_data, left_on = 'EmployeeID', right_on = 'EmployeeID')
df_master_data = df_master_data.merge(df_avg_work_duration, left_on = 'EmployeeID', right_on = 'EmployeeID')

df_master_data.head()


df_master_data.describe().round(decimals = 2)


df_master_data.isnull().sum()

Age                         0
Attrition                   0
BusinessTravel              0
Department                  0
DistanceFromHome            0
Education                   0
EducationField              0
EmployeeCount               0
EmployeeID                  0
Gender                      0
JobLevel                    0
JobRole                     0
MaritalStatus               0
MonthlyIncome               0
NumCompaniesWorked         19
Over18                      0
PercentSalaryHike           0
StandardHours               0
StockOptionLevel            0
TotalWorkingYears           9
TrainingTimesLastYear       0
YearsAtCompany              0
YearsSinceLastPromotion     0
YearsWithCurrManager        0
EnvironmentSatisfaction    25
JobSatisfaction            20
WorkLifeBalance            38
JobInvolvement              0
PerformanceRating           0
Avg_duration_sec            0
dtype: int64


df_master_data.dropna(inplace = True)


df_final = df_master_data.drop(['EmployeeID', 'Over18', 'StandardHours', 'EmployeeCount'], axis = 1)
df_final.head()


df_final.shape

(4300, 26)


df_categorical = ['Attrition', 'BusinessTravel', 'Department', 
                  'Education', 'EducationField', 'Gender', 
                  'JobRole', 'MaritalStatus', 'EnvironmentSatisfaction', 
                  'JobSatisfaction', 'WorkLifeBalance', 'JobInvolvement', 'PerformanceRating']


df_numerical = df_final.columns[~df_final.columns.isin(df_categorical)]
df_numerical

Index(['Age', 'DistanceFromHome', 'JobLevel', 'MonthlyIncome',
       'NumCompaniesWorked', 'PercentSalaryHike', 'StockOptionLevel',
       'TotalWorkingYears', 'TrainingTimesLastYear', 'YearsAtCompany',
       'YearsSinceLastPromotion', 'YearsWithCurrManager', 'Avg_duration_sec'],
      dtype='object')


# categorical variables
df_final[df_categorical].head()


# Numerical variables
df_final[df_numerical].head()


df_final.describe()


# Attrition
df_final.Attrition.value_counts(normalize = True)

No    0.838
Yes   0.162
Name: Attrition, dtype: float64


# Attrition
fig = px.histogram(df_final, x = 'Attrition', title = 'Attrition Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# BusinessTravel
df_final.BusinessTravel.value_counts(normalize = True)

Travel_Rarely       0.710
Travel_Frequently   0.188
Non-Travel          0.102
Name: BusinessTravel, dtype: float64


# BusinessTravel
fig = px.histogram(df_final, x = 'BusinessTravel', title = 'Business Travel Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Department
df_final.Department.value_counts(normalize = True)

Research & Development   0.653
Sales                    0.304
Human Resources          0.043
Name: Department, dtype: float64


# Department
fig = px.histogram(df_final, x = 'Department', title = 'Department Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Education
df_final.Education.value_counts(normalize = True)

Bachelor        0.388
Master          0.272
College         0.191
Below College   0.116
Doctor          0.033
Name: Education, dtype: float64


# Education
fig = px.histogram(df_final, x = 'Education', title = 'Education Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# EducationField
df_final.EducationField.value_counts(normalize = True)

Life Sciences      0.411
Medical            0.317
Marketing          0.109
Technical Degree   0.089
Other              0.055
Human Resources    0.019
Name: EducationField, dtype: float64


# EducationField
fig = px.histogram(df_final, y = 'EducationField', title = 'Education Field Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), 
                  xaxis = dict(showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Gender
df_final.Gender.value_counts(normalize = True)

Male     0.598
Female   0.402
Name: Gender, dtype: float64


# Gender
fig = px.histogram(df_final, x = 'Gender', title = 'GenderDistribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# JobRole
df_final.JobRole.value_counts(normalize = True)

Sales Executive             0.222
Research Scientist          0.200
Laboratory Technician       0.176
Manufacturing Director      0.098
Healthcare Representative   0.088
Manager                     0.070
Sales Representative        0.056
Research Director           0.055
Human Resources             0.036
Name: JobRole, dtype: float64


# JobRole
fig = px.histogram(df_final, y = 'JobRole', title = 'Job Role Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), 
                  xaxis = dict(showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# MaritalStatus
df_final.MaritalStatus.value_counts(normalize = True)

Married    0.458
Single     0.321
Divorced   0.221
Name: MaritalStatus, dtype: float64


# MaritalStatus
fig = px.histogram(df_final, x = 'MaritalStatus', title = 'Marital Status Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# EnvironmentSatisfaction
df_final.EnvironmentSatisfaction.value_counts(normalize = True)

High        0.307
Very High   0.305
Medium      0.195
Low         0.193
Name: EnvironmentSatisfaction, dtype: float64


# EnvironmentSatisfaction
fig = px.histogram(df_final, x = 'EnvironmentSatisfaction', title = 'Environment Satisfaction Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# EnvironmentSatisfaction
df_final.JobSatisfaction.value_counts(normalize = True)

Very High   0.310
High        0.301
Low         0.197
Medium      0.191
Name: JobSatisfaction, dtype: float64


# JobSatisfaction
fig = px.histogram(df_final, x = 'JobSatisfaction', title = 'Job Satisfaction Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# WorkLifeBalance
df_final.WorkLifeBalance.value_counts(normalize = True)

Better   0.607
Good     0.234
Best     0.105
Bad      0.055
Name: WorkLifeBalance, dtype: float64


# WorkLifeBalance
fig = px.histogram(df_final, x = 'WorkLifeBalance', title = 'Work Life Balance Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# JobInvolvement
df_final.JobInvolvement.value_counts(normalize = True)

High        0.590
Medium      0.257
Very High   0.098
Low         0.056
Name: JobInvolvement, dtype: float64


# JobInvolvement
fig = px.histogram(df_final, x = 'JobInvolvement', title = 'Job Involvement Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# PerformanceRating
df_final.PerformanceRating.value_counts(normalize = True)

Excellent     0.846
Outstanding   0.154
Name: PerformanceRating, dtype: float64


# PerformanceRating
fig = px.histogram(df_final, x = 'PerformanceRating', title = 'Performance Rating Distribution', text_auto = True, width = 400, height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Categorical variables
df_categorical

['Attrition',
 'BusinessTravel',
 'Department',
 'Education',
 'EducationField',
 'Gender',
 'JobRole',
 'MaritalStatus',
 'EnvironmentSatisfaction',
 'JobSatisfaction',
 'WorkLifeBalance',
 'JobInvolvement',
 'PerformanceRating']


# Attrition vs BusinessTravel
df_tab_BT = pd.crosstab(df_final.BusinessTravel, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_BT, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for BusinessTravel
df_odd_BT = df_tab_BT['Yes'] / df_tab_BT['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_BT, 
             x = df_odd_BT.index,
             text_auto = '.2f',
             title = 'Attrition odd by Business Travel Status',
             labels = {'y': 'Attrition odd', 'x': 'Business Travel Frequency'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs Education
df_tab_E = pd.crosstab(df_final.Education, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_E, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for Education
df_odd_E = df_tab_E['Yes'] / df_tab_E['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_E, 
             x = df_odd_E.index,
             text_auto = '.2f',
             title = 'Attrition odd by Education Level',
             labels = {'y': 'Attrition odd', 'x': 'Education Level'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs EducationField
df_tab_EF = pd.crosstab(df_final.EducationField, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_EF, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for EducationField
df_odd_EF = df_tab_EF['Yes'] / df_tab_EF['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_EF, 
             x = df_odd_EF.index,
             text_auto = '.2f',
             title = 'Attrition odd by Education Fields',
             labels = {'y': 'Attrition odd', 'x': 'Education Field'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs Gender
df_tab_G = pd.crosstab(df_final.Gender, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_G, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for Gender
df_odd_G = df_tab_G['Yes'] / df_tab_G['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_G, 
             x = df_odd_G.index,
             text_auto = '.2f',
             title = 'Attrition odd by Genders',
             labels = {'y': 'Attrition odd', 'x': 'Gender'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs JobRole
df_tab_JR = pd.crosstab(df_final.JobRole, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_JR, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for JobRole
df_odd_JR = df_tab_JR['Yes'] / df_tab_JR['No']

# Visualizing Attrition odds
fig = px.bar(x = df_odd_JR, 
             y = df_odd_JR.index,
             text_auto = '.2f',
             title = 'Attrition odd by Job Roles',
             labels = {'y': 'Attrition odd', 'x': 'Job Role'},
             width = 600,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), 
                  xaxis = dict(showticklabels = False), 
                  autosize = True, 
                  plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs MaritalStatus
df_tab_MS = pd.crosstab(df_final.MaritalStatus, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_MS, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for MaritalStatus
df_odd_MS = df_tab_MS['Yes'] / df_tab_MS['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_MS, 
             x = df_odd_MS.index,
             text_auto = '.2f',
             title = 'Attrition odd by Marital Status',
             labels = {'y': 'Attrition odd', 'x': 'Marital Status'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs EnvironmentSatisfaction
df_tab_ES = pd.crosstab(df_final.EnvironmentSatisfaction, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_ES, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for EnvironmentSatisfaction
df_odd_ES = df_tab_ES['Yes'] / df_tab_ES['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_ES, 
             x = df_odd_ES.index,
             text_auto = '.2f',
             title = 'Attrition odd by Environment Satisfaction',
             labels = {'y': 'Attrition odd', 'x': 'Environment Satisfaction'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs JobSatisfaction
df_tab_JS = pd.crosstab(df_final.JobSatisfaction, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_JS, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for JobSatisfaction
df_odd_JS = df_tab_JS['Yes'] / df_tab_JS['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_JS, 
             x = df_odd_JS.index,
             text_auto = '.2f',
             title = 'Attrition odd by Job Satisfaction',
             labels = {'y': 'Attrition odd', 'x': 'Job Satisfaction'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs WorkLifeBalance
df_tab_WLB = pd.crosstab(df_final.WorkLifeBalance, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_WLB, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for WorkLifeBalance
df_odd_WLB = df_tab_WLB['Yes'] / df_tab_WLB['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_WLB, 
             x = df_odd_WLB.index,
             text_auto = '.2f',
             title = 'Attrition odd by Work Life Balance',
             labels = {'y': 'Attrition odd', 'x': 'Work Life Balance'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs JobInvolvement
df_tab_JI = pd.crosstab(df_final.JobInvolvement, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_JI, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for JobInvolvement
df_odd_JI = df_tab_JI['Yes'] / df_tab_JI['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_JI, 
             x = df_odd_JI.index,
             text_auto = '.2f',
             title = 'Attrition odd by Job Involvement',
             labels = {'y': 'Attrition odd', 'x': 'Job Involvement'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition vs PerformanceRating
df_tab_PR = pd.crosstab(df_final.PerformanceRating, df_final.Attrition, normalize = True)

# heatmap
fig = px.imshow(df_tab_PR, text_auto = '.2f', width = 400, height = 400)
fig.show()


# Attrition odds for PerformanceRating
df_odd_PR = df_tab_PR['Yes'] / df_tab_PR['No']

# Visualizing Attrition odds
fig = px.bar(y = df_odd_PR, 
             x = df_odd_PR.index,
             text_auto = '.2f',
             title = 'Attrition odd by Performance Rating',
             labels = {'y': 'Attrition odd', 'x': 'Performance Rating'},
             width = 400,
             height = 400)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = False), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Numerical variables
df_numerical

Index(['Age', 'DistanceFromHome', 'JobLevel', 'MonthlyIncome',
       'NumCompaniesWorked', 'PercentSalaryHike', 'StockOptionLevel',
       'TotalWorkingYears', 'TrainingTimesLastYear', 'YearsAtCompany',
       'YearsSinceLastPromotion', 'YearsWithCurrManager', 'Avg_duration_sec'],
      dtype='object')


# Attrition odd by Ages
df_tab_A = pd.crosstab(df_final.Age, df_final.Attrition, normalize = True)
df_odd_A = df_tab_A['Yes'] / df_tab_A['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_A, 
              x = df_odd_A.index,
              title = 'Attrition odd by Ages',
              labels = {'y': 'Attrition odd', 'x': 'Age'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by DistanceFromHome
df_tab_DFH = pd.crosstab(df_final.DistanceFromHome, df_final.Attrition, normalize = True)
df_odd_DFH = df_tab_DFH['Yes'] / df_tab_DFH['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_DFH, 
              x = df_odd_DFH.index,
              title = 'Attrition odd by Distance From Home',
              labels = {'y': 'Attrition odd', 'x': 'Distance From Home'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by JobLevel
df_tab_JL = pd.crosstab(df_final.JobLevel, df_final.Attrition, normalize = True)
df_odd_JL = df_tab_JL['Yes'] / df_tab_JL['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_JL, 
              x = df_odd_JL.index,
              title = 'Attrition odd by Job Level',
              labels = {'y': 'Attrition odd', 'x': 'Job Level'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by MonthlyIncome
df_tab_MI = pd.crosstab(pd.cut(df_final.MonthlyIncome, bins = 10), df_final.Attrition, normalize = True)
df_odd_MI = df_tab_MI['Yes'] / df_tab_MI['No']
df_odd_MI.index = ['(9900.1, 29080.0]', '(29080.0, 48070.0]', '(48070.0, 67060.0]', '(67060.0, 86050.0]', '(86050.0, 105040.0]',
                  '(105040.0, 124030.0]', '(124030.0, 143020.0]', '(143020.0, 162010.0]', '(162010.0, 181000.0]', '(181000.0, 199990.0]']

# Visualizing Attrition odds
fig = px.line(y = df_odd_MI, 
              x = df_odd_MI.index,
              title = 'Attrition odd by Monthly Income bins',
              labels = {'y': 'Attrition odd', 'x': 'Monthly Income'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by NumCompaniesWorked
df_tab_NCW = pd.crosstab(df_final.NumCompaniesWorked, df_final.Attrition, normalize = True)
df_odd_NCW = df_tab_NCW['Yes'] / df_tab_NCW['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_NCW, 
              x = df_odd_NCW.index,
              title = 'Attrition odd by Numbers of Companies Worked',
              labels = {'y': 'Attrition odd', 'x': 'Num Companies Worked'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by PercentSalaryHike
df_tab_PSH = pd.crosstab(df_final.PercentSalaryHike, df_final.Attrition, normalize = True)
df_odd_PSH = df_tab_PSH['Yes'] / df_tab_PSH['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_PSH, 
              x = df_odd_PSH.index,
              title = 'Attrition odd by Percent Salary Hike',
              labels = {'y': 'Attrition odd', 'x': 'Percent Salary Hike'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by StockOptionLevel
df_tab_SOL = pd.crosstab(df_final.StockOptionLevel, df_final.Attrition, normalize = True)
df_odd_SOL = df_tab_SOL['Yes'] / df_tab_SOL['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_SOL, 
              x = df_odd_SOL.index,
              title = 'Attrition odd by Stock Option Levels',
              labels = {'y': 'Attrition odd', 'x': 'Stock Option Level'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by TotalWorkingYears
df_tab_TWY = pd.crosstab(df_final.TotalWorkingYears, df_final.Attrition, normalize = True)
df_odd_TWY = df_tab_TWY['Yes'] / df_tab_TWY['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_TWY, 
              x = df_odd_TWY.index,
              title = 'Attrition odd by Total Working Years',
              labels = {'y': 'Attrition odd', 'x': 'Total Working Years'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by TrainingTimesLastYear
df_tab_TTLY = pd.crosstab(df_final.TrainingTimesLastYear, df_final.Attrition, normalize = True)
df_odd_TTLY = df_tab_TTLY['Yes'] / df_tab_TTLY['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_TTLY, 
              x = df_odd_TTLY.index,
              title = 'Attrition odd by Training Times Last Year',
              labels = {'y': 'Attrition odd', 'x': 'Training Times Last Year'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by YearsAtCompany
df_tab_YAC = pd.crosstab(df_final.YearsAtCompany, df_final.Attrition, normalize = True)
df_odd_YAC = df_tab_YAC['Yes'] / df_tab_YAC['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_YAC, 
              x = df_odd_YAC.index,
              title = 'Attrition odd by Years At Company',
              labels = {'y': 'Attrition odd', 'x': 'Years At Company'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by YearsSinceLastPromotion
df_tab_YSLP = pd.crosstab(df_final.YearsSinceLastPromotion, df_final.Attrition, normalize = True)
df_odd_YSLP = df_tab_YSLP['Yes'] / df_tab_YSLP['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_YSLP, 
              x = df_odd_YSLP.index,
              title = 'Attrition odd by Years Since Last Promotion',
              labels = {'y': 'Attrition odd', 'x': 'Years Since Last Promotion'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by YearsWithCurrManager
df_tab_YWCM = pd.crosstab(df_final.YearsWithCurrManager, df_final.Attrition, normalize = True)
df_odd_YWCM = df_tab_YWCM['Yes'] / df_tab_YWCM['No']

# Visualizing Attrition odds
fig = px.line(y = df_odd_YWCM, 
              x = df_odd_YWCM.index,
              title = 'Attrition odd by Years With Current Manager',
              labels = {'y': 'Attrition odd', 'x': 'Years With Current Manager'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# Attrition odd by Avg_duration_sec
df_tab_AWD = pd.crosstab(pd.cut(df_final.Avg_duration_sec, bins = 10), df_final.Attrition, normalize = True)
df_odd_AWD = df_tab_AWD['Yes'] / df_tab_AWD['No']
df_odd_AWD.index = ['(18522.189, 20429.824]', '20429.824, 22318.573]', '(22318.573, 24207.321]', '(24207.321, 26096.069]', '(26096.069, 27984.817]',
                  '(27984.817, 29873.565]', '(29873.565, 31762.313]', '(31762.313, 33651.061]', '(33651.061, 35539.809]', '(35539.809, 37428.557]']

# Visualizing Attrition odds
fig = px.line(y = df_odd_AWD, 
              x = df_odd_AWD.index,
              title = 'Attrition odd by Average working duration (sec)',
              labels = {'y': 'Attrition odd', 'x': 'Average working duration (sec)'},
              width = 500,
              height = 500)

# Updating layout to reduce clutter
fig.update_layout(yaxis = dict(showgrid = False, zeroline = False, showline = False, showticklabels = True), autosize = True, plot_bgcolor = 'white')

# Showing figure
fig.show()


# generate dummies from categorical variables
df_logit_data = pd.get_dummies(df_final, columns = df_categorical)
df_logit_data.head()


# dropping columns belonging to the baseline to avoid multicollinearity!
df_baseline = ['Attrition_No', 
               'BusinessTravel_Non-Travel', 
               'Department_Human Resources', 
               'Education_Below College', 
               'EducationField_Human Resources',
               'Gender_Female', 
               'JobRole_Human Resources', 
               'MaritalStatus_Single', 
               'EnvironmentSatisfaction_Low', 
               'JobSatisfaction_Low', 
               'WorkLifeBalance_Bad',
               'JobInvolvement_Low', 
               'PerformanceRating_Excellent']
df_logit_data.drop(df_baseline, axis = 1, inplace = True)
df_logit_data.head()


# Rescaling variables
df_logit_data['MonthlyIncome'] = df_logit_data.MonthlyIncome / 1000
df_logit_data['Avg_duration_sec'] = df_logit_data.Avg_duration_sec / 3600
df_logit_data.rename(columns = {'Avg_duration_sec': 'Avg_duration_hr'}, inplace = 1)


# Prepare data for the full model
df_x = df_logit_data.drop(['Attrition_Yes'], axis = 1)
df_x = sm.add_constant(df_x)
df_y = df_logit_data['Attrition_Yes']

# Train Test Split
df_x_train, df_x_valid, df_y_train, df_y_valid = train_test_split(df_x, df_y, train_size = 0.8, random_state = 2)

# Checking correlations
fig = px.imshow(df_x.drop('const', axis = 1).corr(), text_auto = '.2f', width = 1500, height = 1500)
fig.show()


# fitting the full model
model_logit_full = sm.GLM(df_y_train, df_x_train, family = sm.families.Binomial())
result_logit_full = model_logit_full.fit(method = 'newton')
result_logit_full.summary()


# Calculating in sample accuracy for the full model
tab_valid_full = pd.DataFrame({'EmployeeID': df_y_train.index,'Attrition': df_y_train})
tab_valid_full['Forecast Attrition Probability'] = result_logit_full.predict(df_x_train)
tab_valid_full['Forecast Attrition'] = tab_valid_full['Forecast Attrition Probability'].map(lambda x: 1 if x > 0.5 else 0)
metrics.accuracy_score(tab_valid_full.Attrition, tab_valid_full['Forecast Attrition'])

0.8625


# Extracting statistically insignificant variables
table_coef_full = result_logit_full.summary().tables[1]
table_coef_full = pd.read_html(table_coef_full.as_html(), header=0, index_col=0)[0]
table_coef_full[table_coef_full['P>|z|'] > 0.05]


# Extracting insignificant variables
df_insignificant = table_coef_full[table_coef_full['P>|z|'] > 0.05].index
df_insignificant

Index(['const', 'DistanceFromHome', 'MonthlyIncome', 'PercentSalaryHike',
       'StockOptionLevel', 'Education_Bachelor', 'Education_College',
       'Education_Doctor', 'Education_Master', 'EducationField_Life Sciences',
       'EducationField_Marketing', 'EducationField_Medical',
       'EducationField_Other', 'Gender_Male',
       'JobRole_Healthcare Representative', 'JobRole_Laboratory Technician',
       'JobRole_Manager', 'JobRole_Manufacturing Director',
       'JobRole_Research Scientist', 'JobRole_Sales Executive',
       'JobRole_Sales Representative', 'JobInvolvement_High',
       'JobInvolvement_Medium', 'JobInvolvement_Very High',
       'PerformanceRating_Outstanding'],
      dtype='object')


# Extracting data for the reduced model
df_logit_reduced_data = df_logit_data.loc[:, ~df_logit_data.columns.isin(df_insignificant)]

# Prepare data for the reduced model
df_x_reduced = df_logit_reduced_data.drop('Attrition_Yes', axis = 1)
df_x_reduced = sm.add_constant(df_x_reduced)
df_y_reduced = df_logit_reduced_data['Attrition_Yes']

# Train Test Split
df_x_train_reduced, df_x_valid_reduced, df_y_train_reduced, df_y_valid_reduced = train_test_split(df_x_reduced, df_y_reduced, train_size = 0.8, random_state = 2)

# Checking correlations
fig = px.imshow(df_x_reduced.drop('const', axis = 1).corr(), text_auto = '.2f', width = 1500, height = 1300)
fig.show()


# Fitting reduced model
model_logit_reduced = sm.GLM(df_y_train_reduced, df_x_train_reduced, family = sm.families.Binomial())
result_logit_reduced = model_logit_reduced.fit(method = 'Newton')
result_logit_reduced.summary()


# Calculating in sample accuracy for the reduced model
tab_valid_reduced = pd.DataFrame({'EmployeeID': df_y_train_reduced.index,'Attrition': df_y_train_reduced})
tab_valid_reduced['Forecast Attrition Probability'] = result_logit_reduced.predict(df_x_train_reduced)
tab_valid_reduced['Forecast Attrition'] = tab_valid_reduced['Forecast Attrition Probability'].map(lambda x: 1 if x > 0.5 else 0)
metrics.accuracy_score(tab_valid_reduced.Attrition, tab_valid_reduced['Forecast Attrition'])

0.8616279069767442


# Extract data for the min model
df_logit_min_data = df_logit_reduced_data.loc[:, ~df_logit_reduced_data.columns.isin(['EducationField_Technical Degree'])]

# Prepare data for the min model
df_x_min = df_logit_min_data .drop('Attrition_Yes', axis = 1)
df_x_min = sm.add_constant(df_x_min)
df_y_min = df_logit_min_data ['Attrition_Yes']

# Train Test Split
df_x_train_min, df_x_valid_min, df_y_train_min, df_y_valid_min = train_test_split(df_x_min, df_y_min, train_size = 0.8, random_state = 2)

# Checking correlations
fig = px.imshow(df_x_min.drop('const', axis = 1).corr(), text_auto = '.2f', width = 1500, height = 1300)
fig.show()


# Fitting min model
model_logit_min = sm.GLM(df_y_train_min, df_x_train_min, family = sm.families.Binomial())
result_logit_min = model_logit_min.fit(method = 'Newton')
result_logit_min.summary()


# Calculating in sample accuracy for the min model
tab_valid_min = pd.DataFrame({'EmployeeID': df_y_train_min.index,'Attrition': df_y_train_min})
tab_valid_min['Forecast Attrition Probability'] = result_logit_min.predict(df_x_train_min)
tab_valid_min['Forecast Attrition'] = tab_valid_min['Forecast Attrition Probability'].map(lambda x: 1 if x > 0.5 else 0)
metrics.accuracy_score(tab_valid_min.Attrition, tab_valid_min['Forecast Attrition'])

0.861046511627907


# generate forecast table for the full model
tab_valid_full = pd.DataFrame({'EmployeeID': df_y_valid.index,'Attrition': df_y_valid})
tab_valid_full['Forecast Attrition Probability'] = result_logit_full.predict(df_x_valid)
tab_valid_full['Forecast Attrition'] = tab_valid_full['Forecast Attrition Probability'].map(lambda x: 1 if x > 0.5 else 0)
tab_valid_full.head()


# confusion matrix for the full model
mat_confusion_full = metrics.confusion_matrix(tab_valid_full.Attrition, tab_valid_full['Forecast Attrition'])
mat_confusion_full

array([[693,  20],
       [107,  40]], dtype=int64)


# overall accuracy of the full model
metrics.accuracy_score(tab_valid_full.Attrition, tab_valid_full['Forecast Attrition'])

0.8523255813953489


# generate forecast table for the reduced model
tab_valid_reduced = pd.DataFrame({'EmployeeID': df_y_valid_reduced.index,'Attrition': df_y_valid_reduced})
tab_valid_reduced['Forecast Attrition Probability'] = result_logit_reduced.predict(df_x_valid_reduced)
tab_valid_reduced['Forecast Attrition'] = tab_valid_reduced['Forecast Attrition Probability'].map(lambda x: 1 if x > 0.5 else 0)
tab_valid_reduced.head()


# confusion matrix for the reduced model
mat_confusion_reduced = metrics.confusion_matrix(tab_valid_reduced.Attrition, tab_valid_reduced['Forecast Attrition'])
mat_confusion_reduced

array([[699,  14],
       [106,  41]], dtype=int64)


# overall accuracy of the reduced model
metrics.accuracy_score(tab_valid_reduced.Attrition, tab_valid_reduced['Forecast Attrition'])

0.8604651162790697


# generate forecast table for the min model
tab_valid_min = pd.DataFrame({'EmployeeID': df_y_valid_min.index,'Attrition': df_y_valid_min})
tab_valid_min['Forecast Attrition Probability'] = result_logit_min.predict(df_x_valid_min)
tab_valid_min['Forecast Attrition'] = tab_valid_min['Forecast Attrition Probability'].map(lambda x: 1 if x > 0.5 else 0)
tab_valid_min.head()


# confusion matrix for the min model
mat_confusion_min = metrics.confusion_matrix(tab_valid_min.Attrition, tab_valid_min['Forecast Attrition'])
mat_confusion_min

array([[698,  15],
       [107,  40]], dtype=int64)


# overall accuracy of the min model
metrics.accuracy_score(tab_valid_min.Attrition, tab_valid_min['Forecast Attrition'])

0.858139534883721


table_coef_min = result_logit_min.summary().tables[1]
table_coef_min = pd.read_html(table_coef_min.as_html(), header=0, index_col=0)[0]
table_coef_min['Realized effect'] = np.exp(table_coef_min.coef)
table_coef_min[['coef', 'Realized effect']]


# attrition odd for Age = 18 and BusinessTravel = Non-Travel
1*(0.969**18)

0.567319859821517


# attrition odd for Age = 19 and BusinessTravel = Travel_Rarely
1*(0.969**18)*2.450

1.3899336565627167


table_coef_min.loc[table_coef_min['Realized effect'] > 1, ['coef', 'Realized effect']]


table_coef_min.loc[table_coef_min['Realized effect'] < 1, ['coef', 'Realized effect']]

	EmployeeID	EnvironmentSatisfaction	JobSatisfaction	WorkLifeBalance
0	1	3.000	4.000	2.000
1	2	3.000	2.000	4.000
2	3	2.000	2.000	1.000
3	4	4.000	4.000	3.000
4	5	4.000	1.000	3.000

	2015-01-01	2015-01-02	2015-01-05	2015-01-06	2015-01-07	2015-01-08	2015-01-09	2015-01-12	2015-01-13	2015-01-14	2015-01-15	2015-01-16	2015-01-19	2015-01-20	2015-01-21	2015-01-22	2015-01-23	2015-01-26	2015-01-27	2015-01-28	2015-01-29	2015-01-30	2015-02-02	2015-02-03	2015-02-04	2015-02-05	2015-02-06	2015-02-09	2015-02-10	2015-02-11	2015-02-12	2015-02-13	2015-02-16	2015-02-17	2015-02-18	2015-02-19	2015-02-20	2015-02-23	2015-02-24	2015-02-25	2015-02-26	2015-02-27	2015-03-02	2015-03-03	2015-03-04	2015-03-05	2015-03-06	2015-03-09	2015-03-10	2015-03-11	2015-03-12	2015-03-13	2015-03-16	2015-03-17	2015-03-18	2015-03-19	2015-03-20	2015-03-23	2015-03-24	2015-03-25	2015-03-26	2015-03-27	2015-03-30	2015-03-31	2015-04-01	2015-04-02	2015-04-03	2015-04-06	2015-04-07	2015-04-08	2015-04-09	2015-04-10	2015-04-13	2015-04-14	2015-04-15	2015-04-16	2015-04-17	2015-04-20	2015-04-21	2015-04-22	2015-04-23	2015-04-24	2015-04-27	2015-04-28	2015-04-29	2015-04-30	2015-05-01	2015-05-04	2015-05-05	2015-05-06	2015-05-07	2015-05-08	2015-05-11	2015-05-12	2015-05-13	2015-05-14	2015-05-15	2015-05-18	2015-05-19	2015-05-20	2015-05-21	2015-05-22	2015-05-25	2015-05-26	2015-05-27	2015-05-28	2015-05-29	2015-06-01	2015-06-02	2015-06-03	2015-06-04	2015-06-05	2015-06-08	2015-06-09	2015-06-10	2015-06-11	2015-06-12	2015-06-15	2015-06-16	2015-06-17	2015-06-18	2015-06-19	2015-06-22	2015-06-23	2015-06-24	2015-06-25	2015-06-26	2015-06-29	2015-06-30	2015-07-01	2015-07-02	2015-07-03	2015-07-06	2015-07-07	2015-07-08	2015-07-09	2015-07-10	2015-07-13	2015-07-14	2015-07-15	2015-07-16	2015-07-17	2015-07-20	2015-07-21	2015-07-22	2015-07-23	2015-07-24	2015-07-27	2015-07-28	2015-07-29	2015-07-30	2015-07-31	2015-08-03	2015-08-04	2015-08-05	2015-08-06	2015-08-07	2015-08-10	2015-08-11	2015-08-12	2015-08-13	2015-08-14	2015-08-17	2015-08-18	2015-08-19	2015-08-20	2015-08-21	2015-08-24	2015-08-25	2015-08-26	2015-08-27	2015-08-28	2015-08-31	2015-09-01	2015-09-02	2015-09-03	2015-09-04	2015-09-07	2015-09-08	2015-09-09	2015-09-10	2015-09-11	2015-09-14	2015-09-15	2015-09-16	2015-09-17	2015-09-18	2015-09-21	2015-09-22	2015-09-23	2015-09-24	2015-09-25	2015-09-28	2015-09-29	2015-09-30	2015-10-01	2015-10-02	2015-10-05	2015-10-06	2015-10-07	2015-10-08	2015-10-09	2015-10-12	2015-10-13	2015-10-14	2015-10-15	2015-10-16	2015-10-19	2015-10-20	2015-10-21	2015-10-22	2015-10-23	2015-10-26	2015-10-27	2015-10-28	2015-10-29	2015-10-30	2015-11-02	2015-11-03	2015-11-04	2015-11-05	2015-11-06	2015-11-09	2015-11-10	2015-11-11	2015-11-12	2015-11-13	2015-11-16	2015-11-17	2015-11-18	2015-11-19	2015-11-20	2015-11-23	2015-11-24	2015-11-25	2015-11-26	2015-11-27	2015-11-30	2015-12-01	2015-12-02	2015-12-03	2015-12-04	2015-12-07	2015-12-08	2015-12-09	2015-12-10	2015-12-11	2015-12-14	2015-12-15	2015-12-16	2015-12-17	2015-12-18	2015-12-21	2015-12-22	2015-12-23	2015-12-24	2015-12-25	2015-12-28	2015-12-29	2015-12-30	2015-12-31
1	NaT	2015-01-02 09:43:45	2015-01-05 10:08:48	2015-01-06 09:54:26	2015-01-07 09:34:31	2015-01-08 09:51:09	2015-01-09 10:09:25	2015-01-12 09:42:53	2015-01-13 10:13:06	NaT	2015-01-15 10:01:24	2015-01-16 10:19:08	NaT	2015-01-20 09:50:34	2015-01-21 09:49:42	2015-01-22 09:47:45	2015-01-23 09:23:44	NaT	2015-01-27 09:50:37	2015-01-28 09:56:13	2015-01-29 09:53:47	2015-01-30 10:09:26	2015-02-02 09:38:43	2015-02-03 10:23:38	2015-02-04 09:48:37	2015-02-05 09:52:36	2015-02-06 09:53:23	2015-02-09 10:01:45	2015-02-10 10:14:18	2015-02-11 10:18:44	2015-02-12 10:10:35	2015-02-13 09:13:07	2015-02-16 10:14:02	2015-02-17 10:03:08	2015-02-18 10:23:06	NaT	2015-02-20 09:54:56	2015-02-23 09:46:59	2015-02-24 10:11:18	2015-02-25 09:52:36	2015-02-26 09:56:33	2015-02-27 09:58:46	2015-03-02 10:19:43	2015-03-03 10:08:37	2015-03-04 10:05:38	NaT	2015-03-06 09:55:53	2015-03-09 10:28:34	2015-03-10 09:47:30	2015-03-11 09:48:59	2015-03-12 10:10:51	2015-03-13 10:07:18	NaT	2015-03-17 10:05:22	2015-03-18 10:28:21	2015-03-19 10:01:52	2015-03-20 10:37:49	2015-03-23 10:11:19	2015-03-24 10:33:19	2015-03-25 09:41:35	NaT	2015-03-27 09:47:30	2015-03-30 10:11:44	2015-03-31 10:08:13	2015-04-01 10:12:37	2015-04-02 09:45:27	2015-04-03 10:00:30	2015-04-06 09:40:19	2015-04-07 10:16:43	2015-04-08 10:04:34	2015-04-09 09:21:27	2015-04-10 09:46:25	2015-04-13 09:39:30	2015-04-14 09:58:48	2015-04-15 09:55:56	2015-04-16 09:46:07	2015-04-17 09:54:13	2015-04-20 10:03:25	2015-04-21 09:50:41	2015-04-22 09:56:16	2015-04-23 10:12:42	2015-04-24 10:05:40	2015-04-27 10:12:01	2015-04-28 09:57:24	2015-04-29 09:46:15	2015-04-30 09:48:30	NaT	2015-05-04 09:40:52	2015-05-05 09:54:59	2015-05-06 09:49:06	2015-05-07 10:06:47	2015-05-08 09:55:02	NaT	2015-05-12 09:50:17	2015-05-13 10:24:03	2015-05-14 09:50:43	2015-05-15 09:55:32	NaT	2015-05-19 09:49:06	2015-05-20 10:00:39	2015-05-21 09:53:15	2015-05-22 10:19:44	2015-05-25 10:15:25	2015-05-26 10:17:01	2015-05-27 09:41:25	2015-05-28 09:57:00	NaT	NaT	2015-06-02 10:20:49	2015-06-03 09:47:19	2015-06-04 10:23:40	NaT	2015-06-08 10:17:56	NaT	2015-06-10 09:54:33	2015-06-11 09:47:09	2015-06-12 10:13:55	2015-06-15 09:50:19	2015-06-16 09:59:04	2015-06-17 09:46:15	2015-06-18 10:03:15	2015-06-19 10:06:21	2015-06-22 09:48:40	2015-06-23 09:56:55	2015-06-24 09:59:40	2015-06-25 09:52:01	2015-06-26 10:07:58	2015-06-29 10:01:19	2015-06-30 10:27:40	2015-07-01 09:39:02	2015-07-02 10:07:33	2015-07-03 09:59:57	2015-07-06 09:37:06	2015-07-07 10:08:17	2015-07-08 09:56:30	2015-07-09 09:21:57	2015-07-10 09:43:31	2015-07-13 10:07:21	2015-07-14 10:06:39	2015-07-15 09:54:34	2015-07-16 10:22:47	NaT	2015-07-20 10:25:50	2015-07-21 09:48:05	2015-07-22 09:52:29	2015-07-23 10:04:42	2015-07-24 09:34:15	2015-07-27 09:56:24	2015-07-28 10:19:57	2015-07-29 09:48:10	2015-07-30 09:52:24	2015-07-31 10:11:14	2015-08-03 10:03:33	2015-08-04 09:59:34	2015-08-05 09:50:51	2015-08-06 09:56:52	2015-08-07 09:51:30	2015-08-10 10:12:23	2015-08-11 10:08:29	2015-08-12 09:39:08	2015-08-13 09:47:09	2015-08-14 10:00:21	2015-08-17 09:24:23	2015-08-18 10:25:27	2015-08-19 10:14:41	2015-08-20 09:57:56	2015-08-21 10:07:11	2015-08-24 10:07:49	2015-08-25 09:47:59	2015-08-26 09:53:49	2015-08-27 10:16:21	2015-08-28 09:53:47	2015-08-31 10:08:07	NaT	2015-09-02 10:37:59	2015-09-03 09:41:16	2015-09-04 10:11:00	2015-09-07 10:17:58	2015-09-08 10:31:57	2015-09-09 10:28:33	2015-09-10 09:54:28	2015-09-11 10:02:49	2015-09-14 10:15:40	2015-09-15 10:26:09	2015-09-16 10:11:03	NaT	2015-09-18 10:16:06	2015-09-21 09:48:01	2015-09-22 10:34:52	2015-09-23 10:03:15	2015-09-24 10:00:12	2015-09-25 10:00:00	2015-09-28 09:28:45	2015-09-29 09:51:58	2015-09-30 09:52:41	2015-10-01 10:05:28	NaT	2015-10-05 10:02:00	2015-10-06 09:48:24	2015-10-07 09:32:05	2015-10-08 09:39:01	2015-10-09 09:33:40	2015-10-12 10:14:36	NaT	2015-10-14 10:19:43	2015-10-15 10:19:51	2015-10-16 09:50:41	2015-10-19 09:55:08	2015-10-20 10:00:37	NaT	NaT	2015-10-23 10:03:33	2015-10-26 09:51:07	2015-10-27 09:25:10	2015-10-28 09:50:30	2015-10-29 09:50:22	2015-10-30 09:51:07	2015-11-02 10:01:58	2015-11-03 10:28:53	2015-11-04 09:47:00	2015-11-05 10:24:57	2015-11-06 10:15:27	NaT	NaT	NaT	2015-11-12 10:02:34	2015-11-13 09:29:49	2015-11-16 10:16:02	2015-11-17 09:57:23	2015-11-18 10:13:24	2015-11-19 09:46:48	2015-11-20 10:09:35	2015-11-23 09:54:17	2015-11-24 10:02:07	2015-11-25 10:01:51	2015-11-26 10:18:45	2015-11-27 10:24:49	2015-11-30 10:04:24	2015-12-01 09:31:27	2015-12-02 09:57:52	2015-12-03 10:05:55	2015-12-04 09:55:09	2015-12-07 09:28:15	2015-12-08 09:54:56	2015-12-09 09:51:52	2015-12-10 09:40:25	2015-12-11 09:46:49	2015-12-14 10:03:33	NaT	2015-12-16 10:21:19	NaT	NaT	2015-12-21 09:55:29	2015-12-22 10:04:06	2015-12-23 10:14:27	2015-12-24 10:11:35	NaT	2015-12-28 10:13:41	2015-12-29 10:03:36	2015-12-30 09:54:12	2015-12-31 10:12:44
2	NaT	2015-01-02 10:15:44	2015-01-05 10:21:05	NaT	2015-01-07 09:45:17	2015-01-08 10:09:04	2015-01-09 09:43:26	2015-01-12 10:00:07	2015-01-13 10:43:29	NaT	2015-01-15 09:37:57	2015-01-16 09:57:18	2015-01-19 10:23:43	2015-01-20 09:29:03	2015-01-21 09:46:45	2015-01-22 10:03:51	2015-01-23 09:20:06	NaT	2015-01-27 10:07:48	2015-01-28 10:08:25	2015-01-29 09:52:04	2015-01-30 09:49:49	2015-02-02 10:07:26	2015-02-03 09:55:45	2015-02-04 10:25:41	2015-02-05 10:05:11	2015-02-06 09:12:39	NaT	2015-02-10 10:10:13	2015-02-11 09:40:20	2015-02-12 10:10:09	2015-02-13 09:35:25	2015-02-16 10:04:12	2015-02-17 09:45:05	2015-02-18 09:54:42	2015-02-19 10:11:49	2015-02-20 10:06:18	2015-02-23 09:41:58	2015-02-24 09:44:22	2015-02-25 09:58:39	2015-02-26 09:59:07	2015-02-27 10:31:41	2015-03-02 09:55:43	2015-03-03 10:31:20	2015-03-04 09:56:59	NaT	2015-03-06 10:01:10	2015-03-09 10:02:33	2015-03-10 09:32:40	2015-03-11 09:57:02	2015-03-12 09:59:32	2015-03-13 09:59:14	2015-03-16 09:56:19	2015-03-17 09:36:08	2015-03-18 10:00:32	2015-03-19 09:46:51	2015-03-20 10:06:06	2015-03-23 10:02:02	NaT	2015-03-25 10:03:04	2015-03-26 09:52:38	2015-03-27 10:02:55	2015-03-30 10:04:24	2015-03-31 10:30:25	2015-04-01 09:46:24	2015-04-02 09:53:55	2015-04-03 10:30:21	2015-04-06 10:18:14	2015-04-07 10:22:22	2015-04-08 09:46:42	2015-04-09 10:02:22	2015-04-10 09:47:56	2015-04-13 09:33:46	2015-04-14 09:50:19	2015-04-15 10:06:41	2015-04-16 10:07:24	2015-04-17 09:40:35	2015-04-20 10:04:05	2015-04-21 10:21:53	2015-04-22 09:40:33	2015-04-23 10:06:54	2015-04-24 10:10:19	2015-04-27 09:33:44	2015-04-28 09:52:51	NaT	2015-04-30 10:14:03	NaT	2015-05-04 09:53:54	2015-05-05 10:25:20	2015-05-06 09:46:04	2015-05-07 09:49:37	2015-05-08 09:56:40	2015-05-11 09:58:30	2015-05-12 09:44:55	2015-05-13 10:06:35	NaT	2015-05-15 09:43:03	NaT	2015-05-19 09:48:05	2015-05-20 10:18:00	2015-05-21 09:42:47	2015-05-22 10:37:50	2015-05-25 09:46:03	2015-05-26 09:42:16	2015-05-27 09:53:20	2015-05-28 09:54:58	2015-05-29 09:52:45	2015-06-01 09:54:45	2015-06-02 09:57:56	2015-06-03 10:10:48	2015-06-04 09:31:48	2015-06-05 10:06:28	2015-06-08 09:45:19	2015-06-09 09:59:08	2015-06-10 09:39:05	2015-06-11 09:55:03	NaT	2015-06-15 09:45:02	2015-06-16 10:15:23	2015-06-17 09:52:23	2015-06-18 09:55:27	2015-06-19 10:13:33	2015-06-22 09:48:24	2015-06-23 09:59:12	2015-06-24 10:27:17	2015-06-25 10:12:33	2015-06-26 09:55:00	2015-06-29 10:02:27	2015-06-30 10:13:31	2015-07-01 09:45:31	2015-07-02 10:04:21	2015-07-03 10:00:01	2015-07-06 10:10:37	2015-07-07 10:29:29	2015-07-08 09:38:19	2015-07-09 10:21:59	2015-07-10 10:30:44	NaT	2015-07-14 10:35:52	2015-07-15 09:47:06	2015-07-16 09:59:13	NaT	2015-07-20 10:18:08	2015-07-21 10:23:11	2015-07-22 09:32:15	2015-07-23 09:40:12	2015-07-24 10:15:22	NaT	2015-07-28 10:16:14	2015-07-29 09:58:33	2015-07-30 09:57:10	2015-07-31 10:15:38	2015-08-03 09:58:28	2015-08-04 10:17:10	2015-08-05 09:38:46	2015-08-06 10:16:03	2015-08-07 09:52:22	2015-08-10 09:37:38	2015-08-11 09:54:35	2015-08-12 09:27:52	2015-08-13 09:50:57	2015-08-14 09:38:27	2015-08-17 09:52:16	2015-08-18 09:34:06	2015-08-19 09:43:02	2015-08-20 10:16:38	2015-08-21 10:07:18	2015-08-24 09:36:46	2015-08-25 09:42:22	2015-08-26 10:15:22	2015-08-27 10:11:04	2015-08-28 09:50:51	2015-08-31 10:23:10	2015-09-01 10:23:47	2015-09-02 09:57:01	2015-09-03 09:56:07	2015-09-04 10:33:03	2015-09-07 09:58:33	NaT	2015-09-09 10:17:43	2015-09-10 10:28:40	2015-09-11 09:58:20	2015-09-14 09:43:25	2015-09-15 09:25:53	2015-09-16 09:26:29	NaT	2015-09-18 10:27:07	2015-09-21 10:03:31	2015-09-22 09:35:23	2015-09-23 10:12:56	2015-09-24 10:02:52	2015-09-25 09:37:12	2015-09-28 10:11:06	2015-09-29 10:00:31	2015-09-30 10:22:56	2015-10-01 10:08:29	NaT	2015-10-05 10:02:26	2015-10-06 10:08:57	2015-10-07 10:10:19	2015-10-08 10:04:03	2015-10-09 09:40:41	2015-10-12 10:11:30	2015-10-13 10:14:39	2015-10-14 10:10:48	NaT	2015-10-16 10:20:19	2015-10-19 10:04:13	2015-10-20 09:39:10	2015-10-21 09:47:15	2015-10-22 09:56:54	2015-10-23 09:53:38	2015-10-26 09:49:43	2015-10-27 10:29:20	2015-10-28 09:47:39	2015-10-29 09:52:02	2015-10-30 09:47:37	2015-11-02 10:04:45	2015-11-03 09:36:03	2015-11-04 09:58:34	2015-11-05 09:50:08	2015-11-06 10:02:38	NaT	NaT	NaT	2015-11-12 09:54:47	2015-11-13 09:26:10	2015-11-16 10:22:00	2015-11-17 09:26:04	2015-11-18 10:10:39	NaT	2015-11-20 10:01:09	2015-11-23 09:51:11	2015-11-24 09:19:04	2015-11-25 09:43:44	2015-11-26 10:34:30	2015-11-27 10:15:10	2015-11-30 09:46:46	2015-12-01 09:56:22	2015-12-02 09:55:43	2015-12-03 10:05:37	2015-12-04 10:02:05	2015-12-07 09:36:05	2015-12-08 10:01:21	2015-12-09 09:49:23	2015-12-10 10:06:05	2015-12-11 10:15:18	2015-12-14 10:00:01	2015-12-15 10:30:18	2015-12-16 10:01:18	2015-12-17 09:15:08	2015-12-18 10:37:17	2015-12-21 09:49:02	2015-12-22 10:33:51	2015-12-23 10:12:10	NaT	NaT	2015-12-28 09:31:45	2015-12-29 09:55:49	2015-12-30 10:32:25	2015-12-31 09:27:20
3	NaT	2015-01-02 10:17:41	2015-01-05 09:50:50	2015-01-06 10:14:13	2015-01-07 09:47:27	2015-01-08 10:03:40	2015-01-09 10:05:49	2015-01-12 10:03:47	2015-01-13 10:21:26	NaT	2015-01-15 09:55:11	2015-01-16 10:05:36	2015-01-19 09:47:53	2015-01-20 09:57:09	2015-01-21 10:29:40	2015-01-22 09:59:11	2015-01-23 10:16:34	NaT	2015-01-27 10:07:30	2015-01-28 10:05:43	2015-01-29 10:06:48	2015-01-30 10:14:36	2015-02-02 09:54:45	2015-02-03 09:27:11	2015-02-04 10:04:03	2015-02-05 10:08:11	2015-02-06 10:23:51	2015-02-09 10:08:43	2015-02-10 10:26:18	2015-02-11 10:02:13	2015-02-12 09:55:10	2015-02-13 10:32:34	2015-02-16 10:18:43	2015-02-17 10:04:54	2015-02-18 10:16:19	2015-02-19 09:47:19	2015-02-20 10:20:51	2015-02-23 10:14:02	2015-02-24 10:23:28	2015-02-25 09:59:06	2015-02-26 10:01:22	2015-02-27 09:57:26	2015-03-02 10:02:38	2015-03-03 10:07:45	2015-03-04 10:15:26	NaT	2015-03-06 09:48:49	2015-03-09 10:17:45	2015-03-10 09:46:10	2015-03-11 10:26:39	2015-03-12 09:56:28	2015-03-13 09:36:23	2015-03-16 10:07:30	2015-03-17 10:00:43	2015-03-18 10:20:10	2015-03-19 09:54:40	NaT	2015-03-23 10:04:28	2015-03-24 10:18:38	2015-03-25 09:43:22	2015-03-26 09:37:02	NaT	2015-03-30 09:54:55	2015-03-31 10:00:57	2015-04-01 09:52:42	2015-04-02 10:24:02	2015-04-03 10:01:42	2015-04-06 09:33:15	2015-04-07 10:13:13	2015-04-08 10:38:41	2015-04-09 10:17:34	2015-04-10 10:28:08	2015-04-13 10:14:55	2015-04-14 09:29:50	2015-04-15 10:06:52	2015-04-16 09:46:13	2015-04-17 10:16:08	2015-04-20 09:36:16	2015-04-21 10:07:10	2015-04-22 09:56:42	NaT	2015-04-24 10:10:15	2015-04-27 09:29:29	2015-04-28 10:01:45	2015-04-29 09:54:28	2015-04-30 09:40:30	NaT	2015-05-04 09:55:15	2015-05-05 09:53:50	2015-05-06 10:20:45	2015-05-07 09:49:38	2015-05-08 10:21:01	2015-05-11 09:47:03	2015-05-12 09:39:48	2015-05-13 09:50:23	2015-05-14 09:45:22	2015-05-15 09:48:59	2015-05-18 10:03:24	2015-05-19 09:40:26	2015-05-20 09:40:20	2015-05-21 09:37:39	2015-05-22 10:04:08	2015-05-25 10:06:54	2015-05-26 10:28:05	2015-05-27 10:14:07	2015-05-28 10:13:25	2015-05-29 10:08:23	2015-06-01 09:57:32	2015-06-02 09:58:49	2015-06-03 10:03:00	2015-06-04 09:32:13	2015-06-05 09:43:51	2015-06-08 09:31:20	2015-06-09 09:49:58	2015-06-10 10:14:49	2015-06-11 10:07:21	2015-06-12 10:10:53	2015-06-15 09:52:17	2015-06-16 09:33:01	2015-06-17 09:50:53	2015-06-18 10:01:04	2015-06-19 09:47:22	2015-06-22 09:52:10	2015-06-23 09:44:50	NaT	2015-06-25 10:10:41	2015-06-26 10:02:07	2015-06-29 09:33:13	2015-06-30 10:13:47	2015-07-01 10:07:56	2015-07-02 10:26:28	2015-07-03 09:40:28	2015-07-06 10:02:42	2015-07-07 10:50:49	2015-07-08 09:56:24	2015-07-09 10:08:14	2015-07-10 09:58:44	2015-07-13 09:59:18	2015-07-14 09:54:55	2015-07-15 09:42:13	2015-07-16 10:00:16	NaT	2015-07-20 10:12:37	2015-07-21 09:39:36	2015-07-22 09:50:19	2015-07-23 10:27:02	2015-07-24 09:58:29	2015-07-27 10:11:51	2015-07-28 09:44:58	2015-07-29 10:29:58	2015-07-30 10:27:08	2015-07-31 09:32:14	2015-08-03 09:49:21	2015-08-04 09:37:19	NaT	2015-08-06 10:00:11	2015-08-07 09:36:58	2015-08-10 09:51:11	2015-08-11 09:49:26	2015-08-12 10:26:18	2015-08-13 10:12:57	2015-08-14 09:51:22	2015-08-17 09:59:35	2015-08-18 09:57:40	2015-08-19 10:06:09	2015-08-20 10:09:06	2015-08-21 10:28:51	2015-08-24 10:04:52	2015-08-25 10:09:53	2015-08-26 10:26:55	2015-08-27 09:08:23	2015-08-28 10:07:20	2015-08-31 09:44:35	2015-09-01 09:51:52	2015-09-02 09:52:28	2015-09-03 10:05:51	2015-09-04 10:11:53	2015-09-07 09:28:00	2015-09-08 09:38:21	2015-09-09 09:45:09	2015-09-10 09:49:52	2015-09-11 09:57:16	2015-09-14 10:27:59	2015-09-15 10:11:20	2015-09-16 09:55:26	NaT	2015-09-18 09:54:29	2015-09-21 09:29:30	2015-09-22 09:35:39	2015-09-23 09:56:54	2015-09-24 10:31:35	2015-09-25 09:40:55	2015-09-28 09:55:28	2015-09-29 10:25:49	2015-09-30 10:11:02	2015-10-01 09:58:27	NaT	2015-10-05 10:10:21	2015-10-06 09:56:07	2015-10-07 10:09:43	2015-10-08 09:46:36	2015-10-09 10:00:44	2015-10-12 10:14:10	2015-10-13 10:22:14	2015-10-14 10:20:42	2015-10-15 10:12:05	2015-10-16 09:41:55	2015-10-19 10:03:40	2015-10-20 10:02:12	2015-10-21 10:52:27	2015-10-22 10:10:44	2015-10-23 10:08:37	2015-10-26 10:29:26	2015-10-27 09:48:57	2015-10-28 09:54:52	2015-10-29 09:47:27	2015-10-30 09:51:47	2015-11-02 09:54:18	2015-11-03 09:52:40	2015-11-04 10:19:14	2015-11-05 10:23:27	2015-11-06 10:06:29	NaT	NaT	NaT	2015-11-12 10:14:47	2015-11-13 09:43:37	2015-11-16 10:02:56	2015-11-17 09:51:38	2015-11-18 10:12:13	2015-11-19 10:08:46	2015-11-20 10:06:39	2015-11-23 10:02:01	2015-11-24 09:53:52	2015-11-25 10:16:19	2015-11-26 10:07:02	NaT	2015-11-30 10:01:33	2015-12-01 10:02:52	2015-12-02 10:10:34	2015-12-03 10:18:25	2015-12-04 10:06:40	2015-12-07 10:21:09	2015-12-08 09:59:19	2015-12-09 10:17:28	NaT	2015-12-11 09:49:55	2015-12-14 09:42:31	2015-12-15 09:54:48	2015-12-16 09:48:34	2015-12-17 09:53:17	2015-12-18 10:15:14	2015-12-21 10:10:28	2015-12-22 09:44:44	2015-12-23 10:15:54	2015-12-24 10:07:26	NaT	2015-12-28 09:42:05	2015-12-29 09:43:36	2015-12-30 09:34:05	2015-12-31 10:28:39
4	NaT	2015-01-02 10:05:06	2015-01-05 09:56:32	2015-01-06 10:11:07	2015-01-07 09:37:30	2015-01-08 10:02:08	2015-01-09 10:08:12	2015-01-12 10:13:42	2015-01-13 09:53:22	NaT	2015-01-15 10:00:50	2015-01-16 09:58:06	2015-01-19 09:43:11	2015-01-20 10:29:06	2015-01-21 10:04:33	2015-01-22 09:51:07	2015-01-23 09:56:56	NaT	2015-01-27 09:48:31	2015-01-28 10:00:39	2015-01-29 09:49:28	2015-01-30 09:56:31	2015-02-02 10:14:08	2015-02-03 10:01:31	2015-02-04 10:31:44	2015-02-05 10:02:39	2015-02-06 09:24:21	2015-02-09 09:56:27	NaT	2015-02-11 10:00:32	2015-02-12 10:01:48	2015-02-13 10:14:10	2015-02-16 09:50:27	2015-02-17 09:52:42	2015-02-18 09:39:22	2015-02-19 09:43:55	2015-02-20 10:01:49	2015-02-23 09:33:30	2015-02-24 10:27:00	2015-02-25 09:45:59	2015-02-26 09:48:05	2015-02-27 09:43:15	NaT	2015-03-03 10:15:24	2015-03-04 09:59:04	NaT	NaT	2015-03-09 10:05:52	2015-03-10 09:29:22	2015-03-11 09:57:24	2015-03-12 09:41:16	2015-03-13 09:52:58	2015-03-16 09:56:00	2015-03-17 09:52:20	2015-03-18 10:25:14	2015-03-19 10:26:39	2015-03-20 10:22:47	2015-03-23 10:21:28	2015-03-24 10:26:25	2015-03-25 10:00:08	2015-03-26 10:21:30	NaT	2015-03-30 10:11:13	2015-03-31 09:59:04	2015-04-01 09:48:31	2015-04-02 09:37:22	2015-04-03 09:55:13	2015-04-06 09:59:50	2015-04-07 10:35:40	2015-04-08 10:26:15	2015-04-09 10:12:10	2015-04-10 10:22:56	2015-04-13 09:31:58	NaT	2015-04-15 10:12:59	2015-04-16 09:45:58	2015-04-17 10:04:10	2015-04-20 09:51:49	2015-04-21 10:13:27	2015-04-22 09:50:42	2015-04-23 09:37:10	2015-04-24 09:58:19	2015-04-27 09:53:47	2015-04-28 09:24:22	2015-04-29 09:55:33	2015-04-30 10:02:10	NaT	2015-05-04 10:28:52	2015-05-05 10:00:44	2015-05-06 10:18:13	2015-05-07 10:03:39	2015-05-08 10:00:50	2015-05-11 10:23:52	2015-05-12 09:36:52	2015-05-13 10:13:15	2015-05-14 09:45:33	2015-05-15 09:27:48	2015-05-18 09:29:24	2015-05-19 09:52:54	2015-05-20 10:05:04	2015-05-21 09:33:56	NaT	2015-05-25 09:55:48	2015-05-26 10:10:44	2015-05-27 10:20:30	2015-05-28 09:45:38	2015-05-29 10:12:37	2015-06-01 10:14:37	2015-06-02 09:54:11	2015-06-03 09:52:39	2015-06-04 10:06:30	2015-06-05 09:45:42	2015-06-08 09:49:32	2015-06-09 10:19:40	2015-06-10 10:09:14	2015-06-11 09:59:59	2015-06-12 10:17:33	2015-06-15 10:11:20	2015-06-16 09:57:08	2015-06-17 09:41:36	2015-06-18 09:39:27	2015-06-19 09:34:20	2015-06-22 10:10:20	2015-06-23 09:42:51	2015-06-24 10:08:58	2015-06-25 09:47:00	2015-06-26 09:53:39	2015-06-29 10:03:00	2015-06-30 09:42:37	2015-07-01 09:21:09	2015-07-02 09:43:19	2015-07-03 09:53:23	2015-07-06 09:50:21	2015-07-07 10:24:34	2015-07-08 10:13:37	2015-07-09 10:02:30	2015-07-10 10:20:48	2015-07-13 10:06:03	2015-07-14 10:13:16	2015-07-15 10:21:49	2015-07-16 09:50:24	NaT	2015-07-20 10:00:48	2015-07-21 09:50:21	NaT	2015-07-23 10:21:26	2015-07-24 09:27:01	2015-07-27 10:06:37	2015-07-28 09:24:12	2015-07-29 09:51:04	2015-07-30 10:00:50	2015-07-31 09:47:58	2015-08-03 10:11:15	2015-08-04 09:38:39	NaT	2015-08-06 09:57:51	2015-08-07 09:48:50	2015-08-10 10:15:50	2015-08-11 10:00:04	2015-08-12 09:35:06	2015-08-13 09:50:28	2015-08-14 09:37:57	2015-08-17 10:08:57	2015-08-18 10:08:19	2015-08-19 09:58:18	2015-08-20 09:58:16	2015-08-21 09:54:32	NaT	2015-08-25 09:51:55	2015-08-26 09:53:52	2015-08-27 10:06:05	NaT	2015-08-31 09:50:42	2015-09-01 09:40:25	2015-09-02 09:28:38	2015-09-03 09:56:30	2015-09-04 10:12:19	2015-09-07 10:24:08	2015-09-08 10:21:37	2015-09-09 10:18:14	2015-09-10 09:19:24	2015-09-11 10:50:44	2015-09-14 09:43:15	2015-09-15 09:51:29	2015-09-16 09:37:48	NaT	2015-09-18 10:16:55	2015-09-21 10:08:13	2015-09-22 09:58:12	2015-09-23 09:41:19	2015-09-24 10:14:13	NaT	2015-09-28 10:01:47	2015-09-29 10:05:44	2015-09-30 10:30:29	2015-10-01 09:53:38	NaT	NaT	2015-10-06 09:53:14	2015-10-07 10:02:55	2015-10-08 09:30:44	2015-10-09 10:12:55	2015-10-12 10:17:48	2015-10-13 10:18:19	2015-10-14 09:54:16	2015-10-15 09:43:10	2015-10-16 09:56:29	2015-10-19 09:57:36	2015-10-20 09:12:03	2015-10-21 10:30:37	2015-10-22 09:49:39	2015-10-23 09:31:09	2015-10-26 09:59:23	2015-10-27 09:41:26	2015-10-28 09:38:11	2015-10-29 09:53:39	NaT	2015-11-02 10:00:05	2015-11-03 10:29:56	2015-11-04 10:12:46	2015-11-05 10:08:09	NaT	NaT	NaT	NaT	2015-11-12 10:08:26	2015-11-13 09:37:08	2015-11-16 09:42:23	2015-11-17 10:20:38	2015-11-18 10:02:33	2015-11-19 10:27:15	2015-11-20 10:01:14	2015-11-23 09:55:40	2015-11-24 10:00:46	2015-11-25 09:33:48	2015-11-26 10:24:11	2015-11-27 10:09:17	2015-11-30 09:50:21	2015-12-01 09:52:48	2015-12-02 10:09:28	2015-12-03 09:24:05	2015-12-04 09:52:37	2015-12-07 10:00:22	2015-12-08 10:04:10	2015-12-09 10:25:19	2015-12-10 09:39:15	2015-12-11 09:46:02	2015-12-14 10:20:36	2015-12-15 09:37:17	2015-12-16 10:22:09	2015-12-17 09:54:36	2015-12-18 10:17:38	2015-12-21 09:58:21	2015-12-22 10:04:25	2015-12-23 10:11:46	2015-12-24 09:43:15	NaT	2015-12-28 09:52:44	2015-12-29 09:33:16	2015-12-30 10:18:12	2015-12-31 10:01:15
5	NaT	2015-01-02 10:28:17	2015-01-05 09:49:58	2015-01-06 09:45:28	2015-01-07 09:49:37	2015-01-08 10:19:44	2015-01-09 10:00:50	2015-01-12 10:29:27	2015-01-13 09:59:32	NaT	2015-01-15 10:06:12	2015-01-16 10:03:50	NaT	2015-01-20 10:10:29	2015-01-21 10:28:15	2015-01-22 10:10:10	2015-01-23 09:34:34	NaT	2015-01-27 09:56:59	2015-01-28 09:45:03	2015-01-29 10:11:41	2015-01-30 10:24:50	2015-02-02 09:43:27	2015-02-03 09:55:59	2015-02-04 10:03:25	2015-02-05 10:02:17	2015-02-06 09:55:43	2015-02-09 10:15:16	2015-02-10 09:43:48	2015-02-11 10:03:36	2015-02-12 10:02:17	2015-02-13 09:44:55	2015-02-16 09:55:58	2015-02-17 10:09:22	2015-02-18 09:37:58	2015-02-19 09:38:21	2015-02-20 10:02:12	2015-02-23 10:25:42	2015-02-24 09:51:00	2015-02-25 09:55:22	2015-02-26 09:58:05	2015-02-27 10:07:47	2015-03-02 09:59:53	2015-03-03 09:42:11	2015-03-04 10:00:32	NaT	2015-03-06 09:53:21	2015-03-09 09:56:58	2015-03-10 10:02:48	2015-03-11 09:48:03	2015-03-12 09:34:03	2015-03-13 10:12:48	2015-03-16 09:59:26	2015-03-17 10:16:28	2015-03-18 09:49:21	2015-03-19 10:06:49	2015-03-20 09:46:16	2015-03-23 10:12:47	2015-03-24 09:37:38	2015-03-25 10:16:56	2015-03-26 10:06:01	2015-03-27 09:47:43	2015-03-30 09:59:29	2015-03-31 10:28:28	2015-04-01 09:46:04	2015-04-02 09:54:15	2015-04-03 09:51:44	2015-04-06 10:05:02	2015-04-07 09:49:12	2015-04-08 10:08:27	2015-04-09 09:57:47	2015-04-10 10:09:16	2015-04-13 09:59:22	2015-04-14 09:58:02	2015-04-15 09:58:30	2015-04-16 09:49:06	2015-04-17 10:02:28	2015-04-20 09:55:16	NaT	2015-04-22 10:09:26	2015-04-23 10:00:47	2015-04-24 10:18:18	2015-04-27 10:18:43	2015-04-28 09:41:17	2015-04-29 10:21:11	2015-04-30 10:20:45	NaT	2015-05-04 09:41:58	2015-05-05 10:09:45	2015-05-06 10:28:38	2015-05-07 10:05:24	2015-05-08 10:20:21	2015-05-11 09:43:11	2015-05-12 09:46:57	2015-05-13 10:09:57	2015-05-14 10:07:50	2015-05-15 09:27:13	2015-05-18 10:08:39	2015-05-19 09:41:20	2015-05-20 10:21:00	2015-05-21 09:45:53	2015-05-22 10:13:55	2015-05-25 10:26:55	2015-05-26 09:44:25	2015-05-27 09:56:39	2015-05-28 09:51:58	2015-05-29 09:41:19	2015-06-01 10:22:26	2015-06-02 10:07:35	2015-06-03 10:05:21	2015-06-04 09:46:59	2015-06-05 09:47:52	2015-06-08 09:55:09	2015-06-09 10:36:58	2015-06-10 10:18:44	NaT	2015-06-12 10:25:57	2015-06-15 09:45:05	2015-06-16 10:26:43	2015-06-17 09:47:19	2015-06-18 10:13:49	2015-06-19 09:47:13	2015-06-22 10:04:08	2015-06-23 09:51:11	2015-06-24 10:12:56	2015-06-25 09:59:25	2015-06-26 09:29:47	2015-06-29 10:08:32	2015-06-30 10:03:44	2015-07-01 09:48:35	2015-07-02 09:24:58	2015-07-03 10:08:01	2015-07-06 09:41:01	2015-07-07 10:23:38	2015-07-08 09:46:59	2015-07-09 10:47:18	2015-07-10 10:06:36	2015-07-13 10:00:10	2015-07-14 09:36:55	2015-07-15 09:44:21	2015-07-16 09:34:59	NaT	2015-07-20 10:26:08	2015-07-21 09:42:08	2015-07-22 09:58:04	2015-07-23 10:09:40	2015-07-24 09:43:16	2015-07-27 09:59:05	2015-07-28 10:43:35	2015-07-29 10:54:55	2015-07-30 10:09:52	2015-07-31 09:49:40	2015-08-03 10:23:07	2015-08-04 09:48:50	2015-08-05 09:33:13	2015-08-06 09:56:03	2015-08-07 09:48:23	2015-08-10 10:12:45	2015-08-11 10:11:50	NaT	2015-08-13 10:06:11	2015-08-14 09:48:26	2015-08-17 10:19:25	2015-08-18 09:55:14	2015-08-19 09:45:22	2015-08-20 09:40:50	2015-08-21 09:52:20	2015-08-24 09:59:24	2015-08-25 10:24:46	2015-08-26 09:40:04	2015-08-27 10:00:36	2015-08-28 09:55:44	2015-08-31 10:09:20	2015-09-01 09:48:18	2015-09-02 10:16:14	2015-09-03 10:32:19	2015-09-04 10:04:26	2015-09-07 09:47:03	2015-09-08 10:14:53	2015-09-09 09:45:22	2015-09-10 09:42:04	2015-09-11 09:41:30	2015-09-14 09:48:38	2015-09-15 09:44:13	2015-09-16 09:55:17	NaT	2015-09-18 09:45:17	2015-09-21 09:47:48	2015-09-22 10:08:20	2015-09-23 09:44:15	2015-09-24 09:49:02	2015-09-25 09:46:15	2015-09-28 09:57:55	2015-09-29 09:50:24	2015-09-30 10:01:46	2015-10-01 09:58:38	NaT	2015-10-05 10:01:38	2015-10-06 09:53:54	2015-10-07 09:49:00	2015-10-08 09:52:18	2015-10-09 09:37:05	2015-10-12 09:47:44	2015-10-13 09:44:28	2015-10-14 10:05:50	2015-10-15 09:48:36	2015-10-16 09:59:24	2015-10-19 10:21:33	2015-10-20 09:54:18	2015-10-21 09:40:43	2015-10-22 09:54:53	2015-10-23 10:20:46	2015-10-26 09:26:54	2015-10-27 09:52:14	2015-10-28 10:05:45	2015-10-29 10:47:48	2015-10-30 09:54:08	2015-11-02 10:21:24	2015-11-03 10:14:29	2015-11-04 10:05:50	2015-11-05 10:14:59	2015-11-06 09:56:52	NaT	NaT	NaT	2015-11-12 09:40:29	2015-11-13 09:55:12	2015-11-16 10:15:51	2015-11-17 09:31:09	2015-11-18 10:05:50	2015-11-19 10:07:44	2015-11-20 09:58:14	2015-11-23 10:12:11	2015-11-24 09:56:16	2015-11-25 10:02:15	2015-11-26 09:54:51	2015-11-27 09:50:48	2015-11-30 10:00:02	2015-12-01 10:13:08	2015-12-02 09:38:52	2015-12-03 09:48:57	2015-12-04 09:55:11	2015-12-07 10:01:34	2015-12-08 09:18:02	2015-12-09 10:02:29	2015-12-10 10:18:53	2015-12-11 10:26:26	2015-12-14 10:20:18	2015-12-15 09:55:55	2015-12-16 10:09:25	2015-12-17 09:46:35	2015-12-18 09:58:35	2015-12-21 10:03:41	2015-12-22 10:10:30	2015-12-23 10:13:36	2015-12-24 09:44:24	NaT	2015-12-28 10:05:15	2015-12-29 10:30:53	2015-12-30 09:18:21	2015-12-31 09:41:09

	2015-01-01	2015-01-02	2015-01-05	2015-01-06	2015-01-07	2015-01-08	2015-01-09	2015-01-12	2015-01-13	2015-01-14	2015-01-15	2015-01-16	2015-01-19	2015-01-20	2015-01-21	2015-01-22	2015-01-23	2015-01-26	2015-01-27	2015-01-28	2015-01-29	2015-01-30	2015-02-02	2015-02-03	2015-02-04	2015-02-05	2015-02-06	2015-02-09	2015-02-10	2015-02-11	2015-02-12	2015-02-13	2015-02-16	2015-02-17	2015-02-18	2015-02-19	2015-02-20	2015-02-23	2015-02-24	2015-02-25	2015-02-26	2015-02-27	2015-03-02	2015-03-03	2015-03-04	2015-03-05	2015-03-06	2015-03-09	2015-03-10	2015-03-11	2015-03-12	2015-03-13	2015-03-16	2015-03-17	2015-03-18	2015-03-19	2015-03-20	2015-03-23	2015-03-24	2015-03-25	2015-03-26	2015-03-27	2015-03-30	2015-03-31	2015-04-01	2015-04-02	2015-04-03	2015-04-06	2015-04-07	2015-04-08	2015-04-09	2015-04-10	2015-04-13	2015-04-14	2015-04-15	2015-04-16	2015-04-17	2015-04-20	2015-04-21	2015-04-22	2015-04-23	2015-04-24	2015-04-27	2015-04-28	2015-04-29	2015-04-30	2015-05-01	2015-05-04	2015-05-05	2015-05-06	2015-05-07	2015-05-08	2015-05-11	2015-05-12	2015-05-13	2015-05-14	2015-05-15	2015-05-18	2015-05-19	2015-05-20	2015-05-21	2015-05-22	2015-05-25	2015-05-26	2015-05-27	2015-05-28	2015-05-29	2015-06-01	2015-06-02	2015-06-03	2015-06-04	2015-06-05	2015-06-08	2015-06-09	2015-06-10	2015-06-11	2015-06-12	2015-06-15	2015-06-16	2015-06-17	2015-06-18	2015-06-19	2015-06-22	2015-06-23	2015-06-24	2015-06-25	2015-06-26	2015-06-29	2015-06-30	2015-07-01	2015-07-02	2015-07-03	2015-07-06	2015-07-07	2015-07-08	2015-07-09	2015-07-10	2015-07-13	2015-07-14	2015-07-15	2015-07-16	2015-07-17	2015-07-20	2015-07-21	2015-07-22	2015-07-23	2015-07-24	2015-07-27	2015-07-28	2015-07-29	2015-07-30	2015-07-31	2015-08-03	2015-08-04	2015-08-05	2015-08-06	2015-08-07	2015-08-10	2015-08-11	2015-08-12	2015-08-13	2015-08-14	2015-08-17	2015-08-18	2015-08-19	2015-08-20	2015-08-21	2015-08-24	2015-08-25	2015-08-26	2015-08-27	2015-08-28	2015-08-31	2015-09-01	2015-09-02	2015-09-03	2015-09-04	2015-09-07	2015-09-08	2015-09-09	2015-09-10	2015-09-11	2015-09-14	2015-09-15	2015-09-16	2015-09-17	2015-09-18	2015-09-21	2015-09-22	2015-09-23	2015-09-24	2015-09-25	2015-09-28	2015-09-29	2015-09-30	2015-10-01	2015-10-02	2015-10-05	2015-10-06	2015-10-07	2015-10-08	2015-10-09	2015-10-12	2015-10-13	2015-10-14	2015-10-15	2015-10-16	2015-10-19	2015-10-20	2015-10-21	2015-10-22	2015-10-23	2015-10-26	2015-10-27	2015-10-28	2015-10-29	2015-10-30	2015-11-02	2015-11-03	2015-11-04	2015-11-05	2015-11-06	2015-11-09	2015-11-10	2015-11-11	2015-11-12	2015-11-13	2015-11-16	2015-11-17	2015-11-18	2015-11-19	2015-11-20	2015-11-23	2015-11-24	2015-11-25	2015-11-26	2015-11-27	2015-11-30	2015-12-01	2015-12-02	2015-12-03	2015-12-04	2015-12-07	2015-12-08	2015-12-09	2015-12-10	2015-12-11	2015-12-14	2015-12-15	2015-12-16	2015-12-17	2015-12-18	2015-12-21	2015-12-22	2015-12-23	2015-12-24	2015-12-25	2015-12-28	2015-12-29	2015-12-30	2015-12-31
1	NaT	2015-01-02 16:56:15	2015-01-05 17:20:11	2015-01-06 17:19:05	2015-01-07 16:34:55	2015-01-08 17:08:32	2015-01-09 17:38:29	2015-01-12 16:58:39	2015-01-13 18:02:58	NaT	2015-01-15 17:22:13	2015-01-16 17:35:11	NaT	2015-01-20 16:37:07	2015-01-21 16:55:24	2015-01-22 16:50:47	2015-01-23 17:00:01	NaT	2015-01-27 17:28:22	2015-01-28 17:03:21	2015-01-29 17:18:36	2015-01-30 17:00:25	2015-02-02 16:32:49	2015-02-03 17:35:49	2015-02-04 17:24:56	2015-02-05 17:26:31	2015-02-06 17:21:35	2015-02-09 17:37:50	2015-02-10 17:30:20	2015-02-11 17:30:19	2015-02-12 17:36:42	2015-02-13 16:25:26	2015-02-16 17:50:23	2015-02-17 17:28:06	2015-02-18 18:13:29	NaT	2015-02-20 17:44:52	2015-02-23 17:13:27	2015-02-24 17:24:48	2015-02-25 17:27:37	2015-02-26 17:08:36	2015-02-27 17:21:55	2015-03-02 17:29:08	2015-03-03 16:54:12	2015-03-04 17:50:18	NaT	2015-03-06 17:44:47	2015-03-09 17:53:05	2015-03-10 16:42:53	2015-03-11 16:58:39	2015-03-12 17:15:39	2015-03-13 17:25:55	NaT	2015-03-17 17:00:16	2015-03-18 17:40:13	2015-03-19 17:52:44	2015-03-20 17:47:34	2015-03-23 17:48:18	2015-03-24 17:48:26	2015-03-25 17:08:19	NaT	2015-03-27 17:20:51	2015-03-30 17:33:09	2015-03-31 18:00:07	2015-04-01 17:32:50	2015-04-02 17:24:58	2015-04-03 17:11:46	2015-04-06 16:42:46	2015-04-07 17:55:07	2015-04-08 17:30:12	2015-04-09 17:09:38	2015-04-10 16:53:22	2015-04-13 17:00:23	2015-04-14 17:07:36	2015-04-15 17:23:31	2015-04-16 17:31:32	2015-04-17 17:11:18	2015-04-20 17:45:08	2015-04-21 16:49:13	2015-04-22 17:27:46	2015-04-23 17:32:53	2015-04-24 17:39:25	2015-04-27 17:26:32	2015-04-28 17:50:45	2015-04-29 17:27:45	2015-04-30 17:18:59	NaT	2015-05-04 17:05:30	2015-05-05 17:13:30	2015-05-06 17:16:30	2015-05-07 17:10:33	2015-05-08 17:31:56	NaT	2015-05-12 17:16:58	2015-05-13 17:54:12	2015-05-14 17:44:49	2015-05-15 16:44:33	NaT	2015-05-19 17:09:05	2015-05-20 17:19:49	2015-05-21 17:21:10	2015-05-22 17:27:28	2015-05-25 17:49:48	2015-05-26 17:29:00	2015-05-27 17:34:05	2015-05-28 17:23:52	NaT	NaT	2015-06-02 18:03:51	2015-06-03 17:18:10	2015-06-04 17:26:11	NaT	2015-06-08 17:22:18	NaT	2015-06-10 16:59:04	2015-06-11 17:21:39	2015-06-12 17:39:12	2015-06-15 17:26:02	2015-06-16 17:31:36	2015-06-17 17:17:49	2015-06-18 17:34:32	2015-06-19 17:21:17	2015-06-22 16:59:22	2015-06-23 16:51:41	2015-06-24 17:06:26	2015-06-25 17:37:14	2015-06-26 17:11:06	2015-06-29 17:41:01	2015-06-30 17:45:51	2015-07-01 17:22:27	2015-07-02 17:44:39	2015-07-03 17:09:29	2015-07-06 17:33:57	2015-07-07 17:47:22	2015-07-08 17:26:03	2015-07-09 16:18:10	2015-07-10 17:05:38	2015-07-13 17:23:56	2015-07-14 17:14:19	2015-07-15 17:32:02	2015-07-16 17:39:13	NaT	2015-07-20 17:31:04	2015-07-21 17:03:19	2015-07-22 17:45:13	2015-07-23 16:45:36	2015-07-24 17:03:05	2015-07-27 17:24:48	2015-07-28 17:02:15	2015-07-29 16:57:05	2015-07-30 17:06:20	2015-07-31 17:34:04	2015-08-03 17:00:31	2015-08-04 17:10:18	2015-08-05 17:31:20	2015-08-06 17:27:12	2015-08-07 17:16:59	2015-08-10 17:48:37	2015-08-11 17:40:01	2015-08-12 17:15:47	2015-08-13 17:09:17	2015-08-14 17:08:51	2015-08-17 16:27:43	2015-08-18 18:03:09	2015-08-19 17:09:56	2015-08-20 17:11:05	2015-08-21 17:51:02	2015-08-24 17:37:08	2015-08-25 17:12:59	2015-08-26 17:36:02	2015-08-27 17:57:41	2015-08-28 17:27:04	2015-08-31 17:08:19	NaT	2015-09-02 17:49:13	2015-09-03 17:07:17	2015-09-04 17:42:46	2015-09-07 17:40:58	2015-09-08 17:52:36	2015-09-09 18:00:21	2015-09-10 17:17:02	2015-09-11 17:22:52	2015-09-14 17:07:46	2015-09-15 17:34:11	2015-09-16 17:31:03	NaT	2015-09-18 17:43:14	2015-09-21 17:13:51	2015-09-22 18:14:06	2015-09-23 17:05:53	2015-09-24 17:19:26	2015-09-25 17:43:56	2015-09-28 17:07:25	2015-09-29 17:27:30	2015-09-30 17:14:43	2015-10-01 17:52:44	NaT	2015-10-05 17:03:41	2015-10-06 17:29:15	2015-10-07 16:56:00	2015-10-08 17:08:18	2015-10-09 17:10:00	2015-10-12 17:24:14	NaT	2015-10-14 17:49:02	2015-10-15 17:54:13	2015-10-16 16:40:00	2015-10-19 17:27:58	2015-10-20 17:02:55	NaT	NaT	2015-10-23 17:13:46	2015-10-26 17:35:53	2015-10-27 16:28:13	2015-10-28 17:32:42	2015-10-29 16:57:29	2015-10-30 17:09:54	2015-11-02 16:53:43	2015-11-03 18:04:34	2015-11-04 16:43:40	2015-11-05 18:03:15	2015-11-06 17:15:12	NaT	NaT	NaT	2015-11-12 17:13:17	2015-11-13 16:49:27	2015-11-16 18:03:08	2015-11-17 17:03:06	2015-11-18 17:38:02	2015-11-19 16:46:27	2015-11-20 17:58:40	2015-11-23 17:13:22	2015-11-24 17:37:21	2015-11-25 17:26:51	2015-11-26 17:44:49	2015-11-27 17:30:02	2015-11-30 17:05:11	2015-12-01 16:53:21	2015-12-02 17:32:24	2015-12-03 17:40:59	2015-12-04 17:02:22	2015-12-07 16:21:37	2015-12-08 17:51:23	2015-12-09 17:48:46	2015-12-10 16:52:14	2015-12-11 17:25:56	2015-12-14 17:35:53	NaT	2015-12-16 17:54:26	NaT	NaT	2015-12-21 17:15:50	2015-12-22 17:27:51	2015-12-23 16:44:44	2015-12-24 17:47:22	NaT	2015-12-28 18:00:07	2015-12-29 17:22:30	2015-12-30 17:40:56	2015-12-31 17:17:33
2	NaT	2015-01-02 18:22:17	2015-01-05 17:48:22	NaT	2015-01-07 17:09:06	2015-01-08 17:34:04	2015-01-09 16:52:29	2015-01-12 17:36:48	2015-01-13 18:00:13	NaT	2015-01-15 17:14:44	2015-01-16 17:40:57	2015-01-19 17:58:22	2015-01-20 17:05:13	2015-01-21 17:41:05	2015-01-22 17:26:26	2015-01-23 17:06:50	NaT	2015-01-27 17:35:50	2015-01-28 17:19:48	2015-01-29 17:07:38	2015-01-30 16:53:22	2015-02-02 17:45:18	2015-02-03 17:33:42	2015-02-04 18:04:20	2015-02-05 17:43:25	2015-02-06 17:06:42	NaT	2015-02-10 18:12:17	2015-02-11 17:18:36	2015-02-12 18:08:01	2015-02-13 17:19:25	2015-02-16 17:46:09	2015-02-17 17:09:30	2015-02-18 17:48:56	2015-02-19 18:06:35	2015-02-20 17:31:45	2015-02-23 17:57:18	2015-02-24 17:32:22	2015-02-25 17:43:47	2015-02-26 17:49:55	2015-02-27 18:38:54	2015-03-02 17:36:37	2015-03-03 18:12:57	2015-03-04 17:52:38	NaT	2015-03-06 17:21:33	2015-03-09 18:10:21	2015-03-10 17:14:06	2015-03-11 17:56:14	2015-03-12 17:30:53	2015-03-13 17:48:25	2015-03-16 17:08:38	2015-03-17 16:58:02	2015-03-18 17:16:35	2015-03-19 17:28:42	2015-03-20 17:31:55	2015-03-23 17:58:55	NaT	2015-03-25 17:22:19	2015-03-26 17:48:10	2015-03-27 17:49:22	2015-03-30 17:28:31	2015-03-31 18:28:47	2015-04-01 17:30:06	2015-04-02 17:39:09	2015-04-03 18:07:24	2015-04-06 17:40:31	2015-04-07 17:50:46	2015-04-08 17:09:41	2015-04-09 17:07:38	2015-04-10 17:43:12	2015-04-13 17:45:20	2015-04-14 18:00:46	2015-04-15 17:35:11	2015-04-16 17:21:42	2015-04-17 17:24:55	2015-04-20 17:51:08	2015-04-21 18:49:53	2015-04-22 17:40:46	2015-04-23 18:04:23	2015-04-24 17:42:16	2015-04-27 17:12:05	2015-04-28 17:29:15	NaT	2015-04-30 18:18:58	NaT	2015-05-04 17:41:29	2015-05-05 18:08:25	2015-05-06 17:37:33	2015-05-07 17:26:07	2015-05-08 17:07:25	2015-05-11 17:30:04	2015-05-12 17:39:57	2015-05-13 17:35:24	NaT	2015-05-15 17:06:54	NaT	2015-05-19 17:53:01	2015-05-20 17:30:15	2015-05-21 17:25:40	2015-05-22 18:39:12	2015-05-25 17:50:50	2015-05-26 17:49:25	2015-05-27 17:51:25	2015-05-28 17:11:38	2015-05-29 17:55:55	2015-06-01 18:01:11	2015-06-02 17:34:55	2015-06-03 17:58:25	2015-06-04 16:27:03	2015-06-05 17:46:19	2015-06-08 17:20:20	2015-06-09 17:24:55	2015-06-10 17:44:36	2015-06-11 17:53:52	NaT	2015-06-15 17:48:03	2015-06-16 18:01:24	2015-06-17 18:05:55	2015-06-18 17:48:28	2015-06-19 17:55:56	2015-06-22 17:48:27	2015-06-23 17:46:50	2015-06-24 17:59:00	2015-06-25 18:09:18	2015-06-26 17:35:47	2015-06-29 18:00:33	2015-06-30 17:20:12	2015-07-01 17:27:32	2015-07-02 17:52:49	2015-07-03 18:08:39	2015-07-06 17:53:47	2015-07-07 18:20:24	2015-07-08 17:39:41	2015-07-09 17:28:26	2015-07-10 18:12:57	NaT	2015-07-14 18:06:32	2015-07-15 17:25:39	2015-07-16 18:13:48	NaT	2015-07-20 17:47:07	2015-07-21 18:01:49	2015-07-22 17:20:40	2015-07-23 17:36:14	2015-07-24 18:07:05	NaT	2015-07-28 18:08:31	2015-07-29 17:54:49	2015-07-30 17:19:50	2015-07-31 17:30:49	2015-08-03 17:44:58	2015-08-04 18:08:25	2015-08-05 17:27:32	2015-08-06 18:48:44	2015-08-07 17:47:53	2015-08-10 17:24:08	2015-08-11 17:09:55	2015-08-12 17:13:38	2015-08-13 17:54:56	2015-08-14 17:29:11	2015-08-17 18:04:06	2015-08-18 17:03:21	2015-08-19 17:36:39	2015-08-20 17:56:23	2015-08-21 17:38:55	2015-08-24 17:05:20	2015-08-25 17:11:02	2015-08-26 17:44:47	2015-08-27 18:04:39	2015-08-28 17:24:55	2015-08-31 18:13:22	2015-09-01 17:18:16	2015-09-02 17:26:57	2015-09-03 17:50:40	2015-09-04 18:21:48	2015-09-07 18:10:09	NaT	2015-09-09 17:52:26	2015-09-10 18:22:09	2015-09-11 17:27:25	2015-09-14 17:10:53	2015-09-15 16:50:45	2015-09-16 17:16:37	NaT	2015-09-18 17:51:23	2015-09-21 17:45:44	2015-09-22 16:51:17	2015-09-23 17:55:03	2015-09-24 18:07:54	2015-09-25 17:45:34	2015-09-28 17:52:52	2015-09-29 18:02:18	2015-09-30 18:15:14	2015-10-01 17:33:53	NaT	2015-10-05 18:08:24	2015-10-06 17:12:33	2015-10-07 18:07:16	2015-10-08 18:19:06	2015-10-09 17:18:33	2015-10-12 17:16:51	2015-10-13 18:32:48	2015-10-14 17:45:04	NaT	2015-10-16 17:58:11	2015-10-19 18:00:41	2015-10-20 17:13:28	2015-10-21 16:51:56	2015-10-22 18:30:26	2015-10-23 16:37:09	2015-10-26 17:58:41	2015-10-27 18:23:56	2015-10-28 17:20:29	2015-10-29 17:44:08	2015-10-30 17:32:48	2015-11-02 17:29:17	2015-11-03 17:18:27	2015-11-04 17:54:32	2015-11-05 17:11:57	2015-11-06 17:28:38	NaT	NaT	NaT	2015-11-12 17:34:03	2015-11-13 17:38:25	2015-11-16 18:37:03	2015-11-17 17:26:09	2015-11-18 18:06:23	NaT	2015-11-20 17:52:48	2015-11-23 17:32:43	2015-11-24 17:01:00	2015-11-25 17:14:56	2015-11-26 18:28:44	2015-11-27 18:12:27	2015-11-30 17:18:40	2015-12-01 17:21:07	2015-12-02 18:02:46	2015-12-03 18:08:00	2015-12-04 18:01:03	2015-12-07 17:06:37	2015-12-08 17:44:18	2015-12-09 17:47:47	2015-12-10 17:55:23	2015-12-11 17:42:47	2015-12-14 17:32:11	2015-12-15 17:56:25	2015-12-16 18:16:37	2015-12-17 17:10:50	2015-12-18 18:31:28	2015-12-21 17:34:16	2015-12-22 18:16:35	2015-12-23 17:38:18	NaT	NaT	2015-12-28 17:08:38	2015-12-29 17:54:46	2015-12-30 18:31:35	2015-12-31 17:40:58
3	NaT	2015-01-02 16:59:14	2015-01-05 17:06:46	2015-01-06 16:38:32	2015-01-07 16:33:21	2015-01-08 17:24:22	2015-01-09 16:57:30	2015-01-12 17:28:54	2015-01-13 17:21:25	NaT	2015-01-15 17:21:29	2015-01-16 17:18:13	2015-01-19 16:52:13	2015-01-20 16:52:23	2015-01-21 17:17:50	2015-01-22 17:27:54	2015-01-23 17:11:52	NaT	2015-01-27 17:22:27	2015-01-28 16:24:04	2015-01-29 17:20:07	2015-01-30 17:16:03	2015-02-02 16:59:01	2015-02-03 15:58:24	2015-02-04 17:25:54	2015-02-05 16:29:41	2015-02-06 17:18:15	2015-02-09 16:48:18	2015-02-10 17:15:49	2015-02-11 16:49:22	2015-02-12 16:22:31	2015-02-13 17:41:15	2015-02-16 17:20:05	2015-02-17 16:46:01	2015-02-18 17:19:08	2015-02-19 16:44:56	2015-02-20 17:14:02	2015-02-23 17:59:19	2015-02-24 17:08:34	2015-02-25 16:55:31	2015-02-26 17:34:33	2015-02-27 16:48:44	2015-03-02 17:32:13	2015-03-03 17:11:01	2015-03-04 17:26:45	NaT	2015-03-06 16:35:05	2015-03-09 17:08:34	2015-03-10 16:38:33	2015-03-11 17:31:26	2015-03-12 17:13:00	2015-03-13 16:25:40	2015-03-16 16:53:08	2015-03-17 17:07:58	2015-03-18 17:39:10	2015-03-19 16:27:24	NaT	2015-03-23 16:50:31	2015-03-24 17:12:39	2015-03-25 16:42:17	2015-03-26 17:02:08	NaT	2015-03-30 16:37:47	2015-03-31 17:29:39	2015-04-01 16:47:25	2015-04-02 17:14:02	2015-04-03 16:46:36	2015-04-06 16:27:34	2015-04-07 17:27:19	2015-04-08 17:36:18	2015-04-09 17:45:16	2015-04-10 17:13:27	2015-04-13 17:30:51	2015-04-14 16:43:49	2015-04-15 17:23:07	2015-04-16 16:49:51	2015-04-17 17:52:50	2015-04-20 17:03:14	2015-04-21 17:15:37	2015-04-22 17:23:28	NaT	2015-04-24 17:05:07	2015-04-27 16:29:39	2015-04-28 17:22:20	2015-04-29 16:52:17	2015-04-30 16:43:32	NaT	2015-05-04 16:42:30	2015-05-05 16:13:39	2015-05-06 17:27:27	2015-05-07 16:41:59	2015-05-08 17:13:18	2015-05-11 16:49:00	2015-05-12 16:45:55	2015-05-13 16:40:15	2015-05-14 17:01:56	2015-05-15 16:25:36	2015-05-18 17:17:40	2015-05-19 17:05:17	2015-05-20 17:06:32	2015-05-21 16:44:37	2015-05-22 16:54:06	2015-05-25 17:23:42	2015-05-26 16:44:02	2015-05-27 17:23:12	2015-05-28 16:31:51	2015-05-29 16:53:00	2015-06-01 16:44:52	2015-06-02 17:09:28	2015-06-03 17:21:49	2015-06-04 16:21:03	2015-06-05 16:24:55	2015-06-08 17:09:46	2015-06-09 16:46:00	2015-06-10 17:35:00	2015-06-11 17:20:01	2015-06-12 17:18:04	2015-06-15 16:58:07	2015-06-16 16:27:56	2015-06-17 16:50:32	2015-06-18 17:16:36	2015-06-19 16:43:47	2015-06-22 16:29:10	2015-06-23 16:53:24	NaT	2015-06-25 16:44:56	2015-06-26 17:05:33	2015-06-29 16:19:27	2015-06-30 16:49:09	2015-07-01 16:50:55	2015-07-02 17:17:35	2015-07-03 16:36:11	2015-07-06 18:00:41	2015-07-07 17:36:36	2015-07-08 16:47:57	2015-07-09 18:07:51	2015-07-10 17:01:41	2015-07-13 16:20:14	2015-07-14 17:18:35	2015-07-15 16:54:35	2015-07-16 16:56:24	NaT	2015-07-20 17:07:52	2015-07-21 16:51:57	2015-07-22 16:28:59	2015-07-23 17:23:36	2015-07-24 16:49:58	2015-07-27 17:18:46	2015-07-28 17:28:39	2015-07-29 17:53:35	2015-07-30 17:25:52	2015-07-31 16:44:55	2015-08-03 16:52:05	2015-08-04 16:25:27	NaT	2015-08-06 16:53:15	2015-08-07 16:31:42	2015-08-10 17:06:02	2015-08-11 16:36:01	2015-08-12 17:28:54	2015-08-13 16:57:54	2015-08-14 16:54:16	2015-08-17 16:53:27	2015-08-18 17:15:15	2015-08-19 17:08:09	2015-08-20 16:53:58	2015-08-21 17:29:32	2015-08-24 17:01:36	2015-08-25 16:52:06	2015-08-26 17:06:17	2015-08-27 16:05:12	2015-08-28 16:46:21	2015-08-31 16:29:00	2015-09-01 17:12:34	2015-09-02 17:06:39	2015-09-03 17:14:37	2015-09-04 17:16:44	2015-09-07 16:17:32	2015-09-08 16:46:52	2015-09-09 16:33:08	2015-09-10 17:22:21	2015-09-11 16:32:47	2015-09-14 17:49:44	2015-09-15 16:58:26	2015-09-16 16:51:35	NaT	2015-09-18 16:53:29	2015-09-21 16:42:32	2015-09-22 16:28:40	2015-09-23 17:06:45	2015-09-24 17:33:41	2015-09-25 16:39:34	2015-09-28 17:44:11	2015-09-29 17:52:11	2015-09-30 16:56:37	2015-10-01 17:16:00	NaT	2015-10-05 17:11:32	2015-10-06 17:27:11	2015-10-07 17:19:27	2015-10-08 16:42:29	2015-10-09 16:55:42	2015-10-12 17:19:20	2015-10-13 17:03:46	2015-10-14 17:25:43	2015-10-15 16:59:34	2015-10-16 16:42:49	2015-10-19 16:36:56	2015-10-20 17:00:27	2015-10-21 17:52:36	2015-10-22 17:12:08	2015-10-23 17:00:44	2015-10-26 17:44:21	2015-10-27 17:20:34	2015-10-28 16:22:30	2015-10-29 16:35:41	2015-10-30 16:29:34	2015-11-02 17:35:43	2015-11-03 16:55:12	2015-11-04 17:01:26	2015-11-05 17:04:42	2015-11-06 16:39:49	NaT	NaT	NaT	2015-11-12 17:36:44	2015-11-13 16:43:22	2015-11-16 16:51:03	2015-11-17 17:09:13	2015-11-18 17:28:22	2015-11-19 16:20:40	2015-11-20 17:40:18	2015-11-23 16:58:39	2015-11-24 16:33:43	2015-11-25 17:20:08	2015-11-26 17:34:28	NaT	2015-11-30 17:00:13	2015-12-01 16:59:05	2015-12-02 16:54:49	2015-12-03 17:04:26	2015-12-04 17:10:47	2015-12-07 17:09:04	2015-12-08 17:28:44	2015-12-09 17:49:34	NaT	2015-12-11 17:01:53	2015-12-14 16:48:18	2015-12-15 16:39:52	2015-12-16 16:42:44	2015-12-17 17:06:23	2015-12-18 17:02:23	2015-12-21 17:20:17	2015-12-22 16:32:50	2015-12-23 16:59:43	2015-12-24 16:58:25	NaT	2015-12-28 16:43:31	2015-12-29 17:09:56	2015-12-30 17:06:25	2015-12-31 17:15:50
4	NaT	2015-01-02 17:25:24	2015-01-05 17:14:03	2015-01-06 17:07:42	2015-01-07 16:32:40	2015-01-08 16:53:11	2015-01-09 17:19:47	2015-01-12 17:13:37	2015-01-13 17:11:45	NaT	2015-01-15 16:53:26	2015-01-16 16:52:34	2015-01-19 16:14:18	2015-01-20 17:39:50	2015-01-21 16:46:51	2015-01-22 16:51:48	2015-01-23 17:05:41	NaT	2015-01-27 17:03:48	2015-01-28 17:33:22	2015-01-29 16:44:01	2015-01-30 17:09:42	2015-02-02 17:18:12	2015-02-03 17:27:41	2015-02-04 17:30:22	2015-02-05 17:11:44	2015-02-06 16:33:04	2015-02-09 17:16:29	NaT	2015-02-11 17:04:11	2015-02-12 17:22:16	2015-02-13 17:22:54	2015-02-16 17:11:28	2015-02-17 16:59:20	2015-02-18 16:31:43	2015-02-19 17:15:20	2015-02-20 16:43:41	2015-02-23 16:44:17	2015-02-24 17:30:51	2015-02-25 16:02:49	2015-02-26 17:09:34	2015-02-27 16:59:05	NaT	2015-03-03 17:39:36	2015-03-04 16:26:53	NaT	NaT	2015-03-09 17:15:18	2015-03-10 16:53:12	2015-03-11 17:27:00	2015-03-12 17:18:43	2015-03-13 16:42:00	2015-03-16 16:39:28	2015-03-17 17:04:50	2015-03-18 17:31:49	2015-03-19 17:27:02	2015-03-20 17:35:10	2015-03-23 17:18:20	2015-03-24 17:22:01	2015-03-25 17:20:54	2015-03-26 18:10:16	NaT	2015-03-30 17:13:45	2015-03-31 17:35:52	2015-04-01 17:19:06	2015-04-02 16:32:12	2015-04-03 16:59:23	2015-04-06 17:23:43	2015-04-07 17:39:00	2015-04-08 17:39:25	2015-04-09 17:15:13	2015-04-10 17:21:15	2015-04-13 16:22:01	NaT	2015-04-15 16:42:43	2015-04-16 16:50:43	2015-04-17 17:03:14	2015-04-20 17:10:10	2015-04-21 17:18:07	2015-04-22 17:06:08	2015-04-23 17:15:23	2015-04-24 17:24:56	2015-04-27 17:16:14	2015-04-28 16:19:59	2015-04-29 17:04:12	2015-04-30 17:09:25	NaT	2015-05-04 17:59:06	2015-05-05 16:44:22	2015-05-06 18:08:51	2015-05-07 17:13:02	2015-05-08 17:43:42	2015-05-11 17:31:57	2015-05-12 16:53:20	2015-05-13 17:23:44	2015-05-14 17:01:21	2015-05-15 16:36:35	2015-05-18 16:22:37	2015-05-19 17:23:25	2015-05-20 16:42:27	2015-05-21 16:46:33	NaT	2015-05-25 17:08:33	2015-05-26 17:33:07	2015-05-27 17:55:27	2015-05-28 17:25:42	2015-05-29 17:19:29	2015-06-01 17:12:33	2015-06-02 17:42:17	2015-06-03 17:11:39	2015-06-04 17:33:35	2015-06-05 16:32:56	2015-06-08 17:06:31	2015-06-09 17:31:47	2015-06-10 17:24:30	2015-06-11 17:25:59	2015-06-12 17:24:49	2015-06-15 17:31:18	2015-06-16 16:51:27	2015-06-17 16:57:41	2015-06-18 17:24:34	2015-06-19 16:52:14	2015-06-22 17:44:28	2015-06-23 16:33:07	2015-06-24 17:36:56	2015-06-25 16:44:23	2015-06-26 17:01:52	2015-06-29 17:12:10	2015-06-30 16:54:35	2015-07-01 16:13:03	2015-07-02 17:05:36	2015-07-03 17:23:50	2015-07-06 17:12:57	2015-07-07 17:57:50	2015-07-08 17:10:27	2015-07-09 17:19:00	2015-07-10 17:57:38	2015-07-13 17:28:43	2015-07-14 17:58:30	2015-07-15 17:50:46	2015-07-16 17:05:11	NaT	2015-07-20 16:52:41	2015-07-21 16:39:59	NaT	2015-07-23 17:45:50	2015-07-24 16:50:37	2015-07-27 17:21:13	2015-07-28 16:24:54	2015-07-29 17:42:13	2015-07-30 17:14:45	2015-07-31 17:04:26	2015-08-03 17:50:27	2015-08-04 16:55:41	NaT	2015-08-06 17:00:50	2015-08-07 17:12:50	2015-08-10 17:42:07	2015-08-11 17:39:24	2015-08-12 16:45:38	2015-08-13 16:36:57	2015-08-14 17:02:53	2015-08-17 17:17:49	2015-08-18 17:48:39	2015-08-19 17:17:00	2015-08-20 17:14:47	2015-08-21 16:45:06	NaT	2015-08-25 17:02:23	2015-08-26 16:59:12	2015-08-27 16:46:28	NaT	2015-08-31 16:49:45	2015-09-01 17:08:51	2015-09-02 16:28:03	2015-09-03 17:14:09	2015-09-04 17:17:52	2015-09-07 17:26:41	2015-09-08 17:37:28	2015-09-09 17:39:07	2015-09-10 16:36:34	2015-09-11 18:06:15	2015-09-14 17:36:42	2015-09-15 16:39:57	2015-09-16 16:42:51	NaT	2015-09-18 17:47:54	2015-09-21 17:15:09	2015-09-22 16:57:27	2015-09-23 16:45:31	2015-09-24 17:49:36	NaT	2015-09-28 17:02:26	2015-09-29 17:00:39	2015-09-30 17:21:44	2015-10-01 16:47:16	NaT	NaT	2015-10-06 17:03:32	2015-10-07 17:32:56	2015-10-08 17:00:37	2015-10-09 17:05:07	2015-10-12 17:34:50	2015-10-13 17:25:05	2015-10-14 16:49:13	2015-10-15 16:53:25	2015-10-16 16:44:32	2015-10-19 17:03:32	2015-10-20 16:41:21	2015-10-21 17:33:33	2015-10-22 16:37:16	2015-10-23 17:01:41	2015-10-26 17:25:23	2015-10-27 16:35:01	2015-10-28 16:42:00	2015-10-29 16:57:12	NaT	2015-11-02 17:04:40	2015-11-03 17:44:36	2015-11-04 17:02:18	2015-11-05 17:38:56	NaT	NaT	NaT	NaT	2015-11-12 17:44:45	2015-11-13 16:21:17	2015-11-16 16:43:22	2015-11-17 16:56:08	2015-11-18 17:19:37	2015-11-19 18:03:01	2015-11-20 17:33:33	2015-11-23 17:03:38	2015-11-24 17:49:18	2015-11-25 16:41:49	2015-11-26 17:18:08	2015-11-27 17:06:19	2015-11-30 17:08:57	2015-12-01 17:09:31	2015-12-02 17:13:35	2015-12-03 16:36:51	2015-12-04 16:47:21	2015-12-07 17:24:39	2015-12-08 17:21:05	2015-12-09 17:17:58	2015-12-10 17:10:02	2015-12-11 16:44:02	2015-12-14 17:23:57	2015-12-15 16:37:15	2015-12-16 17:40:56	2015-12-17 17:21:57	2015-12-18 17:55:23	2015-12-21 16:49:09	2015-12-22 17:24:00	2015-12-23 17:36:35	2015-12-24 16:48:21	NaT	2015-12-28 17:19:34	2015-12-29 16:58:16	2015-12-30 17:40:11	2015-12-31 17:09:14
5	NaT	2015-01-02 18:31:37	2015-01-05 17:49:15	2015-01-06 17:26:25	2015-01-07 17:37:59	2015-01-08 17:59:28	2015-01-09 17:44:08	2015-01-12 18:51:21	2015-01-13 18:14:58	NaT	2015-01-15 18:21:48	2015-01-16 18:28:03	NaT	2015-01-20 17:59:24	2015-01-21 18:41:38	2015-01-22 18:27:37	2015-01-23 16:53:11	NaT	2015-01-27 17:52:43	2015-01-28 17:40:46	2015-01-29 18:16:26	2015-01-30 18:26:33	2015-02-02 17:53:21	2015-02-03 17:57:43	2015-02-04 18:03:13	2015-02-05 18:07:43	2015-02-06 17:38:14	2015-02-09 18:26:28	2015-02-10 17:24:32	2015-02-11 18:01:25	2015-02-12 17:42:32	2015-02-13 18:28:09	2015-02-16 17:51:18	2015-02-17 18:03:31	2015-02-18 17:43:37	2015-02-19 17:29:07	2015-02-20 18:16:03	2015-02-23 18:13:52	2015-02-24 17:58:08	2015-02-25 17:57:18	2015-02-26 17:40:40	2015-02-27 18:05:49	2015-03-02 18:41:28	2015-03-03 17:39:12	2015-03-04 18:04:54	NaT	2015-03-06 18:04:19	2015-03-09 18:18:21	2015-03-10 18:06:41	2015-03-11 17:56:40	2015-03-12 17:39:04	2015-03-13 18:15:55	2015-03-16 17:46:49	2015-03-17 18:13:29	2015-03-18 17:55:43	2015-03-19 17:51:13	2015-03-20 17:32:26	2015-03-23 17:53:16	2015-03-24 17:18:09	2015-03-25 18:07:26	2015-03-26 17:53:06	2015-03-27 17:41:37	2015-03-30 17:41:26	2015-03-31 18:16:42	2015-04-01 17:48:19	2015-04-02 18:00:21	2015-04-03 17:41:24	2015-04-06 18:26:22	2015-04-07 17:51:27	2015-04-08 17:43:22	2015-04-09 18:06:31	2015-04-10 18:06:04	2015-04-13 17:51:39	2015-04-14 18:29:43	2015-04-15 18:02:54	2015-04-16 17:59:12	2015-04-17 17:55:12	2015-04-20 18:14:32	NaT	2015-04-22 17:38:59	2015-04-23 17:50:36	2015-04-24 18:08:50	2015-04-27 18:58:57	2015-04-28 17:10:52	2015-04-29 18:00:03	2015-04-30 18:07:51	NaT	2015-05-04 17:36:37	2015-05-05 18:29:57	2015-05-06 19:01:52	2015-05-07 17:27:09	2015-05-08 18:00:47	2015-05-11 17:30:39	2015-05-12 18:24:49	2015-05-13 17:38:22	2015-05-14 18:05:41	2015-05-15 17:15:55	2015-05-18 17:39:56	2015-05-19 18:00:22	2015-05-20 18:17:20	2015-05-21 17:37:11	2015-05-22 18:23:13	2015-05-25 19:05:36	2015-05-26 18:14:29	2015-05-27 18:03:27	2015-05-28 17:36:50	2015-05-29 18:00:28	2015-06-01 18:26:09	2015-06-02 17:55:32	2015-06-03 18:16:53	2015-06-04 17:24:37	2015-06-05 18:01:10	2015-06-08 18:04:36	2015-06-09 18:25:23	2015-06-10 18:07:35	NaT	2015-06-12 18:43:31	2015-06-15 17:52:52	2015-06-16 18:31:37	2015-06-17 18:08:18	2015-06-18 18:42:59	2015-06-19 17:23:54	2015-06-22 18:46:28	2015-06-23 17:40:27	2015-06-24 17:45:55	2015-06-25 17:53:28	2015-06-26 17:44:16	2015-06-29 18:05:00	2015-06-30 18:10:45	2015-07-01 17:31:06	2015-07-02 17:23:40	2015-07-03 17:43:59	2015-07-06 17:11:03	2015-07-07 18:19:10	2015-07-08 17:36:00	2015-07-09 18:43:20	2015-07-10 18:21:59	2015-07-13 17:56:12	2015-07-14 17:26:34	2015-07-15 17:53:49	2015-07-16 17:22:12	NaT	2015-07-20 18:06:55	2015-07-21 18:01:34	2015-07-22 17:40:42	2015-07-23 17:55:48	2015-07-24 17:50:56	2015-07-27 18:23:29	2015-07-28 18:21:29	2015-07-29 18:35:09	2015-07-30 18:32:28	2015-07-31 17:50:13	2015-08-03 18:07:57	2015-08-04 18:06:41	2015-08-05 17:25:16	2015-08-06 17:32:20	2015-08-07 17:36:27	2015-08-10 18:05:13	2015-08-11 18:33:12	NaT	2015-08-13 18:29:03	2015-08-14 17:53:07	2015-08-17 18:31:46	2015-08-18 17:28:23	2015-08-19 18:01:59	2015-08-20 17:34:12	2015-08-21 17:55:17	2015-08-24 18:14:19	2015-08-25 18:50:22	2015-08-26 17:48:10	2015-08-27 17:47:07	2015-08-28 17:37:21	2015-08-31 17:38:06	2015-09-01 17:28:46	2015-09-02 18:37:08	2015-09-03 19:22:01	2015-09-04 18:11:10	2015-09-07 17:35:38	2015-09-08 18:10:45	2015-09-09 17:50:46	2015-09-10 18:06:16	2015-09-11 17:27:08	2015-09-14 17:57:45	2015-09-15 17:31:24	2015-09-16 17:42:22	NaT	2015-09-18 17:20:26	2015-09-21 17:38:34	2015-09-22 18:04:31	2015-09-23 18:02:25	2015-09-24 18:01:54	2015-09-25 18:19:49	2015-09-28 18:09:08	2015-09-29 18:07:01	2015-09-30 17:51:17	2015-10-01 17:37:41	NaT	2015-10-05 18:31:59	2015-10-06 17:42:05	2015-10-07 17:28:47	2015-10-08 17:51:33	2015-10-09 17:17:12	2015-10-12 18:27:44	2015-10-13 17:41:27	2015-10-14 17:58:58	2015-10-15 17:56:00	2015-10-16 17:47:56	2015-10-19 17:58:30	2015-10-20 18:24:21	2015-10-21 17:59:41	2015-10-22 18:14:04	2015-10-23 18:26:48	2015-10-26 17:42:45	2015-10-27 18:11:11	2015-10-28 18:04:54	2015-10-29 18:52:40	2015-10-30 17:29:23	2015-11-02 18:45:59	2015-11-03 17:45:51	2015-11-04 18:12:50	2015-11-05 18:22:40	2015-11-06 18:09:24	NaT	NaT	NaT	2015-11-12 18:01:24	2015-11-13 17:47:07	2015-11-16 18:13:04	2015-11-17 17:25:29	2015-11-18 18:02:00	2015-11-19 17:43:56	2015-11-20 18:32:04	2015-11-23 18:38:54	2015-11-24 18:28:51	2015-11-25 17:55:41	2015-11-26 17:32:31	2015-11-27 17:58:08	2015-11-30 18:26:15	2015-12-01 18:07:48	2015-12-02 17:02:52	2015-12-03 17:28:55	2015-12-04 17:47:17	2015-12-07 18:07:48	2015-12-08 17:50:08	2015-12-09 17:53:44	2015-12-10 18:14:09	2015-12-11 19:08:11	2015-12-14 17:55:40	2015-12-15 18:07:30	2015-12-16 18:17:11	2015-12-17 18:05:47	2015-12-18 17:52:48	2015-12-21 17:43:35	2015-12-22 18:07:57	2015-12-23 18:00:49	2015-12-24 17:59:22	NaT	2015-12-28 17:44:59	2015-12-29 18:47:00	2015-12-30 17:15:33	2015-12-31 17:42:14

	2015-01-02	2015-01-05	2015-01-06	2015-01-07	2015-01-08	2015-01-09	2015-01-12	2015-01-13	2015-01-15	2015-01-16	2015-01-19	2015-01-20	2015-01-21	2015-01-22	2015-01-23	2015-01-27	2015-01-28	2015-01-29	2015-01-30	2015-02-02	2015-02-03	2015-02-04	2015-02-05	2015-02-06	2015-02-09	2015-02-10	2015-02-11	2015-02-12	2015-02-13	2015-02-16	2015-02-17	2015-02-18	2015-02-19	2015-02-20	2015-02-23	2015-02-24	2015-02-25	2015-02-26	2015-02-27	2015-03-02	2015-03-03	2015-03-04	2015-03-06	2015-03-09	2015-03-10	2015-03-11	2015-03-12	2015-03-13	2015-03-16	2015-03-17	2015-03-18	2015-03-19	2015-03-20	2015-03-23	2015-03-24	2015-03-25	2015-03-26	2015-03-27	2015-03-30	2015-03-31	2015-04-01	2015-04-02	2015-04-03	2015-04-06	2015-04-07	2015-04-08	2015-04-09	2015-04-10	2015-04-13	2015-04-14	2015-04-15	2015-04-16	2015-04-17	2015-04-20	2015-04-21	2015-04-22	2015-04-23	2015-04-24	2015-04-27	2015-04-28	2015-04-29	2015-04-30	2015-05-04	2015-05-05	2015-05-06	2015-05-07	2015-05-08	2015-05-11	2015-05-12	2015-05-13	2015-05-14	2015-05-15	2015-05-18	2015-05-19	2015-05-20	2015-05-21	2015-05-22	2015-05-25	2015-05-26	2015-05-27	2015-05-28	2015-05-29	2015-06-01	2015-06-02	2015-06-03	2015-06-04	2015-06-05	2015-06-08	2015-06-09	2015-06-10	2015-06-11	2015-06-12	2015-06-15	2015-06-16	2015-06-17	2015-06-18	2015-06-19	2015-06-22	2015-06-23	2015-06-24	2015-06-25	2015-06-26	2015-06-29	2015-06-30	2015-07-01	2015-07-02	2015-07-03	2015-07-06	2015-07-07	2015-07-08	2015-07-09	2015-07-10	2015-07-13	2015-07-14	2015-07-15	2015-07-16	2015-07-20	2015-07-21	2015-07-22	2015-07-23	2015-07-24	2015-07-27	2015-07-28	2015-07-29	2015-07-30	2015-07-31	2015-08-03	2015-08-04	2015-08-05	2015-08-06	2015-08-07	2015-08-10	2015-08-11	2015-08-12	2015-08-13	2015-08-14	2015-08-17	2015-08-18	2015-08-19	2015-08-20	2015-08-21	2015-08-24	2015-08-25	2015-08-26	2015-08-27	2015-08-28	2015-08-31	2015-09-01	2015-09-02	2015-09-03	2015-09-04	2015-09-07	2015-09-08	2015-09-09	2015-09-10	2015-09-11	2015-09-14	2015-09-15	2015-09-16	2015-09-18	2015-09-21	2015-09-22	2015-09-23	2015-09-24	2015-09-25	2015-09-28	2015-09-29	2015-09-30	2015-10-01	2015-10-05	2015-10-06	2015-10-07	2015-10-08	2015-10-09	2015-10-12	2015-10-13	2015-10-14	2015-10-15	2015-10-16	2015-10-19	2015-10-20	2015-10-21	2015-10-22	2015-10-23	2015-10-26	2015-10-27	2015-10-28	2015-10-29	2015-10-30	2015-11-02	2015-11-03	2015-11-04	2015-11-05	2015-11-06	2015-11-12	2015-11-13	2015-11-16	2015-11-17	2015-11-18	2015-11-19	2015-11-20	2015-11-23	2015-11-24	2015-11-25	2015-11-26	2015-11-27	2015-11-30	2015-12-01	2015-12-02	2015-12-03	2015-12-04	2015-12-07	2015-12-08	2015-12-09	2015-12-10	2015-12-11	2015-12-14	2015-12-15	2015-12-16	2015-12-17	2015-12-18	2015-12-21	2015-12-22	2015-12-23	2015-12-24	2015-12-28	2015-12-29	2015-12-30	2015-12-31
1	25,950.000	25,883.000	26,679.000	25,224.000	26,243.000	26,944.000	26,146.000	28,192.000	26,449.000	26,163.000	0.000	24,393.000	25,542.000	25,382.000	27,377.000	27,465.000	25,628.000	26,689.000	24,659.000	24,846.000	25,931.000	27,379.000	27,235.000	26,892.000	27,365.000	26,162.000	25,895.000	26,767.000	25,939.000	27,381.000	26,698.000	28,223.000	0.000	28,196.000	26,788.000	26,010.000	27,301.000	25,923.000	26,589.000	25,765.000	24,335.000	27,880.000	28,134.000	26,671.000	24,923.000	25,780.000	25,488.000	26,317.000	0.000	24,894.000	25,912.000	28,252.000	25,785.000	27,419.000	26,107.000	26,804.000	0.000	27,201.000	26,485.000	28,314.000	26,413.000	27,571.000	25,876.000	25,347.000	27,504.000	26,738.000	28,091.000	25,617.000	26,453.000	25,728.000	26,855.000	27,925.000	26,225.000	27,703.000	25,112.000	27,090.000	26,411.000	27,225.000	26,071.000	28,401.000	27,690.000	27,029.000	26,678.000	26,311.000	26,844.000	25,426.000	27,414.000	0.000	26,801.000	27,009.000	28,446.000	24,541.000	0.000	26,399.000	26,350.000	26,875.000	25,664.000	27,263.000	25,919.000	28,360.000	26,812.000	0.000	0.000	27,782.000	27,051.000	25,351.000	0.000	25,462.000	0.000	25,471.000	27,270.000	26,717.000	27,343.000	27,152.000	27,094.000	27,077.000	26,096.000	25,842.000	24,886.000	25,606.000	27,913.000	25,388.000	27,582.000	26,291.000	27,805.000	27,426.000	25,772.000	28,611.000	27,545.000	26,973.000	24,973.000	26,527.000	26,195.000	25,660.000	27,448.000	26,186.000	25,514.000	26,114.000	28,364.000	24,054.000	26,930.000	26,904.000	24,138.000	25,735.000	26,036.000	26,570.000	25,018.000	25,844.000	27,629.000	27,020.000	26,729.000	27,374.000	27,092.000	27,399.000	26,528.000	25,710.000	25,400.000	27,462.000	24,915.000	25,989.000	27,831.000	26,959.000	26,700.000	27,733.000	27,680.000	27,197.000	25,212.000	0.000	25,874.000	26,761.000	27,106.000	26,580.000	26,439.000	27,108.000	26,554.000	26,403.000	24,726.000	25,682.000	26,400.000	26,828.000	26,750.000	27,554.000	25,358.000	26,354.000	27,836.000	27,520.000	27,332.000	26,522.000	28,036.000	25,301.000	27,651.000	26,635.000	26,957.000	27,380.000	25,778.000	0.000	26,959.000	27,262.000	24,559.000	27,170.000	25,338.000	0.000	0.000	25,813.000	27,886.000	25,383.000	27,732.000	25,627.000	26,327.000	24,705.000	27,341.000	25,000.000	27,498.000	25,185.000	25,843.000	26,378.000	28,026.000	25,543.000	26,678.000	25,179.000	28,145.000	26,345.000	27,314.000	26,700.000	26,764.000	25,513.000	25,247.000	26,514.000	27,272.000	27,304.000	25,633.000	24,802.000	28,587.000	28,614.000	25,909.000	27,547.000	27,140.000	0.000	27,187.000	0.000	0.000	26,421.000	26,625.000	23,417.000	27,347.000	27,986.000	26,334.000	28,004.000	25,489.000
2	29,193.000	26,837.000	0.000	26,629.000	26,700.000	25,743.000	27,401.000	26,204.000	27,407.000	27,819.000	27,279.000	27,370.000	28,460.000	26,555.000	28,004.000	26,882.000	25,883.000	26,134.000	25,413.000	27,472.000	27,477.000	27,519.000	27,494.000	28,443.000	0.000	28,924.000	27,496.000	28,672.000	27,840.000	27,717.000	26,665.000	28,454.000	28,486.000	26,727.000	29,720.000	28,080.000	27,908.000	28,248.000	29,233.000	27,654.000	27,697.000	28,539.000	26,423.000	29,268.000	27,686.000	28,752.000	27,081.000	28,151.000	25,939.000	26,514.000	26,163.000	27,711.000	26,749.000	28,613.000	0.000	26,355.000	28,532.000	27,987.000	26,647.000	28,702.000	27,822.000	27,914.000	27,423.000	26,537.000	26,904.000	26,579.000	25,516.000	28,516.000	29,494.000	29,427.000	26,910.000	26,058.000	27,860.000	28,023.000	30,480.000	28,813.000	28,649.000	27,117.000	27,501.000	27,384.000	0.000	29,095.000	28,055.000	27,785.000	28,289.000	27,390.000	25,845.000	27,094.000	28,502.000	26,929.000	0.000	26,631.000	0.000	29,096.000	25,935.000	27,773.000	28,882.000	29,087.000	29,229.000	28,685.000	26,200.000	28,990.000	29,186.000	27,419.000	28,057.000	24,915.000	27,591.000	27,301.000	26,747.000	29,131.000	28,729.000	0.000	28,981.000	27,961.000	29,612.000	28,381.000	27,743.000	28,803.000	28,058.000	27,103.000	28,605.000	27,647.000	28,686.000	25,601.000	27,721.000	28,108.000	29,318.000	27,790.000	28,255.000	28,882.000	25,587.000	27,733.000	0.000	27,040.000	27,513.000	29,675.000	26,939.000	27,518.000	28,105.000	28,562.000	28,303.000	0.000	28,337.000	28,576.000	26,560.000	26,111.000	27,990.000	28,275.000	28,126.000	30,761.000	28,531.000	27,990.000	26,120.000	27,946.000	29,039.000	28,244.000	29,510.000	26,955.000	28,417.000	27,585.000	27,097.000	26,914.000	26,920.000	26,965.000	28,415.000	27,244.000	28,212.000	24,869.000	26,996.000	28,473.000	28,125.000	29,496.000	0.000	27,283.000	28,409.000	26,945.000	26,848.000	26,692.000	28,208.000	26,656.000	27,733.000	26,154.000	27,727.000	29,102.000	29,302.000	27,706.000	28,907.000	28,338.000	26,724.000	29,158.000	25,416.000	28,617.000	29,703.000	27,472.000	25,521.000	29,889.000	27,256.000	0.000	27,472.000	28,588.000	27,258.000	25,481.000	30,812.000	24,211.000	29,338.000	28,476.000	27,170.000	28,326.000	27,911.000	26,672.000	27,744.000	28,558.000	26,509.000	26,760.000	27,556.000	29,535.000	29,703.000	28,805.000	28,544.000	0.000	28,299.000	27,692.000	27,716.000	27,072.000	28,454.000	28,637.000	27,114.000	26,685.000	29,223.000	28,943.000	28,738.000	27,032.000	27,777.000	28,704.000	28,158.000	26,849.000	27,130.000	26,767.000	29,719.000	28,542.000	28,451.000	27,914.000	27,764.000	26,768.000	0.000	27,413.000	28,737.000	28,750.000	29,618.000
3	24,093.000	26,156.000	23,059.000	24,354.000	26,442.000	24,701.000	26,707.000	25,199.000	26,778.000	25,957.000	25,460.000	24,914.000	24,490.000	26,923.000	24,918.000	26,097.000	22,701.000	25,999.000	25,287.000	25,456.000	23,473.000	26,511.000	22,890.000	24,864.000	23,975.000	24,571.000	24,429.000	23,241.000	25,721.000	25,282.000	24,067.000	25,369.000	25,057.000	24,791.000	27,917.000	24,306.000	24,985.000	27,191.000	24,678.000	26,975.000	25,396.000	25,879.000	24,376.000	24,649.000	24,743.000	25,487.000	26,192.000	24,557.000	24,338.000	25,635.000	26,340.000	23,564.000	0.000	24,363.000	24,841.000	25,135.000	26,706.000	0.000	24,172.000	26,922.000	24,883.000	24,600.000	24,294.000	24,859.000	26,046.000	25,057.000	26,862.000	24,319.000	26,156.000	26,039.000	26,175.000	25,418.000	27,402.000	26,818.000	25,707.000	26,806.000	0.000	24,892.000	25,210.000	26,435.000	25,069.000	25,382.000	24,435.000	22,789.000	25,602.000	24,741.000	24,737.000	25,317.000	25,567.000	24,592.000	26,194.000	23,797.000	26,056.000	26,691.000	26,772.000	25,618.000	24,598.000	26,208.000	22,557.000	25,745.000	22,706.000	24,277.000	24,440.000	25,839.000	26,329.000	24,530.000	24,064.000	27,506.000	24,962.000	26,411.000	25,960.000	25,631.000	25,550.000	24,895.000	25,179.000	26,132.000	24,985.000	23,820.000	25,714.000	0.000	23,655.000	25,406.000	24,374.000	23,722.000	24,179.000	24,667.000	24,943.000	28,679.000	24,347.000	24,693.000	28,777.000	25,377.000	22,856.000	26,620.000	25,942.000	24,968.000	24,915.000	25,941.000	23,920.000	24,994.000	24,689.000	25,615.000	27,821.000	26,617.000	25,124.000	25,961.000	25,364.000	24,488.000	0.000	24,784.000	24,884.000	26,091.000	24,395.000	25,356.000	24,297.000	25,374.000	24,832.000	26,255.000	25,320.000	24,292.000	25,241.000	25,004.000	24,133.000	23,962.000	25,009.000	23,941.000	24,265.000	26,442.000	26,051.000	25,726.000	25,491.000	24,572.000	25,711.000	24,479.000	27,149.000	23,731.000	26,505.000	24,426.000	24,969.000	25,140.000	25,982.000	24,781.000	25,791.000	25,326.000	25,119.000	28,123.000	26,782.000	24,335.000	26,253.000	25,271.000	27,064.000	25,784.000	24,953.000	24,898.000	25,510.000	24,092.000	25,501.000	24,449.000	25,254.000	23,596.000	25,095.000	25,209.000	25,284.000	24,727.000	26,095.000	27,097.000	23,258.000	24,494.000	23,867.000	27,685.000	25,352.000	24,132.000	24,075.000	23,600.000	26,517.000	25,185.000	24,487.000	26,255.000	26,169.000	22,314.000	27,219.000	24,998.000	23,991.000	25,429.000	26,846.000	0.000	25,120.000	24,973.000	24,255.000	24,361.000	25,447.000	24,475.000	26,965.000	27,126.000	0.000	25,918.000	25,547.000	24,304.000	24,850.000	25,986.000	24,429.000	25,789.000	24,486.000	24,229.000	24,659.000	25,286.000	26,780.000	27,140.000	24,431.000
4	26,418.000	26,251.000	24,995.000	24,910.000	24,663.000	25,895.000	25,195.000	26,303.000	24,756.000	24,868.000	23,467.000	25,844.000	24,138.000	25,241.000	25,725.000	26,117.000	27,163.000	24,873.000	25,991.000	25,444.000	26,770.000	25,118.000	25,745.000	25,723.000	26,402.000	0.000	25,419.000	26,428.000	25,724.000	26,461.000	25,598.000	24,741.000	27,085.000	24,112.000	25,847.000	25,431.000	22,610.000	26,489.000	26,150.000	0.000	26,652.000	23,269.000	0.000	25,766.000	26,630.000	26,976.000	27,447.000	24,542.000	24,208.000	25,950.000	25,595.000	25,223.000	25,943.000	25,012.000	24,936.000	26,446.000	28,126.000	0.000	25,352.000	27,408.000	27,035.000	24,890.000	25,450.000	26,633.000	25,400.000	25,990.000	25,383.000	25,099.000	24,603.000	0.000	23,384.000	25,485.000	25,144.000	26,301.000	25,480.000	26,126.000	27,493.000	26,797.000	26,547.000	24,937.000	25,719.000	25,635.000	27,014.000	24,218.000	28,238.000	25,763.000	27,772.000	25,685.000	26,188.000	25,829.000	26,148.000	25,727.000	24,793.000	27,031.000	23,843.000	25,957.000	0.000	25,965.000	26,543.000	27,297.000	27,604.000	25,612.000	25,076.000	28,086.000	26,340.000	26,825.000	24,434.000	26,219.000	25,927.000	26,116.000	26,760.000	25,636.000	26,398.000	24,859.000	26,165.000	27,907.000	26,274.000	27,248.000	24,616.000	26,878.000	25,043.000	25,693.000	25,750.000	25,918.000	24,714.000	26,537.000	27,027.000	26,556.000	27,196.000	25,010.000	26,190.000	27,410.000	26,560.000	27,914.000	26,937.000	26,087.000	24,713.000	24,578.000	0.000	26,664.000	26,616.000	26,076.000	25,242.000	28,269.000	26,035.000	26,188.000	27,552.000	26,222.000	0.000	25,379.000	26,640.000	26,777.000	27,560.000	25,832.000	24,389.000	26,696.000	25,732.000	27,620.000	26,322.000	26,191.000	24,634.000	0.000	25,828.000	25,520.000	24,023.000	0.000	25,143.000	26,906.000	25,165.000	26,259.000	25,533.000	25,353.000	26,151.000	26,453.000	26,230.000	26,131.000	28,407.000	24,508.000	25,503.000	27,059.000	25,616.000	25,155.000	25,452.000	27,323.000	0.000	25,239.000	24,895.000	24,675.000	24,818.000	0.000	25,818.000	27,001.000	26,993.000	24,732.000	26,222.000	25,606.000	24,897.000	25,815.000	24,483.000	25,556.000	26,958.000	25,376.000	24,457.000	27,032.000	26,760.000	24,815.000	25,429.000	25,413.000	0.000	25,475.000	26,080.000	24,572.000	27,047.000	0.000	27,379.000	24,249.000	25,259.000	23,730.000	26,224.000	27,346.000	27,139.000	25,678.000	28,112.000	25,681.000	24,837.000	25,022.000	26,316.000	26,203.000	25,447.000	25,966.000	24,884.000	26,657.000	26,215.000	24,759.000	27,047.000	25,080.000	25,401.000	25,198.000	26,327.000	26,841.000	27,465.000	24,648.000	26,375.000	26,689.000	25,506.000	26,810.000	26,700.000	26,519.000	25,679.000
5	29,000.000	28,757.000	27,657.000	28,102.000	27,584.000	27,798.000	30,114.000	29,726.000	29,736.000	30,253.000	0.000	28,135.000	29,603.000	29,847.000	26,317.000	28,544.000	28,543.000	29,085.000	28,903.000	29,394.000	28,904.000	28,788.000	29,126.000	27,751.000	29,472.000	27,644.000	28,669.000	27,615.000	31,394.000	28,520.000	28,449.000	29,139.000	28,246.000	29,631.000	28,090.000	29,228.000	28,916.000	27,755.000	28,682.000	31,295.000	28,621.000	29,062.000	29,458.000	30,083.000	29,033.000	29,317.000	29,101.000	28,987.000	28,043.000	28,621.000	29,182.000	27,864.000	27,970.000	27,629.000	27,631.000	28,230.000	28,025.000	28,434.000	27,717.000	28,094.000	28,935.000	29,166.000	28,180.000	30,080.000	28,935.000	27,295.000	29,324.000	28,608.000	28,337.000	30,701.000	29,064.000	29,406.000	28,364.000	29,956.000	0.000	26,973.000	28,189.000	28,232.000	31,214.000	26,975.000	27,532.000	28,026.000	28,479.000	30,012.000	30,794.000	26,505.000	27,626.000	28,048.000	31,072.000	26,905.000	28,671.000	28,122.000	27,077.000	29,942.000	28,580.000	28,278.000	29,358.000	31,121.000	30,604.000	29,208.000	27,892.000	29,949.000	29,023.000	28,077.000	29,492.000	27,458.000	29,598.000	29,367.000	28,105.000	28,131.000	0.000	29,854.000	29,267.000	29,094.000	30,059.000	30,550.000	27,401.000	31,340.000	28,156.000	27,179.000	28,443.000	29,669.000	28,588.000	29,221.000	27,751.000	28,722.000	27,358.000	27,002.000	28,532.000	28,141.000	28,562.000	29,723.000	28,562.000	28,179.000	29,368.000	28,033.000	27,647.000	29,966.000	27,758.000	27,968.000	29,260.000	30,264.000	27,474.000	27,614.000	30,156.000	28,833.000	27,890.000	29,871.000	28,323.000	27,377.000	28,084.000	28,348.000	30,082.000	0.000	30,172.000	29,081.000	29,541.000	27,189.000	29,797.000	28,402.000	28,977.000	29,695.000	30,336.000	29,286.000	27,991.000	27,697.000	26,926.000	27,628.000	30,054.000	31,782.000	29,204.000	28,115.000	28,552.000	29,124.000	30,252.000	27,938.000	29,347.000	28,031.000	28,025.000	27,309.000	28,246.000	28,571.000	29,890.000	29,572.000	30,814.000	29,473.000	29,797.000	28,171.000	27,543.000	30,621.000	28,091.000	27,587.000	28,755.000	27,607.000	31,200.000	28,619.000	28,388.000	29,244.000	28,112.000	27,417.000	30,603.000	29,938.000	29,951.000	29,162.000	29,751.000	29,937.000	28,749.000	29,092.000	27,315.000	30,275.000	27,082.000	29,220.000	29,261.000	29,552.000	30,055.000	28,315.000	28,633.000	28,460.000	28,570.000	27,372.000	30,830.000	30,403.000	30,755.000	28,406.000	27,460.000	29,240.000	30,373.000	28,480.000	26,640.000	27,598.000	28,326.000	29,174.000	30,726.000	28,275.000	28,516.000	31,305.000	27,322.000	29,495.000	29,266.000	29,952.000	28,453.000	27,594.000	28,647.000	28,033.000	29,698.000	27,584.000	29,767.000	28,632.000	28,865.000

	EmployeeID	2015-01-01	2015-01-02	2015-01-05	2015-01-06	2015-01-07	2015-01-08	2015-01-09	2015-01-12	2015-01-13	2015-01-14	2015-01-15	2015-01-16	2015-01-19	2015-01-20	2015-01-21	2015-01-22	2015-01-23	2015-01-26	2015-01-27	2015-01-28	2015-01-29	2015-01-30	2015-02-02	2015-02-03	2015-02-04	2015-02-05	2015-02-06	2015-02-09	2015-02-10	2015-02-11	2015-02-12	2015-02-13	2015-02-16	2015-02-17	2015-02-18	2015-02-19	2015-02-20	2015-02-23	2015-02-24	2015-02-25	2015-02-26	2015-02-27	2015-03-02	2015-03-03	2015-03-04	2015-03-05	2015-03-06	2015-03-09	2015-03-10	2015-03-11	2015-03-12	2015-03-13	2015-03-16	2015-03-17	2015-03-18	2015-03-19	2015-03-20	2015-03-23	2015-03-24	2015-03-25	2015-03-26	2015-03-27	2015-03-30	2015-03-31	2015-04-01	2015-04-02	2015-04-03	2015-04-06	2015-04-07	2015-04-08	2015-04-09	2015-04-10	2015-04-13	2015-04-14	2015-04-15	2015-04-16	2015-04-17	2015-04-20	2015-04-21	2015-04-22	2015-04-23	2015-04-24	2015-04-27	2015-04-28	2015-04-29	2015-04-30	2015-05-01	2015-05-04	2015-05-05	2015-05-06	2015-05-07	2015-05-08	2015-05-11	2015-05-12	2015-05-13	2015-05-14	2015-05-15	2015-05-18	2015-05-19	2015-05-20	2015-05-21	2015-05-22	2015-05-25	2015-05-26	2015-05-27	2015-05-28	2015-05-29	2015-06-01	2015-06-02	2015-06-03	2015-06-04	2015-06-05	2015-06-08	2015-06-09	2015-06-10	2015-06-11	2015-06-12	2015-06-15	2015-06-16	2015-06-17	2015-06-18	2015-06-19	2015-06-22	2015-06-23	2015-06-24	2015-06-25	2015-06-26	2015-06-29	2015-06-30	2015-07-01	2015-07-02	2015-07-03	2015-07-06	2015-07-07	2015-07-08	2015-07-09	2015-07-10	2015-07-13	2015-07-14	2015-07-15	2015-07-16	2015-07-17	2015-07-20	2015-07-21	2015-07-22	2015-07-23	2015-07-24	2015-07-27	2015-07-28	2015-07-29	2015-07-30	2015-07-31	2015-08-03	2015-08-04	2015-08-05	2015-08-06	2015-08-07	2015-08-10	2015-08-11	2015-08-12	2015-08-13	2015-08-14	2015-08-17	2015-08-18	2015-08-19	2015-08-20	2015-08-21	2015-08-24	2015-08-25	2015-08-26	2015-08-27	2015-08-28	2015-08-31	2015-09-01	2015-09-02	2015-09-03	2015-09-04	2015-09-07	2015-09-08	2015-09-09	2015-09-10	2015-09-11	2015-09-14	2015-09-15	2015-09-16	2015-09-17	2015-09-18	2015-09-21	2015-09-22	2015-09-23	2015-09-24	2015-09-25	2015-09-28	2015-09-29	2015-09-30	2015-10-01	2015-10-02	2015-10-05	2015-10-06	2015-10-07	2015-10-08	2015-10-09	2015-10-12	2015-10-13	2015-10-14	2015-10-15	2015-10-16	2015-10-19	2015-10-20	2015-10-21	2015-10-22	2015-10-23	2015-10-26	2015-10-27	2015-10-28	2015-10-29	2015-10-30	2015-11-02	2015-11-03	2015-11-04	2015-11-05	2015-11-06	2015-11-09	2015-11-10	2015-11-11	2015-11-12	2015-11-13	2015-11-16	2015-11-17	2015-11-18	2015-11-19	2015-11-20	2015-11-23	2015-11-24	2015-11-25	2015-11-26	2015-11-27	2015-11-30	2015-12-01	2015-12-02	2015-12-03	2015-12-04	2015-12-07	2015-12-08	2015-12-09	2015-12-10	2015-12-11	2015-12-14	2015-12-15	2015-12-16	2015-12-17	2015-12-18	2015-12-21	2015-12-22	2015-12-23	2015-12-24	2015-12-25	2015-12-28	2015-12-29	2015-12-30	2015-12-31
0	1	0.000	25,950.000	25,883.000	26,679.000	25,224.000	26,243.000	26,944.000	26,146.000	28,192.000	0.000	26,449.000	26,163.000	0.000	24,393.000	25,542.000	25,382.000	27,377.000	0.000	27,465.000	25,628.000	26,689.000	24,659.000	24,846.000	25,931.000	27,379.000	27,235.000	26,892.000	27,365.000	26,162.000	25,895.000	26,767.000	25,939.000	27,381.000	26,698.000	28,223.000	0.000	28,196.000	26,788.000	26,010.000	27,301.000	25,923.000	26,589.000	25,765.000	24,335.000	27,880.000	0.000	28,134.000	26,671.000	24,923.000	25,780.000	25,488.000	26,317.000	0.000	24,894.000	25,912.000	28,252.000	25,785.000	27,419.000	26,107.000	26,804.000	0.000	27,201.000	26,485.000	28,314.000	26,413.000	27,571.000	25,876.000	25,347.000	27,504.000	26,738.000	28,091.000	25,617.000	26,453.000	25,728.000	26,855.000	27,925.000	26,225.000	27,703.000	25,112.000	27,090.000	26,411.000	27,225.000	26,071.000	28,401.000	27,690.000	27,029.000	0.000	26,678.000	26,311.000	26,844.000	25,426.000	27,414.000	0.000	26,801.000	27,009.000	28,446.000	24,541.000	0.000	26,399.000	26,350.000	26,875.000	25,664.000	27,263.000	25,919.000	28,360.000	26,812.000	0.000	0.000	27,782.000	27,051.000	25,351.000	0.000	25,462.000	0.000	25,471.000	27,270.000	26,717.000	27,343.000	27,152.000	27,094.000	27,077.000	26,096.000	25,842.000	24,886.000	25,606.000	27,913.000	25,388.000	27,582.000	26,291.000	27,805.000	27,426.000	25,772.000	28,611.000	27,545.000	26,973.000	24,973.000	26,527.000	26,195.000	25,660.000	27,448.000	26,186.000	0.000	25,514.000	26,114.000	28,364.000	24,054.000	26,930.000	26,904.000	24,138.000	25,735.000	26,036.000	26,570.000	25,018.000	25,844.000	27,629.000	27,020.000	26,729.000	27,374.000	27,092.000	27,399.000	26,528.000	25,710.000	25,400.000	27,462.000	24,915.000	25,989.000	27,831.000	26,959.000	26,700.000	27,733.000	27,680.000	27,197.000	25,212.000	0.000	25,874.000	26,761.000	27,106.000	26,580.000	26,439.000	27,108.000	26,554.000	26,403.000	24,726.000	25,682.000	26,400.000	0.000	26,828.000	26,750.000	27,554.000	25,358.000	26,354.000	27,836.000	27,520.000	27,332.000	26,522.000	28,036.000	0.000	25,301.000	27,651.000	26,635.000	26,957.000	27,380.000	25,778.000	0.000	26,959.000	27,262.000	24,559.000	27,170.000	25,338.000	0.000	0.000	25,813.000	27,886.000	25,383.000	27,732.000	25,627.000	26,327.000	24,705.000	27,341.000	25,000.000	27,498.000	25,185.000	0.000	0.000	0.000	25,843.000	26,378.000	28,026.000	25,543.000	26,678.000	25,179.000	28,145.000	26,345.000	27,314.000	26,700.000	26,764.000	25,513.000	25,247.000	26,514.000	27,272.000	27,304.000	25,633.000	24,802.000	28,587.000	28,614.000	25,909.000	27,547.000	27,140.000	0.000	27,187.000	0.000	0.000	26,421.000	26,625.000	23,417.000	27,347.000	0.000	27,986.000	26,334.000	28,004.000	25,489.000
1	2	0.000	29,193.000	26,837.000	0.000	26,629.000	26,700.000	25,743.000	27,401.000	26,204.000	0.000	27,407.000	27,819.000	27,279.000	27,370.000	28,460.000	26,555.000	28,004.000	0.000	26,882.000	25,883.000	26,134.000	25,413.000	27,472.000	27,477.000	27,519.000	27,494.000	28,443.000	0.000	28,924.000	27,496.000	28,672.000	27,840.000	27,717.000	26,665.000	28,454.000	28,486.000	26,727.000	29,720.000	28,080.000	27,908.000	28,248.000	29,233.000	27,654.000	27,697.000	28,539.000	0.000	26,423.000	29,268.000	27,686.000	28,752.000	27,081.000	28,151.000	25,939.000	26,514.000	26,163.000	27,711.000	26,749.000	28,613.000	0.000	26,355.000	28,532.000	27,987.000	26,647.000	28,702.000	27,822.000	27,914.000	27,423.000	26,537.000	26,904.000	26,579.000	25,516.000	28,516.000	29,494.000	29,427.000	26,910.000	26,058.000	27,860.000	28,023.000	30,480.000	28,813.000	28,649.000	27,117.000	27,501.000	27,384.000	0.000	29,095.000	0.000	28,055.000	27,785.000	28,289.000	27,390.000	25,845.000	27,094.000	28,502.000	26,929.000	0.000	26,631.000	0.000	29,096.000	25,935.000	27,773.000	28,882.000	29,087.000	29,229.000	28,685.000	26,200.000	28,990.000	29,186.000	27,419.000	28,057.000	24,915.000	27,591.000	27,301.000	26,747.000	29,131.000	28,729.000	0.000	28,981.000	27,961.000	29,612.000	28,381.000	27,743.000	28,803.000	28,058.000	27,103.000	28,605.000	27,647.000	28,686.000	25,601.000	27,721.000	28,108.000	29,318.000	27,790.000	28,255.000	28,882.000	25,587.000	27,733.000	0.000	27,040.000	27,513.000	29,675.000	0.000	26,939.000	27,518.000	28,105.000	28,562.000	28,303.000	0.000	28,337.000	28,576.000	26,560.000	26,111.000	27,990.000	28,275.000	28,126.000	30,761.000	28,531.000	27,990.000	26,120.000	27,946.000	29,039.000	28,244.000	29,510.000	26,955.000	28,417.000	27,585.000	27,097.000	26,914.000	26,920.000	26,965.000	28,415.000	27,244.000	28,212.000	24,869.000	26,996.000	28,473.000	28,125.000	29,496.000	0.000	27,283.000	28,409.000	26,945.000	26,848.000	26,692.000	28,208.000	0.000	26,656.000	27,733.000	26,154.000	27,727.000	29,102.000	29,302.000	27,706.000	28,907.000	28,338.000	26,724.000	0.000	29,158.000	25,416.000	28,617.000	29,703.000	27,472.000	25,521.000	29,889.000	27,256.000	0.000	27,472.000	28,588.000	27,258.000	25,481.000	30,812.000	24,211.000	29,338.000	28,476.000	27,170.000	28,326.000	27,911.000	26,672.000	27,744.000	28,558.000	26,509.000	26,760.000	0.000	0.000	0.000	27,556.000	29,535.000	29,703.000	28,805.000	28,544.000	0.000	28,299.000	27,692.000	27,716.000	27,072.000	28,454.000	28,637.000	27,114.000	26,685.000	29,223.000	28,943.000	28,738.000	27,032.000	27,777.000	28,704.000	28,158.000	26,849.000	27,130.000	26,767.000	29,719.000	28,542.000	28,451.000	27,914.000	27,764.000	26,768.000	0.000	0.000	27,413.000	28,737.000	28,750.000	29,618.000
2	3	0.000	24,093.000	26,156.000	23,059.000	24,354.000	26,442.000	24,701.000	26,707.000	25,199.000	0.000	26,778.000	25,957.000	25,460.000	24,914.000	24,490.000	26,923.000	24,918.000	0.000	26,097.000	22,701.000	25,999.000	25,287.000	25,456.000	23,473.000	26,511.000	22,890.000	24,864.000	23,975.000	24,571.000	24,429.000	23,241.000	25,721.000	25,282.000	24,067.000	25,369.000	25,057.000	24,791.000	27,917.000	24,306.000	24,985.000	27,191.000	24,678.000	26,975.000	25,396.000	25,879.000	0.000	24,376.000	24,649.000	24,743.000	25,487.000	26,192.000	24,557.000	24,338.000	25,635.000	26,340.000	23,564.000	0.000	24,363.000	24,841.000	25,135.000	26,706.000	0.000	24,172.000	26,922.000	24,883.000	24,600.000	24,294.000	24,859.000	26,046.000	25,057.000	26,862.000	24,319.000	26,156.000	26,039.000	26,175.000	25,418.000	27,402.000	26,818.000	25,707.000	26,806.000	0.000	24,892.000	25,210.000	26,435.000	25,069.000	25,382.000	0.000	24,435.000	22,789.000	25,602.000	24,741.000	24,737.000	25,317.000	25,567.000	24,592.000	26,194.000	23,797.000	26,056.000	26,691.000	26,772.000	25,618.000	24,598.000	26,208.000	22,557.000	25,745.000	22,706.000	24,277.000	24,440.000	25,839.000	26,329.000	24,530.000	24,064.000	27,506.000	24,962.000	26,411.000	25,960.000	25,631.000	25,550.000	24,895.000	25,179.000	26,132.000	24,985.000	23,820.000	25,714.000	0.000	23,655.000	25,406.000	24,374.000	23,722.000	24,179.000	24,667.000	24,943.000	28,679.000	24,347.000	24,693.000	28,777.000	25,377.000	22,856.000	26,620.000	25,942.000	24,968.000	0.000	24,915.000	25,941.000	23,920.000	24,994.000	24,689.000	25,615.000	27,821.000	26,617.000	25,124.000	25,961.000	25,364.000	24,488.000	0.000	24,784.000	24,884.000	26,091.000	24,395.000	25,356.000	24,297.000	25,374.000	24,832.000	26,255.000	25,320.000	24,292.000	25,241.000	25,004.000	24,133.000	23,962.000	25,009.000	23,941.000	24,265.000	26,442.000	26,051.000	25,726.000	25,491.000	24,572.000	25,711.000	24,479.000	27,149.000	23,731.000	26,505.000	24,426.000	24,969.000	0.000	25,140.000	25,982.000	24,781.000	25,791.000	25,326.000	25,119.000	28,123.000	26,782.000	24,335.000	26,253.000	0.000	25,271.000	27,064.000	25,784.000	24,953.000	24,898.000	25,510.000	24,092.000	25,501.000	24,449.000	25,254.000	23,596.000	25,095.000	25,209.000	25,284.000	24,727.000	26,095.000	27,097.000	23,258.000	24,494.000	23,867.000	27,685.000	25,352.000	24,132.000	24,075.000	23,600.000	0.000	0.000	0.000	26,517.000	25,185.000	24,487.000	26,255.000	26,169.000	22,314.000	27,219.000	24,998.000	23,991.000	25,429.000	26,846.000	0.000	25,120.000	24,973.000	24,255.000	24,361.000	25,447.000	24,475.000	26,965.000	27,126.000	0.000	25,918.000	25,547.000	24,304.000	24,850.000	25,986.000	24,429.000	25,789.000	24,486.000	24,229.000	24,659.000	0.000	25,286.000	26,780.000	27,140.000	24,431.000
3	4	0.000	26,418.000	26,251.000	24,995.000	24,910.000	24,663.000	25,895.000	25,195.000	26,303.000	0.000	24,756.000	24,868.000	23,467.000	25,844.000	24,138.000	25,241.000	25,725.000	0.000	26,117.000	27,163.000	24,873.000	25,991.000	25,444.000	26,770.000	25,118.000	25,745.000	25,723.000	26,402.000	0.000	25,419.000	26,428.000	25,724.000	26,461.000	25,598.000	24,741.000	27,085.000	24,112.000	25,847.000	25,431.000	22,610.000	26,489.000	26,150.000	0.000	26,652.000	23,269.000	0.000	0.000	25,766.000	26,630.000	26,976.000	27,447.000	24,542.000	24,208.000	25,950.000	25,595.000	25,223.000	25,943.000	25,012.000	24,936.000	26,446.000	28,126.000	0.000	25,352.000	27,408.000	27,035.000	24,890.000	25,450.000	26,633.000	25,400.000	25,990.000	25,383.000	25,099.000	24,603.000	0.000	23,384.000	25,485.000	25,144.000	26,301.000	25,480.000	26,126.000	27,493.000	26,797.000	26,547.000	24,937.000	25,719.000	25,635.000	0.000	27,014.000	24,218.000	28,238.000	25,763.000	27,772.000	25,685.000	26,188.000	25,829.000	26,148.000	25,727.000	24,793.000	27,031.000	23,843.000	25,957.000	0.000	25,965.000	26,543.000	27,297.000	27,604.000	25,612.000	25,076.000	28,086.000	26,340.000	26,825.000	24,434.000	26,219.000	25,927.000	26,116.000	26,760.000	25,636.000	26,398.000	24,859.000	26,165.000	27,907.000	26,274.000	27,248.000	24,616.000	26,878.000	25,043.000	25,693.000	25,750.000	25,918.000	24,714.000	26,537.000	27,027.000	26,556.000	27,196.000	25,010.000	26,190.000	27,410.000	26,560.000	27,914.000	26,937.000	26,087.000	0.000	24,713.000	24,578.000	0.000	26,664.000	26,616.000	26,076.000	25,242.000	28,269.000	26,035.000	26,188.000	27,552.000	26,222.000	0.000	25,379.000	26,640.000	26,777.000	27,560.000	25,832.000	24,389.000	26,696.000	25,732.000	27,620.000	26,322.000	26,191.000	24,634.000	0.000	25,828.000	25,520.000	24,023.000	0.000	25,143.000	26,906.000	25,165.000	26,259.000	25,533.000	25,353.000	26,151.000	26,453.000	26,230.000	26,131.000	28,407.000	24,508.000	25,503.000	0.000	27,059.000	25,616.000	25,155.000	25,452.000	27,323.000	0.000	25,239.000	24,895.000	24,675.000	24,818.000	0.000	0.000	25,818.000	27,001.000	26,993.000	24,732.000	26,222.000	25,606.000	24,897.000	25,815.000	24,483.000	25,556.000	26,958.000	25,376.000	24,457.000	27,032.000	26,760.000	24,815.000	25,429.000	25,413.000	0.000	25,475.000	26,080.000	24,572.000	27,047.000	0.000	0.000	0.000	0.000	27,379.000	24,249.000	25,259.000	23,730.000	26,224.000	27,346.000	27,139.000	25,678.000	28,112.000	25,681.000	24,837.000	25,022.000	26,316.000	26,203.000	25,447.000	25,966.000	24,884.000	26,657.000	26,215.000	24,759.000	27,047.000	25,080.000	25,401.000	25,198.000	26,327.000	26,841.000	27,465.000	24,648.000	26,375.000	26,689.000	25,506.000	0.000	26,810.000	26,700.000	26,519.000	25,679.000
4	5	0.000	29,000.000	28,757.000	27,657.000	28,102.000	27,584.000	27,798.000	30,114.000	29,726.000	0.000	29,736.000	30,253.000	0.000	28,135.000	29,603.000	29,847.000	26,317.000	0.000	28,544.000	28,543.000	29,085.000	28,903.000	29,394.000	28,904.000	28,788.000	29,126.000	27,751.000	29,472.000	27,644.000	28,669.000	27,615.000	31,394.000	28,520.000	28,449.000	29,139.000	28,246.000	29,631.000	28,090.000	29,228.000	28,916.000	27,755.000	28,682.000	31,295.000	28,621.000	29,062.000	0.000	29,458.000	30,083.000	29,033.000	29,317.000	29,101.000	28,987.000	28,043.000	28,621.000	29,182.000	27,864.000	27,970.000	27,629.000	27,631.000	28,230.000	28,025.000	28,434.000	27,717.000	28,094.000	28,935.000	29,166.000	28,180.000	30,080.000	28,935.000	27,295.000	29,324.000	28,608.000	28,337.000	30,701.000	29,064.000	29,406.000	28,364.000	29,956.000	0.000	26,973.000	28,189.000	28,232.000	31,214.000	26,975.000	27,532.000	28,026.000	0.000	28,479.000	30,012.000	30,794.000	26,505.000	27,626.000	28,048.000	31,072.000	26,905.000	28,671.000	28,122.000	27,077.000	29,942.000	28,580.000	28,278.000	29,358.000	31,121.000	30,604.000	29,208.000	27,892.000	29,949.000	29,023.000	28,077.000	29,492.000	27,458.000	29,598.000	29,367.000	28,105.000	28,131.000	0.000	29,854.000	29,267.000	29,094.000	30,059.000	30,550.000	27,401.000	31,340.000	28,156.000	27,179.000	28,443.000	29,669.000	28,588.000	29,221.000	27,751.000	28,722.000	27,358.000	27,002.000	28,532.000	28,141.000	28,562.000	29,723.000	28,562.000	28,179.000	29,368.000	28,033.000	0.000	27,647.000	29,966.000	27,758.000	27,968.000	29,260.000	30,264.000	27,474.000	27,614.000	30,156.000	28,833.000	27,890.000	29,871.000	28,323.000	27,377.000	28,084.000	28,348.000	30,082.000	0.000	30,172.000	29,081.000	29,541.000	27,189.000	29,797.000	28,402.000	28,977.000	29,695.000	30,336.000	29,286.000	27,991.000	27,697.000	26,926.000	27,628.000	30,054.000	31,782.000	29,204.000	28,115.000	28,552.000	29,124.000	30,252.000	27,938.000	29,347.000	28,031.000	28,025.000	0.000	27,309.000	28,246.000	28,571.000	29,890.000	29,572.000	30,814.000	29,473.000	29,797.000	28,171.000	27,543.000	0.000	30,621.000	28,091.000	27,587.000	28,755.000	27,607.000	31,200.000	28,619.000	28,388.000	29,244.000	28,112.000	27,417.000	30,603.000	29,938.000	29,951.000	29,162.000	29,751.000	29,937.000	28,749.000	29,092.000	27,315.000	30,275.000	27,082.000	29,220.000	29,261.000	29,552.000	0.000	0.000	0.000	30,055.000	28,315.000	28,633.000	28,460.000	28,570.000	27,372.000	30,830.000	30,403.000	30,755.000	28,406.000	27,460.000	29,240.000	30,373.000	28,480.000	26,640.000	27,598.000	28,326.000	29,174.000	30,726.000	28,275.000	28,516.000	31,305.000	27,322.000	29,495.000	29,266.000	29,952.000	28,453.000	27,594.000	28,647.000	28,033.000	29,698.000	0.000	27,584.000	29,767.000	28,632.000	28,865.000
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
4405	4406	0.000	29,225.000	31,827.000	30,238.000	31,842.000	29,605.000	29,811.000	30,098.000	31,533.000	0.000	30,080.000	32,427.000	32,608.000	30,989.000	30,883.000	31,355.000	28,849.000	0.000	31,754.000	31,744.000	29,399.000	29,905.000	29,846.000	29,690.000	29,814.000	30,777.000	28,306.000	30,474.000	30,337.000	29,972.000	31,772.000	32,186.000	33,306.000	31,217.000	30,516.000	30,207.000	29,009.000	31,269.000	32,335.000	27,945.000	30,556.000	30,747.000	30,285.000	31,358.000	31,194.000	0.000	29,803.000	31,539.000	30,646.000	32,137.000	30,981.000	30,054.000	32,121.000	30,357.000	31,227.000	31,854.000	32,451.000	30,899.000	30,258.000	30,815.000	30,495.000	30,096.000	31,025.000	30,455.000	30,599.000	32,050.000	30,010.000	29,728.000	32,451.000	30,170.000	28,746.000	29,654.000	30,314.000	27,991.000	30,872.000	31,760.000	30,723.000	30,859.000	29,947.000	30,852.000	32,025.000	31,943.000	30,551.000	32,070.000	31,179.000	32,076.000	0.000	29,359.000	32,573.000	0.000	29,447.000	0.000	29,411.000	29,281.000	31,228.000	30,163.000	32,516.000	31,506.000	31,197.000	30,013.000	30,214.000	30,172.000	0.000	30,177.000	31,703.000	31,544.000	31,264.000	31,730.000	33,537.000	28,630.000	31,525.000	29,042.000	32,401.000	30,606.000	31,829.000	31,311.000	30,293.000	29,895.000	31,373.000	30,067.000	29,812.000	31,003.000	29,303.000	29,966.000	31,923.000	32,426.000	31,179.000	30,876.000	29,462.000	29,776.000	30,412.000	31,855.000	30,557.000	30,489.000	31,168.000	31,648.000	30,346.000	29,069.000	30,407.000	31,792.000	30,593.000	0.000	30,968.000	30,568.000	29,198.000	29,778.000	31,505.000	31,476.000	32,078.000	30,226.000	31,432.000	29,069.000	33,890.000	29,541.000	30,961.000	29,909.000	31,255.000	29,640.000	31,272.000	29,908.000	29,475.000	32,800.000	30,611.000	30,845.000	31,776.000	30,889.000	30,149.000	30,193.000	28,983.000	29,618.000	30,504.000	29,698.000	28,954.000	29,883.000	31,078.000	32,523.000	0.000	28,994.000	30,997.000	29,985.000	28,823.000	31,124.000	30,137.000	30,341.000	30,874.000	0.000	31,523.000	31,229.000	30,695.000	30,565.000	30,609.000	31,108.000	29,752.000	33,183.000	30,650.000	28,282.000	0.000	33,086.000	30,009.000	30,881.000	30,078.000	31,734.000	30,369.000	30,159.000	30,074.000	0.000	29,304.000	31,007.000	30,643.000	31,324.000	29,638.000	31,404.000	31,327.000	32,361.000	31,251.000	32,555.000	32,162.000	32,418.000	29,466.000	30,078.000	31,104.000	30,021.000	0.000	0.000	0.000	29,857.000	30,902.000	29,902.000	29,335.000	29,640.000	31,179.000	0.000	30,394.000	29,495.000	32,187.000	30,866.000	31,791.000	29,094.000	31,892.000	29,613.000	29,192.000	30,656.000	30,543.000	31,156.000	31,262.000	29,263.000	29,928.000	30,129.000	29,075.000	29,912.000	30,617.000	29,099.000	29,381.000	29,853.000	30,976.000	30,949.000	0.000	30,536.000	32,669.000	32,197.000	30,629.000
4406	4407	0.000	22,520.000	0.000	19,417.000	20,620.000	22,296.000	20,572.000	21,790.000	22,652.000	0.000	21,649.000	20,133.000	20,237.000	23,461.000	21,930.000	0.000	20,852.000	0.000	24,295.000	22,284.000	22,641.000	23,244.000	0.000	21,254.000	21,616.000	21,768.000	20,147.000	22,540.000	21,578.000	21,617.000	22,650.000	20,718.000	21,925.000	0.000	21,964.000	21,631.000	23,694.000	24,216.000	22,333.000	22,376.000	20,657.000	18,801.000	22,899.000	21,404.000	22,752.000	0.000	22,706.000	22,165.000	22,005.000	22,146.000	23,443.000	22,486.000	21,912.000	22,525.000	21,935.000	22,550.000	21,225.000	21,066.000	23,678.000	20,803.000	22,956.000	23,824.000	20,162.000	22,106.000	23,847.000	21,914.000	22,314.000	22,525.000	21,892.000	20,797.000	22,435.000	21,872.000	22,537.000	20,527.000	23,014.000	22,209.000	20,217.000	23,419.000	21,475.000	20,738.000	22,614.000	22,265.000	21,124.000	22,634.000	21,447.000	20,363.000	0.000	21,163.000	23,257.000	23,085.000	21,352.000	23,375.000	21,760.000	21,862.000	23,035.000	22,589.000	22,365.000	22,088.000	20,557.000	24,533.000	21,761.000	21,574.000	23,188.000	22,435.000	22,208.000	21,830.000	21,911.000	21,628.000	19,906.000	20,229.000	21,439.000	20,468.000	20,683.000	23,096.000	22,438.000	21,787.000	22,922.000	22,970.000	23,260.000	23,175.000	20,969.000	22,613.000	20,780.000	22,273.000	21,284.000	21,459.000	21,133.000	20,746.000	21,643.000	23,239.000	22,394.000	22,463.000	21,816.000	20,129.000	21,361.000	21,370.000	20,998.000	22,411.000	21,534.000	21,926.000	21,395.000	0.000	0.000	21,246.000	21,735.000	21,831.000	21,846.000	21,772.000	21,609.000	22,519.000	23,284.000	20,206.000	22,729.000	22,260.000	22,871.000	19,253.000	22,984.000	22,189.000	21,983.000	21,435.000	22,250.000	23,321.000	22,080.000	22,586.000	22,890.000	21,836.000	22,062.000	22,366.000	22,436.000	21,320.000	21,799.000	22,649.000	22,319.000	22,655.000	0.000	21,330.000	20,885.000	22,136.000	23,583.000	23,314.000	23,145.000	21,723.000	21,764.000	21,972.000	23,142.000	0.000	23,402.000	21,100.000	22,038.000	21,280.000	20,491.000	21,899.000	21,169.000	22,215.000	22,667.000	19,874.000	0.000	21,545.000	22,084.000	21,238.000	0.000	23,808.000	21,564.000	22,292.000	22,374.000	0.000	21,273.000	22,511.000	21,080.000	21,838.000	21,953.000	22,476.000	21,699.000	21,647.000	24,410.000	22,215.000	21,880.000	18,849.000	22,012.000	21,073.000	19,613.000	22,133.000	0.000	0.000	0.000	22,428.000	22,204.000	21,129.000	21,362.000	23,603.000	21,708.000	23,261.000	20,859.000	21,460.000	22,066.000	22,521.000	21,116.000	21,842.000	21,650.000	22,913.000	22,270.000	20,017.000	21,990.000	22,346.000	21,511.000	23,325.000	21,660.000	22,499.000	23,394.000	21,784.000	21,541.000	21,330.000	20,990.000	21,329.000	21,998.000	21,574.000	0.000	20,411.000	23,610.000	20,528.000	22,131.000
4407	4408	0.000	26,194.000	27,307.000	27,509.000	28,750.000	26,267.000	25,314.000	27,993.000	26,922.000	0.000	29,242.000	27,717.000	28,229.000	26,429.000	29,573.000	25,887.000	26,676.000	0.000	26,549.000	0.000	26,548.000	0.000	25,254.000	29,001.000	28,156.000	26,948.000	26,206.000	27,990.000	29,174.000	28,000.000	25,554.000	0.000	27,691.000	29,617.000	27,662.000	26,840.000	28,792.000	28,816.000	28,235.000	26,802.000	30,359.000	28,098.000	26,914.000	28,758.000	30,514.000	0.000	0.000	28,119.000	28,833.000	26,868.000	28,799.000	26,836.000	28,401.000	30,119.000	26,925.000	28,657.000	27,009.000	27,156.000	28,378.000	28,994.000	27,780.000	25,974.000	0.000	27,000.000	27,117.000	26,871.000	28,834.000	27,156.000	26,741.000	29,776.000	0.000	29,466.000	26,665.000	28,029.000	28,081.000	27,950.000	25,114.000	27,466.000	28,462.000	29,446.000	26,924.000	27,131.000	0.000	27,852.000	28,773.000	26,717.000	0.000	28,064.000	27,737.000	28,716.000	26,668.000	28,994.000	28,125.000	28,118.000	27,060.000	0.000	27,772.000	28,548.000	28,541.000	0.000	0.000	27,751.000	29,796.000	28,642.000	29,404.000	27,114.000	28,124.000	27,583.000	28,189.000	27,511.000	27,942.000	27,210.000	28,531.000	27,189.000	29,183.000	29,218.000	25,107.000	25,589.000	26,507.000	27,822.000	26,878.000	0.000	26,668.000	28,231.000	28,880.000	26,967.000	27,741.000	26,919.000	26,712.000	25,916.000	28,551.000	27,153.000	29,696.000	27,921.000	27,511.000	28,317.000	28,203.000	28,891.000	27,550.000	28,524.000	30,217.000	0.000	28,657.000	26,918.000	28,600.000	25,665.000	0.000	28,783.000	26,542.000	26,275.000	0.000	27,922.000	27,555.000	26,618.000	27,171.000	30,005.000	28,154.000	27,127.000	27,780.000	24,918.000	29,393.000	0.000	28,236.000	27,737.000	0.000	28,389.000	27,514.000	28,313.000	27,381.000	27,350.000	28,906.000	29,022.000	29,114.000	27,111.000	26,802.000	28,293.000	26,969.000	27,294.000	27,093.000	30,059.000	27,449.000	27,054.000	27,780.000	28,915.000	26,159.000	0.000	27,330.000	27,021.000	27,454.000	28,447.000	27,798.000	26,043.000	27,369.000	26,660.000	24,718.000	27,174.000	0.000	26,653.000	27,589.000	28,431.000	26,533.000	28,064.000	29,272.000	26,176.000	27,944.000	28,525.000	28,352.000	29,129.000	29,321.000	28,556.000	26,358.000	27,596.000	29,542.000	29,060.000	28,326.000	26,741.000	27,560.000	26,826.000	26,687.000	26,904.000	26,419.000	27,727.000	0.000	0.000	0.000	29,880.000	29,467.000	27,691.000	26,651.000	28,389.000	27,090.000	28,073.000	27,168.000	29,582.000	0.000	28,532.000	25,294.000	27,633.000	25,696.000	29,042.000	28,136.000	28,000.000	27,258.000	0.000	27,224.000	28,690.000	27,389.000	27,607.000	26,860.000	27,660.000	27,667.000	28,028.000	28,318.000	27,913.000	27,908.000	26,647.000	0.000	27,844.000	0.000	27,938.000	29,125.000
4408	4409	0.000	34,292.000	34,513.000	35,238.000	33,808.000	33,136.000	0.000	33,459.000	34,559.000	0.000	34,144.000	33,621.000	33,457.000	35,222.000	34,902.000	34,432.000	33,498.000	0.000	34,568.000	32,317.000	35,427.000	33,344.000	33,175.000	33,821.000	0.000	34,350.000	33,238.000	34,301.000	34,319.000	34,063.000	34,308.000	34,295.000	34,272.000	35,627.000	34,233.000	33,854.000	32,543.000	34,484.000	34,778.000	36,521.000	35,868.000	34,624.000	0.000	32,694.000	34,280.000	0.000	34,146.000	36,930.000	33,489.000	32,640.000	35,661.000	31,374.000	33,252.000	33,395.000	33,947.000	33,703.000	33,020.000	32,381.000	34,354.000	36,694.000	34,546.000	33,817.000	33,972.000	35,888.000	32,917.000	34,578.000	33,453.000	35,393.000	32,952.000	34,498.000	32,877.000	34,343.000	35,047.000	33,626.000	34,430.000	35,893.000	35,024.000	32,566.000	34,488.000	34,082.000	35,689.000	35,188.000	35,023.000	33,871.000	35,515.000	35,031.000	0.000	36,262.000	36,181.000	32,677.000	34,249.000	34,837.000	34,045.000	33,077.000	32,930.000	34,032.000	37,083.000	36,233.000	33,711.000	33,530.000	35,766.000	33,341.000	31,968.000	35,986.000	33,860.000	34,350.000	34,349.000	36,157.000	32,132.000	32,235.000	31,619.000	35,509.000	35,190.000	33,862.000	34,119.000	35,217.000	34,321.000	35,515.000	35,700.000	34,801.000	0.000	35,247.000	32,367.000	33,804.000	35,280.000	33,424.000	32,946.000	36,169.000	33,785.000	32,590.000	33,732.000	33,671.000	32,318.000	33,894.000	36,265.000	34,039.000	33,964.000	35,357.000	34,690.000	32,280.000	34,320.000	0.000	34,307.000	34,920.000	35,510.000	34,323.000	35,054.000	33,920.000	33,662.000	33,024.000	35,092.000	33,787.000	33,061.000	34,287.000	33,270.000	36,425.000	35,859.000	32,251.000	34,080.000	35,367.000	34,425.000	34,339.000	34,989.000	34,327.000	35,919.000	33,420.000	33,558.000	35,531.000	32,834.000	36,049.000	33,008.000	35,795.000	0.000	32,844.000	31,949.000	31,064.000	32,989.000	33,955.000	34,317.000	33,860.000	34,159.000	33,167.000	35,054.000	0.000	33,500.000	0.000	35,939.000	32,858.000	32,975.000	33,963.000	32,622.000	34,397.000	36,170.000	35,058.000	31,642.000	34,231.000	0.000	34,723.000	32,292.000	34,851.000	34,295.000	0.000	33,697.000	34,096.000	34,110.000	31,697.000	33,497.000	33,781.000	34,789.000	34,075.000	33,913.000	34,862.000	33,795.000	35,676.000	33,811.000	32,689.000	35,906.000	33,839.000	36,443.000	34,295.000	35,693.000	33,835.000	0.000	0.000	0.000	33,929.000	35,264.000	33,635.000	34,227.000	34,271.000	33,868.000	34,398.000	34,429.000	31,701.000	35,007.000	34,737.000	32,391.000	0.000	34,988.000	34,267.000	33,076.000	33,229.000	32,620.000	32,636.000	34,059.000	34,862.000	33,332.000	37,047.000	34,944.000	33,118.000	33,318.000	35,891.000	33,627.000	33,741.000	33,270.000	34,912.000	0.000	36,191.000	32,444.000	33,698.000	34,618.000
4409	4410	0.000	24,610.000	26,208.000	24,220.000	24,632.000	26,736.000	25,099.000	24,706.000	26,968.000	0.000	25,532.000	24,682.000	23,255.000	24,929.000	25,229.000	0.000	0.000	0.000	25,666.000	25,686.000	24,227.000	24,405.000	24,190.000	25,404.000	24,985.000	26,148.000	25,776.000	25,377.000	23,688.000	24,534.000	24,728.000	24,709.000	23,804.000	25,085.000	26,052.000	24,326.000	23,242.000	25,188.000	23,373.000	25,184.000	24,330.000	26,359.000	26,421.000	24,624.000	23,374.000	0.000	26,397.000	25,490.000	25,192.000	0.000	25,317.000	24,938.000	24,880.000	0.000	24,233.000	24,128.000	24,165.000	0.000	24,751.000	0.000	25,285.000	26,458.000	26,834.000	23,961.000	25,325.000	27,166.000	25,928.000	24,997.000	23,940.000	25,500.000	0.000	26,309.000	24,106.000	23,952.000	26,064.000	25,235.000	24,102.000	23,112.000	25,658.000	0.000	24,743.000	24,084.000	27,218.000	25,476.000	24,842.000	25,981.000	0.000	25,206.000	24,023.000	0.000	23,701.000	24,573.000	26,302.000	25,683.000	25,829.000	25,593.000	25,355.000	27,099.000	26,244.000	24,718.000	24,217.000	25,766.000	25,273.000	0.000	25,894.000	26,643.000	24,571.000	24,168.000	24,256.000	24,594.000	24,755.000	24,908.000	23,843.000	27,591.000	26,366.000	26,476.000	22,805.000	26,773.000	23,933.000	23,760.000	24,800.000	24,228.000	24,390.000	27,306.000	25,033.000	27,899.000	25,946.000	24,723.000	28,298.000	25,531.000	25,367.000	24,553.000	25,436.000	24,813.000	24,900.000	25,029.000	26,530.000	25,374.000	23,098.000	26,228.000	23,252.000	0.000	26,166.000	0.000	25,629.000	23,449.000	24,622.000	25,029.000	23,448.000	26,764.000	0.000	24,402.000	24,131.000	23,557.000	24,801.000	25,179.000	24,986.000	24,374.000	25,660.000	0.000	25,413.000	25,987.000	25,940.000	26,689.000	26,900.000	25,128.000	21,654.000	24,466.000	25,580.000	22,929.000	25,509.000	25,977.000	25,099.000	25,378.000	25,228.000	25,098.000	23,692.000	23,635.000	27,281.000	25,215.000	23,434.000	25,159.000	26,729.000	24,443.000	26,914.000	0.000	26,206.000	0.000	24,784.000	25,093.000	25,815.000	23,999.000	26,090.000	23,164.000	25,534.000	25,862.000	0.000	26,000.000	26,075.000	25,834.000	26,163.000	26,251.000	25,841.000	25,398.000	23,269.000	25,197.000	27,055.000	27,311.000	25,149.000	25,555.000	26,179.000	24,848.000	26,902.000	23,311.000	26,377.000	25,935.000	24,972.000	24,023.000	27,186.000	24,881.000	22,919.000	26,037.000	0.000	0.000	0.000	25,116.000	23,605.000	0.000	24,744.000	24,190.000	25,059.000	25,270.000	27,159.000	25,556.000	24,991.000	23,396.000	25,591.000	25,814.000	26,513.000	25,364.000	27,078.000	27,547.000	24,853.000	24,516.000	0.000	24,866.000	24,993.000	23,303.000	25,440.000	23,578.000	25,643.000	25,389.000	25,207.000	0.000	24,192.000	22,704.000	0.000	27,213.000	25,864.000	25,026.000	23,390.000

Python Project 3: HR Analytics Case Study¶

Table of contents

1 Case description

2 Goal of the case study

3 Data analysis pipeline

4 Important libraries

5 Importing and validating data

6 Transforming data

6.1 Processing working time

6.2 Recoding values

6.3 Joining tables

6.4 Summary statistics

6.5 Final table

7 Exploratory data analysis

7.1 Univariate analysis

7.2 Bivariate analysis

8 Regression analysis

8.1 Preparing data for logistic regression

8.2 Fitting explanatory models

9 Validating forecasting power and model choice

10 Interpreting results

11 Conclusion & executive summary

	Variable	Meaning	Levels
0	Age	Age of the employee
1	Attrition	Whether the employee left in the previous year...
2	BusinessTravel	How frequently the employees travelled for bus...
3	Department	Department in company
4	DistanceFromHome	Distance from home in kms
5	Education	Education Level	1 'Below College'
6			2 'College'
7			3 'Bachelor'
8			4 'Master'
9			5 'Doctor'
10	EducationField	Field of education
11	EmployeeCount	Employee count
12	EmployeeNumber	Employee number/id
13	EnvironmentSatisfaction	Work Environment Satisfaction Level	1 'Low'
14			2 'Medium'
15			3 'High'
16			4 'Very High'
17	Gender	Gender of employee
18	JobInvolvement	Job Involvement Level	1 'Low'
19			2 'Medium'
20			3 'High'
21			4 'Very High'
22	JobLevel	Job level at company on a scale of 1 to 5
23	JobRole	Name of job role in company
24	JobSatisfaction	Job Satisfaction Level	1 'Low'
25			2 'Medium'
26			3 'High'
27			4 'Very High'
28	MaritalStatus	Marital status of the employee
29	MonthlyIncome	Monthly income in rupees per month
30	NumCompaniesWorked	Total number of companies the employee has wor...
31	Over18	Whether the employee is above 18 years of age ...
32	PercentSalaryHike	Percent salary hike for last year
33	PerformanceRating	Performance rating for last year	1 'Low'
34			2 'Good'
35			3 'Excellent'
36			4 'Outstanding'
37	RelationshipSatisfaction	Relationship satisfaction level	1 'Low'
38			2 'Medium'
39			3 'High'
40			4 'Very High'
41	StandardHours	Standard hours of work for the employee
42	StockOptionLevel	Stock option level of the employee
43	TotalWorkingYears	Total number of years the employee has worked ...
44	TrainingTimesLastYear	Number of times training was conducted for thi...
45	WorkLifeBalance	Work life balance level	1 'Bad'
46			2 'Good'
47			3 'Better'
48			4 'Best'
49	YearsAtCompany	Total number of years spent at the company by ...
50	YearsSinceLastPromotion	Number of years since last promotion
51	YearsWithCurrManager	Number of years under current manager

	Age	Attrition	BusinessTravel	Department	DistanceFromHome	Education	EducationField	EmployeeCount	EmployeeID	Gender	JobLevel	JobRole	MaritalStatus	MonthlyIncome	NumCompaniesWorked	Over18	PercentSalaryHike	StandardHours	StockOptionLevel	TotalWorkingYears	TrainingTimesLastYear	YearsAtCompany	YearsSinceLastPromotion	YearsWithCurrManager
0	51	No	Travel_Rarely	Sales	6	2	Life Sciences	1	1	Female	1	Healthcare Representative	Married	131160	1.000	Y	11	8	0	1.000	6	1	0	0
1	31	Yes	Travel_Frequently	Research & Development	10	1	Life Sciences	1	2	Female	1	Research Scientist	Single	41890	0.000	Y	23	8	1	6.000	3	5	1	4
2	32	No	Travel_Frequently	Research & Development	17	4	Other	1	3	Male	4	Sales Executive	Married	193280	1.000	Y	15	8	3	5.000	2	5	0	3
3	38	No	Non-Travel	Research & Development	2	5	Life Sciences	1	4	Male	3	Human Resources	Married	83210	3.000	Y	11	8	3	13.000	5	8	7	5
4	32	No	Travel_Rarely	Research & Development	10	1	Medical	1	5	Male	1	Sales Executive	Single	23420	4.000	Y	12	8	2	9.000	2	6	0	4

	EmployeeID	Avg_duration_sec
0	1	23,505.626
1	2	25,030.679
2	3	23,320.374
3	4	23,228.458
4	5	26,952.103

	Age	Attrition	BusinessTravel	Department	DistanceFromHome	Education	EducationField	EmployeeCount	EmployeeID	Gender	JobLevel	JobRole	MaritalStatus	MonthlyIncome	NumCompaniesWorked	Over18	PercentSalaryHike	StandardHours	StockOptionLevel	TotalWorkingYears	TrainingTimesLastYear	YearsAtCompany	YearsSinceLastPromotion	YearsWithCurrManager
0	51	No	Travel_Rarely	Sales	6	College	Life Sciences	1	1	Female	1	Healthcare Representative	Married	131160	1.000	Y	11	8	0	1.000	6	1	0	0
1	31	Yes	Travel_Frequently	Research & Development	10	Below College	Life Sciences	1	2	Female	1	Research Scientist	Single	41890	0.000	Y	23	8	1	6.000	3	5	1	4
2	32	No	Travel_Frequently	Research & Development	17	Master	Other	1	3	Male	4	Sales Executive	Married	193280	1.000	Y	15	8	3	5.000	2	5	0	3
3	38	No	Non-Travel	Research & Development	2	Doctor	Life Sciences	1	4	Male	3	Human Resources	Married	83210	3.000	Y	11	8	3	13.000	5	8	7	5
4	32	No	Travel_Rarely	Research & Development	10	Below College	Medical	1	5	Male	1	Sales Executive	Single	23420	4.000	Y	12	8	2	9.000	2	6	0	4

	EmployeeID	EnvironmentSatisfaction	JobSatisfaction	WorkLifeBalance
0	1	High	Very High	Good
1	2	High	Medium	Best
2	3	Medium	Medium	Bad
3	4	Very High	Very High	Better
4	5	Very High	Low	Better

	EmployeeID	JobInvolvement	PerformanceRating
0	1	High	Excellent
1	2	Medium	Outstanding
2	3	High	Excellent
3	4	Medium	Excellent
4	5	High	Excellent

	Age	DistanceFromHome	EmployeeCount	EmployeeID	JobLevel	MonthlyIncome	NumCompaniesWorked	PercentSalaryHike	StandardHours	StockOptionLevel	TotalWorkingYears	TrainingTimesLastYear	YearsAtCompany	YearsSinceLastPromotion	YearsWithCurrManager	Avg_duration_sec
count	4,410.000	4,410.000	4,410.000	4,410.000	4,410.000	4,410.000	4,391.000	4,410.000	4,410.000	4,410.000	4,401.000	4,410.000	4,410.000	4,410.000	4,410.000	4,410.000
mean	36.920	9.190	1.000	2,205.500	2.060	65,029.310	2.690	15.210	8.000	0.790	11.280	2.800	7.010	2.190	4.120	25,033.590
std	9.130	8.110	0.000	1,273.200	1.110	47,068.890	2.500	3.660	0.000	0.850	7.780	1.290	6.130	3.220	3.570	4,553.010
min	18.000	1.000	1.000	1.000	1.000	10,090.000	0.000	11.000	8.000	0.000	0.000	0.000	0.000	0.000	0.000	18,541.080
25%	30.000	2.000	1.000	1,103.250	1.000	29,110.000	1.000	12.000	8.000	0.000	6.000	2.000	3.000	0.000	2.000	21,491.850
50%	36.000	7.000	1.000	2,205.500	2.000	49,190.000	2.000	14.000	8.000	1.000	10.000	3.000	5.000	1.000	3.000	23,999.790
75%	43.000	14.000	1.000	3,307.750	3.000	83,800.000	4.000	18.000	8.000	1.000	15.000	3.000	9.000	3.000	7.000	27,040.800
max	60.000	29.000	1.000	4,410.000	5.000	199,990.000	9.000	25.000	8.000	3.000	40.000	6.000	40.000	15.000	17.000	37,428.560

	Age	DistanceFromHome	JobLevel	MonthlyIncome	NumCompaniesWorked	PercentSalaryHike	StockOptionLevel	TotalWorkingYears	TrainingTimesLastYear	YearsAtCompany	YearsSinceLastPromotion	YearsWithCurrManager	Avg_duration_sec
count	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000	4,300.000
mean	36.927	9.198	2.067	65,059.844	2.690	15.211	0.795	11.285	2.796	7.026	2.190	4.133	25,040.507
std	9.147	8.097	1.107	47,045.399	2.496	3.663	0.854	7.790	1.290	6.148	3.231	3.566	4,557.704
min	18.000	1.000	1.000	10,090.000	0.000	11.000	0.000	0.000	0.000	0.000	0.000	0.000	18,541.076
25%	30.000	2.000	1.000	29,260.000	1.000	12.000	0.000	6.000	2.000	3.000	0.000	2.000	21,488.723
50%	36.000	7.000	2.000	49,360.000	2.000	14.000	1.000	10.000	3.000	5.000	1.000	3.000	24,010.996
75%	43.000	14.000	3.000	83,802.500	4.000	18.000	1.000	15.000	3.000	9.250	3.000	7.000	27,080.194
max	60.000	29.000	5.000	199,990.000	9.000	25.000	3.000	40.000	6.000	40.000	15.000	17.000	37,428.557

Dep. Variable:	Attrition_Yes	No. Observations:	3440
Model:	GLM	Df Residuals:	3389
Model Family:	Binomial	Df Model:	50
Link Function:	Logit	Scale:	1.0000
Method:	newton	Log-Likelihood:	-1153.0
Date:	Mon, 29 Aug 2022	Deviance:	2306.1
Time:	00:11:35	Pearson chi2:	5.40e+03
No. Iterations:	4	Pseudo R-squ. (CS):	0.1867
Covariance Type:	nonrobust

	coef	std err	z	P>\|z\|	[0.025	0.975]
const	0.8988	0.806	1.115	0.265	-0.681	2.479
Age	-0.0328	0.009	-3.835	0.000	-0.050	-0.016
DistanceFromHome	-0.0071	0.007	-1.029	0.304	-0.021	0.006
JobLevel	-0.1080	0.051	-2.105	0.035	-0.209	-0.007
MonthlyIncome	-0.0023	0.001	-1.885	0.059	-0.005	9.04e-05
NumCompaniesWorked	0.1509	0.023	6.456	0.000	0.105	0.197
PercentSalaryHike	0.0082	0.024	0.348	0.728	-0.038	0.054
StockOptionLevel	-0.0846	0.065	-1.303	0.193	-0.212	0.043
TotalWorkingYears	-0.0870	0.015	-5.658	0.000	-0.117	-0.057
TrainingTimesLastYear	-0.1558	0.043	-3.602	0.000	-0.241	-0.071
YearsAtCompany	0.0431	0.022	1.973	0.048	0.000	0.086
YearsSinceLastPromotion	0.1789	0.025	7.216	0.000	0.130	0.228
YearsWithCurrManager	-0.1793	0.028	-6.400	0.000	-0.234	-0.124
Avg_duration_hr	0.4684	0.041	11.474	0.000	0.388	0.548
BusinessTravel_Travel_Frequently	1.5829	0.245	6.468	0.000	1.103	2.063
BusinessTravel_Travel_Rarely	0.8201	0.229	3.586	0.000	0.372	1.268
Department_Research & Development	-0.6684	0.322	-2.075	0.038	-1.300	-0.037
Department_Sales	-0.8224	0.339	-2.426	0.015	-1.487	-0.158
Education_Bachelor	-0.1246	0.183	-0.681	0.496	-0.483	0.234
Education_College	0.0169	0.199	0.085	0.933	-0.374	0.408
Education_Doctor	-0.5862	0.374	-1.567	0.117	-1.319	0.147
Education_Master	-0.1102	0.191	-0.576	0.565	-0.485	0.265
EducationField_Life Sciences	-0.6559	0.434	-1.510	0.131	-1.507	0.195
EducationField_Marketing	-0.8862	0.479	-1.850	0.064	-1.825	0.053
EducationField_Medical	-0.8116	0.435	-1.866	0.062	-1.664	0.041
EducationField_Other	-0.9081	0.485	-1.871	0.061	-1.860	0.043
EducationField_Technical Degree	-0.9362	0.467	-2.007	0.045	-1.851	-0.022
Gender_Male	0.0336	0.113	0.298	0.766	-0.187	0.254
JobRole_Healthcare Representative	0.0453	0.359	0.126	0.899	-0.658	0.748
JobRole_Laboratory Technician	0.3221	0.328	0.982	0.326	-0.321	0.965
JobRole_Manager	-0.1275	0.372	-0.343	0.732	-0.856	0.601
JobRole_Manufacturing Director	-0.4609	0.361	-1.276	0.202	-1.169	0.247
JobRole_Research Director	0.8607	0.361	2.385	0.017	0.153	1.568
JobRole_Research Scientist	0.3895	0.323	1.206	0.228	-0.243	1.022
JobRole_Sales Executive	0.4848	0.321	1.510	0.131	-0.144	1.114
JobRole_Sales Representative	-0.0980	0.378	-0.259	0.796	-0.840	0.643
MaritalStatus_Divorced	-1.0988	0.161	-6.842	0.000	-1.414	-0.784
MaritalStatus_Married	-0.8681	0.122	-7.103	0.000	-1.108	-0.629
EnvironmentSatisfaction_High	-0.8254	0.149	-5.522	0.000	-1.118	-0.532
EnvironmentSatisfaction_Medium	-0.7021	0.166	-4.222	0.000	-1.028	-0.376
EnvironmentSatisfaction_Very High	-1.0805	0.155	-6.983	0.000	-1.384	-0.777
JobSatisfaction_High	-0.5521	0.149	-3.713	0.000	-0.844	-0.261
JobSatisfaction_Medium	-0.5458	0.167	-3.274	0.001	-0.872	-0.219
JobSatisfaction_Very High	-1.1144	0.158	-7.075	0.000	-1.423	-0.806
WorkLifeBalance_Best	-1.2556	0.254	-4.945	0.000	-1.753	-0.758
WorkLifeBalance_Better	-1.3119	0.205	-6.407	0.000	-1.713	-0.911
WorkLifeBalance_Good	-0.9940	0.220	-4.520	0.000	-1.425	-0.563
JobInvolvement_High	-0.4064	0.211	-1.924	0.054	-0.820	0.008
JobInvolvement_Medium	-0.1043	0.225	-0.464	0.643	-0.545	0.336
JobInvolvement_Very High	-0.0610	0.261	-0.234	0.815	-0.572	0.450
PerformanceRating_Outstanding	0.0567	0.236	0.241	0.810	-0.405	0.519

	coef	std err	z	P>\|z\|	[0.025	0.975]
const	-0.0732	0.531	-0.138	0.890	-1.113	0.967
Age	-0.0305	0.008	-3.700	0.000	-0.047	-0.014
JobLevel	-0.1301	0.050	-2.591	0.010	-0.229	-0.032
NumCompaniesWorked	0.1455	0.023	6.449	0.000	0.101	0.190
TotalWorkingYears	-0.0822	0.015	-5.469	0.000	-0.112	-0.053
TrainingTimesLastYear	-0.1381	0.042	-3.323	0.001	-0.220	-0.057
YearsAtCompany	0.0367	0.022	1.691	0.091	-0.006	0.079
YearsSinceLastPromotion	0.1630	0.024	6.698	0.000	0.115	0.211
YearsWithCurrManager	-0.1647	0.027	-6.026	0.000	-0.218	-0.111
Avg_duration_hr	0.4725	0.040	11.874	0.000	0.395	0.551
BusinessTravel_Travel_Frequently	1.6007	0.244	6.552	0.000	1.122	2.080
BusinessTravel_Travel_Rarely	0.8996	0.229	3.929	0.000	0.451	1.348
Department_Research & Development	-1.0192	0.215	-4.749	0.000	-1.440	-0.599
Department_Sales	-1.1537	0.227	-5.083	0.000	-1.599	-0.709
EducationField_Technical Degree	-0.1943	0.200	-0.974	0.330	-0.585	0.197
JobRole_Research Director	0.6024	0.206	2.924	0.003	0.199	1.006
MaritalStatus_Divorced	-1.1440	0.155	-7.387	0.000	-1.448	-0.840
MaritalStatus_Married	-0.8944	0.118	-7.563	0.000	-1.126	-0.663
EnvironmentSatisfaction_High	-0.8299	0.147	-5.663	0.000	-1.117	-0.543
EnvironmentSatisfaction_Medium	-0.6798	0.161	-4.227	0.000	-0.995	-0.365
EnvironmentSatisfaction_Very High	-1.0508	0.151	-6.956	0.000	-1.347	-0.755
JobSatisfaction_High	-0.5181	0.144	-3.594	0.000	-0.801	-0.236
JobSatisfaction_Medium	-0.4779	0.162	-2.952	0.003	-0.795	-0.161
JobSatisfaction_Very High	-1.0723	0.154	-6.985	0.000	-1.373	-0.771
WorkLifeBalance_Best	-1.0702	0.246	-4.358	0.000	-1.552	-0.589
WorkLifeBalance_Better	-1.2202	0.198	-6.156	0.000	-1.609	-0.832
WorkLifeBalance_Good	-0.8960	0.212	-4.229	0.000	-1.311	-0.481

	coef	std err	z	P>\|z\|	[0.025	0.975]
const	-0.0608	0.531	-0.115	0.909	-1.101	0.979
Age	-0.0311	0.008	-3.784	0.000	-0.047	-0.015
JobLevel	-0.1289	0.050	-2.568	0.010	-0.227	-0.031
NumCompaniesWorked	0.1463	0.023	6.485	0.000	0.102	0.191
TotalWorkingYears	-0.0826	0.015	-5.494	0.000	-0.112	-0.053
TrainingTimesLastYear	-0.1372	0.042	-3.303	0.001	-0.219	-0.056
YearsAtCompany	0.0372	0.022	1.717	0.086	-0.005	0.080
YearsSinceLastPromotion	0.1616	0.024	6.661	0.000	0.114	0.209
YearsWithCurrManager	-0.1645	0.027	-6.009	0.000	-0.218	-0.111
Avg_duration_hr	0.4726	0.040	11.872	0.000	0.395	0.551
BusinessTravel_Travel_Frequently	1.6000	0.244	6.554	0.000	1.122	2.078
BusinessTravel_Travel_Rarely	0.8959	0.229	3.917	0.000	0.448	1.344
Department_Research & Development	-1.0234	0.214	-4.773	0.000	-1.444	-0.603
Department_Sales	-1.1593	0.227	-5.112	0.000	-1.604	-0.715
JobRole_Research Director	0.6024	0.206	2.921	0.003	0.198	1.007
MaritalStatus_Divorced	-1.1430	0.155	-7.381	0.000	-1.446	-0.839
MaritalStatus_Married	-0.8905	0.118	-7.543	0.000	-1.122	-0.659
EnvironmentSatisfaction_High	-0.8337	0.146	-5.692	0.000	-1.121	-0.547
EnvironmentSatisfaction_Medium	-0.6825	0.161	-4.244	0.000	-0.998	-0.367
EnvironmentSatisfaction_Very High	-1.0509	0.151	-6.958	0.000	-1.347	-0.755
JobSatisfaction_High	-0.5223	0.144	-3.627	0.000	-0.804	-0.240
JobSatisfaction_Medium	-0.4803	0.162	-2.968	0.003	-0.797	-0.163
JobSatisfaction_Very High	-1.0753	0.153	-7.012	0.000	-1.376	-0.775
WorkLifeBalance_Best	-1.0730	0.246	-4.370	0.000	-1.554	-0.592
WorkLifeBalance_Better	-1.2206	0.198	-6.161	0.000	-1.609	-0.832
WorkLifeBalance_Good	-0.9032	0.212	-4.267	0.000	-1.318	-0.488

	EmployeeID	Forecast Attrition Probability
1808	1808	0.195
21	21	0.014
2214	2214	0.277
1057	1057	0.062
3291	3291	0.080

	EmployeeID	Forecast Attrition Probability
1808	1808	0.198
21	21	0.010
2214	2214	0.310
1057	1057	0.063
3291	3291	0.083

	coef	Realized effect
const	-0.061	0.941
Age	-0.031	0.969
JobLevel	-0.129	0.879
NumCompaniesWorked	0.146	1.158
TotalWorkingYears	-0.083	0.921
TrainingTimesLastYear	-0.137	0.872
YearsAtCompany	0.037	1.038
YearsSinceLastPromotion	0.162	1.175
YearsWithCurrManager	-0.165	0.848
Avg_duration_hr	0.473	1.604
BusinessTravel_Travel_Frequently	1.600	4.953
BusinessTravel_Travel_Rarely	0.896	2.450
Department_Research & Development	-1.023	0.359
Department_Sales	-1.159	0.314
JobRole_Research Director	0.602	1.826
MaritalStatus_Divorced	-1.143	0.319
MaritalStatus_Married	-0.890	0.410
EnvironmentSatisfaction_High	-0.834	0.434
EnvironmentSatisfaction_Medium	-0.682	0.505
EnvironmentSatisfaction_Very High	-1.051	0.350
JobSatisfaction_High	-0.522	0.593
JobSatisfaction_Medium	-0.480	0.619
JobSatisfaction_Very High	-1.075	0.341
WorkLifeBalance_Best	-1.073	0.342
WorkLifeBalance_Better	-1.221	0.295
WorkLifeBalance_Good	-0.903	0.405