import pandas as pd
pd.set_option('display.mpl_style', 'default') # Make the graphs a bit prettier
figsize(15, 5)

bikes = pd.read_csv('../data/bikes.csv', sep=';', encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date')
bikes['Berri 1'].plot()

berri_bikes = bikes[['Berri 1']]

berri_bikes[:5]

berri_bikes.index

berri_bikes.index.day

berri_bikes.index.weekday

berri_bikes['weekday'] = berri_bikes.index.weekday
berri_bikes[:5]

weekday_counts = berri_bikes.groupby('weekday').aggregate(sum)
weekday_counts

weekday_counts.index = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
weekday_counts

weekday_counts.plot(kind='bar')

bikes = pd.read_csv('../data/bikes.csv', 
                    sep=';', encoding='latin1', 
                    parse_dates=['Date'], dayfirst=True, 
                    index_col='Date')
# Add the weekday column
berri_bikes = bikes[['Berri 1']]
berri_bikes['weekday'] = berri_bikes.index.weekday

# Add up the number of cyclists by weekday, and plot!
weekday_counts = berri_bikes.groupby('weekday').aggregate(sum)
weekday_counts.index = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']
weekday_counts.plot(kind='bar')