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import pandas as pd
import datetime as dt

booksv2 = pd.read_csv('book1.csv')

booksv2['Start'] = booksv2['Start'].apply(lambda x: dt.datetime.strptime(str(x),'%d/%m/%Y'))
booksv2['End'] = booksv2['End'].apply(lambda x: dt.datetime.strptime(str(x),'%d/%m/%Y'))
min_date = min(list(booksv2['Start'])+list(booksv2['End']))
max_date = max(list(booksv2['Start'])+list(booksv2['End']))
#year = min_date.year

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def date_generator(from_date,to_date):
    while from_date<=to_date:
        yield from_date
        from_date = from_date + dt.timedelta(days=1)
        
# create a new df with 2 columns
# col1 : Title, col2: DateRead
Title = []
Date = []
for index,row in booksv2.iterrows():

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# create a df with date from 1st to last day of year from min_year
dateList = pd.DataFrame(list(date_generator(dt.datetime(year,1,1,0,0,0),dt.datetime(year,12,31,0,0,0))),columns=['Date'])
dateList.Date = dateList.Date.astype('O')

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# Adding needed columns
bookDf['DateOrig'] = bookDf['Date']
bookDf['Day'] = bookDf['Date'].apply(lambda x: x.day)
bookDf['Month'] = bookDf['Date'].apply(lambda x: dt.datetime.strftime(x,'%b'))
bookDf['DOW'] = bookDf['Date'].apply(lambda x: dt.datetime.strftime(x,'%a'))
bookDf['Month_num'] = bookDf['Date'].apply(lambda x: x.month)
bookDf['DOW_num'] = bookDf['Date'].apply(lambda x: x.weekday())
bookDf['Week_num'] = bookDf['Date'].apply(lambda x: int(dt.datetime.strftime(x,'%W')))

#add proxy for different colours

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# set colors
cmap=['white','red','orange','yellow','green','blue',
      'indigo','violet','purple','grey','pink',
      'brown','black']

f, ax = plt.subplots(figsize=(6, 18))

# drop duplicates for bookDf **End of book A is the start of book B
df = bookDf.copy()
df.drop_duplicates(['Date'],inplace=True)