Converting Month name to full date pandas-CodePudding

My df is like this

import pandas as pd
import numpy as np

df = pd.DataFrame({'Date data':['actual september 2019', 'September'],
                   'Date':['2019.12','2019.12']})

I would like to create a new columne and if df['Date data'] is 'September' I would like to write df['new_column'] = '2019.09'

the expected output is

import pandas as pd
import numpy as np

df = pd.DataFrame({'Date data':['actual september 2019', 'September'],
                   'Date':['2019.12','2019.12'], 'New_column':['2019.12','2019.09']})

i created a variable

month = ('April', 'December', 'February', 'January', 'July-August', 'June', 'March', 'May', 'November', ' October', 'September')

and

df.loc[df['Date data'].isin(month) , 'new_col'] = '2019.9

CodePudding user response：

IIUC, you want to create a new column similar to Date. Rows where Date data is equal to a month I change the column number in Date and put it in the new column.

If all months start with a capital letter (easy):

months = ['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December']
df['New_column'] = df['Date']
for nr, month in enumerate(months):
    df.loc[df['Date data'].eq(month), 'New_column'] = df['Date'].str[:5]   str(nr   1).zfill(2)

If months can be with or without capital letter, use .lower():

months = ['january', 'february', 'march', 'april', 'may', 'june', 'july', 'august', 'september', 'october', 'november', 'december']
df['New_column'] = df['Date']
for nr, month in months:
    df.loc[df['Date data'].str.lower().eq(month), 'New_column'] = df['Date'].str[:5]   str(nr   1).zfill(2)

Output:

               Date data     Date New_column
0  actual september 2019  2019.12    2019.12
1              September  2019.12    2019.09

CodePudding user response：

IIUC, you can use:

from calendar import month_name

mapper = {m.lower(): f'{i:02d}' for i,m in enumerate(month_name)}

df['New_column'] = (df['Date data'].str.lower()
                    .map(mapper)
                    .radd('2019.')
                    .fillna(df['Date'])
                    )

example:

               Date data     Date New_column
0  actual september 2019  2019.12    2019.12
1              September  2019.12    2019.09
2                  ApRil  2019.12    2019.04