I have a pandas dataframe with date index. Like this

                  A         B        C
     date
  2021-04-22      2         1        3
  2021-05-22      3         2        4 
  2021-06-22      4         3        5
  2021-07-22      5         4        6
  2021-08-22      6         5        7     

I want to create a new dataframe that selects rows that are only for 2 days previous for a given date. So for example if I give selected = '2021-08-22', what I need is a new dataframe like below

                  A         B        C
     date
  2021-07-22      5         4        6
  2021-08-22      6         5        7

can someone please help me with this? Many thanks for your help

CodePudding user response：

I'm assuming that you meant months instead of days.

You can use the df.apply method in order to filter the dataframe rows with a function.

Here is a function that received the inputs you described and returns the new dataframe:

Working example

def filter_df(df, date, num_months):
    def diff_month(row):
        date1 = datetime.strptime(row["date"], '%Y-%m-%d')
        date2 = datetime.strptime(date, '%Y-%m-%d')
        return ((date1.year - date2.year) * 12   date1.month - date2.month)

    return df[df.apply(diff_month, axis=1) > - num_months]


print(filter_df(df, "2021-08-22", 2))

CodePudding user response：

You can convert convert the index to DatetimeIndex, then use df[start_date : end_date]

df.index = pd.to_datetime(df.index)
selected = '2021-08-22'
res = df[(pd.to_datetime(selected)-pd.Timedelta(days=2)) : selected]

print(res)

            A  B  C
2021-08-22  6  5  7