I have another issue with summing up a column (Python - Pandas)

I have a data frame "new" with Dates from a periods of 5 days. The 'Dates' column is the type datetime64[ns]. I try to filter the data frame by date, for example "all values between 2021-10-10 and 2021-10-15" or "all values after 2021-10-14" etc. No matter what I try, I get error messages. Starting with:

mask = (new['Date'] > '2021-10-10') & (df['Date'] <= '2021-10-15')

I get:

TypeError: '<=' not supported between instances of 'date time.date' and 'str'

After this error I try to transform the slices, following the advice "The thing is you want to slice using Strings '2017-07-07' while your index is of type date time.date. Your slices should be of this type too. You can do this by defining your start date and end date as follows:

import pandas as pd
startdate = pd. to_datetime("2017-7-7").date()
enddate = pd. to_datetime("2017-7-10").date()
df.loc[startdate:enddate]

(I remove the spaces of course) But now I get

TypeError: '<' not supported between instances of 'int' and 'date time.date'

I just want to sort and filter my data frame by different time periods. Thanks for any help

CodePudding user response：

Just to ensure everything is in the same format use pd.to_datetime() and using infer_datetime_format=True helps with the formatting and speeds up the function too:

df['Date'] = pd.to_datetime(df['Date'],infer_datetime_format=True)

df = df[(df['Date'] > pd.to_datetime('2021-10-10')) & (df['Date'] <= pd.to_datetime('2021-10-15'))]