Change and update values in a pandas dataframe-CodePudding

I am working with a bigger dataframe of which I need to select a time interval, modify the values and update them in this dataframe:

df = pd.DataFrame({'datetime': ['2020-09-01T00:15:00.000000000', '2020-09-01T00:30:00.000000000',
       '2020-09-01T00:45:00.000000000', ...,
       '2020-09-30T23:30:00.000000000', '2020-09-30T23:45:00.000000000',
       '2020-10-01T00:00:00.000000000'],
                          'p': [407.4 , 410.76, 411.6 , ..., 478.8 , 456.12, 451.08],
                          'q': [47.88, 52.08, 53.76, ..., 77.28, 68.04, 63.84]})

For that I selected the desired interval from the function pd.between_time ,modified the values and stored them in a smaller dataframe.:

df1 = (df.between_time(start_time='07:15:00',end_time='17:00:00')).reset_index()

Now I would like to "paste" these values into my larger dataframe. How could I do that? I tested the functions pd.uptade, pd.merge, pd.join but I must be applying them incorrectly because there was loss of information:

df.update(df1)

CodePudding user response：

maybe you can use np.where to update the values ? For example, I create new column, but you can overwrite old one:

df.datetime = pd.to_datetime(df.datetime)
df.set_index('datetime', inplace = True)


df['new_p'] = np.where(df.index.isin(df.between_time(start_time='00:15:00',end_time='00:30:00').index), 99999, df['p'])

Output: