Filter a column based on another column in another df

Question

Say I have a df where time is in time format.

Time lat lon
1/10/2022 11:30 22.12 113.15
1/10/2022 11:32 22.13 113.14
1/10/2022 11:45 22.15 113.19
1/10/2022 12:01 22.11 113.13
1/10/2022 12:11 22.17 113.19

Here is the code

    df['Time']= pd.to_datetime(df['Time'])
    df['Time'] = df['Time'].dt.time

Now, I would like to filter those rows which contain the following time:

timeList = {'Time': ['1/10/2022 11:30', '1/10/2022 11:45', '1/10/2022 12:01']}
    dates = pd.DataFrame(data=timeList)
    dates['Time'] = pd.to_datetime(dates.stack(), format='%d/%m/%Y %H:%M').unstack()
    dates['Time'] = dates['Time'].dt.time

I tried to use isin but it only works with list. Is there a simple way I can do this?

The expected result

Time lat lon
1/10/2022 11:30 22.12 113.15
1/10/2022 11:45 22.15 113.19
1/10/2022 12:01 22.11 113.13

Can you add your isin not working solution to question? It should working , another idea is inner join by merge. — jezrael, Oct 24 '22 at 06:54
Use `out = df[df['Time'].dt.time.isin(dates['Time'].dt.time)]` — jezrael, Oct 24 '22 at 06:59

score 1 · Accepted Answer · answered Oct 24 '22 at 06:57

1

If you want to use isin it is a better idea to use str:

df[df['Time'].astype(str).isin(dates['Time'].astype(str))]

answered Oct 24 '22 at 06:57

Nuri Taş

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Filter a column based on another column in another df

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