How to compare two dataframe timeindex and exclude the NaN rows to get the same length?-CodePudding

I have two time series dataframes. One has some nan values. I can filter out the nans with dropna() and after that I get some missing hours in the time series. What I want is to compare this dataframe timeindex with another dataframe timeindex and exclude the missing hours from the first dataframe. Say like I have 8 rows in the first dataframe and the second dataframe has 6 after dropna, I also want to remove this 2 row with the corresponding timeindex hour in dataframe one. How can I do that?

Dataframe 1:

                              values_1
                                                       
2019-05-07 01:00:00 00:00     50.5
2019-05-07 02:00:00 00:00     45.0
2019-05-07 03:00:00 00:00     50.4
2019-05-07 04:00:00 00:00     61.9
2019-05-07 05:00:00 00:00     34.9
2019-05-07 06:00:00 00:00     23.9
2019-05-07 07:00:00 00:00     68.4
2019-05-07 08:00:00 00:00     85.4

Dataframe 2

                              values_2
                                                       
2019-05-07 01:00:00 00:00     43.5
2019-05-07 02:00:00 00:00     23.0
2019-05-07 03:00:00 00:00     86.4
2019-05-07 04:00:00 00:00     62.9
2019-05-07 05:00:00 00:00     NaN
2019-05-07 06:00:00 00:00     65.9
2019-05-07 07:00:00 00:00     NaN
2019-05-07 08:00:00 00:00     32.4

Now I want to compare this with Dataframe 1 and exclude the 2 rows with the NaN from Dataframe 2 in Dataframe 1.

What I want:

Dataframe 1_filtered:

                              values_1
                                                       
2019-05-07 01:00:00 00:00     50.5
2019-05-07 02:00:00 00:00     45.0
2019-05-07 03:00:00 00:00     50.4
2019-05-07 04:00:00 00:00     61.9
2019-05-07 06:00:00 00:00     23.9
2019-05-07 08:00:00 00:00     85.4

Dataframe 2_filtered

                              values_2
                                                       
2019-05-07 01:00:00 00:00     43.5
2019-05-07 02:00:00 00:00     23.0
2019-05-07 03:00:00 00:00     86.4
2019-05-07 04:00:00 00:00     62.9
2019-05-07 06:00:00 00:00     65.9
2019-05-07 08:00:00 00:00     32.4

CodePudding user response：

You can just pass the index of the filtered df2 to df1

df1.loc[df2.dropna().index]