I have two dataframes. Here is dwpjp.head():
| jp_number | |
|---|---|
| 0 | 25146315052147720191 |
| 1 | 57225427599900052634 |
| 2 | 86076681691411639833 |
| 3 | 50491824499499656478 |
| 4 | 95588382889227620465 |
and ct_data.head():
| imjp_number | imct_id | |
|---|---|---|
| 0 | 23605308039805192764 | x1E5e3ukRyEFRT6SUAF6lg|d543d3d064da465b8576d87 |
| 1 | 57225427599900052634 | aa0d2dac654d4154bf7c09f73faeaf62|-vf6738ee3bed |
| 2 | 53733358271401869469 | 6FfHZRoiWs2VO02Pruk07A|__g3d877adf9d154637be26 |
| 3 | 50491824499499656478 | __gbe204670ca784a01b7207b42a7e5a5d3|54e2c39cd3 |
| 4 | 82143248133286027306 | __g1114a30c6ea548a2a83d5a51718ff0fd|773840905c |
I want two new dataframes cct_data, and dct_data from ct_data. The ct_data dataframe should be split on the condition if the jp_number is present in the dwbjp dataframe then put into cct_data, otherwise put into dct_data.
I tried this for common jp_number present in dwpjp:
cct_data = ct_data[ct_data.isin(dwpjp).any(1).values]
and for the other I negated the condition as follows:
dct_data = ct_data[~[ct_data.isin(dwpjp).any(1).values]]
but results are not getting as below.
cct_data
| imjp_number | imct_id | |
|---|---|---|
| 0 | 57225427599900052634 | aa0d2dac654d4154bf7c09f73faeaf62|-vf6738ee3bed |
| 1 | 50491824499499656478 | __gbe204670ca784a01b7207b42a7e5a5d3|54e2c39cd3 |
and dct_data:
| imjp_number | imct_id | |
|---|---|---|
| 0 | 23605308039805192764 | x1E5e3ukRyEFRT6SUAF6lg|d543d3d064da465b8576d87 |
| 1 | 53733358271401869469 | 6FfHZRoiWs2VO02Pruk07A|__g3d877adf9d154637be26 |
| 2 | 82143248133286027306 | __g1114a30c6ea548a2a83d5a51718ff0fd|773840905c |
Note: jpnumber=imjp_number.