Python Pandas - 按组内唯一值的数量过滤 df

Question

Here is an example of data I'm working on. (as a pandas df)

    index   inv Rev_stream  Bill_type   Net_rev
       1    1   A           Original    -24.77
       2    1   B           Original    -24.77
       3    2   A           Original    -409.33
       4    2   B           Original    -409.33
       5    2   C           Original    -409.33
       6    2   D           Original    -409.33
       7    3   A           Original    -843.11
       8    3   A           Rebill       279.5
       9    3   B           Original    -843.11
      10    4   A           Rebill       279.5
      11    4   B           Original    -843.11
      12    5   B           Rebill       279.5

How could I filter this df, in a way to only get the lines where invoice/Rev_stream combo has both original and rebill kind of Net_rev. In the example above it would be only lines with index 7 and 8.

Is there an easy way to do it, without iterating over the whole dataframe and building dictionaries of invoice+RevStream : Bill_type?

What I'm looking for is some kind of

df = df[df[['inv','Rev_stream']]['Bill_type'].unique().len() == 2]

Unfortunately the code above doesn't work.

Thanks in advance.

Answer 1

You can group your data by inv and Rev_stream columns and then check for each group if both Original and Rebill are in the Bill_type values and filter based on the condition:

(df.groupby(['inv', 'Rev_stream'])
   .filter(lambda g: 'Original' in g.Bill_type.values and 'Rebill' in g.Bill_type.values))