Pandas conditional subset for dataframe with bool values and ints

Question

I have a dataframe with three series. Column A contains a group_id. Column B contains True or False. Column C contains a 1-n ranking (where n is the number of rows per group_id).

I'd like to store a subset of this dataframe for each row that:

1) Column C == 1
OR
2) Column B == True

The following logic copies my old dataframe row for row into the new dataframe:

new_df = df[df.column_b | df.column_c == 1]

Solution 1

IIUC, starting from a sample dataframe like:

A,B,C
01,True,1
01,False,2
02,False,1
02,True,2
03,True,1

you can:

df = df[(df['C']==1) | (df['B']==True)]

which returns:

   A      B  C
0  1   True  1
2  2  False  1
3  2   True  2
4  3   True  1

Solution 2

You've couple of methods for filtering, and performance varies based on size of your data

In [722]: df[(df['C']==1) | df['B']]
Out[722]:
   A      B  C
0  1   True  1
2  2  False  1
3  2   True  2
4  3   True  1

In [723]: df.query('C==1 or B==True')
Out[723]:
   A      B  C
0  1   True  1
2  2  False  1
3  2   True  2
4  3   True  1

In [724]: df[df.eval('C==1 or B==True')]
Out[724]:
   A      B  C
0  1   True  1
2  2  False  1
3  2   True  2
4  3   True  1