pandas isin() fail between dataframes with objects types columns

Question

In [1]: import pandas as pd
   ...: a=pd.DataFrame([1,2,'a'])

In [2]: a.isin([1,'a'])
Out[2]:
       0
0   True
1  False
2   True

In [3]: a.isin(pd.DataFrame([1,'a']))
Out[3]:
       0
0   True
1  False
2  False

why isin cant find 'a' in a DataFrame but can in a list?.

PS: Using pandas 1.0.5

In [4]: pd.version Out[4]: '1.0.5'

ALollz · Answer 1 · 2020-07-25T03:53:40.323

3

The pd.DataFrame.isin docs spell out this behavior pretty clearly, emphasis my own.

If values is a DataFrame, then both the index and column labels must match.

So looking at your two DataFrames side by side:

a   isin  pd.DataFrame([1,'a'])

   0           0
0  1        0  1    True  <- 1 == 1 for col label (0) and index label (0) 
1  2        1  a    False <- 2 != 'a' for col label (0) and index label (1)
2  a                False <- Nothing to align

edited Jul 25 '20 at 03:53

answered Jul 24 '20 at 23:27

ALollz

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hey, thanks, and how to ignore indexing to isin between dataframes ? – Franco Milanese Jul 24 '20 at 23:47
1

@FrancoMilanese You could convert all the values to a single array: `pd.DataFrame([1,'a']).to_numpy().ravel()` – ALollz Jul 24 '20 at 23:54

pandas isin() fail between dataframes with objects types columns

1 Answers1