Drop based on multiple str.contains

Question

I'm trying to drop all rows except where one of two conditions is met in a column, ideally I can do this with a single line of code

DF:

Col1 | Col2  | 

Foo    Bar     
Foo    Bar     
Foo    Too     
Foo    apple   

I tried:

DF = DF[~((DF['Col1'].astype(str).str.contains('Foo')) & (DF['Col2'].astype(str) != ('Bar')) &  (DF['Col2'].astype(str) != ('Too'))]

However, it's deleting all rows does the '&' replace an OR?

The expected result is:

Col1 | Col2  | 

Foo    Bar     
Foo    Bar     
Foo    Too      

Answer 1

For a logical bitwise AND you should be using & . And for the second column you can simplify using isin :

df[df.Col1.str.contains('Foo') & df.Col2.isin(['Bar', 'Too'])]

   Col1   Col2
0  Foo    Bar
1  Foo    Bar
2  Foo    Too

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Now following what you mention your expected output is, you should use the above. If what you do want is the rows where any conditions are fulfilled, you should be using | .