My goal is to properly select all Rows where the relevant columns (dynamically as list) meet specific conditions:
A | Br |
---|---|
* | * |
None | None |
Test | * |
I can easily select the rows (dynamically) where the relevant columns are None/NaN etc with:
df[['A', 'B']].isna().all(1)
If I try the same approach with for example: * my method fails miserably:
df[df[['A', 'B']]=='*'].all(1)
This return every row as True like I would expect from the 'any' keyword??
CodePudding user response:
Need test boolean DataFrame:
m = (df[['A', 'B']]=='*').all(1)
Or:
m = df[['A', 'B']].eq('*').all(1)