Pandas select rows with a specific value in at least one column-CodePudding

Let's take this sample dataframe :

df = pd.DataFrame({'ID':[1,2,3],'Col1':[True,False,False],'Col2':[False,False,False], 'Col3':[True,False,True]})

   ID   Col1   Col2   Col3
0   1   True  False   True
1   2  False  False  False
2   3  False  False   True

I would like to select rows of df having at least one True. I can of course do the following :

df[df["Col1"] | df["Col2"] | df["Col3"]]

But my real dataframe has a lot of columns and consider I don't know their names. How please could I do ?

Expected output :

   ID   Col1   Col2  Col3
0   1   True  False  True
2   3  False  False  True

CodePudding user response：

There is any function for the exact purpose:

df = df.set_index('ID', drop=True)
print(df[df.any(axis='columns')]

# output:
     Col1   Col2  Col3
ID                    
1    True  False  True
3   False  False  True

or without resetting the index:

print(df[df[['Col1', 'Col2', 'Col3']].any(axis='columns')])

# output:
   ID   Col1   Col2  Col3
0   1   True  False  True
2   3  False  False  True

CodePudding user response：

you can use .select_dtypes and boolean filtering with .loc

df.loc[df.select_dtypes('bool').sum(axis=1).ge(1)]


   ID   Col1   Col2  Col3
0   1   True  False  True
2   3  False  False  True