I try to filter a dataframe with a specific condition, but don't now how to get safe that all other columns have to be false.
A | B | C | D | E | F
True True False False False False
True False True False False True
True True True False False False
given this df i want to select every row where A is tru and B or C is True.
df.loc[(df.A == True) & ((df.B == True) or (df.C == True))]
or
df.query('A and (b or C) ')
and my resut would be
A | B | C | D | E | F
True True False False False False
True False True False False True
True False True False False False
but how can I get safe that all other columns that are not to mentioned (D,E,F) have to be False so that the result is
A | B | C | D | E | F
True True False False False False
True False True False False False
CodePudding user response:
You can use another mask with columns.difference
and any
:
m1 = df['A'] & (df['B'] | df['C'])
m2 = ~df[df.columns.difference(['A', 'B', 'C'])].any(axis=1)
df.loc[m1 & m2]
Output:
A B C D E F
0 True True False False False False
2 True True True False False False