Pandas filter data frame rows by function

Question

I want to filter a data frame by more complex function based on different values in the row.

Is there a possibility to filter DF rows by a boolean function like you

Answer 1

I think function is here not necessary, better and mainly faster is use boolean indexing:

m = (df['Name'] == 'Alisa') & (df['Age'] > 24)
print(m)
0      True
1     False
2     False
3     False
4     False
5     False
6      True
7     False
8     False
9     False
10    False
11    False
dtype: bool

#invert mask by ~
df1 = df[~m]

Function solution - is necessary return boolean only, better if some complicated filtering - need return for each row boolean only:

def filter_fn(row):
    if row['Name'] == 'Alisa' and row['Age'] > 24:
        return False
    else:
        return True

df = pd.DataFrame(d, columns=['Name', 'Age', 'Score'])
m = df.apply(filter_fn, axis=1)
print(m)
0     False
1      True
2      True
3      True
4      True
5      True
6     False
7      True
8      True
9      True
10     True
11     True
dtype: bool

df1 = df[m]