I want to delete all rows containing required string ,
Suppose I have following dataframe:
A B C
1 a x
w g n
3 l p
j p v
I want to delete all rows containing string p. I have search for it but most of the answer is on the basis of column name , in my case I will not be aware of column it can be present in any of the column.
Output dataframe should be
A B C
1 a x
w g n
For filtering strings:
df = df[(df != 'p').all(axis=1)]
Compare for not equal:
print ((df != 'p'))
A B C
0 True True True
1 True True True
2 True True False
3 True False True
And test for all Trues per row:
print ((df != 'p').all(axis=1))
0 True
1 True
2 False
3 False
dtype: bool
Or:
df = df[~(df == 'p').any(axis=1)]
Test for equal:
print ((df == 'p'))
A B C
0 False False False
1 False False False
2 False False True
3 False True False
Test at least one True per row:
print ((df == 'p').any(axis=1))
0 False
1 False
2 True
3 True
dtype: bool
Invert boolean mask:
print (~(df == 'p').any(axis=1))
0 True
1 True
2 False
3 False
dtype: bool
For filtering substrings use contains with apply:
df = df[~df.apply(lambda x: x.astype(str).str.contains('p')).any(axis=1)]
Or:
df = df[~df.stack().astype(str).str.contains('p').unstack().any(axis=1)]
print (df)
A B C
0 1 a x
1 w g n
df = df[~(df.isin(['p','a'])).any(1)]df = df[~df.apply(lambda x: x.astype(str).str.contains('p|a')).any(axis=1)]