Keep columns that contains text in pandas dataframe

I would like to keep columns that contains word "FAIL".

Input data:

Expected output:

Current Output:

My code:

import pandas as pd
values = range(1,5)
status_pass = ["PASS"]*len(values)
status1 = status_pass[1:]+["FAIL"]
status2 = status1[::-1]
df = pd.DataFrame({"Values1":values,"Values2":values,"Values3":values,"Status1":status_pass,"Status2":status1,"Status3":status2})
# drop unwanted rows
words_to_keep = ["FAIL"]
df = df[df.stack().groupby(level=0).apply(
    lambda x: all(x.str.contains(w, case=False).any() for w in words_to_keep))]
# Filter by column name
df = df.filter(like='Status', axis=1)

>Solution :

Use DataFrame.loc for filter rows and columns by mask, if need filter by list use DataFrame.isin, if need filter scalar use DataFrame.eq with DataFrame.any for test for at least one match:

words_to_keep = ["FAIL"]
m = df.isin(words_to_keep)

#m = df.eq("FAIL")

out = df.loc[m.any(axis=1), m.any()]
print (out)
  Status2 Status3
0    PASS    FAIL
3    FAIL    PASS

Details:

print (df.isin(words_to_keep))
   Values1  Values2  Values3  Status1  Status2  Status3
0    False    False    False    False    False     True
1    False    False    False    False    False    False
2    False    False    False    False    False    False
3    False    False    False    False     True    False

print (m.any(axis=1))
0     True
1    False
2    False
3     True

print (m.any())
Values1    False
Values2    False
Values3    False
Status1    False
Status2     True
Status3     True
dtype: bool