how to fix None fields as false in a dataframe

Question

       Id      0     1     2     3     4     5
0   apple   True  None  None  None  None  None
1  orange  False  None  True  None  None  None
2  banana   True  None  None  True  None  None
3   guava  False  None  None  None  True  None
4  leeche   None  True  None  None  None  None

above dataframe contains boolean and None value If any of 0-5 columns have false i want to omit them from updated dataframe. considering None denotes True value , so my result should look like

           Id      
0         apple       
2         banana        
4         leeche 

I am not able to understand how to get combined filter on multiple columns.

Answer 1

Use:

cols = ['0','1','2','3','4','5']
df = df.loc[df[cols].ne('False').all(1), ['Id']]
#if False is boolean
#df = df.loc[df[cols].ne(False).all(1), ['Id']]
print (df)
       Id
0   apple
2  banana
4  leeche

If need check all columns without first:

df = df.loc[df.iloc[:, 1:].ne('False').all(1), ['Id']]

Explanation:

First select columns by columns names:

#if strings
cols = ['0','1','2','3','4','5']
#if numeric 
#cols = np.arange(6)
print (df[cols])
       0     1     2     3     4     5
0   True  None  None  None  None  None
1  False  None  True  None  None  None
2   True  None  None  True  None  None
3  False  None  None  None  True  None
4   None  True  None  None  None  None

Then check if not equal False by DataFrame.ne:

#if boolean False
print(df[cols].ne(False))
#if string False
#print(df[cols].ne('False'))
       0     1     2     3     4     5
0   True  True  True  True  True  True
1  False  True  True  True  True  True
2   True  True  True  True  True  True
3  False  True  True  True  True  True
4   True  True  True  True  True  True

And test if all Trues per rows by DataFrame.all:

print(df[cols].ne('False').all(1))
0     True
1    False
2     True
3    False
4     True
dtype: bool

Last filtering by boolean indexing with select Id with [] for one column DataFrame:

print(df[df[cols].ne('False').all(1)])
       Id     0     1     2     3     4     5
0   apple  True  None  None  None  None  None
2  banana  True  None  None  True  None  None
4  leeche  None  True  None  None  None  None

print(df.loc[df[cols].ne('False').all(1), ['Id']])
       Id
0   apple
2  banana
4  leeche