Python pandas: remove df column if condition

Question

I would like to remove this column from the pandas IF data frame, all values ​​in the column are "0%".

my df:

data = {'UK': ['11%', '16%', '7%', '52%', '2%', '5%', '3%', '3%'],
        'US': ['0%', '0%', '0%', '0%', '0%', '0%', '0%', '0%'],
        'DE': ['11%', '16%', '7%', '52%', '2%', '5%', '3%', '3%'],
        'FR': ['11%', '16%', '7%', '52%', '2%', '5%', '3%', '3%']
        }
dummy_df = pd.DataFrame(data, 
                        index=    ['cat1','cat2','cat3','cat4','cat5','cat6','cat7','cat8'], 
                        columns=['UK', 'US', 'DE', 'FR'])

my code is:

dummy_df.drop(dummy_df == '0%',inplace=True)

I get a value error:

ValueError: labels ['UK' 'US' 'DE' 'FR'] not contained in axis

Answer 1

In [186]: dummy_df.loc[:, ~(dummy_df == '0%').all()]
Out[186]:
       UK   DE   FR
cat1  11%  11%  11%
cat2  16%  16%  16%
cat3   7%   7%   7%
cat4  52%  52%  52%
cat5   2%   2%   2%
cat6   5%   5%   5%
cat7   3%   3%   3%
cat8   3%   3%   3%

Explanation:

Comparing with the '0%' that you have already received, this gives the following data framework:

In [182]: dummy_df == '0%'
Out[182]:
         UK    US     DE     FR
cat1  False  True  False  False
cat2  False  True  False  False
cat3  False  True  False  False
cat4  False  True  False  False
cat5  False  True  False  False
cat6  False  True  False  False
cat7  False  True  False  False
cat8  False  True  False  False

Now we want to know which columns all Trues have:

In [183]: (dummy_df == '0%').all()
Out[183]:
UK    False
US     True
DE    False
FR    False
dtype: bool

And finally, we can index with these logical values (but with the opposite sign ~, because you do not want to want to choose where it is True) dummy_df.loc[:, ~(dummy_df == '0%').all()].

Similarly, you can also do: dummy_df.loc[:, (dummy_df != '0%').any()](selects columns where at least one value is not equal to "0%")

Answer 2

, != '0%'

In [163]: cols = (dummy_df != '0%').any()

In [164]: cols
Out[164]:
UK     True
US    False
DE     True
FR     True
dtype: bool

cols, True

In [165]: dummy_df[cols[cols].index]
Out[165]:
       UK   DE   FR
cat1  11%  11%  11%
cat2  16%  16%  16%
cat3   7%   7%   7%
cat4  52%  52%  52%
cat5   2%   2%   2%
cat6   5%   5%   5%
cat7   3%   3%   3%
cat8   3%   3%   3%