Pandas Group Columns by Value of 1 and Sort By Frequency

I have to take this dataframe:

d = {'Apple': [0,0,1,0,1,0], 'Aurora': [0,0,0,0,0,1], 'Barn': [0,1,1,0,0,0]}
df = pd.DataFrame(data=d)

  Apple Aurora Barn
0   0   0   0
1   0   0   1
2   1   0   1
3   0   0   0
4   1   0   0
5   0   1   0

And count the frequency of the number one in each column, and create a new dataframe that looks like this:

df = pd.DataFrame([['Apple',0.3333], ['Aurora',0.166666], ['Barn', 0.3333]], columns = ['index', 'value'])

    index   value
0   Apple   0.333300
1   Aurora  0.166666
2   Barn    0.333300

I have tried this:

df['freq'] = df.groupby(1)[1].transform('count')

But I get an error: KeyError: 1

So I’m not sure how to count the value 1 across rows and columns, and group by column names and the frequency of 1 in each column.

>Solution :

If I understand correctly, you could do simply this:

freq = df.mean()

Output:

>>> freq
Apple     0.333333
Aurora    0.166667
Barn      0.333333
dtype: float64