Pandas Data Frame in Python. Proportions and Transpose

Question

I have the following data frame in Pandas. The idea is to generate an additional data frame IDs based on the proportion of the variable TYPE, transposing it into columns. Any help is appreciated!

d = {'ID': [1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2], 'TYPE': ['A','A','A','B','B','B','B','C','C','C','A','A','B','B','B','B','B','B']}
df = pd.DataFrame(data=d)
df


    ID   A       B       C
    1   0.30    0.40    0.3
    2   0.25    0.75    0.0

Answer 1

Use SeriesGroupBy.value_counts with parameter normalize=True and reshape by Series.unstack :

df = df.groupby('ID')['TYPE'].value_counts(normalize=True).unstack(fill_value=0)
print (df)
TYPE     A     B    C
ID                   
1     0.30  0.40  0.3
2     0.25  0.75  0.0

Then if necessary column from index :

df = df.rename_axis(None, axis=1).reset_index()
print (df)
   ID     A     B    C
0   1  0.30  0.40  0.3
1   2  0.25  0.75  0.0