Separate text into columns and pivot table

I have a dataframe where one of the columns has its items separated with commas. It looks like:

My goal is to create a matrix that has as header all the unique values from column Data, meaning [a,b,c,d,e]. Then as rows a flag indicating if the value is at that particular row.
The matrix should look like this:

To separate column Data what I did is:

df['data'].str.split(',', expand = True)

Then I dont know how to proceed to allocate the flags to each of the columns.

Can anybody help me with this?

Thank you very much
Regards

>Solution :

Maybe you can try this without pivot.

Create the dataframe.

import pandas as pd
import io

s = '''Data
a,b,c
a,c,d
d,e
a,e
a,b,c,d,e'''

df = pd.read_csv(io.StringIO(s), sep = "\s+")

We can use pandas.Series.str.split with expand argument equals to True. And value_counts each rows with axis = 1.

Finally fillna with zero and change the data into integer with astype(int).

df["Data"].str.split(pat = ",", expand=True).apply(lambda x : x.value_counts(), axis = 1).fillna(0).astype(int)

#
    a   b   c   d   e
0   1   1   1   0   0
1   1   0   1   1   0
2   0   0   0   1   1
3   1   0   0   0   1
4   1   1   1   1   1

And then merge it with the original column.

new = df["Data"].str.split(pat = ",", expand=True).apply(lambda x : x.value_counts(), axis = 1).fillna(0).astype(int)
pd.concat([df, new], axis = 1)

#
    Data        a   b   c   d   e
0   a,b,c       1   1   1   0   0
1   a,c,d       1   0   1   1   0
2   d,e         0   0   0   1   1
3   a,e         1   0   0   0   1
4   a,b,c,d,e   1   1   1   1   1