Spliting and Pivoting a column of different string length in Python

August 14, 2022

I have this dataframe.

+-----+--------+--------------------------------+
|ID   |Date    |Text                            | 
+-----+--------+--------------------------------+
|1    |1 Jan   |This is a text                  |
|2    |2 Jan   |Text can be of variant length   |
+-----+--------+--------------------------------+

How can i split and pivot the Text column to the ID and Date?

+-----+--------+-------+
|ID   |Date    |Text   | 
+-----+--------+-------+
|1    |1 Jan   |This   |
|1    |1 Jan   |is     |
|1    |1 Jan   |a      |
|1    |1 Jan   |text   |
|2    |2 Jan   |Text   |
|2    |2 Jan   |can    |
|2    |2 Jan   |be     |
|2    |2 Jan   |of     |
|2    |2 Jan   |variant|
|2    |2 Jan   |length |
+-----+--------+-------+

I know that for pivot, I can use df.stack() but i am having trouble with splitting it due to the difference in length for each text.

I would really appreciate any help.

>Solution :

try this code and refer this documentation https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.explode.html

df = pd.DataFrame({'col1':[1,2],'col2':['1 Jan', '2 Jan'],'col3':['This is a text','Text can be of varient length']})
df['col3'] = df['col3'].str.split(' ')
a = df.explode('col3')
print(a)

Output:

   col1   col2     col3
0     1  1 Jan     This
0     1  1 Jan       is
0     1  1 Jan        a
0     1  1 Jan     text
1     2  2 Jan     Text
1     2  2 Jan      can
1     2  2 Jan       be
1     2  2 Jan       of
1     2  2 Jan  varient
1     2  2 Jan   length