Pandas Data Series: Convert Series of lists to one Series

Pandas: Data Series Exercise-10 with Solution

Write a Pandas program to convert Series of lists to one Series.

Sample Solution :

Python Code :

import pandas as pd
s = pd.Series([
    ['Red', 'Green', 'White'],
    ['Red', 'Black'],
    ['Yellow']])
print("Original Series of list")
print(s)
s = s.apply(pd.Series).stack().reset_index(drop=True)
print("One Series")
print(s)

Sample Output:

Original Series of list
0    [Red, Green, White]
1           [Red, Black]
2               [Yellow]
dtype: object
One Series
0       Red
1     Green
2     White
3       Red
4     Black
5    Yellow
dtype: object                      

Explanation:

s = pd.Series([ ['Red', 'Green', 'White'], ['Red', 'Black'], ['Yellow']]) : This line creates a Pandas Series object 's' containing a sequence of three lists of strings.

s = s.apply(pd.Series).stack().reset_index(drop=True)

In the above code:

s.apply(pd.Series): Applies the pd.Series() constructor to each element of the Pandas Series object 's' using the .apply() method. This converts each list element into a separate Pandas Series object with one row per element.

Output:
        0      1      2
0     Red  Green  White
1     Red  Black    NaN
2  Yellow    NaN    NaN

s.apply(pd.Series).stack(): The .stack() method is then applied to the resulting object. The resulting object will have a hierarchical index with the original index and a secondary index for each element of the original lists.
Output:
0  0       Red
   1     Green
   2     White
1  0       Red
   1     Black
2  0    Yellow
dtype: object

s.apply(pd.Series).stack().reset_index(drop=True): Finally the .reset_index() method with the 'drop' parameter set to True is then applied to reset the index of the Series object 's' and drop the old index.
Output:
0       Red
1     Green
2     White
3       Red
4     Black
5    Yellow
dtype: object

Python-Pandas Code Editor:

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