Pandas Data Series: Stack two given series vertically and horizontally

Last update on April 03 2025 13:11:54 (UTC/GMT +8 hours)

37. Stack Series

Write a Pandas program to stack two given series vertically and horizontally.

Sample Solution :

Python Code :

import pandas as pd
series1 = pd.Series(range(10))
series2 = pd.Series(list('pqrstuvwxy'))
print("Original Series:")
print(series1)
print(series2)
series1.append(series2)
df = pd.concat([series1, series2], axis=1)
print("\nStack two given series vertically and horizontally:")
print(df)

Sample Output:

Original Series:
0    0
1    1
2    2
3    3
4    4
5    5
6    6
7    7
8    8
9    9
dtype: int64
0    p
1    q
2    r
3    s
4    t
5    u
6    v
7    w
8    x
9    y
dtype: object

Stack two given series vertically and horizontally:
   0  1
0  0  p
1  1  q
2  2  r
3  3  s
4  4  t
5  5  u
6  6  v
7  7  w
8  8  x
9  9  y

Explanation:

series1 = pd.Series(range(10)): This code creates a Pandas Series object called ‘series1’ containing integers from 0 to 9, generated using the range() function.

series2 = pd.Series(list('pqrstuvwxy')): This code creates another Pandas Series object called ‘series2‘ containing characters from the string "pqrstuvwxy", generated using the list() function.

series1.append(series2): This code appends ‘series2’ to ‘series1’ and returns a new Series object that includes both Series objects.

df = pd.concat([series1, series2], axis=1): This code concatenates ‘series1’ and ‘series2’ horizontally using pd.concat() and stores the result in a DataFrame called df.

Finally print() function prints the DataFrame ‘df’.

For more Practice: Solve these Related Problems:

Write a Pandas program to stack two Series vertically and then compute the row-wise sum.
Write a Pandas program to stack two Series horizontally and then calculate the element-wise product.
Write a Pandas program to stack two Series vertically, reset the index, and then merge with an additional Series.
Write a Pandas program to stack two Series horizontally and then convert the result into a MultiIndex DataFrame.

Python-Pandas Code Editor:

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