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Pandas: Create a new DataFrame based on existing Series and override the existing columns names


11. Create New DataFrame from Existing Series

Write a Pandas program to create a new DataFrame based on existing series, using specified argument and override the existing columns names.

Sample Solution:

Python Code :

import pandas as pd
s1 = pd.Series([0, 1, 2, 3], name='col1')
s2 = pd.Series([0, 1, 2, 3])
s3 = pd.Series([0, 1, 4, 5], name='col3')
df = pd.concat([s1, s2, s3], axis=1, keys=['column1', 'column2', 'column3'])
print(df)

Sample Output:

    column1  column2  column3
0        0        0        0
1        1        1        1
2        2        2        4
3        3        3        5          

For more Practice: Solve these Related Problems:

  • Write a Pandas program to construct a new DataFrame from multiple Series and override the default column names.
  • Write a Pandas program to create a DataFrame from a list of Series and then assign custom column headers.
  • Write a Pandas program to build a DataFrame from Series objects while explicitly specifying column names and index.
  • Write a Pandas program to generate a DataFrame from existing Series and then rename the columns using a dictionary.

Python Code Editor:

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