Transposing DataFrame: Pandas data manipulation

Python Pandas Numpy: Exercise-31 with Solution

Create a new DataFrame by transposing an existing one.

Sample Solution:

Python Code:

import pandas as pd

# Create a sample DataFrame
data = {'Name': ['Imen', 'Karthika', 'Cosimo', 'Cathrine'],
        'Age': [25, 30, 22, 35],
        'Salary': [50000, 60000, 45000, 70000]}

df = pd.DataFrame(data)

# Transpose the DataFrame using transpose() method
transposed_df = df.transpose()
# Alternatively, you can use the .T attribute
# transposed_df = df.T

# Display the transposed DataFrame


            0         1       2         3
Name     Imen  Karthika  Cosimo  Cathrine
Age        25        30      22        35
Salary  50000     60000   45000     70000


Here's a breakdown of the above code:

  • First we create a sample DataFrame (df) with columns 'Name', 'Age', and 'Salary'.
  • The df.transpose() method transposes the DataFrame, swapping rows and columns.
  • Alternatively, you can use df.T for the same effect.
  • The resulting transposed_df DataFrame is printed, showing the transposed layout.


Flowchart: Transposing DataFrame: Pandas data manipulation.

Python Code Editor:

Previous: Renaming columns in Pandas DataFrame.
Next: Merging Pandas DataFrames on multiple columns.

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