Transposing DataFrame: Pandas data manipulation

Last update on December 21 2024 07:43:25 (UTC/GMT +8 hours)

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
print(transposed_df)

Output:

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

Explanation:

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:

Python Code Editor:

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