w3resource

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
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:

Flowchart: Transposing DataFrame: Pandas data manipulation.

Python Code Editor:

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

What is the difficulty level of this exercise?

Test your Programming skills with w3resource's quiz.



Become a Patron!

Follow us on Facebook and Twitter for latest update.

It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.

https://w3resource.com/python-exercises/pandas_numpy/pandas_numpy-exercise-31.php