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:
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.
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
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics