Sorting Pandas DataFrame by values: Python data manipulation

Python Pandas Numpy: Exercise-28 with Solution

Sort a Pandas DataFrame by values in a specific column.

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)

# Sort the DataFrame by the 'Salary' column in ascending order
sorted_df = df.sort_values(by='Salary')

# Display the sorted DataFrame


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


Here's a breakdown of the above code:

  • We created a sample DataFrame (df) with columns 'Name', 'Age', and 'Salary'.
  • The df.sort_values(by='Salary') method sorts the DataFrame based on the values in the 'Salary' column in ascending order.
  • The resulting "sorted_df" DataFrame is displayed, showing the rows sorted by the 'Salary' column.


Flowchart: Sorting Pandas DataFrame by values: Python data manipulation.

Python Code Editor:

Previous: Generating and identifying unique values in a NumPy array.
Next: Applying custom function to salary: Pandas DataFrame operation.

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