Group by and Filter Groups in Pandas

Last update on April 11 2025 12:51:00 (UTC/GMT +8 hours)

4. Group by and Filter Groups

Write a Pandas program that implements the technique of grouping and filtering groups to refine your data analysis and insights.

Sample Solution:

Python Code :

import pandas as pd
# Sample DataFrame
data = {'Category': ['A', 'A', 'B', 'B', 'C', 'C'],
        'Value': [1, 2, 3, 4, 5, 6]}
df = pd.DataFrame(data)
print("Sample DataFrame:")
print(df)
# Group by 'Category'
grouped = df.groupby('Category')
# Filter groups where the sum of 'Value' > 5
print("\nFilter groups where the sum of 'Value' > 5")
filtered = grouped.filter(lambda x: x['Value'].sum() > 5)

print(filtered)

Output:

Sample DataFrame:
  Category  Value
0        A      1
1        A      2
2        B      3
3        B      4
4        C      5
5        C      6

Filter groups where the sum of 'Value' > 5
  Category  Value
2        B      3
3        B      4
4        C      5
5        C      6

Explanation:

• Import pandas.
• Create a sample DataFrame.
• Group by 'Category'.
• Filter groups where the sum of 'Value' > 5.
• Print the filtered DataFrame.

For more Practice: Solve these Related Problems:

• Write a Pandas program to group data and then filter out groups where the total sum of a numeric column is below a threshold.
• Write a Pandas program to group a DataFrame and keep only those groups whose average exceeds a given value.
• Write a Pandas program to group data and filter groups based on a custom condition applied to the count of records in each group.
• Write a Pandas program to group data and filter groups dynamically based on the standard deviation of a numeric column.

Python Code Editor:

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