Pandas: Split the specified dataframe into groups and count unique values of 'value' column

Last update on April 04 2025 13:44:22 (UTC/GMT +8 hours)

15. Grouping and Counting Unique Values

Write a Pandas program to split the following dataframe into groups and count unique values of 'value' column.

Test Data:

   id value
0   1     a
1   1     a
2   2     b
3   3  None
4   3     a
5   4     a
6   4  None
7   4     b

Sample Solution:

Python Code :

import pandas as pd
df = pd.DataFrame({
    'id': [1, 1, 2, 3, 3, 4, 4, 4],
    'value': ['a', 'a', 'b', None, 'a', 'a', None, 'b']
})
print("Original DataFrame:")
print(df)
print("Count unique values:")
print (df.groupby('value')['id'].nunique())

Sample Output:

Original DataFrame:
   id value
0   1     a
1   1     a
2   2     b
3   3  None
4   3     a
5   4     a
6   4  None
7   4     b
Count unique values:
value
a    3
b    2
Name: id, dtype: int64

For more Practice: Solve these Related Problems:

• Write a Pandas program to group the dataframe by a specific column and then count the unique values of another column within each group.
• Write a Pandas program to split the dataframe by a grouping key and then calculate unique counts for the 'value' column.
• Write a Pandas program to group by an identifier and then use nunique() to count unique occurrences in a target column.
• Write a Pandas program to group the dataframe and then display a summary table with unique value counts for each group.

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Pandas program to split the following dataframe into groups based on all columns and calculate Groupby value counts on the dataframe.
Next: Write a Pandas program to split a given dataframe into groups and list all the keys from the GroupBy object.