Count unique values per groups in Python Pandas

To count unique values per groups in Python Pandas, we can use df.groupby('column_name').count().

Steps

• Create a two-dimensional, size-mutable, potentially heterogeneous tabular data, df.
• Print the input DataFrame, df.
• Use df.groupby('rank')['id'].count() to find the count of unique values per groups and store it in a variable "count".
• Print the count from Step 3.

Example

import pandas as pd df = pd.DataFrame(     {        "id": [1, 2, 1, 3, 5, 1, 4, 3, 6, 7],        'rank': [1, 4, 1, 2, 1, 4, 6, 1, 5, 3]     } ) print"Input DataFrame 1 is:\n", df count = df.groupby('rank')['id'].count() print"Frequency of ranks:\n", count

Output

Input DataFrame 1 is:    id  rank 0   1    1 1   2    4 2   1    1 3   3    2 4   5    1 5   1    4 6   4    6 7   3    1 8   6    5 9   7    3 Frequency of ranks: rank 1  4 2  1 3  1 4  2 5  1 6  1 Name: id, dtype: int64