Count unique values per groups in Python Pandas

Python Server Side Programming Programming

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

Rishikesh Kumar Rishi

Updated on: 2021-09-14T12:07:37+05:30

6K+ Views

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