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Unique combinations of values in selected columns in Pandas DataFrame and count

Given a Pandas DataFrame, we have to find the unique combinations of values in selected columns and count them.
Submitted by Pranit Sharma, on June 19, 2022

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and the data.

A DataFrame column may contain similar or unique values based on the type of dataset. If a DataFrame contains two or more types of repeating values, we may need to make unique combinations of values in DataFrame and count each of these combinations and their particular values.

Unique combinations of values in selected columns

For this purpose, we use pandas.DataFrame.value_counts() method. This method is useful when we want to count the number of each repeating value. Also, it groups all the repeating values in a column and gives their count in a separate column.

To work with pandas, we need to import pandas package first, below is the syntax:

import pandas as pd

Let us understand with the help of an example,

Python program to unique combinations of values in selected columns in Pandas DataFrame and count

# Importing pandas package
import pandas as pd

# Creating a DataFrame
df = pd.DataFrame({
    'A':[1,1,1,1,0,1,1,0,1],
    'B':[1,1,1,1,0,1,1,0,1]
})

# Display DataFrame
print("Created DataFrame\n",df,"\n")

# Value count
print("Unique combination and their count:\n",df.value_counts())

Output

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