How to get unique values from multiple columns in a pandas groupby?

Given a pandas dataframe, we have to get unique values from multiple columns in a pandas groupby.
Submitted by Pranit Sharma, on September 20, 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 data.

Getting unique values from multiple columns in a pandas groupby

groupby() method is a simple but very useful concept in pandas. By using this, we can create grouping of certain values and perform some operations of those values.

The groupby() method splits the object, applies some operation, and then combines them to create a group and hence large amount of data and computations can be performed on these groups.

Basically, groupby operation packs the data into an object and if we want to check out that data, we need to access that object and we are going to get all the keys of this object.

We are supposed to find the unique values from multiple groupby,

Let us understand with the help of an example,

Python code to get unique values from multiple columns in a pandas groupby

# Importing pandas package
import pandas as pd

# Importing numpy package
import numpy as np

# Creating a dictionary
d = {
    'A':[10,10,10,20,20,20],
    'B':['a','a','b','c','c','b'],
    'C':['b','d','d','f','e','f']
}

# Creating a DataFrame
df = pd.DataFrame(d)

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

# Finding unique values
res = df.groupby('A')['B','C'].apply(lambda x: list(np.unique(x)))

# Display Result
print("Unique Values:\n",res)

Output:

Example: Get unique values from multiple columns

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