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Pandas groupby and qcut

Learn, how to use groupby() and qcut() method in Python pandas?
Submitted by Pranit Sharma, on November 22, 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.

Problem statement

Suppose we are given a dataframe with multiple columns we need to find a way to structure this Pandas dataframe by using groupby() and qcut() commands to return one column that has the nested values, suppose we are given two groups of data and we want qcut applied to each group and then return the output to one column.

Use of groupby() and qcut()

For this purpose, we will simply create a dataframe with 2 columns (say A and B). We will then use the groupby() method on these columns and use a transform function inside which we will create a Lambda function with the comprehension statement by using the qcut() method.

Let us understand with the help of an example,

Python program to demonstrate how to use of groupby() and qcut()

# Importing pandas package
import pandas as pd

# Importing numpy package
import numpy as np

# Creating dataframe
df = pd.DataFrame({
    'A':'123456'.split(),
    'B':[1, 5, 0]*2
})

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

# using groupby and qcut
df['C'] =  df.groupby(['A'])['B'].transform(lambda x: pd.qcut(x, 3, labels=range(1,4)))

# Display Result
print('New DataFrame:\n',df)

Output

The output of the above program is:

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