## Pandas Group by Quantile

Python is the most commonly used for developing software among programmers. It provides multiple built-in functions/methods inside the different modules for multitasking, such as calculating the desired nth number of quartiles between two points and many more. For this purpose, the “**groupby.quantile()**” function can be used.

This blog will discuss:

## What is a Quantile Group in Python?

In Python, the quantile indicates the particular part of the dataset that defines how many values are above and below a specific limit in a distribution. In Python, the quantiles follow the generic concept of quantile group. To perform this task, it takes input in the form of an array with the number and as a result, generates the value at the “**nth**” quantile.

## What is the “groupby.quantile()” Function in Python?

The “**groupby.quantile()**” function is utilized for calculating the quartile by the group in Python. This functionality can be utilized provided by importing the “**pandas**” module. It is commonly utilized for data analysis. To do so, first, it will divide each row in a provided DataFrame into equal groups sized on a particular column’s values. Then, it finds the aggregated values for each divided group.

Now, move ahead and check out the provided example for a better understanding!

**Example **

First, import the “**pandas**” module. Then, create a new “**courses**” DataFrame with values. After that, use the DataFrame() method and then, call the “**groupby.quantile()**” function along with the required parameters. For instance, we have provided the DataFrame column name as “**Name**” and quantile values as “**0.25**”:

courses = {'Name': ['Maria', 'Maria', 'Maria',

'Alex', 'Alex', 'Alex',

'David', 'David', 'David'],

'Marks': [1, 5, 6, 9, 2, 9, 9, 3, 5]

}

df = pd.DataFrame(courses)

print(df.groupby('Name').quantile(0.25))

As you can see, we have successfully retrieved the 25th quantile of the group from the newly created DataFrame with respect to all column elements:

If you want to get the 5th quantile of the group, then simply place the “**0.50**” inside the “**groupby.quantile()**” function as a parameter:

**Output**

You can also get the 75th quantile of the group from the desired DataFrame by using the “**0.75**” value and passing it as an argument to the “**groupby.quantile()**” function:

That’s all! We have briefly explained the “groupby.quantile()” function in Python.

## Conclusion

The “groupby.quantile()” function can be utilized for calculating the quartile by the group in Python. It can be utilized by importing the “**pandas**” module for data analysis. This article demonstrated about the “**groupby.quantile()**” function in Python in detail.

Source: linuxhint.com