Pandas Quantile Implementation in Python: 3 Steps Only

Pandas Quantile Implementation in Python

There are many methods in the pandas python module that you can manipulate any dataframe easily. If you want to divide the dataframe into two parts then pandas quantile method is for you. In this entire tutorial, you will know how to implement pandas quantile with steps.

Steps to Implement Pandas Quantile

In this section, you will know all the steps required to implement pandas quantile.

Step 1: Import the required library

The first basic step is to import all the necessary libraries. In this tutorial, I am using only the pandas module so let’s import it.

import pandas as pd

Step 2: Create a Dummy Dataframe

The next step is to create a sample dataframe for the implementation. For simplicity, I am creating a simple dataframe. But you can use your own dataframe. Use the below code to create sample dataframe.

import pandas as pd
data = {"col1":[1,2,3,4,5,6],"col2":[1,10,100,100,200,300]}
df = pd.DataFrame(data)
print(df)

Output

Sample dataframe for Pandas Quantile
Sample dataframe for Pandas Quantile

 

Step 3: Apply the pandas quantile on the dataframe

Now let’s apply the pandas.quantile() method on the dataframe. Below are the examples I have compiled for you.

Example 1: Using single quantile() on dataframe

Let’s find a single quantile on the data frame. To do so you have to pass only a single quantile value. For example, I want to find the quantile value of 10% that is 0.1.

import pandas as pd
data = {"col1":[1,2,3,4,5,6],"col2":[1,10,100,100,200,300]}
df = pd.DataFrame(data)
df.quantile(.1)

Output

Finding ten percent Quantile on dataframe
Finding ten per cent Quantile on dataframe

Example 2: Using multiple quantile() on dataframe

You can also pass more than one quantile value inside the quantile() method. It will find the quantile value for each quantile. Execute the below lines of code.

import pandas as pd
data = {"col1":[1,2,3,4,5,6],"col2":[1,10,100,100,200,300]}
df = pd.DataFrame(data)
df.quantile([.2,0.5])

Output

Finding Quantile value using multiple quantile on dataframe
Finding Quantile value using multiple quantiles on dataframe

Example 3: Finding quantile value column-wise

You can also find the quantile value row-wise. To do so you have to pass the axis = 0 as an argument. The default axis value for this method is 0. So you will get the quantile value row-wise. Example 1 and example 2 is using the axis =0. To find the quantile value column-wise you have to use axis = 1 as an argument. Use the below lines of code to get the value.

import pandas as pd
data = {"col1":[1,2,3,4,5,6],"col2":[1,10,100,100,200,300]}
df = pd.DataFrame(data)
print(df.quantile(.1,axis=1))

Output

Finding Quantile value columnwise on the dataframe
Finding Quantile value columnwise on the dataframe

Conclusion

Quantile allows you to divide the dataframe into two parts. The one is valued below the quantile and the other is greater than the quantile. These are the steps for the implementation of the pandas quantile method on dataframe. I hope you have liked this tutorial. If you have any doubt then you can contact us for more help.

 

Source:

Quantile Doumentation

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Meet Sukesh ( Chief Editor ), a passionate and skilled Python programmer with a deep fascination for data science, NumPy, and Pandas. His journey in the world of coding began as a curious explorer and has evolved into a seasoned data enthusiast.
 
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