How to find rank in a pandas dataframe?

How to find rank in a pandas dataframe?

How to find rank in a pandas dataframe?

This recipe helps you find rank in a pandas dataframe


Recipe Objective

The rank() function is used to compute numerical data ranks (1 through n) along axis. By default, equal values are assigned a rank that is the average of the ranks of those values.

So this recipe is a short example on How to find rank in a pandas dataframe. Let's get started.

Step 1 - Import the library

import pandas as pd

Let's pause and look at these imports. Pandas is generally used for performing mathematical operation and preferably over arrays.

Step 2 - Setup the Data

df = pd.DataFrame({"A":[0, 1, 2, 3, 5, 9], "B":[11, 5, 8, 6, 7, 8], "C":[2, 5, 10, 11, 9, 8]})

Here we have setup a random dataset with some random values in it.

Step 3 - Finding rank

df['default_rank'] = df['B'].rank() print(df)

Here we are applied rank to find out the rank order of column B.

Step 4 - Let's look at our dataset now

Once we run the above code snippet, we will see:

Scroll down to the ipython file to look at the results.

We can see the how the rank are assigned. Equal values takes equal ranks, midway between other ranks.

Relevant Projects

Data Science Project in Python on BigMart Sales Prediction
The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.

Loan Eligibility Prediction using Gradient Boosting Classifier
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.

Build a Collaborative Filtering Recommender System in Python
Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.

Identifying Product Bundles from Sales Data Using R Language
In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.

Perform Time series modelling using Facebook Prophet
In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.

Predict Census Income using Deep Learning Models
In this project, we are going to work on Deep Learning using H2O to predict Census income.

Customer Market Basket Analysis using Apriori and Fpgrowth algorithms
In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.

Topic modelling using Kmeans clustering to group customer reviews
In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.

Ensemble Machine Learning Project - All State Insurance Claims Severity Prediction
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.

Customer Churn Prediction Analysis using Ensemble Techniques
In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.