What are Pareto charts in tableau Explain with example

This recipe explains what are Pareto charts in tableau This recipe explains them with example

Recipe Objective - What are Pareto Charts in Tableau? Explain with example

A Pareto chart contains both line graphs and bar graphs containing bars in descending order, and the line graph represents the ascending cumulative total. It is named after Vilfredo Pareto, a famous Italian engineer, economist and sociologist and formulated the renowned Pareto Principle.

Steps to create Pareto Chart.

Step 1 > Connect the "world_cup_2018_squads.xlsx" data set.

Step 2 > Drag the "Team" dimension and drop it onto the column shelf.

Step 3 > Sort the "Team" dimension in descending order by field.

Step 4 > Drag the "Goals" measure and drop it onto the row shelf.

Step 5 > Drag the "Goals" measure and drop it onto the far right of visualization until the appearance of dotted line to create dual-axis view.

Step 6 > Under Marks card, change automatic to Line of SUM(Goals)(2).

Step 7 > Click SUM(Goals)(2) and Add Running Total as a primary table calculation.

Step 8 > Add Percent of Total as a secondary table calculation in SUM(Goals)(2).

Step 9 > Change color of line graph to Red of SUM(Goals)(2).

Our Pareto Chart is Ready!

What Users are saying..

profile image

Ray han

Tech Leader | Stanford / Yale University
linkedin profile url

I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop... Read More

Relevant Projects

Langchain Project for Customer Support App in Python
In this LLM Project, you will learn how to enhance customer support interactions through Large Language Models (LLMs), enabling intelligent, context-aware responses. This Langchain project aims to seamlessly integrate LLM technology with databases, PDF knowledge bases, and audio processing agents to create a comprehensive customer support application.

Learn How to Build a Linear Regression Model in PyTorch
In this Machine Learning Project, you will learn how to build a simple linear regression model in PyTorch to predict the number of days subscribed.

Build a Text Generator Model using Amazon SageMaker
In this Deep Learning Project, you will train a Text Generator Model on Amazon Reviews Dataset using LSTM Algorithm in PyTorch and deploy it on Amazon SageMaker.

Learn to Build an End-to-End Machine Learning Pipeline - Part 2
In this Machine Learning Project, you will learn how to build an end-to-end machine learning pipeline for predicting truck delays, incorporating Hopsworks' feature store and Weights and Biases for model experimentation.

Credit Card Fraud Detection as a Classification Problem
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.

FEAST Feature Store Example for Scaling Machine Learning
FEAST Feature Store Example- Learn to use FEAST Feature Store to manage, store, and discover features for customer churn prediction machine learning project.

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.

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

Build Regression (Linear,Ridge,Lasso) Models in NumPy Python
In this machine learning regression project, you will learn to build NumPy Regression Models (Linear Regression, Ridge Regression, Lasso Regression) from Scratch.

Ecommerce product reviews - Pairwise ranking and sentiment analysis
This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.