What is drill down in tableau Explain

This recipe explains what is drill down in tableau

Recipe Objective:-What is drill down in tableau? Explain.

Step 1:-

Import any data set in the data source. For example, here, the "Bestsellers with categories" books data set excel file is imported.

Step 2:-

There is only one sheet that is bestsellers with categories. It will appear in the schema pane.

Step 3:-

Go to sheet1; here, different dimensions and measures are available. Now drag and drop the author and genre dimension in the row shelf. Similarly, drag and drop the user rating measure (sum of user rating) in the column shelf.

Learn About the Application of ARCH and GARCH models in Real-World

Step 4:-

It will create a horizontal bar chart in the worksheet canvas. Go to the Genre dimension, drag and drop it over the Author dimension so that a hierarchy will be created, by which we can drill down author and genre easily. Basically, drill down in tableau is an expansion of dimension that we have used in the hierarchy.

Step 5:-

Here the hierarchy named "Books" is being created under the dimensions. This hierarchy consists of author, genre, and name dimensions, which can be drilled down or expanded in the row shelf. The drill-down will be using a "+" symbol at the start; it will turn to the "-" symbol when expanded.

What Users are saying..

profile image

Abhinav Agarwal

Graduate Student at Northwestern University
linkedin profile url

I come from Northwestern University, which is ranked 9th in the US. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge.... Read More

Relevant Projects

MLOps Project to Build Search Relevancy Algorithm with SBERT
In this MLOps SBERT project you will learn to build and deploy an accurate and scalable search algorithm on AWS using SBERT and ANNOY to enhance search relevancy in news articles.

Build Customer Propensity to Purchase Model in Python
In this machine learning project, you will learn to build a machine learning model to estimate customer propensity to purchase.

AWS MLOps Project for Gaussian Process Time Series Modeling
MLOps Project to Build and Deploy a Gaussian Process Time Series Model in Python on AWS

Build Real Estate Price Prediction Model with NLP and FastAPI
In this Real Estate Price Prediction Project, you will learn to build a real estate price prediction machine learning model and deploy it on Heroku using FastAPI Framework.

Classification Projects on Machine Learning for Beginners - 1
Classification ML Project for Beginners - A Hands-On Approach to Implementing Different Types of Classification Algorithms in Machine Learning for Predictive Modelling

Learn Hyperparameter Tuning for Neural Networks with PyTorch
In this Deep Learning Project, you will learn how to optimally tune the hyperparameters (learning rate, epochs, dropout, early stopping) of a neural network model in PyTorch to improve model performance.

Build an End-to-End AWS SageMaker Classification Model
MLOps on AWS SageMaker -Learn to Build an End-to-End Classification Model on SageMaker to predict a patient’s cause of death.

Build a Face Recognition System in Python using FaceNet
In this deep learning project, you will build your own face recognition system in Python using OpenCV and FaceNet by extracting features from an image of a person's face.

Build a Graph Based Recommendation System in Python-Part 2
In this Graph Based Recommender System Project, you will build a recommender system project for eCommerce platforms and learn to use FAISS for efficient similarity search.

Expedia Hotel Recommendations Data Science Project
In this data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.