What is the use of the ISNULL statement in tableau

This recipe explains what is the use of the ISNULL statement in tableau

Recipe Objective:-What is the use of the ISNULL statement in tableau?

Step 1:-

Import any data set in the data source. For example, here the "Sample sales data" data set excel file is imported.

Step 2:-

Drag and drop the orders sheet in the schema pane.

Step 3:-

Go to sheet1; here, different dimensions and measures are available. Click on the drop-down available at the top right corner under the dimensions.

Sentiment Analysis Project on eCommerce Product Reviews with Source Code

Step 4:-

Click on the Create Calculated Field option, a window named Calculation1 will appear. We can rename it to "State isnull". The ISNULL statement works as true or false. If there are any Null values, it will show true; otherwise, it will show false, that is, there is no empty field present. 

Step 5:-

Go to the window of "State isnull", now type ISNULL[State]. Since the State is a string data type, it consists of the names of states in text form. Hence the ISNULL statement displays false. Then click on apply and ok.

Step 6:-

A new field, "State isnull" will appear in the dimensions. Double-click on "State isnull" to appear in the row shelf and say false as the state is a string data type. We can drag and drop the State dimension in the row shelf, so all the state names will appear under the state dimension, and "State isnull" will display false for all. Click on profit measure (sum of profit) . All this data will be available in table form.

Step 7:-

Use the Statement as:- ISNULL[State], click on apply and ok as said in step 5.

What Users are saying..

profile image

Gautam Vermani

Data Consultant at Confidential
linkedin profile url

Having worked in the field of Data Science, I wanted to explore how I can implement projects in other domains, So I thought of connecting with ProjectPro. A project that helped me absorb this topic... Read More

Relevant Projects

Loan Eligibility Prediction in Python using H2O.ai
In this loan prediction project you will build predictive models in Python using H2O.ai to predict if an applicant is able to repay the loan or not.

AWS Project to Build and Deploy LSTM Model with Sagemaker
In this AWS Sagemaker Project, you will learn to build a LSTM model on Sagemaker for sales forecasting while analyzing the impact of weather conditions on Sales.

Learn to Build an End-to-End Machine Learning Pipeline - Part 1
In this Machine Learning Project, you will learn how to build an end-to-end machine learning pipeline for predicting truck delays, addressing a major challenge in the logistics industry.

Build ARCH and GARCH Models in Time Series using Python
In this Project we will build an ARCH and a GARCH model using Python

Deep Learning Project for Beginners with Source Code Part 1
Learn to implement deep neural networks in Python .

Azure Deep Learning-Deploy RNN CNN models for TimeSeries
In this Azure MLOps Project, you will learn to perform docker-based deployment of RNN and CNN Models for Time Series Forecasting on Azure Cloud.

Avocado Machine Learning Project Python for Price Prediction
In this ML Project, you will use the Avocado dataset to build a machine learning model to predict the average price of avocado which is continuous in nature based on region and varieties of avocado.

Walmart Sales Forecasting Data Science Project
Data Science Project in R-Predict the sales for each department using historical markdown data from the Walmart dataset containing data of 45 Walmart stores.

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.

Natural language processing Chatbot application using NLTK for text classification
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.