TabPy is an Analytics Extension from Tableau that allows users to execute Python Scripts and saved functions using Tableau. With TabPy, we can run Python Script on the fly and display results as a visualization. It is also possible to control data sent to TabPy by interacting with the Tableau worksheet and dashboard via the parameters.

We all know Python programming is the most popular language used to work on various statistical problems. Using this language with Tableau is a significant improvement in improving the effectiveness of a Developer.

Now, let’s discuss why you need to start using TabPy.

Key Reasons

For Data Cleaning Purpose: With TabPy, we can perform data cleaning on messy data by removing non-useful columns, missing values, and as well any other actions we might want to perform. TabPy gives Developers the feel of working smarter.

For Building predictive algorithms: Predictive Modeling is a way we use our data and statistics to predict the outcome of a data model. This process is also known as predictive analysis. Therefore, using TabPy, we can build our Predictive Algorithms inside Tableau.

Churn prediction: Churn Prediction is another vital aspect business owners mostly dwell on. With TabPy, we can learn when and why users leave. We can also detect patterns we need in our data, predict and prevent them from happening.

Writing Calculated Field in Python: We can also write our calculated field with Python without using Tableau with the help of TabPy. Using Python whenever we want to do advanced analytics is also always advisable.

Lead scoring: Leads generation is another essential sector lot of business owners works hard to convert leads into payable customers. We can create an efficient conversion funnel with Python for scoring users’ behavior with a predictive model. This can be made possible with TabPy as well.

Now that we’ve seen the major reasons TabPy is very good to use in Tableau, let’s see how we can install it.

How to Install TabPy

We’ll install TabPy using Anaconda Navigator through the Anaconda Prompt.

Step 1

Open your Anaconda prompt and create a virtual environment using the below command. This isn’t compulsory, though.

1 conda create — name virtualenv

Step 2

Now, let’s upgrade our pip version with the command below.

1 python -m pip install — upgrade pip

Step3

Our Pip has been upgraded, and we can move further to install TabPy. From the image below, TabPy was installed earlier on my machine.

1 pip install tabpy

Step 4

By now, you should have TabPy installed on your machine. Let’s run the server now. We can run using the command below inside the same Anaconda prompt. So, you type tabpy, and you should have a similar image we have below.

1 tabpy

Now, you open your browser and visit this URL http://localhost:9004/ to verify the web service is running. You should have an image like this.

Step 5

What we need to do next is to make Tableau connected with Tabpy, open our Tableau Desktop, and click on help -> Settings and Performance ->Manage Analytics Extension Connection.

This brings up a pop-up. You select TabPy as the External Service, indicate the server as localhost and Port as 9004, then click OK.

Now we’ve created a connection.

Have you started exploring TabPy ? What was your experience like? Share your thoughts in the comments section below.