ChatGPT has taken data evaluation to the following level (again) with the assistance of a recent plugin. And no, I’m not referring to the code interpreter, which will not be yet available to all ChatGPT Plus subscribers, but to a recent plugin called Noteable.
Noteable is a recent ChatGPT plugin available on the plugin store that helps us do data evaluation in seconds! You simply need to make use of the prompt I’ll show you in this text to start out working with this plugin.
Here’s how Noteable can provide help to automate your data evaluation.
For those who don’t feel like reading, you may watch my YouTube video as an alternative.
Organising Noteable
First, we want to put in Noteable. To achieve this, go to the Plugin Store and seek for Noteable. Once you discover it, just click on install!
After installing Noteable, the window below will pop up. You’ve got to create an account before beginning to work with this plugin.
Why do we want an account? Well, ChatGPT will display the visualizations and evaluation we ask for, but all of the code is barely going to be available in a notebook format in Noteable. On top of that, we want to create a project on Noteable to work with the plugin.
After you log in, you’ll see an area just like the one below with a default project called “My First Project.” Click on that project or create one from scratch.
When you’re on a project, copy the link. We’ll use that link in the following section. The format of the link should appear to be the one below.
https://app.noteable.io/p//
The Prompt to Use
Now it’s time to let Noteable do data evaluation for us! Here’s the prompt we’re going to make use of.
Load this dataset: Use this as my default project:
Act as a knowledge scientist and analyze ...
As you may see, we only need to supply the link to our dataset and project. That’s just about it!
Things get a bit more tricky with the instructions. You possibly can let Noteable make a generic but quick evaluation or you may specify what you should get within the prompt. Let’s take a look.
1. Quick Data Evaluation with Noteable
First, we’ll let Noteable perform the information evaluation by itself without giving much detail on the features we wish to give attention to.
Let’s automate the information evaluation for a dataset with population data from 1955 to 2020 for all countries around the globe.
Load this dataset: https://github.com/ifrankandrade/python-course-for-excel-users/blob/predominant/4.Data%20Visualization/population_total.csv
Use this as my default project:
Act as a knowledge scientist and analyze the dataset and make charts and graphs to point out the key trends in population growth around the globe
Here’s the dataset overview Noteable gives.
Then it robotically focuses on the 5 most populous countries in 2020 and makes a lineplot to point out the population growth from 1955 to 2020.
Finally, it adds some notes to finish the evaluation. Pretty good!
2. Customized Data Evaluation with Noteable
Now we’ll tell ChatGPT and Noteable the form of evaluation we wish to perform. For this instance, we’ll use a dataset that incorporates details about soccer players from the sport FIFA 20. We’ll specify the visualizations we wish to get and the columns to make use of within the prompt below.
Load this dataset: https://raw.githubusercontent.com/ifrankandrade/data-visualization/predominant/datasets/players_20.csv
Use this as my default project:
Act as a knowledge scientist and analyze the soccer players from only the countries United States, Canada, England, Brazil, and Argentina. Make a barplot to research the column “overall” which represents how good a player is at soccer. Make a histogram and a boxplot to explore the common height of players in such countries. Make a scatterplot to see how the load of players is distributed. Finally, make a piechart to see the highest 10 most useful players (value_eur) from the USA.
The result’s just amazing! ChatGPT and Noteable consider all the main points I discussed.
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