Author(s): John Loewen, PhD

Originally published on Towards AI.

Exploratory analysis and data storytelling on global forest loss

Prompting GPT-4 for exploratory data analysis and storytelling are an essential tool to add to your data science toolbox.

For example, bar chart analysis, including grouped bar charts and rate-change, offers different perspectives on a particular data series.

In this tutorial, let’s use GPT-4’s impressive data analysis capabilities to analyze the Global Tree Cover Loss dataset.

With simple prompting, we can create multiple bar chart visualizations from our data set to provide a more granular country level analysis.

Let’s step through some examples!

The foundation of any good visualization is the dataset. For this tutorial, we’re working with a tree cover loss dataset.

The Global Forest Watch data set contains key statistics about global forests, including rates of forest change, forest extent and drivers of deforestation (found HERE). At their website, scroll down until you see the following:

Global annual tree cover loss dataset.

Click on the download icon to download the file.

After you have downloaded the file, you will need to unzip it. In the new directory there will be a few files. You can use the Upload File utility as part of the GPT-4 interface to load our data set.

In the GPT-4 chat window, click on the ‘+’ icon to upload a file.Select the file called… Read the full blog for free on Medium.

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Published via Towards AI