How to Create Interactive Maps in Python

This is what you’ll make by the end of this article!

Table of Contents

· Introduction
· Importing the Libraries
· Peeking at the Data
· Creating the Final Map
· Video Explanation

Introduction

In this article, I’ll show you how to display the map in the image above. It might look intimidating, but it’s really not! In fact, it only takes a couple lines of code.

Importing the Libraries

There are 4 visualization libraries needed for this to work:

If you forget to import one of these libraries, you will run into an error since the map won’t render properly.

Now, we’re going to load our data with the help of the GeoPandas library. It has a method called .read_file where you pass in the file path.

I’m going to use a dataset on Chicago’s crime, health, and population stats in 2014. You can download it here: https://geodacenter.github.io/data-and-lab/comarea_vars/.

Photo by Sawyer Bengston on Unsplash

Here’s what the code looks like:

NOTE: The file path may be different for you, depending on where your dataset is located in your machine.

Doing this will make “file” a GeoDataFrame, which means we’re closer to getting our final map.

Peeking at the Data

I just want to look at the first 5 rows of this GeoDataFrame. All I have to do is call the .head method:

If you keep scrolling through the dataset, you’ll notice that the last column says “geometry”:

This column has a bunch of Polygon objects that contain coordinate points. These Polygons allow Python to create a map from the data, and every GeoDataFrame must have this column.

Creating the Final Map

We only have two lines of code left! The nice thing is that the GeoPandas library provides us with .explore. In this simple method, we just have to pass in the column name(s).

I want to see how the property crime rates differ across the different Chicago areas, so I’m gonna say this:

In this case, “Property_C” is the column name in the dataset. But you can put in whatever column you want since you’re the analyst!

Here’s what the final result looks like:

The cool thing is that you can move the map around and zoom in/out. I encourage you to try it yourself!

Video Explanation

Thank you so much for reading this article! If you want to see me walk through all the steps that I just talked about, then feel free to check out this video:

It’ll only take 3 minutes of your time 😀!

Originally published at https://dylans0ng.github.io on July 27, 2023.