plot us population density on map python

Plot us population density on map python download#

Below are all of the packages we will be using in this post. We are currently using version 0.8.1 of tidycensus and version 2.1-1 of tmap. Our previous blog post on reading spatial files into R.Our previous blog post on mapping and analyzing raster data in R.Our DataCamp course on working with sf and raster objects in R.If you need a refresher on working with spatial data in R we recommend the following: This post assumes a basic understanding of data manipulation with dplyr and a basic understanding of working with spatial objects using the sf package.

Plot us population density on map python download#

If you’d prefer to skip to Part 2 you can download the Census data here. Referring to the data in Part 1, Part 2 outlines the map-making process using tmap. Part 1 focuses on the collection of Census data using tidycensus. This post is is intended to mimic a real-world task that requires both data collection and data visualization of geographic data and is broken into in two parts. Note that this post is designed to allow you to skip ahead to the tmap section if mapping is what you’re interested in.

Customizing layout features and adding attributes to the map.

Part 2: Creating beautiful maps with tmap.

Initial visualization of the health insurance data using ggplot.

Part 1: Using tidycensus to collect US Census data.

The tidycensus package, authored by Kyle Walker, streamlines geographic and tabular data downloads while the tmap package, written by Martijn Tennekes, vastly simplifies creating maps with multiple layers, accepts many different spatial object types and makes it easy to add scale bars, north arrows and other cartographic details. The tidycensus and tmap R packages make an incredible duo for working with and visualizing US Census data.