Overview

In this tutorial you will apply the lessons you’ve learned in Pandas, Folium, and Plotly to map a new dataset. You might want to draw from:

The Dataset

You are going to start from scratch and try to analyze and map a new historical dataset: 1877-official-register.csv. This comes from the Official Register of the United States, for 1877. This is a bi-annual directory of workers employed by the federal government, listing their location (state and county) and salary for that year. Unlike a similar dataset you worked with in 💻 Mapping with Folium I, this dataset is made up of all other kinds of government employees besides postmasters. Note: this only includes data for western states and territories.

Tasks

  • Explore the basic contents of the dataset
  • Make a map showing the locations of these employees
  • Add popup/tooltip options that show the name of the location, the government agency, and the number of people working there
  • Create another map where locations are sized according to the number of people employed there.
  • Adjust sizes of the markers by creating categories and marker sizes
  • Draw on your Pandas and Plotly skills to look at and visualize other dimensions of the data:
    • What were the top 10 individual locations measured by the largest number of employees?
    • Which states had the most government employees working in the state?
    • Which government departments employed the largest number of people?
    • How many different locations of government employees did each state have?