In-class exercise¶
Goal: Show the change in Access to Electricity by country over time.
Use World Development Indicators data.
Click
CSV file.Unzip it.
From that folder, use
WDICSV.csv(or similar).
You’re welcome to view the data in a spreadsheet, but please use Python for any cleaning, filtering, visualization, etc.
Feel free to explore; the important thing is you’re getting practice, not that you complete it.
Demo: Mapping¶
Map complaint counts by CD
This should help us better understand trends across the city. We’ll follow this example, using community district GIS data.
Jump to the map, work backwards
Load the 311 requests per capita data from last class¶
https://
Fun fact (for a certain kind of person): What the zoom level means
What visualization should I use?¶
Rudimentary guidelines:
| What do you want to do? | Chart type |
|---|---|
| Show changes over time | Line chart |
| Compare values for categorical data | Bar chart |
| Compare two numeric variables | Scatter plot |
| Count things / show distribution across a range | Histogram |
| Show geographic trends | Map (choropleth, hexbin, bubble, etc.) |
The Data Design Standards go into more detail.