Explored the London Fire Brigades incident response times from the start of the 999 call to the first fire engine arrival across the 32 London boroughs from 2010 to 2021.
🔥 Got good practice extracting, exploring, and cleaning data using Pandas
🚒 Stretched myself with creating highly customised plots with Matplotlib
⏱️ Learned Geopandas to handle GeoJson's and create Choropleth Map Plots
Excel files were downloaded from here: https://data.london.gov.uk/dataset/incident-response-times-fire-facts
Each .xlsx file had multiple sheets. The relevant sheet for this project was sheet 6.1 which had the average incident response times from the start of the 999 call to the first fire engine arrival in minutes. They were arranged by year on columns, and borough on rows.
- Creating a side-by-side bar chart in Matplotlib using custom xticks values and bar widths
- Using different tick values and tick labels to make the scale understandable to a viewer
- Creating Colourmap objects to have a consistent colour scheme betweeen the Geoplots and Matplotlib plots
- Using subplots to have multiple pie charts and to create white space
- Creating a colourbar object to communicate the Choropleth plot clearly
- Using padding and coordinates to relocate legend and title objects
- Making and customizing bbox objects
