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murals's Introduction

Collecting the data

  • Manually collected the points of murals in three neighborhoods
  • The three neighborhoods were: Old North St. Louis, Covenant Blu Grand Center, Forest Park Southeast
  • Used geojson.io to plot the relative locations of the murals

Datawrapper

  • Downloaded a shpfile containing the neighborhoods boundaries from the City of St. Louis' open data portal
  • Exported a separate geojson of each of the three neighborhoods in QGIS
  • Imported the neighborhood boundaries and the points for each neighborhood into their own graphic in Datawrapper: 1, 2, 3
  • Created the bike route in Google My Maps and exported as a KML, save to geojson
  • Each part of the route in Google My Maps needed to be its own individual segment
  • Export the chart without headers or background from Datawrapper into Illustrator

Illustrator

  • Imported SVG file from Datawrapper
  • Ungrouped all the layers
  • Re-organized the contents into four layers: ai2html-settings, interactions:svg, furniture and basemap
  • Export the artboard using ai2html
  • Add the following settings to ai2html export: inline_svg: true, png_transparent: yes
  • For static graphics, added the SVG output to the story
  • For the scrollytelling portion, copy and pasted ai2html output into story and used Scrollama to animate features

Data analysis

  • Analysis used in the story can be found in analysis.ipynb
  • Crime data scraped from the St. Louis Post-Dispatch's crime tracker using Selenium
  • Census data scraped from the City of St. Louis using BeautifulSoup
  • Walkability data scraped from Walk Score using BeautifulSoup
  • Percent of race in a neighborhood: ((pct_group - total population of neighborhood) / total population of neighborhood ) * 100
  • Murals per capita: (num_murals / total population of neighborhood)

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