/london-immigration-raids-map

Data for an immigration raid mapping project, for raids in London, from 2014 onwards

Primary LanguageHTML

Immigration raids in London

This repo contains the data behind the https://antiraids.github.io/ FOI investigation.

How to used

  1. ☑ LondonRaids.py: munge the FOI data into a useable format
  2. ☑ MakeItInteractive.py: making the interactive choropleth
  3. ☑ ByEthnicity.py: munging the ethnicity data
  4. ☑ Trends.py: visualise, calculate trends
  5. ☑ TellingTheStory.ipynb: making static plots for the site, along with the narrative of the analysis
  6. ☑ interactive_line.ipynb: making interactive line plots of raids per area per year, for the site
  7. ☑ EthnicityRegression.ipynb: investigating the ethnicity correlations using Bayesian regression. Original investigation was done in the ethnicity_regression.py file, changed to .ipynb for ease of following the flow.

Data sources

Data file Source Used in
AmendedData\\LondonRaidsByYear.csv LondonRaids.py TellingTheStory.ipynb
AmendedData\\TotalLondonRaidsByYear.csv LondonRaids.py TellingTheStory.ipynb, Trends.py
AmendedData\\PopnRaidsRate.csv MakeItInteractive.py TellingTheStory.ipynb
AmendedData\\PostcodeEthnicityRates_toplevel.csv ByEthnicity.py TellingTheStory.ipynb
AmendedData\\PostcodeEthnicityRates_keylines.csv ByEthnicity.py TellingTheStory.ipynb
AmendedData\\RaidTrends.csv Trends.py TellingTheStory.ipynb
AmendedData\\TotalLondonPostcodesWithData.shp LondonRaids.py MakeItInteractive.py
AmendedData\\LondonPop.csv LondonRaids.py MakeItInteractive.py
RawData\\missingpop.csv "Street Check" e.g. for EC4R MakeItInteractive.py
RawData\\KS201EW_Postcode district_Ethnic group.csv Nomis ByEthnicity.py
RawData\55886 xxx Appendix A.xlsx Home Office FOI LondonRaids.py
RawData\57252 xxx Appendix A.xlsx Home Office FOI LondonRaids.py
RawData\56323 xxx Annex.xlsx Home Office FOI LondonRaids.py
RawData\56325 xxx Annex.xlsx Home Office FOI LondonRaids.py
RawData\\57894 PDF scrape_2019RaidsENW.txt (for 2019) Home Office FOI LondonRaids.py
RawData\\64002 xxx Annex.xlsx (for 2020) Home Office FOI LondonRaids.py
RawData\\68195 xxx Annex B.xlsx (for 2021) Home Office FOI LondonRaids.py
RawData\\FOI 2022 immigration raids - FOI 76110.csv (for 2022) Home Office FOI LondonRaids.py
PostalDistrict.shp* From University of Edinburgh, via StackExchange LondonRaids.py
RawData\PostDistNames.csv Wikipedia LondonRaids.py, to assign names to postcode areas
RawData\ECPostDistNames.csv Wikipedia LondonRaids.py, to assign names to postcode areas
RawData\Nomis KS101EW usual resident population London.csv Nomis LondonRaids.py
RawData\returns-datasets-dec-2022.xlsx Gov.uk deportation_data_investigation.py

* not included in this repo for size reasons (as it is 85 MB)

Notes

Timespan: the FOI data runs from 2014 to 2022 inclusive.

Tools used:

  • Straight-up Python for the data munging and basic analysis
  • Folium and Geopandas packages to visualise the data in a choropleth map, weighed by number of immigration raids since 2014, and also optionally by immigration raids per 1,000 residents.
  • mpld3 for the interactive charts

Hat tips to:

Notes:

  • By "London", we mean the "London postal district" i.e. any postcode with postcode area N, NW, SW, SE, W, WC, E or EC.
  • For a lot of the preparation time, the assumption was that "postcode district" was the correct term for what is actually technically the "outward code" -- so there are a lot of references to "district" and "postdist" in the code.