Web Visualizations

Description

This project gives several interactive visualizations of 311 service requests for graffitti removal in the city of chicago. They may be viewed at the following link.

Web visualizations link

Technologies Employed

• postgreSQL
• Python
  • SQLAlchemy
  • pandas
  • Jupyter Lab
  • csv
  • pandas
  • json
• JavaScript
  • D3
  • Plotly.js
  • Leaflet.js
• HTML
• CSS

Setup

1. Export data to 311_Service_Requests_-_Graffiti_Removal_-_No_Duplicates.csv from the Chicago data portal
2. Run python script data_munge.py to extract relevant data.
3. Create a local database to store data for subsequent analysis.

createdb graffiti

4. Use postgreSQL to run the schema.sql file to create the GraffitiData table

psql -d graffiti -f schema.sql

5. Use postgreSQL to load the cleaned csv into the newly created table.

psql -d graffiti -c "COPY GraffitiData(creation_date,status,completion_date,type_of_service_request,surface_type,graffiti_location,zip,ward,community_area,latitude,longitude) FROM 'path_to_file/gra_req_clean.csv' WITH DELIMITER ',' CSV;"

6. Create a file databaseconfig to hold credentials for the database.

7. Use the do_querries.ipynb jupyter notebook to create the json files used by the plots.

Notes

Demographic data from Chicago data portal

2010 Census data from CMAP Data Hub