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CoP: Data Science: Analyze correlations between metro locations and 311-data requests #107

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hackforla/311-data
#1257
@ryanmswan

Description

@ryanmswan

Overview

Investigate whether there are meaningful trends associated with metro stops and metro lines with regards to requests tracked by 311-data in LA County.

Action Items

  • Define requirements for 311 data (adding notes to the resources section and discussing at the Data Science CoP meeting
    • Do you need a one-time or ongoing dump of the data?
    • Do you need subset of data (i.e. certain years) or the entire data set (approx. 4 million rows or 11 GB)?
      • If a subset is needed, please define subset characteristics (i.e. date range, etc.)
    • Do you need online access via an API or a download of data?
    • Add dependency label and put in the icebox until 311 data is provided
  • Find available data sources and add to Resources section below
  • Determine is this is one-time or ongoing project (and assign appropriate label)
  • Write one-sheet
    • Define stakeholder
    • Summarize project including value add
    • Define project 6 month roadmap
    • Detail history (if any)
  • Define tools to be used to visualize combined data
  • Create issues for the following
    • EDA (Exploratory Data Analysis) of metro data
    • Identify correlations between distance from metro stop and request type
    • Determine if correlations observed are solely due to metro stop or are more broadly associated with population density or other factors
    • Combine geolocation data for metro lines with district types
    • Compare correlations/trends between different districts within each type
    • Compare LA county data with other California counties, compare with district types within county. (Post MVP)
    • Compare with statewide trends and within district types. (Post MVP)

Resources

Information about 311 Data here
Access 311 data here
http://geohub.lacity.org/datasets/metro-rail-lines-stops
https://developer.metro.net/docs/gis-data/overview/
District types issue: #118

use 2019 data for 311
streetlights
crime
metrostops

tools
google colab, sklearn, pandas

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