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Going Beyond EDA: A Deeper Analysis of NYC 311 Street Flooding Complaints 📈

The objective of this presentation is to examine multiple approaches for gaining deeper insights and a better understanding of the NYC 311 Street Flood Complaints open data.

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Event Details 📅

NYC Open Data Website: NYC Open Data Week 2023

Date: Saturday, March 18, 2023 🕘

Analysis Book: nyc-street-flooding-analysis.datalife.nyc

Presentation Slides: ⭳ Download

Contributors 💻

Presenter LinkedIn GitHub Twitter
Ho Hsieh LinkedIn GitHub followers
Nathan Williamson LinkedIn GitHub followers
Mark Bauer LinkedIn GitHub followers Twitter Follow
Chidi Ezeolu LinkedIn GitHub followers

Installation 💽

Application Installs

  1. Install Anaconda to manage Python packages and environments.

  2. Install Git to maintain version control.

  3. Install Graphviz to build diagrams with code.

Terminal Commands

  1. Clone nyc-street-flood-analysis repo

    git clone https://github.com/datalifenyc/nyc-street-flood-analysis.git
  2. Enter folder directory of local repo

    cd nyc-street-flood-analysis
  3. Install requirements

    conda env create -f environment.yml

    Two alternative environment files are provided, which offer detailed library versions (environment-no-builds.yml) and build info (environment-with-builds.yml).

  4. Activate conda environment

    conda activate nyc-street-flood-analysis
  5. Install and Configure Git to track large notebook files

    Step 1: Install Step 2: Configure
    git lfs install git lfs track "*.ipynb"

    Jupyter Notebooks with maps tend to larger in size. For best practices and to avoid commit warning/errors, as well as, issues pushing repo to GitHub, use Git Large File Storage (Git LFS): website | docs | repo.

    To push lfs updates to repo, enter:

    git lfs push origin main

Notes

Jupyter Notebooks can be found in the analysis-book folder.