Python Basics for City Data:
An Introductory Tutorial Using Chicago's Municipal Datasets

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About

This tutorial is designed as an introductory journey into Python programming, specifically tailored for those starting from scratch. It leverages Chicago city data as a practical case study, providing hands-on experience and relevant examples for urban data analysis.

It begins with the fundamentals, including installation and importing of key libraries such as numpy, pandas, matplotlib, and scikit-learn. As the tutorial progresses, it delves into basic yet essential data transformations, cleaning, and analysis techniques.

Whether you're a complete beginner or someone with some basic Python knowledge, this tutorial offers the flexibility to either follow along sequentially or choose individual notebooks that align with your specific interest.

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Prerequisites

Before beginning, ensure you have the following tools installed:

• Python:

  • Download the latest version here.

• Visual Studio Code (Recommended):

  • Download here.
  • You can also use anything else that will run Jupyter Notebook (such as Anaconda).

• Pip:

  • Installation requires using the command prompt.

Installation Steps for Pip

1. Open Command Terminal:

   • Access the cmd terminal on your system.

2. Install Pip using Curl:

   • Curl is a tool for transferring data requests to and from a server.

   • Use the following command:

     curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
     python get-pip.py
     

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Overview

Introduction

• Overview of Python:
  • Discusses Python as a language, its benefits, and use cases.
  • Includes installation of basic libraries: numpy, pandas, matplotlib, and scikit-learn.

Part 1: Education Data

• Analysis of CPS Schools Data:
  • Utilizes education data from Chicago Public Schools (CPS).
  • Incorporates geographic data to explore school progress reports in various Chicago zip codes.

Part 2: CTA Data

• [Description of Part 2 content]

Part 3: Crime Data

• [Description of Part 3 content]

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Description of Data Sources

The datasets used in this project are sourced from the City of Chicago Data Portal and other specific repositories. Below is a detailed breakdown of each data source:

City of Chicago Data Portal

• Main Portal:
  • Access all datasets at City of Chicago Data Portal.

CTA Ridership Data

• Dataset Details:

  • Data regarding CTA ridership, including station entries and daily totals.

  • Explore the data here.

  • CTA Ridership API Endpoint

Crime Data

• Chicago Police Department:
  • Detailed crime statistics and datasets available at Chicago Crime Data.

Education Data

• Chicago Public Schools Progress Reports:
  • Access the data at CPS School Progress Reports.
  • Progress Report API Endpoint

Geographic Data (Zip Codes)

• Dataset on ZIP Codes:
  • Geographic boundaries and ZIP code information available at Boundaries - ZIP Codes.