Mark Bauer

• 1. Introduction
• 2. Notebooks
• 3. Data
• 4. Open Source Applications Used in Project
• 5. Additional Resources

NYC Open Data provides a treasure-trove of information - all publicly available with a click of a button. While having access to data is great, its analysis is often a difficult process for beginners, potentially creating barriers in one's open data journey. Additionally, performing data analysis in a reproducible way is often limited or even discarded altogether.

Data Analysis Using Python: A Beginner’s Guide Featuring NYC Open Data is a four-part series as listed in the sections below. These collection of notebooks serve as references/user guides for how to apply Python to real-world Data Analysis projects. The repository features notebooks that will utilize the Python programming language and datasets from NYC Open Data. This series exemplifies how data analytics can be used for discovering useful information and supporting decision-making.

Sections include:

Part 1: Reading and Writing Files in Python.

Part 2: Data Inspection, Cleaning, and Wrangling in Python.

Part 3: Plotting and Data Visualization in Python.

Part 4: Geospatial Data and Mapping.

You can run an interactive example on MyBinder through your browser - no installation required: click here . Loading MyBinder is a bit slow and takes ~5 minutes, but it will load eventually.

You can view these notebooks through your browser by clicking View under the Static Webpage column.

• Anaconda: A distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment.
• Project Jupyter: Project Jupyter is a non-profit, open-source project, born out of the IPython Project in 2014 as it evolved to support interactive data science and scientific computing across all programming languages.
  • Jupyter Notebook: The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
  • nbviewer: A web application that lets you enter the URL of a Jupyter Notebook file, renders that notebook as a static HTML web page, and gives you a stable link to that page which you can share with others.
  • Binder: The Binder Project is an open community that makes it possible to create sharable, interactive, reproducible environments.

• NYC Open Data: Open Data is free public data published by New York City agencies and other partners.
• Sodapy Tutorial Using NYC Open Data: This tutorial demonstrates how to use sodapy and provides examples of querying data using Socrata Query Language or SoQL.
• Analyzing NYC's 311 Street Flooding Complaints from 2010 to 2020: Analysis of street flooding complaints with NYC Open Data's 311 dataset. Provides an example of a real-world project using Python for Data Analysis.

I can be reached at:

Twitter: markbauerwater
LinkedIn: markebauer
GitHub: mebauer