pattyjula/bigdata-demo

This repository contain content on big data processing and analysis given at the "Data Batcave" on August 16, 2018.

Guide to Python Data Viz Demonstration

Process

1. Live code parts of 01-data-cleanse-example
2. Live code sections of 02-plot-crimes
3. Display complete code for 03-plot-calls-for-service
   • Only output PNG files are included in this 03 folder

Objectives

• Understand conversion of CSV file to a dataframe
• Understand use of conditionals and looping
• Examine methods for data cleansing and discuss importance of doing so
• Discuss value of normalizing data sets
• Review Python libraries such as matplotlib, pandas, and seaborn for visualizing data
• Be able to run .ipynb files from Jupyter Notebook
• Be able to run .py files from Gitbash, Command Prompt or Teminal

Requirements

Necessary if attendees want to run programs

• Python 3.6.x 64-bit from Anaconda

• Jupyter Notebook (typically installed with Anaconda)

• Optionally Git

• Download or clone the repository

  • With SSH key git clone [email protected]:CityOfLosAngeles/data-batcave-trainings.git
  • no SSH key? try git clone https://github.com/CityOfLosAngeles/data-batcave-trainings.git

Matplotlib Install Reference

• From within virtual enivornment enter command: python -mpip install --upgrade matplotlib
  • This will update your matplotlib version so it works better with the code
  • Optionally users can run command from local machine with command: pip install --upgrade matplotlib
  • confirm version print(mpl.__version__)

Resources

This is a short list of Python Resources. Signing up for MOTW-3 is highly recommended

• Module of the Week MOTW-3
• Self study resource
• Automate the Boring Stuff with Python