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