Getting Started w/ Python: Difference between revisions

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== Python Introduction ==
== Python Introduction ==
# Open https://github.com/jvdkwast/Python3_Jupyter_Notebook
* Good Tutorial
# Click Code > Download ZIP
*# Open https://github.com/jvdkwast/Python3_Jupyter_Notebook
# Download to your working directory and Extract
*# Click Code > Download ZIP
# Double click on PythonIntro.ipynb
*# Download to your working directory and Extract
*# Double click on PythonIntro.ipynb


# imports & libraries
 
# Variables (numbers, strings, lists, tuples, dictionaries, objects)
* Python Runthrough
# functions
*# imports & libraries
# looping
*# Variables (numbers, strings, lists, tuples, dictionaries, objects)
# if, elif, else
*# functions
*# looping
*# if, elif, else


== Pandas and Data Manipulation ==
== Pandas and Data Manipulation ==

Revision as of 04:22, 13 January 2023


Installation

  1. Install Python for Windows
    1. Add Python to Environment Variables (Checked)
  2. Install VSCode for Windows
    1. From Extensions, install the following:
      1. Python
      2. Jupyter

Setup

  1. Create a Working Directory (Documents > FOQA)
  2. Open Working Directory from VSCode
    1. File > Open Folder > Select Folder
    2. If prompted, Trust the folder
  3. Download pySara from Teams > FOQA > Files > Python > pysara.zip and extract to your new working directory
  4. From the pysara folder extracted to your working directory, double click on Getting Started.ipynb. It should open in VSCode
  5. To install required libraries:
    • Terminal menu > New Terminal
    • pip install pandas seaborn numpy requests plotly

Jupyter Introduction

  1. Cell Types: Code and Markup
  2. Shortcuts (hit escape to enter command mode)
    • Shift Enter: Execute Cell
    • A: Add Cell Above
    • B: Add Cell Below
    • DD: Delete Cell
    • F: Find/Find and Replace
    • Enter: Enter edit mode
  3. Markdown
    • Headers
    • Lists

Python Introduction


  • Python Runthrough
    1. imports & libraries
    2. Variables (numbers, strings, lists, tuples, dictionaries, objects)
    3. functions
    4. looping
    5. if, elif, else

Pandas and Data Manipulation

  • Pivot Tables