cm009.Rmd

---
title: "Introduction to Python"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(cache=TRUE)
```

# cm009 - October 24, 2016

## Overview

* Introduce the Python programming language
* Review why it is helpful to learn both Python and R
* Demonstrate the use of Python and R in a data analysis project
* Identify common types of data in Python
* Identify the major differences between Python and R
* Practice writing basic code in Python

## Slides and links

* [Slides](extras/cm009_slides.html)
* [Using Python Basics for R Users](python_gentle_intro.html)
* [Git repository for Gentle Introduction from R to Python](https://github.com/jmausolf/Gentle_R_to_Python)

* [How to apply face recognition API technology to data journalism with R and python](https://benheubl.github.io/data%20analysis/fr/)
* [Python vs R: head to head data analysis](https://www.dataquest.io/blog/python-vs-r/)
* [Comparison of basic commands in R vs. Python](http://mathesaurus.sourceforge.net/matlab-python-xref.pdf) - ignore the MATLAB stuff. Also note that this comparison is several years old, so some specific functions may have changed, but the gist of it should still be accurate.


## To do for Wednesday

* [Finish homework 4](hw04-analysis-pipeline.html)
* Make sure [Python is installed and working](setup02.html)
* Read chapters 8, 10 from [Think Python](http://proquestcombo.safaribooksonline.com.proxy.uchicago.edu/book/programming/python/9781449332006)