Data Analysis using Python

Data Analysis using Python and Pandas

Scope

1. Using notebooks for data analysis pipeline
2. Introduction to pandas
3. Loading data
4. Using it like Excel
5. Plotting data using pandas, matplotlib, and seaborn.
6. Presenting the results.

Dependencies

• Python >3.5 - using Anaconda
• Jupyter notebook - comes in anaconda package
• pandas, matplotlib, numpy, seaborn - comes in anaconda package
• pandas-datareader

Install using conda install pandas-datareader seaborn

Documentation

• Pandas: http://pandas.pydata.org/pandas-docs/stable/index.html
• Seaborn: http://seaborn.pydata.org/index.html

Useful resources:

• Official pandas introduction: http://pandas.pydata.org/pandas-docs/version/0.19.2/10min.html
• Detailed intro to pandas: http://nbviewer.jupyter.org/gist/TomAugspurger/2457b5debf072ac0318d3d14e63145d5
• Lots of exercises to practice pandas: https://github.com/guipsamora/pandas_exercises