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An introduction to data analysis in Python

An introduction to data analysis in Python

The Basics

1. The Basics
2. Data collections
3. Functions
4. Loops

NumPy

1. Starting data handling in Python - NumPy
2. The numpy module
3. Data indexing, simulation, and summary statistics

pandas

1. The pandas module
2. Accessing data in Pandas
3. Boolean operations with Pandas
4. The power of groupby and aggregation
5. Custom functions

pandas - advanced uses

1. Advanced data handling with pandas
2. Data surgery - reshaping data with melt
3. There and back again - reshaping data with .pivot_table() .
4. Data surgery - joining DataFrames with pd.concat and pd.merge

Data Visualisation

1. Introducing matplotlib
2. Using seaborn for smoother data visualisation
3. Advanced plotting with seaborn

Statistical Analysis

1. (Frequentist) Statistics in Python
2. Statistics with statsmodels and scipy.stats
3. Generalised Linear Models
4. Hierarchical or mixed models
5. Bonus section - I ts J ust A L inear M odel

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By Alex Jones, Ph.D
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