Download Introduction to Python for Econometrics, Statistics and Numerical Analysis by Kevin Sheppard, Python is a widely used general purpose programing language, which happens to be suited to econometrics and different additional general purpose data analysis tasks. These notes give an introduction to Python for a beginning programmer. they may also be helpful for an experienced Python programmer interested in using NumPy, SciPy, and matplotlib for numerical and statistical analaysis. Download the pdf from below to explore all topics and start learning.


1 Introduction
2 Python 2.7 vs. 3 (and the rest)
3 Built-in Data Types
4 Arrays and Matrices
5 Basic Math
6 Basic Functions and Numerical Indexing
7 Special Arrays
8 Array and Matrix Functions
9 Importing and Exporting Data
10 Inf, NaN and Numeric Limits
11 Logical Operators and Find
12 Advanced Selection and Assignment
13 Flow Control, Loops and Exception Handling
14 Dates and Times
15 Graphics
16 pandas
17 Structured Arrays
18 Custom Function and Modules
19 Probability and Statistics Functions
20 Statistical Analysis with statsmodels
21 Non-linear Function Optimization
22 String Manipulation
23 File System Operations
24 Performance and Code Optimization
25 Improving Performance using Numba
26 Improving Performance using Cython
27 Executing Code in Parallel
28 Object-Oriented Programming (OOP)
29 Other Interesting Python Packages
30 Examples
31 Quick Reference