Introduction to Python for Econometrics, Statistics and Data Analysis

Introduction to Python for Econometrics, Statistics and Data Analysis – Ebook PDF Instant Download/Delivery

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• Author: Kevin Sheppard

Python is a popular general purpose programming language which is well suited to a wide range of problems. Recent developments have extended Python’s range of applicability to econometrics, statistics and general numerical analysis. Python – with the right set of add-ons – is comparable to domain-specific languages such as R, MATLAB or Julia.

This book provides an introduction to Python for a beginning programmer. They may also be useful for an experienced Python programmer interested in using NumPy, SciPy, and matplotlib for numerical and statistical analaysis. They should also be useful for students, researchers or practitioners who require a versatile platform for econometrics, statistics or general numerical analysis (e.g. numeric solutions to economic models or model simulation).

Table contents:

1 Introduction

2 Python 2.7 vs. 3 (and the rest)

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

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