Coding for Economists|凡凡私薦第10期

本期推薦一份編程資料,作者是Arthur Turrell ,來自Research and Capability at the ONS Data Science Campus。

Welcome to coding for economists, a guide for economists on what programming is, why it’s useful, and how to do it.
The book aims to give you the skills you need to code for economics, while also giving you bits and pieces of information about programming more generally that might be useful to you. It’s suitable for complete beginners who have never written any code before. Some of the later chapters are suitable for people who have coded before too.
Naturally, at times, I have made choices regarding what to include, what to omit, and what to recommend. I have given recommendations based on what will serve you best in the long-run. Very occasionally, like the Karate Kid painting Mr Miyagi’s fence, you will wonder why such and such a thing is useful for coding in an economics context. But, also like the Karate Kid, you will find that you weren’t just learning to paint a fence, you were becoming a karate (coding) master.

1.Coding

1.1 Preliminaries

1.2 Basics of Coding

1.3 Advanced Coding

1.4 Options for Writing Code

2.Workflow

2.1 Tips for Better Coding

2.2 Tools for Better Coding

2.3 The Command Line

3.Data

3.1 Data Analysis Quickstart

3.2 Working with Data

3.3 Exploratory Data Analysis

3.4 Reading and Writing Files

3.5 Extracting Data

3.6 Sharing Data

3.7 Advanced Data

4.Data Visualisation

4.1 Intro to Data Visualisation

4.2 Common Plots

4.3 Animation

5.Econometrics

5.1 Probability and Random Processes

5.2 Statistics

5.3 Regression

6.Text Analysis

6.1 Introduction to Text

6.2 Natural Language Processing

7.Time

7.1 Introduction to Time

7.2 Time Series

8.Geospatial

8.1 Intro to Geo-Spatial Analysis

8.2 Geo-Spatial Visualisation

9.Mathematics with Code

9.1 Intro to Mathematics with Code

10.Automation

10.1 Automating Research Outputs

11.Coming from...

11.1 Coming from Stata

11.2 Coming from Matlab

11.3 Coming from R

11.4 Coming from Excel

https://aeturrell.github.io/coding-for-economists/econmt-statistics.html

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