/Programming-Statistics-and-Econometrics-Resources

Programming, statistics and econometrics resources

Programming, Statistics, and Econometrics Resources

# 📌 Find
resources = ["Books", "Websites", "Other Repos", "Academic Papers"]

# 📌 on these 
topics = {"Programming": ["Python", "R"],

          "Statistics": ["Coming Soon!"],

          "Econometrics": ["OLS Regression Analysis & Time Series",
                           "Microeconometrics & Statistical Models",
                           "Applied Econometrics & Causal Inference",
                           "Computational Methods in Econometrics"],}

Select the titles to go to the relevant sections.

Resources

Programming 🧑‍💻

Contents

📌 Python

📌 R

(currently Python and R primarily)

🎯 Fundamentals

Python fundamentals: books, websites and other github repos

‣ Books 📚

Name Description Link 🔗 Learn/Practice
Paragraph Text Link Practice

‣ Websites 💻

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Python Cheatsheet For quick reference, covering various topics (loops, functions, OOP and more). Based on 'Automate the Boring Stuff with Python' book and other sources. Link Learn

‣ Github repos

Name Description Link 🔗 Learn/Practice
Full Speed Python For self-learners with topics and exercises Link Learn + Practice (exercises from the Superior School of Technology of Setúbal)
Paragraph Text Link Practice

Back to contents

🎯 Data analytics & Data Science

Python data analytics and data science resources: books, websites and other github repos

‣ Books 📚

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Paragraph Text Link Practice

‣ Websites 💻

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
PandasAI Combining data analysis with AI and making the process conversational! Link Practice

‣ Github repos

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Awesome Public Datasets A list of public datasets in various domains (ranging from climate to cancer) Link Practice

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🎯 Machine Learning

Machine Learning in Python: books, websites and other github repos

‣ Books 📚

Name Description Link 🔗 Learn/Practice
Paragraph Text Link Practice

‣ Websites 💻

Name Description Link 🔗 Learn/Practice
Header Title Link Learn

‣ Github repos

Name Description Link 🔗 Learn/Practice
Paragraph Text Link Practice

Back to contents

🎯 Algorithms & Data Structures

Python algorithms and data structures: books, websites and other github repos

‣ Books 📚

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Paragraph Text Link Practice

‣ Websites 💻

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Paragraph Text Link Practice

‣ Github repos

Name Description Link 🔗 Learn/Practice
The Algorithms Search up any algorithm to find out more Link Learn
Advanced Data Structures with Python Algorithms and data structures uses and examples, especially useful for competitive programming Link Learn

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🎯 Apps + Others

Python apps + other areas: books, websites and other github repos

‣ Books 📚

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Paragraph Text Link Practice

‣ Websites 💻

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
ReactPy Text Link Practice

‣ Github repos

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
PyWebIO Building web applications without the need for HTML and JS Link Practice

Back to contents

Statistics 📊

Coming soon!

Econometrics + Causal Inference 📈

Contents

📌 OLS regression analysis

📌 Microeconometrics & Statistical Models

📌 Time Series

📌 Applied Econometrics + Causal Inference

📌 Computational Methods in Econometrics

🎯 Fundamentals of Causal Inference

Causal inference fundamentals including Judea Pearl's work, DAGs, matching, and more!

‣ Books 📚

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Paragraph Text Link Practice

‣ Websites 💻

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
The Mixtape with Scott A podcast involving discussions with economists, scientists and more. The site also includes sessions on causal inference methods. Link Learn

‣ Github repos

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Practice

‣ Academic Papers

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Practice

Back to contents

🎯 Difference in Differences

All about the estimating technique, assumptions, violations and more!

‣ Books 📚

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Paragraph Text Link Practice

‣ Websites 💻

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Text Practice

‣ Github repos

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Practice

‣ Academic Papers

Name Description Link 🔗 Learn/Practice
Header Title Link Learn
Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania Labour market effects of an increase in the minimum wage in New Jersey in 1992 Link Learn

Back to contents

..Others coming soon!

Questions

How can I contribute?
- Any contributions are welcome, as this repo is not exhaustive.
- If you would like to, please get in touch on Linkedin or email (in my profile homepage: readme or site) or feel free to make a pull request.
- Don't forget to share this with anyone who might find it useful!
Why these resources/areas in particular?
- The topics interest me and will help me keep track of my progress and learning (and hope this does the same for you as well!) They are also suited for those interested in (academic or professional) careers or topics at the intersection of econometrics, statistics and programming.
- Resources in the econometrics and statistics sections provide guidance on statistical models, causal inference, time series analysis, and more, making them especially useful for those interested in data science and machine learning. Each of the statistics and econometrics areas has resources on applications to programming as well.
- Having everything in one place makes it much easier to find resources without having to search through the vast amount of information in various locations (that's probably not organised well too!) You're more likely to delve into an area if you're provided with sufficient details and can find adequate information and resources to get started.
Are these resources suitable for those with a beginner, intermediate, or advanced background?
- The resources are intended to suit individuals with varying backgrounds.
- You can get an idea of the levels by reading the descriptions and selecting the relevant links.
- You're welcome to contribute by adding an additional column to the tables and providing this information!
Additional notes
- Resources with a github repository and website are only included in either of the two sections.
- All of the resources listed here are intended to be entirely free to use, thereby omitting some popular resources. Please refer to the contribute section if you would like to add anything that's missing.
- I'm working to add more resources when I find any and get the time to.