Displaying 1 to 7 from 7 results

Pandas - Powerful Python Data Analysis Toolkit

  •    Python

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions. It supports aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets, High performance merging and joining of data sets, Time series-functionality, Hierarchical axis indexing and lot more.

fecon235 - Computational tools for financial economics

  •    Jupyter

This is a free open source project for software tools in financial economics. We develop code for research notebooks which are executable scripts capable of statistical computations, as well as, collection of raw data in real-time. This serves to verify theoretical ideas and practical methods interactively. Economic and financial data, both historical and the most current.

masteringmetrics - R code for Angrist & Pischke Mastering Metrics

  •    R

This repository R code and text for [R Code for Mastering 'Metrics](https://jrnold.github.io/masteringmetrics/), which contains the R code to reproduce the analyses in *Mastering 'Metrics* by Joshua D. Angrist and Jörn-Steffen Pischke.




Econ5121A - Lecture notes for Econ5121A: Econometric Theory and Applications

  •    Jupyter

My lectures are based primarily on Bruce Hansen's textbook. I have substantially updated my lecture notes this year to bring forward the teaching of R and demonstrate its use along with theory.

econ5170 - Econ5170@CUHK: Computational Methods in Economics (2018 Spring)

  •    Jupyter

Naijia Guo and Zhentao Shi co-teach Econ5170. Zhentao covers the following topics. This README file will be updated as the course progresses. Code scripts will be provided.

data-science-toolkit - Collection of stats, modeling, and data science tools in Python and R.

  •    Jupyter

Welcome! The purpose of this repository is to serve as stockpile of statistical methods, modeling techniques, and data science tools. The content itself includes everything from educational vignettes on specific topics to tailored functions built to enhance and optimize analyses. This is and will remain a work in progress, and I welcome all contributions and constructive criticism. If you have a suggestion or request, please make use of the "Issues" tab and I will respond expeditiously. All are welcome and encouraged to contribute to this repository. My only request is that you include a detailed description of your contribution, that your code be thoroughly-commented, and that you test your contribution locally with the most recent version of the Master branch integrated prior to submitting the PR.





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