bruceR
priceR
bruceR | priceR | |
---|---|---|
1 | 1 | |
153 | 55 | |
- | - | |
4.9 | 7.1 | |
7 months ago | 3 months ago | |
R | R | |
GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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bruceR
priceR
-
Choosing Julia, Matlab, Python or R in economics?
I was an economist doing econometrics in excel when in 2014 the datasets went being a few 10,000's rows to a few 1,000,000's rows. I found R easiest to learn simply as a CS outsider because it was less strict about package versions and installation requirements, which made it easier for a beginner. I learned it by googling every little step ('how read in csv', 'how create new column in data.frame' etc) until I had a ~40 line R script that did what I was previously doing by hand in excel. It ran in a few seconds and did what took excel about 10 minutes.
A few years later I wrote an open source economics library in R: https://github.com/stevecondylios/priceR#pricer- It converts between nominal and real prices, converts between 171 currencies, and has a few regex's for pulling numeric data out of text (e.g. salaries out of job descriptions).
Some specific observations regarding the article:
- Comparing computation speed seems a bizarre metric to care about. 6x faster matters on things that take minutes, hours or days, but less so for operations that already run in under 1000ms. Developer experience is usually more important IME.
What are some alternatives?
expotools - Useful methods for Exposome research.
fecon235 - Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
targets-minimal - A minimal example data analysis project with the targets R package
collapse - Advanced and Fast Data Transformation in R
WeightedTreemaps - Create Voronoi and Sunburst Treemaps from Hierarchical data
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
poibin - Poisson Binomial Probability Distribution for Python
lmForc - R package for evaluating linear forecasting models.
QuantEcon.jl - Julia implementation of QuantEcon routines
groundhog - Reproducible R Scripts Via Date Controlled Installing & Loading of CRAN & Git Packages
SciPy - SciPy library main repository