|3 months ago||11 days ago|
|GNU General Public License v3.0 or later||GNU General Public License v3.0 or later|
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Is there a recommended library for asynchronous HTTP servers in R?
4 projects | /r/Rlanguage | 3 Jun 2021
PSA: You don't need fancy stuff to do good work.
10 projects | /r/datascience | 9 May 2023
Before diving into advanced machine learning algorithms or statistical models, we need to start with the basics: collecting and organizing data. Fortunately, both Python and R offer a wealth of libraries that make it easy to collect data from a variety of sources, including web scraping, APIs, and reading from files. Key libraries in Python include requests, BeautifulSoup, and pandas, while R has httr, rvest, and dplyr.
5 projects | dev.to | 9 Jan 2023
Modern Polars: an extensive side-by-side comparison of Polars and Pandas
5 projects | news.ycombinator.com | 7 Jan 2023
It really can't be said enough how pandas is a mess. It has way too much surface area and no common thread pulling it all together. This gets obvious when you work with better dataframe libs like dplyr  or DataFramesMeta . I've worked on production systems with all of these libs, this is not gratuitous bashing.
How do I find R code for R functions?
2 projects | /r/rprogramming | 21 Nov 2022
There are two ways you can generally see the source code for packages. The simplest is to look for the github repository for the package (assuming it exists). For dplyr, it's here. Easiest way to find these is to google search "r github" plus the name of the package. Usually it'll be one of the first results. The github repo would also usually be linked on the package's CRAN page. However, be aware that this may be a development version of the package and not the same version that is currently released on CRAN (e.g. dplyr on CRAN is version 1.0.10, but on github it is listed as version 18.104.22.16800, which will probably become version 1.1.0 when it is released onto CRAN).
People who live near other people vote for Democrats
4 projects | /r/dataisbeautiful | 9 Nov 2022
Tools used: various packages in R (tidycensus, dplyr, ggplot2, sf)
Used Cars Data Scraping - R & Github Actions & AWS
2 projects | dev.to | 11 Sep 2022
It came up with the idea of how to combine Data Engineering with Cloud and automation. I needed to find a data source as it would be an automated pipeline, so I needed a dynamic source. At the same time, I wanted to find a site where I thought retrieving data would not be a problem and do practice with both rvest and dplyr. After I had no problems with my experiments with Carvago, I added the necessary data cleaning steps. Another thing I aimed for in the project was to keep the data in different ways in different environments. While raw (daily CSV) and processed data were written to the Github repo, I wrote the processed data to PostgreSQL on AWS RDS. In addition, I sync the raw and processed data to S3 to be able to use it with Athena. However, I have separated some stages for GitHub Actions to be a good practice. For example, in the first stage, I added synchronization with AWS S3 as a separate action while scraping data, cleaning, and printing fundamental analysis to a simple log file. If there is no error after all this, I added a report with RMarkdown and the action that will be published on github.io. Thus, I created an end-to-end data pipeline where the data from the source is made to offer basic reporting with simple processing.
Quick candlestick summaries with Elixir's Explorer
8 projects | dev.to | 22 Aug 2022
The API is heavily influenced by Tidy Data and borrows much of its design from dplyr. The philosophy is heavily influenced by this passage from dplyr's documentation:
tidytable v0.8.1 is on CRAN - it also comes with a new logo! Need data.table speed with tidyverse syntax? Check out tidytable.
2 projects | /r/rstats | 22 Aug 2022
Also - I might have been the one that put in the request for .by in dplyr 😅
ibis-datasette: Query datasette servers without writing a line of SQL
2 projects | /r/Python | 18 Aug 2022
For my day job I work on ibis. ibis lets users write queries using a familiar dataframe-like API, and then execute those queries on a number of SQL (and non-SQL) backends. Think of it like dplyr but for Python.
Beginner Help with Combining Columns - in a dataset about movie ratings theres a list of the seperate genres with "0" as "is not" and "1" being "is *genre*". Now to ease analysis i imagine id have to convert this data into something more usable? how would i do this? - thank you to any helpers
2 projects | /r/rprogramming | 8 Jul 2022
The special function mutate() and pivot_longer() come from the package dplyr which helps to make R-syntax more readable.
What are some alternatives?
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
Rustler - Safe Rust bridge for creating Erlang NIF functions
explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
nx - Multi-dimensional arrays (tensors) and numerical definitions for Elixir
ggplot2 - An implementation of the Grammar of Graphics in R
rmarkdown - Dynamic Documents for R
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
polars - Fast multi-threaded, hybrid-out-of-core query engine focussing on DataFrame front-ends
magrittr - Improve the readability of R code with the pipe
axon - Nx-powered Neural Networks
quanteda - An R package for the Quantitative Analysis of Textual Data