tidypolars
dplyr
tidypolars | dplyr | |
---|---|---|
7 | 40 | |
309 | 4,658 | |
- | 0.5% | |
8.0 | 7.1 | |
3 months ago | 7 days ago | |
Python | R | |
MIT License | 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.
tidypolars
-
Modern Polars: a side-by-side comparison with Pandas
I recommend trying tidypolars
-
Modern Polars: an extensive side-by-side comparison of Polars and Pandas
There’s a tidypolars package that appears to be well-maintained https://github.com/markfairbanks/tidypolars
-
R Tidyverse / dplyr is life changing!
tidypolars is one I’ve seen. Still very new, but it’s built on top of polars (which is a little more like dplyr to begin with), so it’s much faster than pandas.
-
Introducing tidypolars - a Python data frame package with syntax familiar to R tidyverse users
If I misunderstood your question - feel free to open a discussion with a small code example and we can talk through how you can do it in tidypolars.
- Introducing tidypolars - a Python data frame package for R tidyverse users
-
Tidyverse appreciation thread
Try out tidypolars. It's really close to tidyverse syntax and it's a lot faster than pandas as well
dplyr
-
Show HN: Open-source, browser-local data exploration using DuckDB-WASM and PRQL
That's great feedback, thanks!
This tool definitely comes from a place of personal need - beyond just handling large files, I've also never really gelled well with the Excel/Google Sheet model of changing data in place as if you were editing text. I'm a Data Scientist and always preferred the chained data transforms you see in things like dplyr (https://dplyr.tidyverse.org/) or Polars (https://pola.rs/) and I feel this tool maps very closely to the chained model.
Also, thank you for the feature requests! Those would all be very useful - we'll put them on the roadmap.
-
IS it possible for a R package to set an R option that only affects that package?
There's an example of how to use zzz.R with a .onload() function to set options in the dplyr code base: https://github.com/tidyverse/dplyr/blob/bbcfe99e29fe737d456b0d7adc33d3c445a32d9d/R/zzz.r
-
Calculation within a data table by calling on specific values in two columns
Look at the tidyverse, especially the case_when or mutate functions.
-
PSA: You don't need fancy stuff to do good work.
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.
-
Creating data frame
It looks like your syntax is wrong. I think you’re trying to calculate a new variables in your data frame, or alter an existing column in a data frame. Have a look at the select() function in this reference for the proper syntax to use. https://dplyr.tidyverse.org/ Does that help?
-
I'm designing a shirt for a friend, it has 4 embroidered images of things they like/do. One thing is coding, they use R... I'm wondering two things. 1) What's a good image or piece of code or something that I should use? and 2) should I even add it to the design the shirt?
A lot of populat libraries have their own logos. Maybe one of them would be good. Check out dplyr for example: https://dplyr.tidyverse.org/
-
Anyone use Python for statistics, particularly DOE or QA/QC? What are your thoughts?
I hope you give it a try when you get a chance: https://dplyr.tidyverse.org/
-
Rstudio tidyverse help!
You can read up on the dplyr-verbs here, which I strongly suggest for your exam! In the code examples, you can simply click on any function you don't understand and it will take you directly to the documentation. Good Luck!
- Beginner question
- osdc-2023-assignment1
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
tidytable - Tidy interface to 'data.table'
Rustler - Safe Rust bridge for creating Erlang NIF functions
dtplyr - Data table backend for dplyr
ggplot2 - An implementation of the Grammar of Graphics in R
db-benchmark - reproducible benchmark of database-like ops
nx - Multi-dimensional arrays (tensors) and numerical definitions for Elixir
extendr - R extension library for rust designed to be familiar to R users.
explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
rmarkdown - Dynamic Documents for R