progress
dplyr
progress | dplyr | |
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1 | 40 | |
456 | 4,658 | |
0.7% | 0.5% | |
6.6 | 7.1 | |
2 months ago | 3 days ago | |
R | R | |
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.
progress
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Hi, is there any way where I can see the progress of my running code/model in R? I want to see the percentage of the work done in bars, not the elapsed time.
Program it in yourself with the ‘progress’ package. The easiest way to do it is just iterate on a For loop, some people might be scandalised, but it’s readable and simple.
dplyr
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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.
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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
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Calculation within a data table by calling on specific values in two columns
Look at the tidyverse, especially the case_when or mutate functions.
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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.
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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?
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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/
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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/
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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?
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
Rustler - Safe Rust bridge for creating Erlang NIF functions
ggplot2 - An implementation of the Grammar of Graphics in R
nx - Multi-dimensional arrays (tensors) and numerical definitions for Elixir
explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
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 - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
regression-js - Curve Fitting in JavaScript.
axon - Nx-powered Neural Networks
magrittr - Improve the readability of R code with the pipe
quanteda - An R package for the Quantitative Analysis of Textual Data