magrittr
ggplot2
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magrittr | ggplot2 | |
---|---|---|
10 | 62 | |
951 | 6,316 | |
0.0% | 1.2% | |
2.3 | 9.4 | |
about 1 year ago | 7 days ago | |
R | R | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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magrittr
- This is not a pipe - René Magritte
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Six programming languages I’d like to see
R (yes, the statistics language) has exactly this.
You can literally extract the body of a function as a list of "call" objects (which are themselves just dressed-up lists of symbols), inject/delete/modify individual statements, and then re-cast your new list to a new function object.
I don't know why the original devs thought this was necessary or even desirable in a statistics package, but it turns out to be a lot of fun to program with. It has also made possible a wide variety of clever and elegant custom syntaxes, such as a pipe infix operator implemented as a 3rd-party library without any custom language extensions [0]. The pipe infix operator got so popular that it was eventually made part of the language core syntax in version 4.1 [1].
[0]: https://magrittr.tidyverse.org/
[1]: https://www.r-bloggers.com/2021/05/the-new-r-pipe/
- Hadley is pro- base pipe.
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Functional pipes in python like %>% from R's magrittr
In R (thanks to magrittr) you can now perform operations with a more functional piping syntax via %>%. This means that instead of coding this:
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Question about dot notation
Try reading the documentation for magrittr.
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When did WG21 decide this is what networking looks like?
Related note: the statistical programming language R has a library named magrittr to support the pipe operator.
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How can I find the data entry of the row after one found?
About the pipe (%>%) symbol, it's provided by the magrittr package. The package documentation details how to use the pipe operator.
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Best practice for chaining nested functions?
I was wondering what some good ways are to handle nested function calls without chaining them in long, ugly nested statements. I am looking for functionality similar to the pipe forward operator %>% in magrittr/R or |> in F#.
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I much prefer `data.action()` to `action(data). Is it an r/unpopularopinion?
You may like R: https://magrittr.tidyverse.org
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What's so "tidy" about tidyverse?
Agreed on everything else you said (especially the type safety stuff, it massively helps in production), but one correction: magrittr is absolutely in the tidyverse suite. It's not considered one of its "core" packages that it visibly tells you it loads, but magrittr is loaded when calling library(tidyverse) and development of the package is handled by the tidyverse team under their Github account: https://github.com/tidyverse/magrittr
ggplot2
- ggplot2
- Ask HN: How do you build diagrams for the web?
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Visualizing shapefiles in R with sf and ggplot2!
ggplot2
- Ask HN: What plotting tools should I invest in learning?
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Relative frequency of letters in five-letter English words (Wordle aid) [OC]
I got the list of five-letter words from the words package in R, created the QWERTY keyboard grid with base R and tibble, and visualized the data with geom_tile in the ggplot2 package.
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[OC] U.S. News & World Report Best Colleges: 2002 to 2023
Thanks, it's an interesting idea! I definitely could implement this with scale_fill_gradientn) in ggplot2.
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Facts about Aaron Boone's Ejections as Manager
I used the ggplot2 package in R to create these figures.
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Fueling Innovation and Collaborative Storytelling
This might not be at the top of your list, but science fiction often presents advanced data analysis and visualization technologies. Open source data analysis tools such as Python's Pandas and R's ggplot2 have revolutionized the field, making complex data manipulation and visualization accessible to all. In the science fiction novel The Martian, astronaut Mark Watney uses a variety of data analysis and visualization tools to survive on Mars. He uses Python's Pandas to clean and organize data, and he uses R's ggplot2 to create visualizations of his data. These tools allow him to make sense of the vast amounts of data and help him to make critical decisions about his survival.
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[OC] Visualizing Financial Market Returns Across Many Asset Classes via Heatmaps
Sorry about the slow reply, but the auto-moderator seems to be deleting my comments (for some unknown reason). I will try once more: the geom_tile function in ggplot2.
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[OC] Forbes List of Highest-Earning Musicians: 1987 to 2021
Visual cues are a much better idea, thanks! Unfortunately, I don't know how to do that in ggplot2, either (I created these figures in R).
What are some alternatives?
dplyr - dplyr: A grammar of data manipulation
Altair - Declarative statistical visualization library for Python
scenebuilder - Scene Builder is a visual, drag 'n' drop, layout tool for designing JavaFX application user interfaces.
tmap - R package for thematic maps
kitten - A statically typed concatenative systems programming language.
vega - A visualization grammar.
power-fx-host-samples - Samples for hosting Power Fx engine.
libuv-tutorial - http://nikhilm.github.io/uvbook/
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
FiraCode - Free monospaced font with programming ligatures
glue - Glue strings to data in R. Small, fast, dependency free interpreted string literals.