ggplot2-book
dtplyr

ggplot2-book | dtplyr | |
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31 | 24 | |
1,590 | 671 | |
0.6% | 0.1% | |
0.0 | 3.6 | |
6 months ago | 22 days ago | |
Perl | R | |
- | GNU General Public License v3.0 or later |
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ggplot2-book
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Does anyone else absolutely love plotting their data
I also only recently started using ggplot after doing most of my graphs with base R‘s plot() function. I started by reading ggplot2 by Hadley Wickham which is also available as a free ebook. Reading the first few chapters is enough to enable you to plot many basic plots. I can’t imagine going back to any other visualization tool ever again. Absolutely love the freedom ggplot gives you.
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I am starting to learn R and I love it. I would like to learn at least 1 another simmilar language. Which one(s) should I learn?
His ggplot book will teach you all you need to know about R plotting, and is probably right at your current level. It is likewise pretty great, ggplot
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What are your favorite softwares for data visualization?
The OG book is still the best in my opinion! https://ggplot2-book.org/
- Data analysis skills before/in lieu of master’s program
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How can I do this graph?
You could use base R, see ?plot but a lot of people would use ggplot2. However, looking at your data it won’t look very good because there’s going to be very few points per country.
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Can someone explain how R project are organized and deployed?
If you included DESCRIPTION to your repository (like in ggplot2-book - https://github.com/hadley/ggplot2-book/blob/master/DESCRIPTION ) devtools::install_deps() and renv::install() will install dependencies listed there as would pip with requirements.txt , you can trigger this from your R script, from command line or from whatever deployment / automation tool you are using.
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[Q] is majoring in stats a bad choice if i suck at programming?
Chapters 1-8 of https://adv-r.hadley.nz/, https://r4ds.had.co.nz/ , and https://ggplot2-book.org/ were covered in my statistical computing courses. I don't think it gets much more advanced than that at the undergrad level.
- How to add color?
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How can I make a line graph!?
You can check out more about Ggplot2 here: https://ggplot2-book.org/
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Ask HN: How would you spatialize higher dimensional data?
* "ggplot2: Elegant graphics for data analysis" : https://ggplot2-book.org/
dtplyr
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Tidyverse 2.0.0
Can’t say I’ve used it, but isn’t that what dtplyr is supposed to provide?
https://dtplyr.tidyverse.org/
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Error when trying to use dtplyr::lazy_dt, "invalid argument to unary operator"
# I am trying to follow the example at https://dtplyr.tidyverse.org/
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Millions of rows
FYI the developer of tidytable has been developing dtplyr for the Tidyverse. You might like that too!
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fuzzyjoin - "Error in which(m) : argument to 'which' is not logical"
If you need speed, you should consider using dtplyr (or tidytable), or even dbplyr with duckdb.
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Best alternative to Pandas 2023?
https://dtplyr.tidyverse.org/ ?
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R Dialects Broke Me
If you want data.table speed, but using dplyr/tidy then dtplyr is a good package to have handy. Personally I love R, and choose R + NodeJS as my gotos for everything I do, and use Python only when I have to.
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Merging csv from environment.
Also, that dataset is quite big, and the "base" Tidyverse will be excessively slow. You should supplement the "base" Tidyverse packages (i.e. dplyr and tidyr) with either dtplyr or dbplyr (+ duckDB). I'd suggest starting with dtplyr, which should handle 10M+ rows fine.
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mutate ( ) function is only working in code chunk I run it in. It does not change the column in my data frame other than in that one code chunk.
If you want, there's a "substitute" for dplyr called dtplyr (also part of the Tidyverse), which "translates" your dplyr/tidyr code into data.table behind the scenes, and allows you to make your modifications apply directly to the original dataset by default:
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R process taking over 2 hours to run suddenly
Install the dtplyr package and change your code to:
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DS student here: why use R over Python?
Get the best of both worlds (tidyverse + data.tables) with dtplyr, a data.table backend for dplyr.
What are some alternatives?
r4ds - R for data science: a book
tidytable - Tidy interface to 'data.table'
cheatsheets - Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.
tidypolars - Tidy interface to polars
mech - 🦾 Mech is a programming language for building data-driven systems like robots, games, and interfaces. Start here!
vaex - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
forcats - 🐈🐈🐈🐈: tools for working with categorical variables (factors)
dataiter - Simple, light-weight data frames for Python
handson-ml2 - A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Datamancer - A dataframe library with a dplyr like API
tidyr - Tidy Messy Data
tidyexplain - 🤹♀ Animations of tidyverse verbs using R, the tidyverse, and gganimate
