ggplot2-book
r4ds
ggplot2-book | r4ds | |
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31 | 166 | |
1,588 | 4,658 | |
0.5% | 0.8% | |
0.0 | 6.6 | |
6 months ago | 16 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/
r4ds
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Visualizing Data on a Mesh with Displacement Mapping in R
My personal favorite resource is "R for Data Science" by Hadley Wickham. It covers lots of nice data manipulation and visualization examples, and provides a good introduction to the tidyverse, which is a particular dialect of R that's well-suited for data analysis. It's available for free at:
https://r4ds.hadley.nz/
For more specialized analytical methods there are lots of textbooks out there that provide a deep dive into packages for a specific field (e.g. survival analysis, machine learning, time series), but for general data manipulation and visualization it's hard to beat R4DS.
- Ask HN: Learning Maths from the Ground Up
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Any suggestions on where I can learn R studio for an affordable cost?
https://r4ds.hadley.nz is free and very good
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Help with Understanding data loading/cleaning in R.
R for Data Science teaches you the tidyverse packages, which makes data wrangling so much easier!
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Learning R & statistics
One of the best free resources is the R4DS book by Hadley Wickham. You should make sure you start with the in progress second edition. https://r4ds.hadley.nz/
- Trying to learn Rstudio
- Questions as incoming PhD political science student
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First R project
The first edition of R4DS is quite old now. Check out the soon to be released second edition: https://r4ds.hadley.nz/
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Is R dead?
R for Data Science (2nd Ed), the updated guide from Hadley Wickham
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[Career] Strong Mathematics Background, Limited "Technical" Background
The big skills gap you have is in practical data exploration and transformation, which will be a large part of any data-centric role. As much as people may have distaste for it, there is no avoiding data manipulation as critical foundational enabler of all inferential and predictive modeling work. SQL is the lingua franca here and well worth picking up the basics (joins, window functions, handling dates and times, etc.), plus learning how to implement similar transformations in R and Python. With appropriately transformed data, you then need to be able to visualize it effectively using tools like Tableau or ggplot2 in R. I would not necessarily seek courses or certificates in it but expect to be evaluated on them in technical interview screenings, so self-study accordingly. R for Data Science by Hadley Wickham is a great free resource for these topics for R.
What are some alternatives?
cheatsheets - Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.
swirl - :cyclone: Learn R, in R.
mech - 🦾 Mech is a programming language for building data-driven systems like robots, games, and interfaces. Start here!
lab02_R_intro - Vežbe 2: Uvod u R
forcats - 🐈🐈🐈🐈: tools for working with categorical variables (factors)
R-vs.-Python-for-Data-Science
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.
fasteR - Fast Lane to Learning R!
tidyr - Tidy Messy Data
data_to_viz - Leading to the dataviz you need
dtplyr - Data table backend for dplyr
tidytuesday - Official repo for the #tidytuesday project