absmapsdata
r4ds
absmapsdata | r4ds | |
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3 | 165 | |
57 | 4,366 | |
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5.5 | 8.4 | |
9 months ago | 15 days ago | |
R | R | |
- | GNU General Public License v3.0 or later |
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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.
absmapsdata
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Total Cases (x) vs Current Cases (y) as % of population in VIC LGAs, animated from Dec 2021 to today
It's using the R language with absmapsdata for the maps and gganimate to do the animation.
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Covid-19 in Melbourne in 51 Seconds, 2020-02-15 to 2021-10-20 (details + alternate link in comments)
Produced using R, Tidyverse, gganimate and absmapsdata.
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Covid-19 in Melbourne in 100 Seconds, 2020-02-15 to 2021-10-08 (details + alternate link in comments)
Background/fill = Active cases in LGA Central Dot Colour = New cases in LGA Grey = No Cases Dark to Bright = Log scale low to high Produced using R, Tidyverse, gganimate and absmapsdata. Covid-19 data from https://www.coronavirus.vic.gov.au/latest-covid-19-data
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.
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There’s a lot of data science books out there, any recommendations for must-reads?
I just looked and there is now a second edition! https://r4ds.hadley.nz/
What are some alternatives?
tmap - R package for thematic maps
swirl - :cyclone: Learn R, in R.
echarty - The goal of echarty is to provide a minimal interface, a “glue”, between R and ECharts, then let your R data lists build the chart. There are utilities included to assist with data preparation, Shiny with proxy and JS plugins. Have the full functionality of ECharts in R with minimal overhead!
fasteR - Fast Lane to Learning R!
ShinyWebAppWithFormAndLeafletMap - This repo contains the code to build a webapp for data collection and viewing the map on a leaflet map using R Shiny. The specific webapp that I built is aimed to collect data of sustainability practices of various eateries around the world, in the times of climate change.
tidytuesday - Official repo for the #tidytuesday project
awesome-R - A curated list of awesome R packages, frameworks and software.
viridis - Colorblind-Friendly Color Maps for R
lab02_R_intro - Vežbe 2: Uvod u R
R-vs.-Python-for-Data-Science
ggplot2-book - ggplot2: elegant graphics for data analysis
dplyr - dplyr: A grammar of data manipulation