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11-resources.Rmd
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# More resources
## Projects using this data
* [Inferred Route Preferences in Bike Sharing](https://urbandatacyclist.com/2018/03/15/predicting-route-preferences-in-bike-sharing/) (this one uses R and prints the code used!)
* [Station-Level Forecasting of Bike Sharing Ridership: Station Network Effects in Three U.S. Systems](https://nacto.org/wp-content/uploads/2015/07/2012_Rixey_Station-Level-Forecasting-of-Bike-Sharing-Ridership.pdf)
* [Where do the Nice Riders go?](https://streets.mn/2012/03/21/where-do-the-nice-riders-go/)
## General R Programming
* [List of *free* online R books](https://bookdown.org/)
* [R cheat sheets](https://www.rstudio.com/resources/cheatsheets/)
* [R for Data Science](https://r4ds.had.co.nz/)
* [Advanced R](http://adv-r.had.co.nz/)
* [Software Carpentry: Programming with R](https://swcarpentry.github.io/r-novice-inflammation/)
* [Data Carpentry: R for Social Scientists](https://datacarpentry.org/r-socialsci/)
* [Data Carpentry: Introduction to R for Geospatial Data](https://datacarpentry.org/r-intro-geospatial/)
* [Data Carpentry: Introduction to Raster and Vector Geospatial Data in R](https://datacarpentry.org/r-raster-vector-geospatial/)
* [CASA UCL Introduction to R](https://andrewmaclachlan.github.io/CASA0005/prac2.html)
## R Projects (and reproducibility)
* [R OpenSci Reprocibility Guide](https://ropensci.github.io/reproducibility-guide/sections/introduction/)
* [R OpenSci Community Call: Reproducible Research with R](https://ropensci.org/commcalls/2019-07-30/)
## R Markdown
* [R Markdown: The Definitive Guide](https://bookdown.org/yihui/rmarkdown/)
* [flexdashboard: Easy interactive dashboards for R](https://rmarkdown.rstudio.com/flexdashboard/)
* [R Markdown gallery](https://rmarkdown.rstudio.com/gallery.html)
## Wrangling & Visualization
* [Writing Narratives with Data: An Introduction to ggplot (by me)](https://www.katiejolly.io/data-narratives-ggplot/)
* [Exploring DC's bikeshare system: Wrangling with dplyr (by me)](https://www.katiejolly.io/bikeshare-dplyr/)
* [Political Donations from the STEM Community: Learning dplyr (by me)](https://www.katiejolly.io/political-donations-dplyr/)
* Suzan Baert's blog posts on dplyr tricks: [Basic to Advanced Ways to Select Columns](https://suzan.rbind.io/2018/01/dplyr-tutorial-1/), [Transforming your columns into the right shape](https://suzan.rbind.io/2018/02/dplyr-tutorial-2/), [Basic and more advanced ways to filter rows](https://suzan.rbind.io/2018/02/dplyr-tutorial-3/), [Summarizing and slicing your data](https://suzan.rbind.io/2018/04/dplyr-tutorial-4/)
* [Top 50 ggplot2 visualizations- The master list (with full R code)](http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html)
* Complete ggplot2 tutorial [part 1](http://r-statistics.co/Complete-Ggplot2-Tutorial-Part1-With-R-Code.html) and [part 2](http://r-statistics.co/Complete-Ggplot2-Tutorial-Part2-Customizing-Theme-With-R-Code.html)
## Reading in Data
* [This R data import tutorial is everything you need](https://www.datacamp.com/community/tutorials/r-data-import-tutorial)
* [Reading and writing CSV files](https://swcarpentry.github.io/r-novice-inflammation/11-supp-read-write-csv/)
## Modeling and Statistical Inference
* [Statistical Inference via Data Science](https://moderndive.com/)
* [OpenIntro R Labs](https://www.openintro.org/stat/labs.php?stat_lab_software=R)
* [Learning Statistics with R: A tutorial for pyschology students and other beginners](https://learningstatisticswithr.com/book/)
## GIS and Urban Planning
* [Geocomputation in R](https://geocompr.robinlovelace.net/)
* [stplanr: A package for sustainable transport planning in R](https://docs.ropensci.org/stplanr/)