The easy way to get started with R is to use RStudio. You will need to install both R and RStudio. Here are the software packages you need to install:
Windows
Mac OSX
file.edit('~/.Rprofile')
In that file, you will need to add the following settings:
Mac OSX:
Sys.setenv(http_proxy="http://proxy:8080")
Windows:
http_proxy=http://proxy:8080
Instructions were based from the following articles:
Once you have set up internet access, you should be able to install R packages. The yhat blog lists 10 R packages they wish they'd known about earlier.
Windows
Mac OSX
- http://xquartz.macosforge.org/landing/
- http://cran.csie.ntu.edu.tw/
- http://www.rstudio.com/products/rstudio/download/
file.edit('~/.Rprofile')
In that file, you will need to add the following settings:
Mac OSX:
Sys.setenv(http_proxy="http://proxy:8080")
Windows:
http_proxy=http://proxy:8080
Instructions were based from the following articles:
- https://support.rstudio.com/hc/en-us/articles/200488488-Configuring-R-to-Use-an-HTTP-Proxy
- http://www.kenbenoit.net/how-to-set-proxy-settings-for-r-mac-osx/
Once you have set up internet access, you should be able to install R packages. The yhat blog lists 10 R packages they wish they'd known about earlier.
- sqldf (for selecting from data frames using SQL)
- forecast (for easy forecasting of time series)
- plyr (data aggregation)
- stringr (string manipulation)
- Database connection packages RPostgreSQL, RMYSQL, RMongo, RODBC, RSQLite
- lubridate (time and date manipulation)
- ggplot2 (data visulization)
- qcc (statistical quality control and QC charts)
- reshape2 (data restructuring)
- randomForest (random forest predictive models)
- http://blog.yhathq.com/posts/10-R-packages-I-wish-I-knew-about-earlier.html
- https://support.rstudio.com/hc/en-us/articles/201057987-Quick-list-of-useful-R-packages
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