However, after more than 25 years of development, the R ecosystem can seem overwhelming to newcomers. All these features help you think about problems as a data scientist, while supporting fluent interaction between your brain and the computer. R is not just a programming language, but it is also an interactive ecosystem including a runtime, libraries, development environments, and extensions. Once R and RStudio are installed, open RStudio to make sure that it works and there are no errors when you open it.We think R is a great place to start your data science journey because it is an environment designed for data science. Under Installers select the version for your distribution.
To install RStudio, go to the RStudio Download page. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Or you can use your package manager (e.g. You can download the binary files for your distribution from CRAN. R is available through most Linux package managers. Once R and RStudio are installed, open RStudio to make sure it works and you don’t get any error messages. Once it’s downloaded, double click the file to install it. Under Installers select RStudio current version # - Mac OS X 10.6+ (64-bit) to download it. Double click on the file that was downloaded and R will install. pkg file for the version of OS X that you have and the file will download. Go to CRAN and click on Download R for (Mac) OS X. Once R and RStudio are installed, open RStudio to make sure that you don’t get any error messages. Under Installers select RStudio current version # - Windows XP/Vista/7/8/10. exe file that was downloaded in the step above. Be able to download and install R and Rstudio on your laptop. SECTION 15 LAST CLASS: FINAL PROJECT PRESENTATIONS. SECTION 14 FINAL PROJECTS & COURSE FEEDBACK DISCUSSION. SECTION 10 MIDTERM REVIEW / PRESENTATION BEST PRACTICES. SECTION 9 STUDY FIRE USING REMOTE SENSING DATA. 8.1 Fire / spectral remote sensing data - in R. SECTION 8 QUANTIFY FIRE IMPACTS - REMOTE SENSING. 
SECTION 7 MULTISPECTRAL IMAGERY R - NAIP, LANDSAT, FIRE & REMOTE SENSING.Uncertainty in Scientific Data & Metadata SECTION 5 LIDAR DATA IN R - REMOTE SENSING UNCERTAINTY.Refine R Markdown Reports with Images and Basemaps
SECTION 2 INTRO TO R & WORK WITH TIME SERIES DATA.
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