Pros and Cons of R

Where R beats Excel

-Provide a trail of your work

-Easier for someone else to review

-Ease of repeatability

-Easier to find your mistakes and correct

-No messy directory full of workbooks

-Can pull in data from APIs, servers, SPSS files, and many other formats

-Can do web scraping

-Make web pages from your analysis

-Connect RStudio to Github for version control

-More robust for statistical analyses

-Summarizing data. More versatile than Pivot Tables.

-Easier to create new columns (even ones that don’t get stored in your table)

-More versatile for data cleaning

-You can do mapping!

-Open source: many users constantly making it better

The cons of R

-Higher learning curve

-No point and click. Lots of typing

-Charts are harder to make (but so many more options!)

-More time needed on front-end of analysis

-Harder to do on deadline until you get proficient

-There are almost too many packages, many doing the same things!

-Package and function naming can be confusing. As just one example: To import data we used a readr function called “read_csv”. But Base R has an import function called “read.csv”. They behave quite differently.

-The “how to” information that comes with the packages is minimal and oftentimes confusing. However, I’ve found better guidance on blogs and other websites.