1. Import the file into R using read.csv( ) function
2. Prepare data.frame for analysis. Arrange variables (rename, drop, or keep variables), clean data (gsub or conditional assignments with ifelse() ), and apply appropriate data structure (i.e. integer, numerical, character, factors, etc.)
3. export at least several frequency tables, cross-tabulations, and several histograms (preferably clean and with color, with appropriate titles and axis labels, etc.). You may want to look into table( ), ftable( ), gmodles::CrossTable, hist( ), ggplot2, and plotly, among others. Question: How do you show and compare the results across multiple classes?

Submit a report that examine part 2 and part 3.

nameidsis_idsectionsection_idsection_sis_idsubmittedattempt3121367: My favorite color is...03121430: My favorite New England state is...03121431: My favorite animal is1n correctn incorrectscoreAbbey Feloney81862001044454FOEL Training Sandbox Course - Littlefield7252020-08-21 15:32:50 UTC1Purple0New Hampshire0Cat0030Donisa Norman82413001040628FOEL Training Sandbox Course - Littlefield7252020-08-21 15:30:35 UTC1Red0Vermont0Dog1121Kate Chan11081001424041FOEL Training Sandbox Course - Littlefield7252020-08-21 15:30:27 UTC1Green0Maine0Dog1211Cathy Swain96001844289FOEL Training Sandbox Course - Littlefield7252020-08-21 15:30:10 UTC1Purple0Maine0Dog1211