Summary

Let’s summarize what we learned in this section.

• Explore data: We saw that whenever data is imported into R, we should always spend some time exploring it to check for errors and to make sure that everything is imported correctly. Looking at the structure of the data frame with the str() function is one of the fastest ways to see if there are any typos in the original data file.

• Plotting is necessary: We learned that to explore data, scatterplots, box and whisker plots, histograms, density plots, and so on should be made. It’s crucial to look at the data from many different perspectives to see if anything looks out of the ordinary.

• Data filtration: We discussed that whether square brackets ([]) or the filter() function is chosen, learning how to use logical operators is crucial to being able to efficiently navigate and subset the data as needed.

• dplyr: We learned about dplyr, which is a fantastic package for summarizing data quickly and efficiently.