Learning Outcomes

• Use forcats functions to manage factors in R
• Use lubridate functions in R in conjunction with functions from dplyr and tidyr.

Factors

1. Load the gss_cat data from the forcats package.

2. Find how many observations fell into each factor level of rincome. Don’t overthink this one - it’s one function we’ve been using for over a month!

3. Plot a barplot of the distribution of rincome, ordering levels from by frequency

4. You think “Not applicable”, “Don’t Know”, “No answer”, and “Refused” aren’t very useful for your plot. Use fct_other() to collapse these into one factor level and plot again. Note: fct_other() is new! Read the documentation.

5. Reorder the levels of the relig variable by the mean number of tv hours watched. Show the new factor order and then plot with a boxplot.

Dates

1. Many people have created a “Coronavirus Birthday”, the first date they went into lockdown, quarantine, or began extreme social distancing. This is usually in March 2020. How many seconds have passed since this time (i.e., calculate the duration in seconds)? If you can’t remember, use March 15, 2020.

   • Hint: This is the same as the BTS example from the lecture.

2. Use seconds_to_period() to go from the duration (q1) to the period since your “Coronavirus Birthday”.

3. For the rest of this exercise, we will use the data from capital_trips_2016.csv. Read these data into R from the data directory and review the variables with glimpse(). These data are from a bikesharing program.

4. Rename variables to conform to “best practices” for variable names i.e., no spaces in the names. Feel free to experiment with the handy janitor::clean_names() function here if you’d like.

5. Convert the start date and end date variables to be date-times.

6. Use the start date and end date variables to calculate the duration of each trip.

7. How much time elapsed between the start of the first trip and the end of the the last trip.