Learning Quote of the Day

"It’s not just what you know, but how you practice what you know that determines how well the learning serves you later."

― Peter C. Brown, Make It Stick

Plicker time!

Problem 1

What is faceting?

  1. Creates small multiples of the same plot over a different categorical variable
  2. Creates small multiples of the same plot over a different numerical variable
  3. Create large multiples of the same plot over a different categorical variable
  4. Create small variables of the same plot over a similar numerical variable

Problem 2

What type of plot is usually preferred for an explanatory categorical variable and a response categorical variable?

  1. Faceted boxplot
  2. Side-by-side barplot
  3. Stacked barplot
  4. Faceted barplot

Problem 3

Given the 'weather' dataset, what function would we use to choose only the variables of humidity and precipitation?

  1. arrange(weather, humid, precip)
  2. select(weather, humid, precip)
  3. filter(weather, humid, precip)
  4. summarize(weather, humid)

Problem 4

What is the process of decomposing frames into less redundant tables without losing info?

  1. framing
  2. decomposing
  3. tabling
  4. normalizing

Problem 5

What R code would you use to find the mean and standard deviation of temperature in the weather data set?

  1. weather %>% summarize(mean = mean(temp),
          std_dev = sd(temp))
  2. weather %>% summarize(mean = mean(temp, na.rm = TRUE),
          std_dev = sd(temp, na.rm = TRUE))
  3. weather %>% summarize(mean = (mean = temp),
          std_dev = (sd = temp))
  4. weather %>% summarize(mean = (mean == temp),
          std_dev = (sd == temp))

Problem 6

Find the mean gdpPercap of each region for each year

  1. region_perCap <- gap %>% group_by(year) %>%
  summarize(mean_perCap = mean(gdpPercap))
  2. region_perCap <- gap %>% 
  summarize(region, year, mean_perCap = mean(gdpPercap))
  3. region_perCap <- gap %>% group_by(region, year) %>% 
  summarize(mean_perCap = mean(gdpPercap))
  4. region_perCap <- gap %>% group_by(region) %>% 
  summarize(mean_perCap = mean(gdpPercap))

Reflect

  • What concepts are you having the hardest time with right now? Be as specific as possible.

  • What else can I do to help you work with dplyr and ggplot2?

  • What else will you be doing to help yourself work with dplyr and ggplot2?