Tidyverse Quiz 28

Tidyverse Quiz: 15 Questions to Challenge Your R Knowledge. Test your R Language skills with this 20-question Tidyverse quiz! From dplyr to ggplot2, see how well you know data wrangling, visualization, summary statistics, and more. Perfect for R Language beginners and experts- can you score 100%? Let us start with the Tidyverse Quiz R Language.

Tidyverse Quiz: 20 Questions to Challenge Your R Knowledge

• Which one of these libraries is widely used for data manipulation in R?
• What do you need to do to use tidyverse commands in R?
• When you run the line: dat <- read_csv(“my_data.csv”). What kind of object is dat?
• Which is NOT a principle of tidy data?
• If there is missing data in a .csv file that you import, what should you do?
• The tidyverse replaces the techniques for manipulating data with base R.
• Which of the following are steps in the data-wrangling process?
• Which of these are advantages of Tibbles over data frames?
• Looking at tidyverse.org, how many core packages are included in the tidyverse?
• Suppose you have a tibble called “cities” with columns including population (“population”), a measure of economic activity (“gdp”), and the state in which the city is located (“state”). Which of these commands would select rows from the dataset where the value for population is more than 3,000, the value for economic activity is less than 120,000, and the city is not located in Alabama?
• Suppose you have a dataset that looks like this:
  colors <- c(“red”,”green”,”yellow”)
  speeds <- c(“slow”,”fast”,”medium”)
  my_dat <- data.frame(colors,speeds)
  What is the correct code to recode the “colors” column so that red equals 0, green equals 2, and yellow equals 1?
  Suppose you have a tibble named “dat” that has a time, date, employee, and sales column. You are reviewing someone’s R code and see the following lines:
  my_time <- filter(dat,time == 1)
  my_time_and_date <- filter(my_time,date>5)
  group_by_employee_my_time_and_date <- group_by(my_time_and_date, employee) summarise(group_by_employee_my_time_and_date, average=mean(sales))
  Which of these would do the same thing using piping?
• Suppose you have a data frame named “dat” with two numeric columns, $value1$ and $value2$. You want to add a third column called $my_value$, where the value in each row is the product of multiplying the other two values in the row by one another. Which is the correct line of code?
• Suppose you have a tibble saved into your R environment as “$my_dat$” with two columns named “$alpha$” and “$beta$”. You want to rename the “$beta$” column and call it “$gamma$”. Which of these will create a new tibble with the renamed column?
• Suppose you have a tibble saved to the object $my_dat$ with two columns, $alpha$ and $beta$. These are filled with numeric data. Which of these will arrange the data in descending order by $alpha$?
• Which of these accurately describes piping?
• Which tidyverse package is used for data import and management?
• To combine functions, use the ————.
• Which of the following is NOT one of the four groups in the tidyverse library?
• Functions contained in packages such as dplyr are used to:

Statistics, Data Analysis, and Quiz