R Programming with Tidyverse Quiz

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Questions and Answers

Which funcon in the dyverse is used to restrict to certain observations in the data?

mean()
summarize
group_by
filter() (correct)

Which funcon in the dyverse is used to restrict to certain columns in the data?

mean()
select() (correct)
summarize
group_by

What code would correctly construct a dataframe with average price per date from the Uber dataset?

uber %>% group_by(date) %>% summarize(meancost=mean(cost)) (correct)
uber %>% by(cost) %>% summarize(meancost=mean(date))
uber %>% group_by(date,cost) %>% summarize(meancost=mean(cost))
uber %>% group_by(date,ride_id) %>% summarize(meancost=mean(cost))

If you want to calculate the total cost over time using the Uber dataset, which approach would you NOT use?

<p>uber %>% mutate(total_cost=sum(cost)) (D)</p> Signup and view all the answers

Which function should you avoid using if you want to obtain the average cost per ride in the Uber dataset?

<p>ungroup() (C)</p> Signup and view all the answers

Flashcards

Restricting observations (data)

Using the filter() function from the "dplyr" package to select specific rows in a data frame based on certain conditions.

Restricting columns (data)

Using the select() function from the "dplyr" package to choose specific columns from a data frame.

Calculating average cost by date

Using group_by(date) and summarize(meancost = mean(cost)) to calculate the average cost for each unique date in a dataset (e.g., Uber rides).

Incorrect Uber Data Aggregation

Grouping by both "date" and "ride_id" in calculating the average cost by date is redundant and generally not the correct way to compute average ride cost over time. Grouping by just "date" is sufficient.

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Incorrect mean calculation

Using functions like by() inappropriately in the dplyr pipeline to calculate average costs by date leads to incorrect results. Use dplyr's specialized functions for effective data manipulation rather than base R's functions for this kind of operation.

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Study Notes

Question 1

To filter observations in 'tidyverse', use the filter() function.

Question 2

To select columns, use select().

Question 3

The correct code to calculate the average cost per date is: uber %>% group_by(date) %>% summarize(meancost=mean(cost)).
This groups data by date and then calculates the mean cost (cost) for each grouping (date).

Question 4

The provided code is missing. Therefore, I cannot determine the value of start after execution.

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Description

Test your knowledge of the Tidyverse in R programming with this quiz. It covers essential functions like filter() and select() and includes a question on calculating averages using group_by() and summarize(). Perfect for students looking to reinforce their data manipulation skills!