Data Manipulation With Dplyr — Part 1 MCQs with Explanations

select() is the correct answer to “In dplyr, what function is used to select specific columns from a data frame”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

filter() is the correct answer to “How do you filter rows in a dplyr data frame based on a specific condition using filter()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Orders the rows based on a specific column is the correct answer to “In dplyr, what does the arrange() function do”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

mutate() is the correct answer to “What function is used to create a new variable in a dplyr data frame based on existing variables”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

summarize() is the correct answer to “How do you perform a group-wise summary operation using dplyr's group_by() and summarize() functions”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Removes duplicate rows from a data frame is the correct answer to “What is the purpose of the distinct() function in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Creates a new variable based on existing ones is the correct answer to “In dplyr, what does the mutate() function do”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

left_join() is the correct answer to “How do you join two data frames based on a common column using dplyr's left_join()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Chains together a sequence of operations is the correct answer to “In dplyr, what is the purpose of the %>% operator (pipe operator)”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Applies a summary function to each group is the correct answer to “What is the role of the summarize() function in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

summarize(mean_score = mean(score)) is the correct answer to “In dplyr, how do you calculate the mean of a numeric variable named score for each group using summarize()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

rename() is the correct answer to “What function is used to rename columns in a dplyr data frame”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

filter(!is.na(variable)) is the correct answer to “In dplyr, how do you filter rows where a specific variable is not missing using filter()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

n() is the correct answer to “How do you count the number of rows in a dplyr data frame”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

top_n(5, value) is the correct answer to “In dplyr, how do you select the top 5 rows based on a variable named value in descending order”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Groups the data frame by a specified column is the correct answer to “What does the group_by() function do in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

select(starts_with("partial_name")) is the correct answer to “In dplyr, how do you select columns based on a partial name using the select() function”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

filter(multiple_conditions) is the correct answer to “What function is used to filter rows based on multiple conditions in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

inner_join() is the correct answer to “How do you perform an inner join between two data frames in dplyr using inner_join()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

summarize(count = n()) is the correct answer to “In dplyr, how do you calculate the total count of observations in each group using summarize()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Removes the grouping of the data frame is the correct answer to “What is the purpose of the ungroup() function in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

distinct(category) is the correct answer to “How do you select distinct values from a column named category in dplyr using distinct()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Extracts specific rows from a data frame is the correct answer to “In dplyr, what does the slice() function do”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Renames all columns in a data frame is the correct answer to “What does the rename_all() function do in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

summarize(median_price = median(price)) is the correct answer to “How do you calculate the median of a numeric variable named price for each group in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

choose_cols(matches("specific_pattern")) is the correct answer to “In dplyr, how do you select columns that match a specific pattern using the select() function”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

na_omit() is the correct answer to “What function is used to remove missing values from a dplyr data frame”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

mutate(cumsum = cumsum(sales)) is the correct answer to “In dplyr, how do you calculate the cumulative sum of a variable named sales within each group”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

To create a switch case statement in a column is the correct answer to “How is the case_when() function used in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Samples random rows from a data frame is the correct answer to “In dplyr, what does the slice_sample() function do”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Filters unique rows based on all specified columns is the correct answer to “In dplyr, what is the purpose of the distinct() function when used with multiple columns”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

mutate(total_price = price1 + price2) is the correct answer to “How do you create a new column total_price in dplyr that is the sum of two existing columns price1 and price2”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Removes rows based on specified conditions is the correct answer to “What is the purpose of the filter() function in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

select(starts_with("a")) is the correct answer to “How do you select columns from a dplyr data frame where the column names start with the letter 'a'”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

summarize(total = sum(quantity), average = mean(quantity)) is the correct answer to “In dplyr, how do you calculate the sum and mean of a numeric variable named quantity for each group”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Performs a left outer join between two data frames is the correct answer to “What is the role of the left_join() function in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

filter(between(variable, lower_bound, upper_bound)) is the correct answer to “In dplyr, how do you filter rows where a specific variable is within a range using filter()”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

n_distinct(category) is the correct answer to “How do you count the number of distinct values in a column named category in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

filter(condition1 & condition2) is the correct answer to “In dplyr, how do you filter rows based on multiple conditions using the AND logic”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.

Sorts a column in descending order is the correct answer to “What does the desc() function do in dplyr”. This question is standard in competitive examination syllabi for Data Manipulation With Dplyr.