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Questions and Answers
When using %>%, each function must return a result that can be passed to the next function in the chain.
When using %>%, each function must return a result that can be passed to the next function in the chain.
True
In dplyr, the summarize() function cannot use %>% for grouped summaries.
In dplyr, the summarize() function cannot use %>% for grouped summaries.
False
The count() function in dplyr is often combined with %>% to count rows within groups.
The count() function in dplyr is often combined with %>% to count rows within groups.
True
The pipe operator %>% allows for nesting functions without deeply embedding code.
The pipe operator %>% allows for nesting functions without deeply embedding code.
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dplyr functions like mutate can be used with conditional statements to create new variables.
dplyr functions like mutate can be used with conditional statements to create new variables.
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The summarize(across()) function in dplyr is used to apply functions across multiple columns.
The summarize(across()) function in dplyr is used to apply functions across multiple columns.
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dplyr's left_join() function merges two data frames by keeping all rows from the left data frame.
dplyr's left_join() function merges two data frames by keeping all rows from the left data frame.
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The inner_join() function in dplyr merges data frames and keeps only rows with matching keys.
The inner_join() function in dplyr merges data frames and keeps only rows with matching keys.
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The anti_join() function retains all rows from the left data frame that have no match in the right data frame.
The anti_join() function retains all rows from the left data frame that have no match in the right data frame.
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