The data verb functions all take a data frame as their first argument and return a data frame as their output. The chaining syntax lets the output of one function become the input to the following function, so you do not have to repeat the name of the data frame. An alternative syntax is to assign the output of one function to a named object, then use the object as the first argument to the next function in the computation. Each of the following statements, EXCEPT one, will accomplish the same calculation. Identify the statement that does NOT match the others. O BabyNames %>% group_by( year, sex ) %>% summarise( totalBirths sum(count)) group_by( BabyNames, year, sex) %>% Bummarie

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The data verb functions all take a data frame as their first argument and return a data frame as
their output. The chaining syntax lets the output of one function become the input to the following
function, so you do not have to repeat the name of the data frame. An alternative syntax is to
assign the output of one function to a named object, then use the object as the first argument to
the next function in the computation. Each of the following statements, EXCEPT one, will
accomplish the same calculation.
Identify the statement that does NOT match the others.
O BabyNames %>%
group_by( year, sex ) %>%
summarise( totalBirths=sum(count))
group_by( BabyNames, year, sex) %>%
summarise( totalBirths=sum(count))
O group_by( BabyNalnes, year, sex ) %>%
summarise( BabyNames, totalBirths = sum(count))
O Tmp <- group_by(BabyNames, year, sex)
summarise( Tmp, totalBirths=sum(count))
Transcribed Image Text:The data verb functions all take a data frame as their first argument and return a data frame as their output. The chaining syntax lets the output of one function become the input to the following function, so you do not have to repeat the name of the data frame. An alternative syntax is to assign the output of one function to a named object, then use the object as the first argument to the next function in the computation. Each of the following statements, EXCEPT one, will accomplish the same calculation. Identify the statement that does NOT match the others. O BabyNames %>% group_by( year, sex ) %>% summarise( totalBirths=sum(count)) group_by( BabyNames, year, sex) %>% summarise( totalBirths=sum(count)) O group_by( BabyNalnes, year, sex ) %>% summarise( BabyNames, totalBirths = sum(count)) O Tmp <- group_by(BabyNames, year, sex) summarise( Tmp, totalBirths=sum(count))
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