Advanced Variable Creation

Hi David, when I run this code: mutate(race_ethnicity = str_remove(race_ethnicity, "x2018_2019")), nothing happens?

I'm stuck with an error that it can't find my race_ethnicity variable (I see it in my data frame): Error: Problem with mutate() input race_ethnicity. x object 'race_ethnicity' not found ℹ Input race_ethnicity is str_remove(race_ethnicity, "x2018_19"). Run rlang::last_error() to see where the error occurred.

CODE: enrollment_by_race_ethnicity_18_19 % select(-contains("grade")) %>% select(-contains("kindergarten")) %>% select(-contains("percent")) %>% pivot_longer(cols = -district_id, names_to = "race_ethnicity", values_to = "number_of_students") %>% mutate(number_of_students = na_if(number_of_students, "-")) %>% mutate(number_of_students = replace_na(number_of_students, 0)) %>% mutate(number_of_students = as.numeric(number_of_students)) %>% summarize(total = sum(number_of_students)) %>% mutate(race_ethnicity = str_remove(race_ethnicity, "x2018_19"))

Is it just me or does the syntax for recode seem backwards to normal programming convention? I would have expected the new value to be left of the equals sign and the old value to be on the right side of the equals sign. Are there other instances of R where we would need to watch out for this? (Or maybe I'm the one who's backwards!)

Judging by the warning messages generated in the video, am I correct in concluding that R is smart enough to exclude the NA entries from being recoded inappropriately (e.g., when using the TRUE option in case_when)? I ask because SPSS isn't so smart, depending upon how the receding is specified. Also, if one wanted to recode the NA entries, the missing = new value option could be used, correct? I'm just checking my understanding of the help page.

Hello David. I have run the code successfully but it only shows the changes in the tibble and not in the data view. How do I reflect the change in the data frame? What may be the issue

Hi David, thanks again for the great instruction. Out of curiosity, is there a function similar to Excel's substitute function? In Excel I would use the substitute function to substitute " " for every "" and wrap a proper function around it to capitalize each word. Something like =proper(substitute(B2, "", " ")). Case_When is great but is potentially time consuming if there are 50 different instances.

This code:

enrolment_by_race_ethnicity % select(-contains("grade")) %>% select(-contains("kindergarten")) %>% select(-contains("percent")) %>% pivot_longer(cols = -district_id, names_to = "race_ethnicity", values_to = "number_of_students") %>% mutate(number_of_students = na_if(number_of_students,"-")) %>% mutate(number_of_students = as.numeric(number_of_students)) %>% mutate(number_of_students = replace_na(number_of_students, 0)) %>% mutate(race_ethnicity = str_remove(race_ethnicity, "x2018_19_")) %>% mutate(race_ethnicity = recode(race_ethnicity, "american_indian_alaska_native" = "American Indian/Alaska Native", "asian" = "Asian", "black_african_american" = "Black/African American", "hispanic_latino" = "Hispanic/Latino", "multiracial" = "Multiracial", "native_hawaiian_pacific_islander" = "Native Hawaiian/Pacific Islander", "white" = "White" ))

... produces this error - I don't understand why the arguments are "unused":

Error in mutate(): ! Problem while computing race_ethnicity = recode(...). Caused by error in recode(): ! unused arguments (american_indian_alaska_native = "American Indian/Alaska Native", asian = "Asian", black_african_american = "Black/African American", hispanic_latino = "Hispanic/Latino", multiracial = "Multiracial", native_hawaiian_pacific_islander = "Native Hawaiian/Pacific Islander", white = "White")

Hi David, I noticed that you left the following line (from the last lesson) in your code, and that you added the various methods of mutation after it in the pipeline: summarize(number_proficient = sum(number_proficient, na.rm - TRUE)) I did the same thing and it didn't work. That summarize line resulted in a tiny table that showed only the total number of students in the districts, and it did not contain any instances of "x2018_19" to remove, so I got an error message. I'm not sure why it worked for you to leave it in but not for me.

Hi David, when I followed the solution guide video and used the same exact code lines that you did, I got a table with race_ethnicity being all NA. Any idea what could have happened?

This is my code (error message follows): enrollment_by_race_ethnicity_18_19 % select(-contains("grade")) %>% select(-contains("percent")) %>% select(-contains("kindergarten")) %>% pivot_longer(cols= -district_id, names_to = "race_ethnicity", values_to = "number_of_students") %>% mutate(number_of_students=na_if(number_of_students, "-")) %>% mutate(number_of_students=as.numeric(number_of_students)) %>% mutate(number_of_students=replace_na(number_of_students, 0)) %>% mutate(race_ethnicity=str_remove(race_ethnicity, "x2018_19_")) %>% mutate(race_ethnicity= case_when( race_ethnicity == "american_indian_alaska_native" ~ "American Indian/Alaska Native", race_ethnicity == "asian" ~"Asian", race_ethnicity == "native_hawaiian_pacific_islander" ~ "Native Hawaiian/Pacific Islander", race_ethnicity == "black_african_american" ~ "Black", race_ethnicity == "hispanic_latino" ~ "Hispanic", race_ethnicity == "white" ~ "White", race_ethnicity == "multiracial" ~ "Multiracial" ))

This is the error message: Error in case_when(): ! Failed to evaluate the left-hand side of formula 1. Caused by error: ! object 'race_ethnicity' not found Run rlang::last_trace() to see where the error occurred. >