myData <- read_excel("data/myData.xlsx")
myData## # A tibble: 2,973 × 10
## name state state_code type degree_length room_and_board in_state_tuition
## <chr> <chr> <chr> <chr> <chr> <chr> <dbl>
## 1 Aaniiih… Mont… MT Publ… 2 Year NA 2380
## 2 Abilene… Texas TX Priv… 4 Year 10350 34850
## 3 Abraham… Geor… GA Publ… 2 Year 8474 4128
## 4 Academy… Minn… MN For … 2 Year NA 17661
## 5 Academy… Cali… CA For … 4 Year 16648 27810
## 6 Adams S… Colo… CO Publ… 4 Year 8782 9440
## 7 Adelphi… New … NY Priv… 4 Year 16030 38660
## 8 Adirond… New … NY Publ… 2 Year 11660 5375
## 9 Adrian … Mich… MI Priv… 4 Year 11318 37087
## 10 Advance… Virg… VA For … 2 Year NA 13680
## # ℹ 2,963 more rows
## # ℹ 3 more variables: in_state_total <dbl>, out_of_state_tuition <dbl>,
## # out_of_state_total <dbl>data <- myData %>%
select(name, room_and_board, in_state_tuition, out_of_state_tuition) %>%
filter(name %in% c("Plymouth State University", "University of New Hampshire", "Southern New Hampshire University"))
data## # A tibble: 3 × 4
## name room_and_board in_state_tuition out_of_state_tuition
## <chr> <chr> <dbl> <dbl>
## 1 Plymouth State University 11100 14099 22769
## 2 Southern New Hampshire U… 13120 31136 31136
## 3 University of New Hampsh… 11580 18499 33879data_united <- myData %>%
unite(col = "Tuition", in_state_tuition:out_of_state_tuition, sep = "/")
data_united## # A tibble: 2,973 × 8
## name state state_code type degree_length room_and_board Tuition
## <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 Aaniiih Nakoda C… Mont… MT Publ… 2 Year NA 2380/2…
## 2 Abilene Christia… Texas TX Priv… 4 Year 10350 34850/…
## 3 Abraham Baldwin … Geor… GA Publ… 2 Year 8474 4128/1…
## 4 Academy College Minn… MN For … 2 Year NA 17661/…
## 5 Academy of Art U… Cali… CA For … 4 Year 16648 27810/…
## 6 Adams State Univ… Colo… CO Publ… 4 Year 8782 9440/1…
## 7 Adelphi Universi… New … NY Priv… 4 Year 16030 38660/…
## 8 Adirondack Commu… New … NY Publ… 2 Year 11660 5375/1…
## 9 Adrian College Mich… MI Priv… 4 Year 11318 37087/…
## 10 Advanced Technol… Virg… VA For … 2 Year NA 13680/…
## # ℹ 2,963 more rows
## # ℹ 1 more variable: out_of_state_total <dbl>data_separated <- data_united %>%
separate(col = Tuition, into = c("in_state_total", "out_of_state_total"), sep = "/")## Warning: Expected 2 pieces. Additional pieces discarded in 2973 rows [1, 2, 3, 4, 5, 6,
## 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].data_separated## # A tibble: 2,973 × 8
## name state state_code type degree_length room_and_board in_state_total
## <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 Aaniiih N… Mont… MT Publ… 2 Year NA 2380
## 2 Abilene C… Texas TX Priv… 4 Year 10350 34850
## 3 Abraham B… Geor… GA Publ… 2 Year 8474 4128
## 4 Academy C… Minn… MN For … 2 Year NA 17661
## 5 Academy o… Cali… CA For … 4 Year 16648 27810
## 6 Adams Sta… Colo… CO Publ… 4 Year 8782 9440
## 7 Adelphi U… New … NY Priv… 4 Year 16030 38660
## 8 Adirondac… New … NY Publ… 2 Year 11660 5375
## 9 Adrian Co… Mich… MI Priv… 4 Year 11318 37087
## 10 Advanced … Virg… VA For … 2 Year NA 13680
## # ℹ 2,963 more rows
## # ℹ 1 more variable: out_of_state_total <chr>data %>%
group_by(in_state_tuition, out_of_state_tuition) %>%
summarise(mean = mean(name, na.rm = TRUE))## Warning: There were 3 warnings in `summarise()`.
## The first warning was:
## ℹ In argument: `mean = mean(name, na.rm = TRUE)`.
## ℹ In group 1: `in_state_tuition = 14099` and `out_of_state_tuition = 22769`.
## Caused by warning in `mean.default()`:
## ! argument is not numeric or logical: returning NA
## ℹ Run `dplyr::last_dplyr_warnings()` to see the 2 remaining warnings.## `summarise()` has grouped output by 'in_state_tuition'. You can override using
## the `.groups` argument.## # A tibble: 3 × 3
## # Groups: in_state_tuition [3]
## in_state_tuition out_of_state_tuition mean
## <dbl> <dbl> <dbl>
## 1 14099 22769 NA
## 2 18499 33879 NA
## 3 31136 31136 NA