Working in R, I have a dataframe df that shows the number of students enrolled in each grade.
df <- structure(list(Grade = c("PK3", "PK4", "KG", "Grade 1", "Grade 2",
"Grade 3", "Grade 4", "Grade 5", "Grade 6", "Grade 7", "Grade 8",
"Grade 9", "Grade 10", "Grade 11", "Grade 12", "Ungraded"), Enrolled = c(4967,
6481, 7378, 7041, 6760, 6590, 6473, 6191, 5790, 5693, 5614, 7254,
4951, 4250, 3792, 238)), row.names = c(NA, -16L), class = c("tbl_df",
"tbl", "data.frame"))
I want to append two rows at the end: one which shows total enrollment in grades K-12 and the other which shows total enrollment for grades PK-12. I wrote code to do this using the {janitor} package, but this code seems unnecessarily long and complicated. Is there a better way to tell the code to append one row that sums up rows 3 to 16, and another row that sums up rows 1 to 16?
df2 = df %>% filter(Grade != "PK3" & Grade != "PK4") %>%
adorn_totals(where="row", name="k_12_total") %>%
filter(Grade == "k_12_total")
df = rbind(df, df2)
df2 = df %>% filter(Grade != "k_12_total") %>%
adorn_totals(where="row", name="pk_12_total") %>%
filter(Grade == "pk_12_total")
df = rbind(df, df2)
What if we simply just append two 1-row dataframes with the sums you want. Assuming you already know the indices its as easy as:
rbind(df,
data.frame(Grade = "k_12_total", Enrolled = sum(df$Enrolled[3:16])),
data.frame(Grade = "pk_12_total", Enrolled = sum(df$Enrolled[1:16])))
#> Grade Enrolled
#> 1 PK3 4967
#> 2 PK4 6481
#> 3 KG 7378
#> 4 Grade 1 7041
#> 5 Grade 2 6760
#> 6 Grade 3 6590
#> 7 Grade 4 6473
#> 8 Grade 5 6191
#> 9 Grade 6 5790
#> 10 Grade 7 5693
#> 11 Grade 8 5614
#> 12 Grade 9 7254
#> 13 Grade 10 4951
#> 14 Grade 11 4250
#> 15 Grade 12 3792
#> 16 Ungraded 238
#> 17 k_12_total 78015
#> 18 pk_12_total 89463
For multiple years use colSums:
#example data
df$Enrolled2020 <- df$Enrolled + sample(-100:100, nrow(df))
rbind(df,
data.frame(Grade = "k_12_total", t(colSums(df[3:16,2:3])) ),
data.frame(Grade = "pk_12_total", t(colSums(df[1:16,2:3]))))
#> Grade Enrolled Enrolled2020
#> 1 PK3 4967 5066
#> 2 PK4 6481 6422
#> 3 KG 7378 7359
#> 4 Grade 1 7041 6977
#> 5 Grade 2 6760 6713
#> 6 Grade 3 6590 6585
#> 7 Grade 4 6473 6386
#> 8 Grade 5 6191 6232
#> 9 Grade 6 5790 5765
#> 10 Grade 7 5693 5701
#> 11 Grade 8 5614 5701
#> 12 Grade 9 7254 7198
#> 13 Grade 10 4951 4912
#> 14 Grade 11 4250 4189
#> 15 Grade 12 3792 3730
#> 16 Ungraded 238 256
#> 17 k_12_total 78015 77704
#> 18 pk_12_total 89463 89192