Sample data frame tt_small
using dput below.
I wnat to use GGally to do some exploratory analysis, however the chartlets have snipped labels since the text is too long.
library(GGally)
comparisson <- c("teacher_prefix", "project_grade_category",
"teacher_number_of_previously_posted_projects", "project_is_approved")
tt_small %>% ggpairs(comparisson)
Note how the column names are cut off. I then found this SO post on how to get around this issue.
Using the solution based on str_wrap()
in the above post I tried this:
comparisson_new <- comparisson %>% str_replace_all("_", " ") %>% str_wrap(width = 10)
tt_small <- tt_small %>% rename_at(vars(comparisson), function(x) ~comparisson_new)
tt_small %>% ggpairs(comparisson_new)
However this gives an error:
Error in eval(expr, envir, enclos) : object 'teacher' not found
Why is this not working and how can I amend my code so that the labels wrap neatly along the column titles of the charts?
tt_small <- structure(list(teacher_prefix = c("Mrs.", "Mr.", "Ms.", "Mr.",
"Mrs.", "Mr.", "Ms.", "Mrs.", "Mrs.", "Mrs.", "Mrs.", "Mr.",
"Mrs.", "Mr.", "Mrs.", "Ms.", "Ms.", "Ms.", "Ms.", "Mrs.", "Mrs.",
"Mrs.", "Mrs.", "Ms.", "Ms.", "Mrs.", "Mrs.", "Ms.", "Ms.", "Mrs.",
"Mrs.", "Mrs.", "Mrs.", "Mrs.", "Mr.", "Mrs.", "Mrs.", "Mrs.",
"Mr.", "Mrs.", "Mrs.", "Mrs.", "Mrs.", "Mrs.", "Ms.", "Mrs.",
"Mrs.", "Ms.", "Mrs.", "Ms.", "Ms.", "Mrs.", "Mr.", "Ms.", "Mrs.",
"Mrs.", "Ms.", "Mrs.", "Teacher", "Mrs.", "Teacher", "Teacher",
"Ms.", "Mrs.", "Mrs.", "Mrs.", "Mrs.", "Ms.", "Ms.", "Mrs.",
"Mrs.", "Mrs.", "Mrs.", "Ms.", "Mrs.", "Mrs.", "Ms.", "Ms.",
"Ms.", "Mrs.", "Mrs.", "Ms.", "Ms.", "Mr.", "Teacher", "Mrs.",
"Ms.", "Mrs.", "Ms.", "Mrs.", "Mrs.", "Ms.", "Mrs.", "Mrs.",
"Ms.", "Mr.", "Mr.", "Mr.", "Mrs.", "Mrs."), project_grade_category = c("Grades 3-5",
"Grades 6-8", "Grades PreK-2", "Grades 9-12", "Grades 6-8", "Grades 6-8",
"Grades 6-8", "Grades PreK-2", "Grades PreK-2", "Grades PreK-2",
"Grades 6-8", "Grades 6-8", "Grades 9-12", "Grades 6-8", "Grades PreK-2",
"Grades PreK-2", "Grades 3-5", "Grades 3-5", "Grades 3-5", "Grades PreK-2",
"Grades PreK-2", "Grades PreK-2", "Grades PreK-2", "Grades 3-5",
"Grades PreK-2", "Grades 6-8", "Grades 3-5", "Grades PreK-2",
"Grades 3-5", "Grades 3-5", "Grades PreK-2", "Grades 3-5", "Grades PreK-2",
"Grades PreK-2", "Grades 3-5", "Grades 3-5", "Grades 3-5", "Grades PreK-2",
"Grades 3-5", "Grades 9-12", "Grades 3-5", "Grades 6-8", "Grades PreK-2",
"Grades PreK-2", "Grades 3-5", "Grades PreK-2", "Grades PreK-2",
"Grades 6-8", "Grades PreK-2", "Grades 3-5", "Grades 3-5", "Grades PreK-2",
"Grades 9-12", "Grades 6-8", "Grades 9-12", "Grades 3-5", "Grades 9-12",
"Grades PreK-2", "Grades 6-8", "Grades 3-5", "Grades 3-5", "Grades 9-12",
"Grades 3-5", "Grades 3-5", "Grades PreK-2", "Grades 3-5", "Grades PreK-2",
"Grades 9-12", "Grades 3-5", "Grades 3-5", "Grades PreK-2", "Grades 3-5",
"Grades 3-5", "Grades 3-5", "Grades 9-12", "Grades 3-5", "Grades PreK-2",
"Grades PreK-2", "Grades PreK-2", "Grades PreK-2", "Grades 3-5",
"Grades 9-12", "Grades PreK-2", "Grades 3-5", "Grades PreK-2",
"Grades 3-5", "Grades 3-5", "Grades PreK-2", "Grades 3-5", "Grades 3-5",
"Grades PreK-2", "Grades 3-5", "Grades PreK-2", "Grades PreK-2",
"Grades 6-8", "Grades 3-5", "Grades 9-12", "Grades 9-12", "Grades PreK-2",
"Grades PreK-2"), teacher_number_of_previously_posted_projects = c(0L,
0L, 3L, 9L, 1L, 0L, 1L, 3L, 17L, 0L, 15L, 132L, 1L, 55L, 2L,
2L, 0L, 40L, 0L, 6L, 2L, 1L, 16L, 13L, 25L, 0L, 5L, 10L, 0L,
0L, 17L, 60L, 143L, 4L, 185L, 0L, 16L, 3L, 54L, 4L, 1L, 4L, 2L,
8L, 9L, 4L, 0L, 0L, 4L, 0L, 30L, 45L, 7L, 1L, 2L, 0L, 5L, 13L,
0L, 0L, 0L, 51L, 6L, 30L, 0L, 0L, 41L, 0L, 3L, 7L, 4L, 0L, 0L,
0L, 30L, 0L, 1L, 2L, 185L, 1L, 0L, 1L, 2L, 2L, 0L, 4L, 19L, 0L,
38L, 2L, 27L, 1L, 2L, 1L, 4L, 147L, 0L, 2L, 33L, 0L), project_is_approved = c(1L,
NA, 1L, NA, NA, 1L, 1L, NA, 0L, 1L, NA, 1L, 1L, 0L, 0L, NA, 0L,
1L, 0L, NA, NA, 1L, 1L, NA, 1L, NA, 0L, 1L, 0L, 1L, NA, NA, 1L,
NA, 1L, 1L, NA, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L,
NA, 1L, 1L, NA, 1L, 0L, 1L, 1L, NA, NA, 1L, 1L, 1L, 1L, 1L, NA,
1L, NA, NA, NA, 1L, NA, 1L, NA, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, NA, 0L, 0L, NA, NA, NA, 1L, 1L, 1L, 1L, 0L, 1L, 1L, NA,
0L, 1L, 1L)), row.names = c(74804L, 205050L, 106381L, 229684L,
244626L, 11850L, 137365L, 232126L, 143433L, 118769L, 248878L,
117915L, 176239L, 148944L, 26771L, 234045L, 64008L, 10940L, 85292L,
248263L, 231365L, 180195L, 166592L, 258602L, 170544L, 184282L,
141506L, 154530L, 75207L, 38263L, 250469L, 234674L, 179641L,
206887L, 6402L, 124266L, 197260L, 56283L, 82752L, 60241L, 37139L,
107813L, 107599L, 95927L, 39647L, 36100L, 60605L, 121182L, 69171L,
223092L, 11920L, 115001L, 207771L, 31702L, 145881L, 53711L, 33166L,
195904L, 232763L, 97382L, 172967L, 24664L, 99853L, 71355L, 211848L,
116637L, 210657L, 211261L, 206567L, 114377L, 196198L, 163626L,
184678L, 163L, 123602L, 57240L, 98768L, 159344L, 91481L, 28900L,
63350L, 173718L, 108602L, 204957L, 26748L, 113086L, 256118L,
232219L, 230506L, 45519L, 33985L, 169823L, 89323L, 170772L, 83304L,
48804L, 203412L, 24337L, 121371L, 133000L), class = "data.frame", .Names = c("teacher_prefix",
"project_grade_category", "teacher_number_of_previously_posted_projects",
"project_is_approved"))