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[1] 4library(tidyverse)── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr 1.2.1 ✔ readr 2.2.0
✔ forcats 1.0.1 ✔ stringr 1.6.0
✔ ggplot2 4.0.3 ✔ tibble 3.3.1
✔ lubridate 1.9.5 ✔ tidyr 1.3.2
✔ purrr 1.2.2
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(dplyr)maltreatment <-read_csv("Maltreatment_Types_of_Victims_20260801.csv")Rows: 54 Columns: 21
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (1): State
dbl (12): Sex Trafficking Only, Unknown Only, Medical Neglect Only Percent, ...
num (8): Medical Neglect Only, Neglect Only, Other Only, Physical Abuse Onl...
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.head(maltreatment)# A tibble: 6 × 21
State `Medical Neglect Only` `Neglect Only` `Other Only` `Physical Abuse Only`
<chr> <dbl> <dbl> <dbl> <dbl>
1 Alab… 49 3380 NA 5114
2 Alas… 37 1445 NA 111
3 Ariz… NA 11332 NA 682
4 Arka… 1279 3421 1 1286
5 Cali… NA 50799 117 2161
6 Colo… 80 9517 NA 854
# ℹ 16 more variables: `Psychological Maltreatment Only` <dbl>,
# `Sexual Abuse Only` <dbl>, `Sex Trafficking Only` <dbl>,
# `Unknown Only` <dbl>, `Multiple Maltreatment Types` <dbl>,
# `Total Victims` <dbl>, `Medical Neglect Only Percent` <dbl>,
# `Neglect Only Percent` <dbl>, `Other Only Percent` <dbl>,
# `Physical Abuse Only Percent` <dbl>,
# `Psychological Maltreatment Only Percent` <dbl>, …tail(maltreatment)# A tibble: 6 × 21
State `Medical Neglect Only` `Neglect Only` `Other Only` `Physical Abuse Only`
<chr> <dbl> <dbl> <dbl> <dbl>
1 Wash… NA 2831 NA 569
2 West… NA 1173 NA 902
3 Wisc… NA 2802 NA 546
4 Wyom… 2 655 NA 13
5 Nati… 5614 399992 17614 67678
6 Repo… 36 52 21 52
# ℹ 16 more variables: `Psychological Maltreatment Only` <dbl>,
# `Sexual Abuse Only` <dbl>, `Sex Trafficking Only` <dbl>,
# `Unknown Only` <dbl>, `Multiple Maltreatment Types` <dbl>,
# `Total Victims` <dbl>, `Medical Neglect Only Percent` <dbl>,
# `Neglect Only Percent` <dbl>, `Other Only Percent` <dbl>,
# `Physical Abuse Only Percent` <dbl>,
# `Psychological Maltreatment Only Percent` <dbl>, …str(maltreatment)spc_tbl_ [54 × 21] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ State : chr [1:54] "Alabama" "Alaska" "Arizona" "Arkansas" ...
$ Medical Neglect Only : num [1:54] 49 37 NA 1279 NA ...
$ Neglect Only : num [1:54] 3380 1445 11332 3421 50799 ...
$ Other Only : num [1:54] NA NA NA 1 117 ...
$ Physical Abuse Only : num [1:54] 5114 111 682 1286 2161 ...
$ Psychological Maltreatment Only : num [1:54] 16 327 1 25 2115 ...
$ Sexual Abuse Only : num [1:54] 1828 183 389 1415 2264 ...
$ Sex Trafficking Only : num [1:54] 3 1 NA NA NA NA NA NA 14 NA ...
$ Unknown Only : num [1:54] NA NA NA NA NA 9 NA NA NA NA ...
$ Multiple Maltreatment Types : num [1:54] 1287 955 443 995 6659 ...
$ Total Victims : num [1:54] 11677 3059 12847 8422 64115 ...
$ Medical Neglect Only Percent : num [1:54] 0.4 1.2 NA 15.2 NA 0.7 1.1 NA NA 1.9 ...
$ Neglect Only Percent : num [1:54] 28.9 47.2 88.2 40.6 79.2 77.7 58.6 25.1 80.3 39.2 ...
$ Other Only Percent : num [1:54] NA NA NA 0 0.2 NA NA 9.6 NA 24.9 ...
$ Physical Abuse Only Percent : num [1:54] 43.8 3.6 5.3 15.3 3.4 7 2.1 12.9 9.4 5.3 ...
$ Psychological Maltreatment Only Percent: num [1:54] 0.1 10.7 0 0.3 3.3 1 7.4 32.4 NA 0.5 ...
$ Sexual Abuse Only Percent : num [1:54] 15.7 6 3 16.8 3.5 8.1 2.3 9.7 2.4 7.2 ...
$ Sex Trafficking Only Percent : num [1:54] 0 0 NA NA NA NA NA NA 0.8 NA ...
$ Unknown Only Percent : num [1:54] NA NA NA NA NA 0.1 NA NA NA NA ...
$ Multiple Maltreatment Types Percent : num [1:54] 11 31.2 3.4 11.8 10.4 5.5 28.5 10.3 7.1 21.1 ...
$ Total Victims Percent : num [1:54] 100 100 100 100 100 100 100 100 100 100 ...
- attr(*, "spec")=
.. cols(
.. State = col_character(),
.. `Medical Neglect Only` = col_number(),
.. `Neglect Only` = col_number(),
.. `Other Only` = col_number(),
.. `Physical Abuse Only` = col_number(),
.. `Psychological Maltreatment Only` = col_number(),
.. `Sexual Abuse Only` = col_number(),
.. `Sex Trafficking Only` = col_double(),
.. `Unknown Only` = col_double(),
.. `Multiple Maltreatment Types` = col_number(),
.. `Total Victims` = col_number(),
.. `Medical Neglect Only Percent` = col_double(),
.. `Neglect Only Percent` = col_double(),
.. `Other Only Percent` = col_double(),
.. `Physical Abuse Only Percent` = col_double(),
.. `Psychological Maltreatment Only Percent` = col_double(),
.. `Sexual Abuse Only Percent` = col_double(),
.. `Sex Trafficking Only Percent` = col_double(),
.. `Unknown Only Percent` = col_double(),
.. `Multiple Maltreatment Types Percent` = col_double(),
.. `Total Victims Percent` = col_double()
.. )
- attr(*, "problems")=<pointer: 0x7fe883050ea0> maltreatment_victims <- maltreatment |>
group_by(State) |>
summarize(
`Total Victims` = mean(`Total Victims`),
`Medical Neglect Only` = mean(`Medical Neglect Only`),
`Neglect Only` = mean(`Neglect Only`),
)
print(maltreatment_victims)# A tibble: 54 × 4
State `Total Victims` `Medical Neglect Only` `Neglect Only`
<chr> <dbl> <dbl> <dbl>
1 Alabama 11677 49 3380
2 Alaska 3059 37 1445
3 Arizona 12847 NA 11332
4 Arkansas 8422 1279 3421
5 California 64115 NA 50799
6 Colorado 12246 80 9517
7 Connecticut 8042 87 4709
8 Delaware 1248 NA 313
9 District of Columbia 1857 NA 1492
10 Florida 32915 616 12893
# ℹ 44 more rowsplot(maltreatment_victims$`Total Victims`, maltreatment_victims$`Medical Neglect Only`,
col = "blue", pch = 16,
main = "Scatter Plot", xlab = "Total Victims", ylab = "Medical Neglect")
The echo: false option disables the printing of code (only output is displayed).
p1 <- maltreatment_victims |>
ggplot(aes(x= `Medical Neglect Only`, fill= State)) +
geom_histogram(position="identity")+
scale_fill_discrete(name = "Medical Neglect Only") + geom_histogram(bins = 15)
print(p1)`stat_bin()` using `bins = 30`. Pick better value `binwidth`.Warning: Removed 16 rows containing non-finite outside the scale range (`stat_bin()`).
Removed 16 rows containing non-finite outside the scale range (`stat_bin()`).
p2 <- maltreatment_victims |>
ggplot(aes(x= `Neglect Only`, fill= State)) +
geom_histogram(position="identity") +
scale_fill_discrete(name = "Neglect Only") + geom_histogram(bins = 15)
print(p2)`stat_bin()` using `bins = 30`. Pick better value `binwidth`.