1 + 1[1] 2Project 1
Quarto
Quarto enables you to weave together content and executable code into a finished document. To learn more about Quarto see https://quarto.org.
Running Code
When you click the Render button a document will be generated that includes both content and the output of embedded code. You can embed code like this:
You can add options to executable code like this
[1] 4The echo: false option disables the printing of code (only output is displayed).
library(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(viridis)Loading required package: viridisLitemaltreatment <-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>, …dim(maltreatment)[1] 54 21str(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: 0x7fd496a4e900> mean(maltreatment$`Total Victims`)[1] 24306.26sd(maltreatment$`Total Victims`)[1] 88964.67count(maltreatment)# A tibble: 1 × 1
n
<int>
1 54maltreatment_no_null <- maltreatment |>
filter(
!is.na(`Medical Neglect Only`),
!is.na(`Physical Abuse Only`),
!is.na(`Sexual Abuse Only`)
)
is.na(maltreatment_no_null) State Medical Neglect Only Neglect Only Other Only Physical Abuse Only
[1,] FALSE FALSE FALSE TRUE FALSE
[2,] FALSE FALSE FALSE TRUE FALSE
[3,] FALSE FALSE FALSE FALSE FALSE
[4,] FALSE FALSE FALSE TRUE FALSE
[5,] FALSE FALSE FALSE TRUE FALSE
[6,] FALSE FALSE FALSE FALSE FALSE
[7,] FALSE FALSE FALSE TRUE FALSE
[8,] FALSE FALSE FALSE FALSE FALSE
[9,] FALSE FALSE FALSE FALSE FALSE
[10,] FALSE FALSE FALSE FALSE FALSE
[11,] FALSE FALSE FALSE FALSE FALSE
[12,] FALSE FALSE FALSE TRUE FALSE
[13,] FALSE FALSE FALSE TRUE FALSE
[14,] FALSE FALSE FALSE FALSE FALSE
[15,] FALSE FALSE FALSE FALSE FALSE
[16,] FALSE FALSE FALSE TRUE FALSE
[17,] FALSE FALSE FALSE TRUE FALSE
[18,] FALSE FALSE FALSE TRUE FALSE
[19,] FALSE FALSE FALSE FALSE FALSE
[20,] FALSE FALSE FALSE TRUE FALSE
[21,] FALSE FALSE FALSE FALSE FALSE
[22,] FALSE FALSE FALSE FALSE FALSE
[23,] FALSE FALSE FALSE TRUE FALSE
[24,] FALSE FALSE FALSE TRUE FALSE
[25,] FALSE FALSE FALSE TRUE FALSE
[26,] FALSE FALSE FALSE FALSE FALSE
[27,] FALSE FALSE FALSE FALSE FALSE
[28,] FALSE FALSE FALSE FALSE FALSE
[29,] FALSE FALSE FALSE FALSE FALSE
[30,] FALSE FALSE FALSE FALSE FALSE
[31,] FALSE FALSE FALSE TRUE FALSE
[32,] FALSE FALSE FALSE FALSE FALSE
[33,] FALSE FALSE FALSE FALSE FALSE
[34,] FALSE FALSE FALSE TRUE FALSE
[35,] FALSE FALSE FALSE TRUE FALSE
[36,] FALSE FALSE FALSE TRUE FALSE
[37,] FALSE FALSE FALSE FALSE FALSE
[38,] FALSE FALSE FALSE FALSE FALSE
Psychological Maltreatment Only Sexual Abuse Only Sex Trafficking Only
[1,] FALSE FALSE FALSE
[2,] FALSE FALSE FALSE
[3,] FALSE FALSE TRUE
[4,] FALSE FALSE TRUE
[5,] FALSE FALSE TRUE
[6,] FALSE FALSE TRUE
[7,] FALSE FALSE FALSE
[8,] TRUE FALSE TRUE
[9,] FALSE FALSE TRUE
[10,] FALSE FALSE TRUE
[11,] FALSE FALSE FALSE
[12,] FALSE FALSE TRUE
[13,] FALSE FALSE FALSE
[14,] FALSE FALSE FALSE
[15,] FALSE FALSE FALSE
[16,] FALSE FALSE TRUE
[17,] FALSE FALSE TRUE
[18,] FALSE FALSE TRUE
[19,] FALSE FALSE FALSE
[20,] FALSE FALSE TRUE
[21,] FALSE FALSE TRUE
[22,] FALSE FALSE TRUE
[23,] FALSE FALSE TRUE
[24,] FALSE FALSE TRUE
[25,] FALSE FALSE FALSE
[26,] FALSE FALSE FALSE
[27,] FALSE FALSE FALSE
[28,] FALSE FALSE TRUE
[29,] FALSE FALSE TRUE
[30,] FALSE FALSE TRUE
[31,] FALSE FALSE FALSE
[32,] FALSE FALSE FALSE
[33,] FALSE FALSE FALSE
[34,] FALSE FALSE TRUE
[35,] FALSE FALSE TRUE
[36,] FALSE FALSE TRUE
[37,] FALSE FALSE FALSE
[38,] FALSE FALSE FALSE
Unknown Only Multiple Maltreatment Types Total Victims
[1,] TRUE FALSE FALSE
[2,] TRUE FALSE FALSE
[3,] TRUE FALSE FALSE
[4,] FALSE FALSE FALSE
[5,] TRUE FALSE FALSE
[6,] TRUE FALSE FALSE
[7,] TRUE FALSE FALSE
[8,] TRUE FALSE FALSE
[9,] TRUE FALSE FALSE
[10,] TRUE FALSE FALSE
[11,] TRUE FALSE FALSE
[12,] TRUE FALSE FALSE
[13,] TRUE FALSE FALSE
[14,] TRUE FALSE FALSE
[15,] TRUE FALSE FALSE
[16,] TRUE FALSE FALSE
[17,] TRUE FALSE FALSE
[18,] TRUE FALSE FALSE
[19,] TRUE FALSE FALSE
[20,] TRUE FALSE FALSE
[21,] TRUE FALSE FALSE
[22,] FALSE FALSE FALSE
[23,] TRUE FALSE FALSE
[24,] TRUE FALSE FALSE
[25,] TRUE FALSE FALSE
[26,] TRUE FALSE FALSE
[27,] TRUE FALSE FALSE
[28,] TRUE FALSE FALSE
[29,] TRUE FALSE FALSE
[30,] FALSE FALSE FALSE
[31,] TRUE FALSE FALSE
[32,] TRUE FALSE FALSE
[33,] TRUE FALSE FALSE
[34,] TRUE FALSE FALSE
[35,] TRUE FALSE FALSE
[36,] TRUE FALSE FALSE
[37,] FALSE FALSE FALSE
[38,] FALSE FALSE FALSE
Medical Neglect Only Percent Neglect Only Percent Other Only Percent
[1,] FALSE FALSE TRUE
[2,] FALSE FALSE TRUE
[3,] FALSE FALSE FALSE
[4,] FALSE FALSE TRUE
[5,] FALSE FALSE TRUE
[6,] FALSE FALSE FALSE
[7,] FALSE FALSE TRUE
[8,] FALSE FALSE FALSE
[9,] FALSE FALSE FALSE
[10,] FALSE FALSE FALSE
[11,] FALSE FALSE FALSE
[12,] FALSE FALSE TRUE
[13,] FALSE FALSE TRUE
[14,] FALSE FALSE FALSE
[15,] FALSE FALSE FALSE
[16,] FALSE FALSE TRUE
[17,] FALSE FALSE TRUE
[18,] FALSE FALSE TRUE
[19,] FALSE FALSE FALSE
[20,] FALSE FALSE TRUE
[21,] FALSE FALSE FALSE
[22,] FALSE FALSE FALSE
[23,] FALSE FALSE TRUE
[24,] FALSE FALSE TRUE
[25,] FALSE FALSE TRUE
[26,] FALSE FALSE FALSE
[27,] FALSE FALSE FALSE
[28,] FALSE FALSE FALSE
[29,] FALSE FALSE FALSE
[30,] FALSE FALSE FALSE
[31,] FALSE FALSE TRUE
[32,] FALSE FALSE FALSE
[33,] FALSE FALSE FALSE
[34,] FALSE FALSE TRUE
[35,] FALSE FALSE TRUE
[36,] FALSE FALSE TRUE
[37,] FALSE FALSE FALSE
[38,] TRUE TRUE TRUE
Physical Abuse Only Percent Psychological Maltreatment Only Percent
[1,] FALSE FALSE
[2,] FALSE FALSE
[3,] FALSE FALSE
[4,] FALSE FALSE
[5,] FALSE FALSE
[6,] FALSE FALSE
[7,] FALSE FALSE
[8,] FALSE TRUE
[9,] FALSE FALSE
[10,] FALSE FALSE
[11,] FALSE FALSE
[12,] FALSE FALSE
[13,] FALSE FALSE
[14,] FALSE FALSE
[15,] FALSE FALSE
[16,] FALSE FALSE
[17,] FALSE FALSE
[18,] FALSE FALSE
[19,] FALSE FALSE
[20,] FALSE FALSE
[21,] FALSE FALSE
[22,] FALSE FALSE
[23,] FALSE FALSE
[24,] FALSE FALSE
[25,] FALSE FALSE
[26,] FALSE FALSE
[27,] FALSE FALSE
[28,] FALSE FALSE
[29,] FALSE FALSE
[30,] FALSE FALSE
[31,] FALSE FALSE
[32,] FALSE FALSE
[33,] FALSE FALSE
[34,] FALSE FALSE
[35,] FALSE FALSE
[36,] FALSE FALSE
[37,] FALSE FALSE
[38,] TRUE TRUE
Sexual Abuse Only Percent Sex Trafficking Only Percent
[1,] FALSE FALSE
[2,] FALSE FALSE
[3,] FALSE TRUE
[4,] FALSE TRUE
[5,] FALSE TRUE
[6,] FALSE TRUE
[7,] FALSE FALSE
[8,] FALSE TRUE
[9,] FALSE TRUE
[10,] FALSE TRUE
[11,] FALSE FALSE
[12,] FALSE TRUE
[13,] FALSE FALSE
[14,] FALSE FALSE
[15,] FALSE FALSE
[16,] FALSE TRUE
[17,] FALSE TRUE
[18,] FALSE TRUE
[19,] FALSE FALSE
[20,] FALSE TRUE
[21,] FALSE TRUE
[22,] FALSE TRUE
[23,] FALSE TRUE
[24,] FALSE TRUE
[25,] FALSE FALSE
[26,] FALSE FALSE
[27,] FALSE FALSE
[28,] FALSE TRUE
[29,] FALSE TRUE
[30,] FALSE TRUE
[31,] FALSE FALSE
[32,] FALSE FALSE
[33,] FALSE FALSE
[34,] FALSE TRUE
[35,] FALSE TRUE
[36,] FALSE TRUE
[37,] FALSE FALSE
[38,] TRUE TRUE
Unknown Only Percent Multiple Maltreatment Types Percent
[1,] TRUE FALSE
[2,] TRUE FALSE
[3,] TRUE FALSE
[4,] FALSE FALSE
[5,] TRUE FALSE
[6,] TRUE FALSE
[7,] TRUE FALSE
[8,] TRUE FALSE
[9,] TRUE FALSE
[10,] TRUE FALSE
[11,] TRUE FALSE
[12,] TRUE FALSE
[13,] TRUE FALSE
[14,] TRUE FALSE
[15,] TRUE FALSE
[16,] TRUE FALSE
[17,] TRUE FALSE
[18,] TRUE FALSE
[19,] TRUE FALSE
[20,] TRUE FALSE
[21,] TRUE FALSE
[22,] FALSE FALSE
[23,] TRUE FALSE
[24,] TRUE FALSE
[25,] TRUE FALSE
[26,] TRUE FALSE
[27,] TRUE FALSE
[28,] TRUE FALSE
[29,] TRUE FALSE
[30,] TRUE FALSE
[31,] TRUE FALSE
[32,] TRUE FALSE
[33,] TRUE FALSE
[34,] TRUE FALSE
[35,] TRUE FALSE
[36,] TRUE FALSE
[37,] FALSE FALSE
[38,] TRUE TRUE
Total Victims Percent
[1,] FALSE
[2,] FALSE
[3,] FALSE
[4,] FALSE
[5,] FALSE
[6,] FALSE
[7,] FALSE
[8,] FALSE
[9,] FALSE
[10,] FALSE
[11,] FALSE
[12,] FALSE
[13,] FALSE
[14,] FALSE
[15,] FALSE
[16,] FALSE
[17,] FALSE
[18,] FALSE
[19,] FALSE
[20,] FALSE
[21,] FALSE
[22,] FALSE
[23,] FALSE
[24,] FALSE
[25,] FALSE
[26,] FALSE
[27,] FALSE
[28,] FALSE
[29,] FALSE
[30,] FALSE
[31,] FALSE
[32,] FALSE
[33,] FALSE
[34,] FALSE
[35,] FALSE
[36,] FALSE
[37,] FALSE
[38,] TRUEggplot(data = maltreatment) +
geom_bar(mapping = aes(x = maltreatment$State, y = stat(maltreatment$`Medical Neglect Only`), group = .5)) +
labs(x = "State", y = "Medical Neglect",
title = "Medical Neglect by State")Warning: `stat(maltreatment$`Medical Neglect Only`)` was deprecated in ggplot2 3.4.0.
ℹ Please use `after_stat(maltreatment$`Medical Neglect Only`)` instead.Warning: Removed 16 rows containing missing values or values outside the scale range
(`geom_bar()`).