library(ggplot2)
library(gridExtra)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following object is masked from 'package:gridExtra':
## 
##     combine

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(viridis)

## Loading required package: viridisLite

library(readr)

police = read_csv("police_killings_cleaned.csv")

## Parsed with column specification:
## cols(
##   .default = col_double(),
##   name = col_character(),
##   gender = col_character(),
##   raceethnicity = col_character(),
##   month = col_character(),
##   streetaddress = col_character(),
##   city = col_character(),
##   state = col_character(),
##   namelsad = col_character(),
##   lawenforcementagency = col_character(),
##   cause = col_character(),
##   armed = col_character(),
##   share_white = col_character(),
##   share_black = col_character(),
##   share_hispanic = col_character(),
##   p_income = col_character(),
##   pov = col_character()
## )

## See spec(...) for full column specifications.

ggplot(police) +
  geom_bar(aes(x = raceethnicity))

ggplot(police) + 
  geom_bar(aes(x = gender))

ggplot(police) + 
  geom_bar(aes(x = age))

MOst police shootng victims are men, most are White, Black, and Hispanic. Many are young.

ggplot(police) + 
  geom_bar(aes(x = cause))

Almost all are gunshot victims.