visualizations.Rmd

---
title: "DPS Incident Database Visualizations"
author: "J.Wente"
date: "1/9/2020"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

library(rjson)
library(magrittr)
library(tidyverse)
library(stringi)
library(tidycensus)
library(tidycensus)
library(lubridate)

```

After running the dps_data_process, here we have a small dataset that we can now begin to plot aggregations.
using dps3 for injury and alcohol incidents. Using dps2 for all else. 

```{r}
#Seatbelt use by county
sb<-dps2 %>% group_by(seatBelt,county) %>% summarize(Count=sum(Count)) %>% arrange(Count) %>% filter(seatBelt=="No") %>% 
            arrange(Count) %>%
            ggplot(aes(x=reorder(county,-Count),y=Count)) + geom_bar(stat="identity") + 
          theme(axis.text.x=element_text(angle = 90)) + ggtitle("No Seatbelt use in DPS Incident Data") 
sb

# Acohol by county

alc<- dps3 %>% ggplot(aes(x=reorder(county,-AlcYes),y=AlcYes)) + geom_bar(stat="identity") +    
                  theme(axis.text.x=element_text(angle = 90)) 

```