Week4_MP.Rmd

---
title: "Week4_MP"
author: "Jessica Brown"
date: "2023-09-06"
output: html_document
---


1) How many with no Neighborhoods?

For the Missing Person category using data from 2018 - 2022, there were a total of 4 missing neighborhoods out of 9494 which is very unsignificant.

```{r}
library(ggplot2)
all_df_list$No_Neighborhood_Count
```


```{r}
all_df_list$No_Neighborhood_Count %>% ggplot(aes(x = Field, y = Value, color = "#aaa", fill = "#111")) + labs(x = "No Neighborhood", y = "Count") + geom_bar(stat = "identity", width = .3, show.legend = F)
```


2) Number of Crimes per month?

```{r}
all_df_list$Month_df %>% ggplot(aes(x = Month, y = Count)) + geom_bar(stat = "identity", color = "black", fill = "#00abff") + labs(title = "Missing Person Incidents For All Months of 2018-2022") + theme_gray()
```
```{r}
list2$Month_df %>% ggplot(aes(x = Month, y = Count, color = Month)) + geom_point(size = 2) + geom_line(color = "#777777") + labs(title = "Missing Person Incidents For All Months of 2018-2022") + theme_gray()
```

3) Distribution for time of week?

```{r}
all_df_list$Week_df %>% ggplot(aes(x = Number, y = Count), color = Week) + geom_bar(stat = "identity", color = "black", fill = "#00abff") + labs(title = "Missing Person Incidents For All Months of 2018-2022") + theme_gray()
```

```{r}
list2$Week_df %>% ggplot(aes(x = Count, y = Count2, color = Count)) + geom_point(size = 3) + geom_line(color = "gray") + labs(title = "Missing Person Incidents For All Weeks of 2018-2022") + theme_gray()
```

4) Distribution for time of day?
```{r}
all_df_list$Hour_df %>% ggplot(aes(x = Hour, y = Count), color = Hour) + geom_bar(stat = "identity", color = "black", fill = "#00abff") + labs(title = "Missing Person Incidents For All Months of 2018-2022") + theme_gray()
```


```{r}
list2$Hour_df %>% ggplot(aes(x = Hour, y = Count, color = Count)) + geom_point(size = 2) + labs(title = "Missing Person Incidents For All Weeks of 2018-2022") +geom_line() + theme_gray()
```

5) How Many Were Found?

8066 people out of 9494 reports.
```{r}
all_df_list$Found_df
```
```{r}
all_df_list$Found_df %>% ggplot(aes(x = Found, y = Count, color = "#666", fill = "#000")) + geom_bar(stat = "identity", width = .3, show.legend = F)
```

6) Top 5 Neighborhoods?

```{r}
all_df_list$`Top 5`

```



```{r}
all_df_list$`Top 5` %>% ggplot(aes(x = Neighborhood, y = Count, color = "#666", fill = "#000")) + geom_bar(stat = "identity", width = .7, show.legend = F)
```

```{r}
all_df_list$Neighborhood_Count %>% ggplot(aes(x = Neighborhood, y = Count, color = Neighborhood)) + geom_bar(stat = "identity", width = .7, show.legend = T)
```