---
title: "Crime in SF: Word Discription Analysis"
author: 'AAYUSH SETHI'
output: 
  flexdashboard::flex_dashboard:
    source_code: embed
    vertical_layout: scroll
    theme: yeti
    orientation: column

---

``` {js}
// Inverse color of navigation bar.
$('.navbar-inverse').removeClass('navbar-inverse').addClass('navbar-default');
```

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse) # metapackage with lots of helpful functions
library(caret)
library(highcharter)
library(ggmap)
library(leaflet)
library(plotly)
library(DT)
library(shiny)
library("tm")
library("SnowballC")
library("wordcloud")
library("RColorBrewer")

list.files(path = "../input")
df <- read.csv(file = "~/Desktop/sf.csv")
df2 <- Corpus(VectorSource(df$Descript))
dtm <- TermDocumentMatrix(df2)
m <- as.matrix(dtm)
v <- sort(rowSums(m),decreasing=TRUE)
d <- data.frame(word = names(v),freq=v)
```

Overview
=======================================================================

 Column {.tabset .tabset-fade data-width=700 .colored }
-----------------------------------------------------------------------

### Location
```{r, fig.height=10}
leaflet(df %>% select(latitude,PdDistrict,longitude,Resolution)) %>%
  setView(lng = -122.409981, lat = 37.809326,zoom = 10) %>%
   addTiles() %>% 
  addMarkers(
  clusterOptions = markerClusterOptions())
```

Column {data-width=300}
-----------------------------------------------------------------------

### Crime Description Word Count & Composition
```{r,fig.height=4}
head(d, 10)

```


### Crime Description Word Cloud
```{r,fig.height=4}
set.seed(1234)
wordcloud(words = d$word, freq = d$freq, min.freq = 1,
          max.words=200, random.order=FALSE, rot.per=0.35, 
          colors=brewer.pal(8, "Dark2"))

```






Drunkeness & Prostitution Hotspots
=======================================================================
```{r, fig.height=10}
library(RColorBrewer)
library(leaflet)
library(dplyr)


df.map <- function(categories, n) {

    new.df <- filter(df, Category %in% categories) %>% droplevels() 
    
    pal <- colorFactor(brewer.pal(length(unique(new.df$Category)), "Set1"),
                       domain = new.df$Category)

    leaflet(new.df[1:n,]) %>% 
        addProviderTiles("CartoDB.Positron") %>% 
        addCircleMarkers (lng =  ~longitude, lat =  ~latitude, 
                          color = ~pal(Category),
                          opacity = .7, radius  = 1) %>%  
        addLegend(pal = pal, values = new.df$Category)
}

df.map(c("SEX OFFENSES FORCIBLE", "PROSTITUTION","DRUNKENNESS"), n = 1000)
```