Read and filter Crime data

library(tidyr)

## Warning: package 'tidyr' was built under R version 3.2.4

population<-read.csv("https://raw.githubusercontent.com/RobertSellers/crime_and_weather_study/master/data/Export/crimeANDweather_v1.csv", sep=",",na.strings = "NA",header = TRUE,stringsAsFactors = FALSE)




head(population,3)

##   X    city state year      lat      long airportID meanMaxF crimeRate
## 1 1 Abilene    TX 1985 32.44874 -99.73314       ABI 42.36712       355
## 2 2 Abilene    TX 1986 32.44874 -99.73314       ABI 44.86849       859
## 3 3 Abilene    TX 1987 32.44874 -99.73314       ABI 44.67397       890

library(plotly)

## Warning: package 'plotly' was built under R version 3.2.4

## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 3.2.4

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:graphics':
## 
##     layout

population<- subset(population,population$city=='Akron City' & population$year >2005)
plot_ly(population, x = year, y = crimeRate, size = crimeRate,color = meanMaxF,opacity = meanMaxF, mode = "markers")

#tidy<-subset(tidy,tidy$city=='New' & tidy$State=='NY')

library(plotly)
plot_ly(tidy, x = Year, y = city, size = crimeRate,color = temp,opacity = size, mode = "markers")

library(plotly)
p <- plot_ly(
  x = tidy$Year,
  y = tidy$temp,
  name = "SF Zoo",
  type = "bar",
  color= tidy$Count
)
p