Baltimore Emissions 3D plot using Plotly

NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")

library(plyr)
library(ggplot2)
library(plotly)

## 
## Attaching package: 'plotly'

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

## The following objects are masked from 'package:plyr':
## 
##     arrange, mutate, rename, summarise

## The following object is masked from 'package:stats':
## 
##     filter

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

Including Plots

# Subset data and plot
baltimoreNEI <- subset(NEI, NEI$fips == "24510")
plot_data <- ddply(baltimoreNEI, .(year, type), numcolwise(sum))
head(plot_data)

##   year     type Emissions
## 1 1999 NON-ROAD  522.9400
## 2 1999 NONPOINT 2107.6250
## 3 1999  ON-ROAD  346.8200
## 4 1999    POINT  296.7950
## 5 2002 NON-ROAD  240.8469
## 6 2002 NONPOINT 1509.5000

plot_ly(plot_data,  x = ~year, y = ~Emissions,  z = ~type) %>%
  add_markers(color = ~type)