title	author	date	output
Exploratory Graphing Project 2	Yilmaz Rona	September 20, 2015	html_document

Introduction

This is the submission for Project 2 of Exploratory Data Analysis.

It contains all the code needed to generate the plots from the source data, Project dataset from EPA National Emissions database [29Mb].

Preparation

Libraries Required

• downloader
• ggplot2

library(downloader)
library(ggplot2)

Files to source

• download_data.R
  • environment.NEI.data: Sets environmental variables used to specify file names and locations. Should be modified as needed to point this software to the appropriate locations on the user's system.
  • download.NEI.data: Downloads the dataset from the EPA National Emissions database (only needs to be run once).
  • load.NEI.data: Generic function to load one of the RDS files into memory. Called by other functions.
  • NEI.PM25.data: Loads the PM2.5 data frame from disk and returns it. Called by plotting functions
  • NEI.ClassCodes: Loads the Classification Codes data frame from disk and returns it. Called by plotting functions
• Plot1.R
  • make.NEI.plot1: Reads the PM2.5 data and produces a plot of total US Emissions by year.
• Plot2.R
  • make.NEI.plot2: Reads the PM2.5 data and produces a plot of total Emissions by year within Baltimore, MD.
• Plot3.R
  • make.NEI.plot3: Reads the PM2.5 data and produces a plot of total Emissions by year within Baltimore, MD broken down by type.
• Plot4.R
  • make.NEI.plot4: Reads the PM2.5 data and SCC data and produces a plot of total Emissions from coal use by year within the US broken down by Type (ie Source).
• Plot5.R
  • make.NEI.plot5: Reads the PM2.5 data and SCC data and produces a plot of total Emissions from different types of motor vehicles by year within Baltimore city broken down by EI Sector.
• Plot6.R
  • make.NEI.plot6: Reads the PM2.5 data and SCC data and produces a plots of total Emissions from different types of motor vehicles by year broken down by EI Sector comparing Baltimore City with LA County.

Execution

1. Modify the function Environment.NEI.data in download_data.R as needed to run the code on your system.
2. Source the files.
3. Execute download.NEI.data
4. Execute desired plot functions.

Plots will be saved to working directory.