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Exploratory-Data-Analysis-Assingment

About this repository

This repository was created for the peer-graded assignment of:

Course 3: Exploratory Data Analysis,
from Data Science Specialization,
by Johns Hopkins University,
on coursera

The course is taught by:

  • Jeff Leek, Phd
  • Roger D. Peng, Phd
  • Brian Caffo, Phd

As putted by the teachers of the course:

The overall goal of this assignment is to explore the National Emissions Inventory database and see what it say
about fine particulate matter pollution in the United states over the 10-year period 1999–2008. You may use any R
package you want to support your analysis.

The assignment asked to:

You must address the following questions and tasks in your exploratory analysis.
For each question/task you will need to make a single plot.
Unless specified, you can use any plotting system in R to make your plot.

  1. Have total emissions from PM2.5 decreased in the United States from 1999 to 2008? Using the base plotting
    system, make a plot showing the total PM2.5 emission from all sources for each of the years 1999, 2002, 2005,
    and 2008.
  2. Have total emissions from PM2.5 decreased in the Baltimore City, Maryland (fips == "24510") from
    1999 to 2008? Use the base plotting system to make a plot answering this question.
  3. Of the four types of sources indicated by the type (point, nonpoint, onroad, nonroad) variable, which of
    these four sources have seen decreases in emissions from 1999–2008 for Baltimore City? Which have seen
    increases in emissions from 1999–2008? Use the ggplot2 plotting system to make a plot answer this question.
  4. Across the United States, how have emissions from coal combustion-related sources changed from 1999–2008?
  5. How have emissions from motor vehicle sources changed from 1999–2008 in Baltimore City?
  6. Compare emissions from motor vehicle sources in Baltimore City with emissions from motor vehicle sources in
    Los Angeles County, California (fips == "06037"). Which city has seen greater changes over time in motor
    vehicle emissions?

For each plot you should:

  1. Construct the plot and save it to a PNG file.
  2. Create a separate R code file (plot1.R, plot2.R, etc.) that constructs the corresponding plot,
    i.e. code in plot1.R constructs the plot1.png plot.
    Your code file should include code for reading the data so that the plot can be fully reproduced.
    You must also include the code that creates the PNG file.
    Only include the code for a single plot (i.e. plot1.R should only include code for producing plot1.png)
  3. Upload the PNG file on the Assignment submission page.
  4. Copy and paste the R code from the corresponding R file into the text box at the appropriate point in the
    peer assessment.