Plot1.R

getwd()

## [1] "E:/Coursera/ProjectCourse2"

library(plyr)
# Reading Data
NEI <- readRDS("summarySCC_PM25.rds")
# General Check NEI
dim(NEI)

## [1] 6497651       6

head(NEI)

##     fips      SCC Pollutant Emissions  type year
## 4  09001 10100401  PM25-PRI    15.714 POINT 1999
## 8  09001 10100404  PM25-PRI   234.178 POINT 1999
## 12 09001 10100501  PM25-PRI     0.128 POINT 1999
## 16 09001 10200401  PM25-PRI     2.036 POINT 1999
## 20 09001 10200504  PM25-PRI     0.388 POINT 1999
## 24 09001 10200602  PM25-PRI     1.490 POINT 1999

sum(is.na(NEI))

## [1] 0

str(NEI)

## 'data.frame':    6497651 obs. of  6 variables:
##  $ fips     : chr  "09001" "09001" "09001" "09001" ...
##  $ SCC      : chr  "10100401" "10100404" "10100501" "10200401" ...
##  $ Pollutant: chr  "PM25-PRI" "PM25-PRI" "PM25-PRI" "PM25-PRI" ...
##  $ Emissions: num  15.714 234.178 0.128 2.036 0.388 ...
##  $ type     : chr  "POINT" "POINT" "POINT" "POINT" ...
##  $ year     : int  1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 ...

# Question 01
# Have total emissions from PM2.5 decreased in the United States from 1999 to 2008? 

total_EY <- aggregate(Emissions ~ year, NEI, sum) 
dim(total_EY) 

## [1] 4 2

print(total_EY)

##   year Emissions
## 1 1999   7332967
## 2 2002   5635780
## 3 2005   5454703
## 4 2008   3464206

barplot((total_EY$Emissions)*10^(-6),
        names.arg = total_EY$year,
        xlab = "Year",
        ylab = "Total PM2.5 Emission (10^6)",
        main="Total PM2.5 Emissions From All United States",
        border = "blue")

# Answer 01
# The chart show us that pollution in 2008 is less than in 1999, and so the answer is, yes.
# There is a decrease from 1999 to 2008. The air have less pollution PM2.5 in 2008.