plot2.R

#Hi! To make the data manipulation process easier I use some packages from the famous tidyverse. Specifically,
#I use lubridate, dplyr, stringr, and another package called "hms" to convert the second column to a time format.
#If you want to install these packages, you're going to need to run "install.packages("tidyverse")",
#"install.packages("lubridate")", "install.packages("stringr")", and "install.packages("hms")".


#Part 1 - Load the packages:

library(tidyverse)
library(lubridate)
library(hms)

#Part 2 - Read the Individual household electric power consumption Data Set.

#For that purpose, I preestablish each column with its atomic vector type, except for the first and second columns,
#which I will handle in just a moment:

household <- read.csv(
  "household_power_consumption.txt",
  sep = ";",
  colClasses = c("character", "character", "numeric", "numeric", "numeric", "numeric", "numeric", "numeric", "numeric"),
  na.strings = "?"
  )

#Part 3 - Convert the 1st and 2nd columns to appropriate types.

#Here I use dmy from the "lubridate" package to convert the first column to a data class, and then as_hms from the 
#"hms" package to convert the second column to a time format:

household$Date <- dmy(household$Date)
household$Time <- as_hms(household$Time)

#Part 4 - Filtering those observations corresponding to 2017-02-01 and 2017-02-02.

#For that purpose, I use dplyr and its function "filter" alongside lubridate::year, lubridate::month, and lubridate::day:

household <- household %>% 
  dplyr::filter(year(Date) == 2007, month(Date) == 2, day(Date) %in% c(1,2))

#Part 5 - New column "Date_time" to create our second plot.

#In order to have the plot we want, it is necessary to create a column in "datetime" format. For that, I use
#"mutate" from dplyr to create this new column, "ymd_hms" from lubridate, and "str_c" from stringr:

Sys.setlocale("LC_TIME", "English")

household <- household %>% 
  dplyr::mutate(Date_time = ymd_hms(str_c(Date, " ", Time)))

#Part 6 - The Second Plot of this assignment with what we have learned so far.

#Here I tweak the code to output the plot in a PNG file as the graphics device instead of the screen device:

png("plot2.png", width = 480, height = 480)

with(household, plot(
  Date_time,
  Global_active_power,
  type = "l",
  xlab = "",
  ylab = "Global Active Power (kilowatts)"
  )
)

dev.off()