plot2.R

library(dplyr)

# Reading the data into R and selecting given dates
energy_data <- read.table("household_power_consumption.txt", sep = ";",na.strings = "?")
colnames(energy_data) <- energy_data[1,]
energy_data <- energy_data[-1, ] 
energy_tib <- as_tibble(energy_data)
energy_data_sel <- subset(energy_data, energy_data$Date == "1/2/2007"| energy_tib$Date == "2/2/2007")
energy_data_sel <- energy_data_sel %>% mutate_at(c('Global_active_power', 'Global_reactive_power',
                                                   'Voltage', 'Global_intensity', 'Sub_metering_1', 'Sub_metering_2', 'Sub_metering_3'), as.numeric)

# Converting single-digit day and month to two-digit format and then converting from character
# to date format
convert_to_two_digits <- function(dates) {
        parts <- strsplit(dates, "/")
        dates <- sapply(parts, function(x) {
                x[1] <- sprintf("%02d", as.numeric(x[1])) # Convert day to two digits
                x[2] <- sprintf("%02d", as.numeric(x[2])) # Convert month to two digits
                paste(x, collapse = "/")
        })
        return(dates)
}
energy_data_sel <- energy_data_sel %>% mutate(Date, date = convert_to_two_digits(Date))
energy_data_sel <- energy_data_sel %>% mutate(datetime = paste(date, Time))
energy_data_sel <- energy_data_sel %>% mutate(datetime, date2 = datetime <- as.POSIXct(datetime, format = "%d/%m/%Y %H:%M:%S"))


# Creating and saving graph
png('plot2.png', width = 480, height = 480)
plot(x=energy_data_sel$date2, y=energy_data_sel$Global_active_power, type = "S", 
     xlab = "", ylab = "Global active power (kilowatts)")
dev.off()