From f3a1ac4cce6ace1e8fd6764fedac0688f5c3ee07 Mon Sep 17 00:00:00 2001
From: emilybcarr <emilybrookereynolds@gmail.com>
Date: Sun, 10 Jan 2016 16:23:24 -0500
Subject: [PATCH] 4 Plots (png) with the R Code to Create Those Plots

---
 plot1.R   |  46 +++++++++++++++++++++++++++++++++
 plot1.png | Bin 0 -> 3734 bytes
 plot2.R   |  47 +++++++++++++++++++++++++++++++++
 plot2.png | Bin 0 -> 4504 bytes
 plot3.R   |  62 ++++++++++++++++++++++++++++++++++++++++++++
 plot3.png | Bin 0 -> 3957 bytes
 plot4.R   |  76 ++++++++++++++++++++++++++++++++++++++++++++++++++++++
 plot4.png | Bin 0 -> 7428 bytes
 8 files changed, 231 insertions(+)
 create mode 100644 plot1.R
 create mode 100644 plot1.png
 create mode 100644 plot2.R
 create mode 100644 plot2.png
 create mode 100644 plot3.R
 create mode 100644 plot3.png
 create mode 100644 plot4.R
 create mode 100644 plot4.png

diff --git a/plot1.R b/plot1.R
new file mode 100644
index 00000000000..6a0725282e8
--- /dev/null
+++ b/plot1.R
@@ -0,0 +1,46 @@
+# What's my available memory?
+    system('systeminfo')
+    #...Available Physical Memory: 345 MB
+
+# How much memory does the file require?
+    object.size(url)
+    #184 bytes = 0.000184 MB
+    #plenty of room
+
+# Read in the data (assuming working directory is set)
+    url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
+    #download.file(url, "household_power_consumption.txt")
+        #^ this does not work because the file is zipped
+        #found help here: http://stackoverflow.com/questions/3053833/using-r-to-download-zipped-data-file-extract-and-import-data
+    temp <- tempfile()
+    download.file(url,temp)
+    mydata <- read.table(unz(temp, "household_power_consumption.txt"), header = TRUE, sep = ";", col.names = c("Date", "Time", "Global_active_power", "Global_reactive_power", "Voltage", "Global_intensity", "Sub_metering_1", "Sub_metering_2", "Sub_metering_3"))
+    mydata_mod <- mydata #create a second df for manipulation
+    
+#Fix the class of the Date and Time variables
+    #Date
+        mydata_mod$Date <- as.Date(as.character(mydata_mod$Date), format = "%d/%m/%Y")
+        class(mydata_mod$Date)
+        #[1] "Date"
+    #Time - Attempt 1
+        #mydata_mod$Time <- strptime(as.character(mydata_mod$Time), format = "%H:%M:%S")
+            #^this adds an unwanted (and incorrect) date portion
+        #mydata_mod$Time <- strftime(mydata_mod$Time, format = "%T")
+            #^this removes the unwanted (and incorrect) date portion, but turns the class back to character
+    #Time - Attempt 2
+        library(chron)
+        mydata_mod$Time <- times(mydata_mod$Time)
+        class(mydata_mod$Time)
+        #[1] "times"
+    
+# Subset the data to the only 2 dates we're interested in
+    mydata_subset <- mydata_mod[mydata_mod$Date == "2007-02-01"|mydata_mod$Date == "2007-02-02",]
+
+# Plot the data
+    mydata_subset$Global_active_power <- as.numeric(as.character(mydata_subset$Global_active_power))
+        #^initially got an error because the variable was a factor
+    png("plot1.png")
+    hist(mydata_subset$Global_active_power, col = "red", main = "Global Active Power", xlab = "Global Active Power (kilowatts)")
+    dev.off()
+
+    
\ No newline at end of file
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diff --git a/plot2.R b/plot2.R
new file mode 100644
index 00000000000..9680eb3bd18
--- /dev/null
+++ b/plot2.R
@@ -0,0 +1,47 @@
+# What's my available memory?
+    system('systeminfo')
+    #...Available Physical Memory: 345 MB
+
+# How much memory does the file require?
+    object.size(url)
+    #184 bytes = 0.000184 MB
+    #plenty of room
+
+# Read in the data (assuming working directory is set)
+    url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
+    #download.file(url, "household_power_consumption.txt")
+        #^ this does not work because the file is zipped
+        #found help here: http://stackoverflow.com/questions/3053833/using-r-to-download-zipped-data-file-extract-and-import-data
+    temp <- tempfile()
+    download.file(url,temp)
+    mydata <- read.table(unz(temp, "household_power_consumption.txt"), header = TRUE, sep = ";", col.names = c("Date", "Time", "Global_active_power", "Global_reactive_power", "Voltage", "Global_intensity", "Sub_metering_1", "Sub_metering_2", "Sub_metering_3"))
+    mydata_mod <- mydata #create a second df for manipulation
+
+#Fix the class of the Date and Time variables
+    #Date
+        mydata_mod$Date <- as.Date(as.character(mydata_mod$Date), format = "%d/%m/%Y")
+        class(mydata_mod$Date)
+        #[1] "Date"
+    #Time - Attempt 1
+        #mydata_mod$Time <- strptime(as.character(mydata_mod$Time), format = "%H:%M:%S")
+        #^this adds an unwanted (and incorrect) date portion
+        #mydata_mod$Time <- strftime(mydata_mod$Time, format = "%T")
+        #^this removes the unwanted (and incorrect) date portion, but turns the class back to character
+    #Time - Attempt 2
+        library(chron)
+        mydata_mod$Time <- times(mydata_mod$Time)
+        class(mydata_mod$Time)
+        #[1] "times"
+
+# Subset the data to the only 2 dates we're interested in
+    mydata_subset <- mydata_mod[mydata_mod$Date == "2007-02-01"|mydata_mod$Date == "2007-02-02",]
+
+# Plot the data
+    #First have to "merge" the Time column data into the Date column, for one date/time variable
+        mydata_subset2 <- mydata_subset
+        mydata_subset2$Date <- strptime(paste(as.character(mydata_subset$Date), as.character(mydata_subset$Time)), format = "%Y-%m-%d %H:%M:%S")
+    #Then plot
+        png("plot2.png")
+        plot(mydata_subset2$Date, mydata_subset2$Global_active_power, type = "l", xlab = "", ylab = "Global Active Power (kilowatts)")
+        dev.off()
+    
\ No newline at end of file
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diff --git a/plot3.R b/plot3.R
new file mode 100644
index 00000000000..f3e658fda37
--- /dev/null
+++ b/plot3.R
@@ -0,0 +1,62 @@
+# What's my available memory?
+    system('systeminfo')
+    #...Available Physical Memory: 345 MB
+
+# How much memory does the file require?
+    object.size(url)
+    #184 bytes = 0.000184 MB
+    #plenty of room
+
+# Read in the data (assuming working directory is set)
+    url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
+    #download.file(url, "household_power_consumption.txt")
+        #^ this does not work because the file is zipped
+        #found help here: http://stackoverflow.com/questions/3053833/using-r-to-download-zipped-data-file-extract-and-import-data
+    temp <- tempfile()
+    download.file(url,temp)
+    mydata <- read.table(unz(temp, "household_power_consumption.txt"), header = TRUE, sep = ";", col.names = c("Date", "Time", "Global_active_power", "Global_reactive_power", "Voltage", "Global_intensity", "Sub_metering_1", "Sub_metering_2", "Sub_metering_3"))
+    mydata_mod <- mydata #create a second df for manipulation
+
+#Fix the class of the Date and Time variables
+    #Date
+        mydata_mod$Date <- as.Date(as.character(mydata_mod$Date), format = "%d/%m/%Y")
+        class(mydata_mod$Date)
+        #[1] "Date"
+    #Time - Attempt 1
+        #mydata_mod$Time <- strptime(as.character(mydata_mod$Time), format = "%H:%M:%S")
+        #^this adds an unwanted (and incorrect) date portion
+        #mydata_mod$Time <- strftime(mydata_mod$Time, format = "%T")
+        #^this removes the unwanted (and incorrect) date portion, but turns the class back to character
+    #Time - Attempt 2
+        library(chron)
+        mydata_mod$Time <- times(mydata_mod$Time)
+        class(mydata_mod$Time)
+        #[1] "times"
+
+# Subset the data to the only 2 dates we're interested in
+    mydata_subset <- mydata_mod[mydata_mod$Date == "2007-02-01"|mydata_mod$Date == "2007-02-02",]
+
+# Plot the data
+    #First have to "merge" the Time column data into the Date column, for one date/time variable
+        mydata_subset2 <- mydata_subset
+        mydata_subset2$Date <- strptime(paste(as.character(mydata_subset$Date), as.character(mydata_subset$Time)), format = "%Y-%m-%d %H:%M:%S")
+    #Then have to get factor variables into numeric form
+        mydata_subset2$Sub_metering_1 <- as.numeric(as.character(mydata_subset2$Sub_metering_1))
+        mydata_subset2$Sub_metering_2 <- as.numeric(as.character(mydata_subset2$Sub_metering_2))
+        #mydata_subset2$Sub_metering_3 is already numeric
+    
+    #Then plot
+        png("plot3.png")
+        
+        plot(mydata_subset2$Date, mydata_subset2$Sub_metering_1, type = "l", xlab = "", ylab = "Energy sub metering", ylim = c(-1,39), yaxt = "n")
+            #found ylim max and min by manually checking max and min of each y data set
+        axis(side = 2, at = c(0,10,20,30))
+        lines(mydata_subset2$Date, mydata_subset2$Sub_metering_2, col = "red")
+        lines(mydata_subset2$Date, mydata_subset2$Sub_metering_3, col = "blue")
+        legend("topright", legend = c("Sub_metering_1", "Sub_metering_2", "Sub_metering_3"), col = c("black", "red", "blue"), lty = 1)
+        
+        dev.off()
+    
+    
+    
+    
\ No newline at end of file
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diff --git a/plot4.R b/plot4.R
new file mode 100644
index 00000000000..fd1ff8776bf
--- /dev/null
+++ b/plot4.R
@@ -0,0 +1,76 @@
+# What's my available memory?
+    system('systeminfo')
+    #...Available Physical Memory: 345 MB
+
+# How much memory does the file require?
+    object.size(url)
+    #184 bytes = 0.000184 MB
+    #plenty of room
+
+# Read in the data (assuming working directory is set)
+    url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
+    #download.file(url, "household_power_consumption.txt")
+        #^ this does not work because the file is zipped
+        #found help here: http://stackoverflow.com/questions/3053833/using-r-to-download-zipped-data-file-extract-and-import-data
+    temp <- tempfile()
+    download.file(url,temp)
+    mydata <- read.table(unz(temp, "household_power_consumption.txt"), header = TRUE, sep = ";", col.names = c("Date", "Time", "Global_active_power", "Global_reactive_power", "Voltage", "Global_intensity", "Sub_metering_1", "Sub_metering_2", "Sub_metering_3"))
+    mydata_mod <- mydata #create a second df for manipulation
+
+#Fix the class of the Date and Time variables
+    #Date
+        mydata_mod$Date <- as.Date(as.character(mydata_mod$Date), format = "%d/%m/%Y")
+        class(mydata_mod$Date)
+        #[1] "Date"
+    #Time - Attempt 1
+        #mydata_mod$Time <- strptime(as.character(mydata_mod$Time), format = "%H:%M:%S")
+        #^this adds an unwanted (and incorrect) date portion
+        #mydata_mod$Time <- strftime(mydata_mod$Time, format = "%T")
+        #^this removes the unwanted (and incorrect) date portion, but turns the class back to character
+    #Time - Attempt 2
+        library(chron)
+        mydata_mod$Time <- times(mydata_mod$Time)
+        class(mydata_mod$Time)
+        #[1] "times"
+
+# Subset the data to the only 2 dates we're interested in
+    mydata_subset <- mydata_mod[mydata_mod$Date == "2007-02-01"|mydata_mod$Date == "2007-02-02",]
+
+# Plot the data
+    #First have to "merge" the Time column data into the Date column, for one date/time variable
+        mydata_subset2 <- mydata_subset
+        mydata_subset2$Date <- strptime(paste(as.character(mydata_subset$Date), as.character(mydata_subset$Time)), format = "%Y-%m-%d %H:%M:%S")
+    #Then have to get factor variables into numeric form
+        mydata_subset2$Sub_metering_1 <- as.numeric(as.character(mydata_subset2$Sub_metering_1))
+        mydata_subset2$Sub_metering_2 <- as.numeric(as.character(mydata_subset2$Sub_metering_2))
+        #mydata_subset2$Sub_metering_3 is already numeric
+        mydata_subset2$Global_reactive_power <- as.numeric(as.character(mydata_subset2$Global_reactive_power))
+        mydata_subset2$Voltage <- as.numeric(as.character(mydata_subset2$Voltage))
+        
+    #Then plot
+        png("plot4.png")
+        
+        par(mfrow = c(2, 2), mar = c(5, 4, 2, 1))
+        
+        #Plot 4a (=Plot2)
+            plot(mydata_subset2$Date, mydata_subset2$Global_active_power, type = "l", xlab = "", ylab = "Global Active Power")
+
+        #Plot 4b (new)
+            plot(mydata_subset2$Date, mydata_subset2$Voltage, type = "l", xlab = "datetime", ylab = "Voltage")
+            
+        #Plot 4c (=Plot3)    
+            plot(mydata_subset2$Date, mydata_subset2$Sub_metering_1, type = "l", xlab = "", ylab = "Energy sub metering", ylim = c(-1,39), yaxt = "n")
+                #found ylim max and min by manually checking max and min of each y data set
+            axis(side = 2, at = c(0,10,20,30))
+            lines(mydata_subset2$Date, mydata_subset2$Sub_metering_2, col = "red")
+            lines(mydata_subset2$Date, mydata_subset2$Sub_metering_3, col = "blue")
+            legend("topright", legend = c("Sub_metering_1", "Sub_metering_2", "Sub_metering_3"), col = c("black", "red", "blue"), lty = 1, cex = 0.7)
+        
+        #Plot 4d (new)
+            plot(mydata_subset2$Date, mydata_subset2$Global_reactive_power, type = "l", xlab = "", ylab = "Global_reactive_power")
+            #^had to change class to numeric from factor to get y-axis units to match example
+        
+        dev.off()
+
+
+
diff --git a/plot4.png b/plot4.png
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