gistfile1.txt

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# Data Analytics Assignment A5: R Script for 6/14 A,B,C,D #
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########## Script Written by Vivek Narang 4/4/17 ##########
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# Importing relevant libraries #
library(reshape)
library(tidyr)
library(readr)
library(dplyr)
library(measurements)

# Reference to the Input file for the tasks #
file <- "C:\\A5InputFile.csv"

# Reading the referenced file for tasks #   
dataBlockReference <- read_delim( file, col_names = T, delim =',')

# Gathering and reshaping the table showing Year and Area Harvested on the table #
reshapedTable<- gather(dataBlockReference, 'Year','Area Harvested', 2:8)
# Printing the reshaped table #
reshapedTable

# Checking if the result file exists for task A. If exists skipping the write operation (Error Handling)# 
if(!file.exists("A5Output_A.csv")){
  # If the result file does not exit, write a new result file for task A #
  write.csv(reshapedTable, "A5Output_A.csv")
}

# Adding Hectares Column for task B. Computing the Hectares for each based on acres data #
reshapedTable$Hectares <- round(conv_unit(reshapedTable$`Area Harvested`, "acre" ,"hectare"), 2);

# Printing the modified table on console #
reshapedTable

# Checking if the result file exists for task B. If exists skipping the write operation (Error Handling)# 
if(!file.exists("A5Output_B.csv")){
  # If the result file does not exit, write a new result file for task B #
  write.csv(reshapedTable, "A5Output_B.csv")
}

# Grouping years for computing sum of hectares for each #
sumHectares <- reshapedTable %>% group_by(Year) %>% summarise(Hectares = sum(Hectares)) 
# Printing the data table on console #
sumHectares

# Checking if the result file exists for task C. If exists skipping the write operation (Error Handling)# 
if(!file.exists("A5Output_C.csv")){
  # If the result file does not exit, write a new result file for task B #
  write.csv(sumHectares, "A5Output_C.csv")
}