Month: December 2016
In this post, I am using SuperStore data to explore some of the data wrangling functions from these two packages.
The data is in the form of an Excel workbook with three sheets namely – Orders, Returns, and Region. I am loading the three different sheets into separate datasets into R, joining them and performing necessary aggregations.
setwd("C:/R") #For accessing and dumping excel files install.packages("openxlsx") library(openxlsx) #Used for data wrangling install.packages("dplyr") library(dplyr) #Used for data wrangling install.packages("tidyr") library(tidyr) #Load three individuals sheets into separate datasets superstore.wb
# Sum of Sales by Product Category data.storeOrders%>% group_by(Product.Category) %>% summarise(Total.Sales = sum(Sales)) %>% arrange(Total.Sales)
#Join data sets and aggregate as per requirement # Inner join the two data sets Order and Users by Region and look at Total Sales by Region data.final % group_by(Region) %>% summarise(Total.Sales = sum(Sales)) data.final