5.1 Data

5.1.1 Import

We will analyze data from a survey in which respondents were asked to rate four brands of office equipment on six dimensions. Download the data here and import them into R:

library(tidyverse)
library(readxl)

office <- read_excel("perceptual_map_office.xlsx","attributes") # don't forget to load the readxl package

5.1.2 Manipulate

office # Check out the data

The data set consists of one identifier, the brand of office equipment, and the average (across respondents) rating of each brand on six attributes: large_choice, low_prices, service_quality, product_quality, convenience, and preference_score. Let’s factorize the identifier:

office <- office %>% 
  mutate(brand = factor(brand))

5.1.3 Recap: importing & manipulating

Here’s what we’ve done so far, in one orderly sequence of piped operations (download the data here):

library(tidyverse)
library(readxl)

office <- read_excel("perceptual_map_office.xlsx","attributes") %>% # 
  mutate(brand = factor(brand))