Instructions:

Analysis (Opinion) 1. The restaurants are displayed in the order they are because data frame is ordered by the frequency. 2. The addition of the percentage column to the table allows the reader to see percentage of customers for each restaurant vs overall restaurant. ————————————————————————

Test out all the libraries we need for the course.

library(readr)
data <- read_csv("/Users/mex/2023 Session/data.2.csv")
length(data$id)
## [1] 1282
library(dplyr)
data %>%
  group_by(restaurant) %>%
  summarise(count = n()) %>%
  mutate(Percentage = count/sum(count) * 100) %>%
  arrange(desc(count))
## # A tibble: 4 × 3
##   restaurant  count Percentage
##   <chr>       <int>      <dbl>
## 1 KFC           335       26.1
## 2 McDonald      320       25.0
## 3 Burger King   319       24.9
## 4 Taco Bell     308       24.0
mydata1 <- matrix(c(3.0585,3.017, 3.100,3.0505,    2.982,  3.119,2.9640,   2.979,  2.949,2.8670,   2.913,  2.821),ncol=3,byrow=TRUE)
 colnames(mydata1) <- c("Overall","Male","Female")
 rownames(mydata1) <- c("McDonald","KFC","Taco Bell","Burger King")
mydata1 <- as.table(mydata1)
mydata1
##             Overall   Male Female
## McDonald     3.0585 3.0170 3.1000
## KFC          3.0505 2.9820 3.1190
## Taco Bell    2.9640 2.9790 2.9490
## Burger King  2.8670 2.9130 2.8210