Webinar-2

Execute the following cell to load the tidyverse library:

library(tidyverse)

Execute the following cell to load the data. Refer to this website http://openmv.net/info/food-texture for data description:

file = 'http://openmv.net/file/food-texture.csv'
foodData = read.csv(file, header = TRUE, row.names = 1)

Print structure of dataframe

str(foodData)

Print first 5 samples of data frame

head(foodData, n = 5)

Modify the data frame

# Rename Oil column to OilPercentage
foodData = foodData %>% rename(OilPercentage = Oil)

# Modify crispy column to reflect high (0) and low (1) crispness
foodData = foodData %>% mutate(Crispy = ifelse(Crispy > 11, 'high', 'low'))

# Change Crispy column to factor type
foodData['Crispy'] = lapply(foodData['Crispy'], factor)

Print structure of modified data frame

str(foodData)

Make a scatter plot between Density (x-axis) and OilPercentage (y-axis). What do you observe from this plot?

p1 = ggplot(data = foodData , aes(x = Density, y = OilPercentage)) +
  geom_point(size = 2) 
p1