Blog Post 4

Visualizing Sales of Eggs

For this analysis I’m chosing dataset poultry_tidy.csv from our classroom. I begin by loading in the dataset using the read_csv() function in the tidyverse.

library(knitr)
library(tidyverse)
data <- read_csv("/Users/shrutishelke1999/Downloads/poultry_tidy - poultry_tidy.csv")
head(data)

# A tibble: 6 × 4
  Product  Year Month    Price_Dollar
  <chr>   <dbl> <chr>           <dbl>
1 Whole    2013 January          2.38
2 Whole    2013 February         2.38
3 Whole    2013 March            2.38
4 Whole    2013 April            2.38
5 Whole    2013 May              2.38
6 Whole    2013 June             2.38

The dataset includes four columns- Product for the kind of eggs, the year and month in which they are sold and the prices in dollars. Let’s begin by looking at the year in which the most sale of eggs happened.

production_max <- data %>% 
arrange(desc(Price_Dollar))

library(ggthemes)
ggplot(production_max, aes(Year,Price_Dollar)) +
geom_col() +
  labs(x = "Year of Production", y = "Price of eggs in Dollars", title = "Selling of Eggs by Year")+ 
  theme_minimal()

In the plot above, we see that the highest sale of eggs happened in the year 2012. To build a step further, let’s group our plot by the kinds of eggs that were sold during the years.

ggplot(production_max, aes(Year,Price_Dollar, color = Product)) +
geom_col() +
  labs(x = "Year of Production", y = "Price of eggs in Dollars", title = "Selling of Eggs by Year")+ 
  theme_minimal()