How to plot volume sold by day

I used the following code to upload my data on R

if (!file.exists("ames-liquor.rds")) {
  url <- "https://github.com/ds202-at-ISU/materials/blob/master/03_tidyverse/data/ames-liquor.rds?raw=TRUE"
  download.file(url, "ames-liquor.rds", mode="wb")
}
data <- readRDS("ames-liquor.rds")

then used this code to extract geographic latitude and longitude

data <- data %>% 
  separate(remove= FALSE,
           col = 'Store Location' , sep=" ",
           into=c("toss-it", "Latitude", "Longitude"))
data <- data %>% mutate(
  Latitude = parse_number(Latitude),
  Longitude = parse_number(Longitude)
)

after that I used this code to plot a scatterplot of lat and long of store locations and provide a visual breakdown of the liquor category (by Category Name ). Include volume sold in the breakdown.

library(tidyverse)
library(janitor)
set.seed(123)
sample <- sample_n(data, size = 12000, replace = F)

new_data <- sample|>clean_names()

final_data <- new_data|>
  separate(col = store_location,
           into = c("x", "latitude", "longitude"), 
           sep = " ")|>
  select(category_name, latitude, longitude, volume_sold_liters)|>
  na.omit()

final_data$longitude = str_sub(final_data$longitude, end = -2)
final_data$latitude = str_sub(final_data$latitude, start = 2)

final_data$longitude = as.numeric(final_data$longitude)
final_data$latitude = as.numeric(final_data$latitude)
final_data$category_name = as_factor(final_data$category_name)

ggplot(final_data, aes(x = latitude, y = longitude)) +
  geom_point() +
  theme_bw() +
  xlab("LATITUDE (degrees)") +
  ylab("LONGITUDE (degrees)")

top_ten <- final_data|>
  group_by(category_name)|>
  summarise(total_volume = sum(volume_sold_liters))|>
  filter(total_volume > 2600)

Now I am really confused on how to
*Find the daily liquor sales in Ames in 2021: summarize number of sales, volume of liquor sold and amount of money spent.
and *Plot volume sold by day (use a scatterplot of volume by day and facet by month). .

Please help me figure it out