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library(readr)
conventional <- read_csv('conventional.csv')
## Rows: 6314 Columns: 7
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): date, type, geography
## dbl (4): average_price, total_volume, year, Mileage
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
plot(total_volume ~ average_price, data = conventional)

library(ggplot2)
ggplot(data = conventional, aes(x = average_price)) +
  geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

library(readr)
organic <- read_csv('organic1.csv')
## Rows: 6314 Columns: 7
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): date, type, geography
## dbl (4): average_price, total_volume, year, Mileage
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
plot(total_volume ~ average_price, data = organic)

library(ggplot2)
ggplot(data = organic, aes(x = average_price)) +
  geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.