gardenR

The gardenR package contains data collected by Lisa Lendway from her vegetable garden, starting in the summer of 2020. Data from the summer of 2021 was added 2022-01-29 (finally!). The data were used in her Introduction to Data Science course at Macalester College to introduce many concepts. For examples, see the tutorials for the course.

If you’d like a visual tour of the garden, check out this YouTube video.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("llendway/gardenR")

Datasets

garden_coords: This dataset gives coordinates for the vertices of the plots in the garden.

2020 (first year I collected data)

garden_harvest: Each row is a “harvest” of a particular vegetable variety. So, each time she harvested a particular vegetable/variety combination, she weighed the entire harvest. There could be multiple harvests of a vegetable/variety combination in a single day. There are two exceptions: all pumpkin and winter squash (vegetable = “squash”) were weighed individually.

garden_spending: summarizes how much was spent on gardening materials.

garden_planting: The rows represent the planting of a vegetable variety. There could be multiple rows for the same vegetable variety, if they were planted on the same day in different plots or on different days.

2021

harvest_2021: Similar to garden_harvest but for 2021.

spending_2021: Similar to garden_spending but for 2021.

planting_2021: Similar to garden_planting but for 2021.

Example

Here is a representation of the plots in the garden - like a bird’s eye view of the garden.

library(gardenR)
library(tidyverse)

for_labs <- garden_coords %>% 
  group_by(plot) %>% 
  summarize(x = mean(x),
            y = mean(y))

garden_coords %>% 
  ggplot(aes(x = x, y = y, group = plot)) +
  geom_polygon() +
  geom_text(data = for_labs, 
            aes(x = x, y = y, label = plot), 
            color = "hotpink",
            size = 5) +
  theme_void() +
  theme(panel.background = element_rect(fill = "lightgray"))

Here is one example plot, using the garden_harvest data.

garden_harvest %>% 
  filter(vegetable == "tomatoes") %>% 
  group_by(date) %>% 
  summarize(daily_wt_g = sum(weight)) %>% 
  ggplot(aes(x = date, y = daily_wt_g)) +
  geom_point(color = "darkred") +
  geom_line(color = "darkred") +
  labs(title = "2020 daily tomato harvest (g)",
       x = "",
       y = "") +
  theme_minimal()