Stardew Valley Data Acquisition

Author

Ziling Zhen & Rain Hartos

Published

October 27, 2024

Introduction

For our project, we decided to scrape data from the wiki pages of one of our favorite video games, Stardew Valley. Stardew Valley is a popular indie farming game that allows players to take on the role of a character who inherits a run-down farm from their grandfather. In the game, players can grow crops, raise animals, fish, mine, and engage in social activities with the towns people.

For our project, we were interested in compiling a list of items from the game that can be farmed or collected. The only way to make money from the game is by selling these items, and the price of the item depends on the quality of the item and the profession(s) of the player. Thus, our dataset includes information on the name, category, subcategory, and the different price points of the item depending on item quality (regular, silver, gold, and iridium) and player’s profession.

To view the qmd, click here.

Approach

All of our data has been accumulated from the Stardew Valley Wiki page. Since each item in the game has a different page and not all of the pages followed a similar structure, we used a combination of harvesting the data in both table form and anywhere on the webpage using rvest with html_text. In the end, we were able to create a dataset from the more important item categories: crops, fish, animal products, and minerals.

Crops

Crops was the most difficult item to scrape from the wiki, since not all of the pages are structured the same. However, we tried our best to automate where we could.

We start be getting a list of all the different crops in the game.

Code

#check that we are allowed to scrape the wiki
robotstxt::paths_allowed("https://stardewvalleywiki.com/Stardew_Valley_Wiki")


 stardewvalleywiki.com

[1] TRUE

Code

session <- bow("https://stardewvalleywiki.com/Stardew_Valley_Wiki", force = TRUE)

# scrape crops page
crops <- bow("https://stardewvalleywiki.com/Crops", force = TRUE)

result <- scrape(crops) |>
  html_nodes(css = "table") |>
  html_table(header = TRUE, fill = TRUE)

seasonal_crops <- result[[134]][2] #table of the season crops so we can use that list

seasonal_crops <- seasonal_crops |>
  mutate(Crops = strsplit(Crops, " • ", fixed = TRUE)) |>
  unnest(Crops) |>
  mutate(Crops = str_replace_all(Crops, " ", "_")) |>
  distinct(Crops)

Create our helper functions for crops:

Code

# function for getting the price at a given page and css selector
get_price <- function(page, css_selector) {
  page |>
  html_nodes(css_selector) |>
  html_text()
}

# function for creating a tibble of base prices, no profession, for a given crop page
crop_base_prices <- function(crop, tiller = FALSE) {
  url <- str_c("https://stardewvalleywiki.com/", crop)
  page <- read_html(url)
  
  qualities <- c("regular", "silver", "gold", "iridium")
  prices <- list()
  
  for (i in seq_along(qualities)) {
    if (tiller) {
      selector <- str_c("tr:nth-child(10) td+ td tr:nth-child(", i, ") td+ td")
    } else {
      selector <- str_c("tr:nth-child(10) tr td:nth-child(1) tr:nth-child(", i, ") td+ td")
    }
    price <- get_price(page, selector)
    prices[[qualities[i]]] <- parse_number(price)
  }
  
  tibble(
    item = crop,
    regular_price = prices$regular,
    silver_price = prices$silver,
    gold_price = prices$gold,
    iridium_price = prices$iridium
  )
}

Create the tibbles for seasonal crops using the helper functions. Note that items 46 (Tea_Leaves), 44 (Sweet Gem Berry), 43 (Qi_Fruit), 41 (Cactus_Fruit), 36 (Grape), 4 (Coffee_Bean) have issues when using the functions, so we will scrape the data manually without the functions.

Code

# list of all our seasonal crops
seasonal_crops_list <- pull(seasonal_crops) # list of our crops tibble

# list of crops, excluding those with known issues
valid_crops_list <- seasonal_crops_list[-c(46, 44, 43, 41, 36, 4)]

# base prices without profession
base_crop_prices <- valid_crops_list |>
  purrr::map_dfr(~ crop_base_prices(.x)) |>
  mutate(profession = as.character(NA))

# prices with Tiller profession
tiller_crop_prices <- valid_crops_list |>
  purrr::map_dfr(~ crop_base_prices(.x, tiller = TRUE)) |>
  mutate(profession = "tiller")

# combine base and tiller crop prices
seasonal_crop_prices <- bind_rows(base_crop_prices, tiller_crop_prices)

Do the same for non seasonal crops:

Code

# non-seasonal crops list, excluding problematic items
other_crops <- c("Apple", "Blackberry", "Pomegranate", "Wild_Plum", "Apricot", 
                 "Cherry", "Spice_Berry", "Peach", "Orange", "Crystal_Fruit", 
                 "Banana", "Mango", "Fiddlehead_Fern")[-c(10, 7, 4, 2)]

# base prices without profession
base_other_crops <- other_crops |>
  purrr::map_dfr(~ crop_base_prices(.x)) |>
  mutate(profession = as.character(NA))

# prices with Tiller profession
tiller_other_crops <- other_crops |>
  purrr::map_dfr(~ crop_base_prices(.x, tiller = TRUE)) |>
  mutate(profession = "tiller")

# combine base and tiller prices into one table and arrange by item
nonseasonal_crop_tbl <- bind_rows(base_other_crops, tiller_other_crops) |>
  arrange(item)

Finally, create a function for the weird crops that have missing quality or selector path was different

Code

# function for the crops that do not have different qualities
crop_weird_prices <- function(item, selector){
  url <- str_c("https://stardewvalleywiki.com/", item)
  page <- read_html(url)
  regular_price <- get_price(page, selector)
  
  tibble(item = item,
      regular_price = parse_number(regular_price))
}

# function for the crops that have different qualities. the Berry is for the fruits that have a weird selector that seems to follow a similar pattern.
crop_weird_prices_w_quality <- function(crop, tiller = FALSE, berry = FALSE ){
  url <- str_c("https://stardewvalleywiki.com/", crop)
  page <- read_html(url)
  
  qualities <- c("regular", "silver", "gold", "iridium")
  prices <- list()
  
  for (i in seq_along(qualities)) {
    if (tiller) {
      selector <- str_c("tr:nth-child(11) td+ td tr:nth-child(", i, ") td+ td")
    } else if (berry){
      selector <- str_c("tr:nth-child(9) tr:nth-child(", i, ") td+ td")
    }else {
      selector <- str_c("tr:nth-child(11) tr td:nth-child(1) tr:nth-child(", i, ") td+ td")
    }
    price <- get_price(page, selector)
    prices[[qualities[i]]] <- parse_number(price)
  }
  
  tibble(
    item = crop,
    regular_price = prices$regular,
    silver_price = prices$silver,
    gold_price = prices$gold,
    iridium_price = prices$iridium
  )
}

Now we make all of the tibbles for the weird crops.

Code

# tea leaves
base_tea_leaves <- crop_weird_prices("Tea_Leaves",
                                     "tr:nth-child(10) tr td:nth-child(1) td+ td")

tiller_tea_leaves <- crop_weird_prices("Tea_Leaves",
                                     "tr:nth-child(10) td+ td td+ td")

tea_leaves <-bind_rows(base_tea_leaves, tiller_tea_leaves)

# qi fruit
base_qi_fruit <-crop_weird_prices("Qi_Fruit",
                                  "tr:nth-child(9) tr td:nth-child(1) td+ td")

tiller_qi_fruit <-crop_weird_prices("Qi_Fruit",
                                  "tr:nth-child(9) td+ td td+ td")

qi_fruit <-bind_rows(base_qi_fruit, tiller_qi_fruit)

# cactus fruit
cactus_fruit <- crop_weird_prices_w_quality("Cactus_Fruit")

cactus_fruit_tiller <- crop_weird_prices_w_quality("Cactus_Fruit", tiller = TRUE)

cactus_fruit <-bind_rows(cactus_fruit, cactus_fruit_tiller)

# grape
grape <- crop_weird_prices_w_quality("Grape")

grape_tiller <- crop_weird_prices_w_quality("Grape", tiller = TRUE)

grape <-bind_rows(grape, grape_tiller)

# coffee bean
coffee_bean <- crop_weird_prices_w_quality("Coffee_Bean")

# wild plum
wild_plum <- crop_weird_prices_w_quality("Wild_Plum", berry = TRUE)

# spice berry
spice_berry <- crop_weird_prices_w_quality("Spice_Berry", berry = TRUE)

# crystal fruit
crystal_fruit <- crop_weird_prices_w_quality("Crystal_Fruit", berry = TRUE)

# Finally, blackberry is just weird and likes to be different, so we did not use a function for it. 
#Blackberry

# base
url <- str_c("https://stardewvalleywiki.com/", "Blackberry")
page <- read_html(url)

qualities <- c("regular", "silver", "gold", "iridium")
prices <- list()

# loop to retrieve and parse prices
for (i in seq_along(qualities)) {
  price <- get_price(page, str_c("tr:nth-child(9) tr td:nth-child(1) tr:nth-child(", i, ") td+ td"))
  prices[[qualities[i]]] <- parse_number(price)
}

blackberry <- tibble(
  item = "Blackberry",
  regular_price = prices$regular,
  silver_price = prices$silver,
  gold_price = prices$gold,
  iridium_price = prices$iridium
)

Now, we can combine all of the crop tibbles into one:

Code

# first chunks of crops 
draft_crops <- bind_rows(seasonal_crop_prices,
                         nonseasonal_crop_tbl,
                         tea_leaves, 
                         qi_fruit, 
                         cactus_fruit, 
                         grape, 
                         coffee_bean, 
                         wild_plum, 
                         blackberry, 
                         spice_berry, 
                         crystal_fruit) |>
  arrange(item)

Lastly, we can add in the category variable and the subcategory variable. to makes things easier, we decided the subcategory would be the crop’s season. Then, we write it to a csv in case the website changes or updates.

Code

# retrieve seasons
seasons <- result[[134]] %>%
  dplyr::select(Season = 1, Crops = 2) |>
  mutate(Crops = strsplit(Crops, " • ", fixed = TRUE)) |>
  unnest(Crops) |>
  mutate(Crops = str_replace_all(Crops, " ", "_"))

# join together seasons and crops
crop_prices <- draft_crops |>
  left_join(seasons, join_by(item == Crops))|>
   mutate(category = "crop",
          sub_category = str_c(Season, " Crop"))|>
  dplyr::select(-Season)

# write csv
#write.csv(crop_prices, "crop_prices.csv")

crop_prices |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	regular_price	silver_price	gold_price	iridium_price	profession	category	sub_category
Amaranth	150	187	225	300	NA	crop	Fall Crop
Amaranth	165	205	247	330	tiller	crop	Fall Crop
Ancient_Fruit	550	687	825	1100	NA	crop	Special Crop
Ancient_Fruit	605	755	907	1210	tiller	crop	Special Crop
Apple	100	125	150	200	NA	crop	NA
Apple	110	137	165	220	tiller	crop	NA
Apricot	50	62	75	100	NA	crop	NA
Apricot	55	68	82	110	tiller	crop	NA
Artichoke	160	200	240	320	NA	crop	Fall Crop
Artichoke	176	220	264	352	tiller	crop	Fall Crop
Banana	150	187	225	300	NA	crop	NA
Banana	165	205	247	330	tiller	crop	NA
Beet	100	125	150	200	NA	crop	Fall Crop
Beet	110	137	165	220	tiller	crop	Fall Crop
Blackberry	20	25	30	40	NA	crop	NA
Blue_Jazz	50	62	75	100	NA	crop	Spring Crop
Blue_Jazz	55	68	82	110	tiller	crop	Spring Crop
Blueberry	50	62	75	100	NA	crop	Summer Crop
Blueberry	55	68	82	110	tiller	crop	Summer Crop
Bok_Choy	80	100	120	160	NA	crop	Fall Crop
Bok_Choy	88	110	132	176	tiller	crop	Fall Crop
Broccoli	70	87	105	140	NA	crop	Fall Crop
Broccoli	77	95	115	154	tiller	crop	Fall Crop
Cactus_Fruit	75	93	112	150	NA	crop	Special Crop
Cactus_Fruit	82	102	123	165	NA	crop	Special Crop
Carrot	35	43	52	70	NA	crop	Spring Crop
Carrot	38	47	57	77	tiller	crop	Spring Crop
Cauliflower	175	218	262	350	NA	crop	Spring Crop
Cauliflower	192	239	288	385	tiller	crop	Spring Crop
Cherry	80	100	120	160	NA	crop	NA
Cherry	88	110	132	176	tiller	crop	NA
Corn	50	62	75	100	NA	crop	Summer Crop
Corn	50	62	75	100	NA	crop	Fall Crop
Corn	55	68	82	110	tiller	crop	Summer Crop
Corn	55	68	82	110	tiller	crop	Fall Crop
Cranberries	75	93	112	150	NA	crop	Fall Crop
Cranberries	82	102	123	165	tiller	crop	Fall Crop
Crystal_Fruit	150	187	225	300	NA	crop	NA
Eggplant	60	75	90	120	NA	crop	Fall Crop
Eggplant	66	82	99	132	tiller	crop	Fall Crop
Fairy_Rose	290	362	435	580	NA	crop	Fall Crop
Fairy_Rose	319	398	478	638	tiller	crop	Fall Crop
Fiddlehead_Fern	90	112	135	180	NA	crop	NA
Fiddlehead_Fern	99	123	148	198	tiller	crop	NA
Garlic	60	75	90	120	NA	crop	Spring Crop
Garlic	66	82	99	132	tiller	crop	Spring Crop
Grape	80	100	120	160	NA	crop	Fall Crop
Grape	88	110	132	176	NA	crop	Fall Crop
Green_Bean	40	50	60	80	NA	crop	Spring Crop
Green_Bean	44	55	66	88	tiller	crop	Spring Crop
Hops	25	31	37	50	NA	crop	Summer Crop
Hops	27	34	40	55	tiller	crop	Summer Crop
Hot_Pepper	40	50	60	80	NA	crop	Summer Crop
Hot_Pepper	44	55	66	88	tiller	crop	Summer Crop
Kale	110	137	165	220	NA	crop	Spring Crop
Kale	121	150	181	242	tiller	crop	Spring Crop
Mango	130	162	195	260	NA	crop	NA
Mango	143	178	214	286	tiller	crop	NA
Melon	250	312	375	500	NA	crop	Summer Crop
Melon	275	343	412	550	tiller	crop	Summer Crop
Orange	100	125	150	200	NA	crop	NA
Orange	110	137	165	220	tiller	crop	NA
Parsnip	35	43	52	70	NA	crop	Spring Crop
Parsnip	38	47	57	77	tiller	crop	Spring Crop
Peach	140	175	210	280	NA	crop	NA
Peach	154	192	231	308	tiller	crop	NA
Pineapple	300	375	450	600	NA	crop	Special Crop
Pineapple	330	412	495	660	tiller	crop	Special Crop
Pomegranate	140	175	210	280	NA	crop	NA
Pomegranate	154	192	231	308	tiller	crop	NA
Poppy	140	175	210	280	NA	crop	Summer Crop
Poppy	154	192	231	308	tiller	crop	Summer Crop
Potato	80	100	120	160	NA	crop	Spring Crop
Potato	88	110	132	176	tiller	crop	Spring Crop
Powdermelon	60	75	90	120	NA	crop	Winter Crop
Powdermelon	66	82	99	132	tiller	crop	Winter Crop
Pumpkin	320	400	480	640	NA	crop	Fall Crop
Pumpkin	352	440	528	704	tiller	crop	Fall Crop
Qi_Fruit	1	NA	NA	NA	NA	crop	Special Crop
Qi_Fruit	1	NA	NA	NA	NA	crop	Special Crop
Radish	90	112	135	180	NA	crop	Summer Crop
Radish	99	123	148	198	tiller	crop	Summer Crop
Red_Cabbage	260	325	390	520	NA	crop	Summer Crop
Red_Cabbage	286	357	429	572	tiller	crop	Summer Crop
Rhubarb	220	275	330	440	NA	crop	Spring Crop
Rhubarb	242	302	363	484	tiller	crop	Spring Crop
Spice_Berry	80	100	120	160	NA	crop	NA
Starfruit	750	937	1125	1500	NA	crop	Summer Crop
Starfruit	825	1030	1237	1650	tiller	crop	Summer Crop
Strawberry	120	150	180	240	NA	crop	Spring Crop
Strawberry	132	165	198	264	tiller	crop	Spring Crop
Summer_Spangle	90	112	135	180	NA	crop	Summer Crop
Summer_Spangle	99	123	148	198	tiller	crop	Summer Crop
Summer_Squash	45	56	67	90	NA	crop	Summer Crop
Summer_Squash	49	61	73	99	tiller	crop	Summer Crop
Sunflower	80	100	120	160	NA	crop	Summer Crop
Sunflower	80	100	120	160	NA	crop	Fall Crop
Sunflower	88	110	132	176	tiller	crop	Summer Crop
Sunflower	88	110	132	176	tiller	crop	Fall Crop
Taro_Root	100	125	150	200	NA	crop	Special Crop
Taro_Root	110	137	165	220	tiller	crop	Special Crop
Tea_Leaves	50	NA	NA	NA	NA	crop	Special Crop
Tea_Leaves	55	NA	NA	NA	NA	crop	Special Crop
Tomato	60	75	90	120	NA	crop	Summer Crop
Tomato	66	82	99	132	tiller	crop	Summer Crop
Tulip	30	37	45	60	NA	crop	Spring Crop
Tulip	33	40	49	66	tiller	crop	Spring Crop
Unmilled_Rice	30	37	45	60	NA	crop	Spring Crop
Unmilled_Rice	33	40	49	66	tiller	crop	Spring Crop
Wheat	25	31	37	50	NA	crop	Summer Crop
Wheat	25	31	37	50	NA	crop	Fall Crop
Wheat	27	34	40	55	tiller	crop	Summer Crop
Wheat	27	34	40	55	tiller	crop	Fall Crop
Wild_Plum	80	100	120	160	NA	crop	NA
Yam	160	200	240	320	NA	crop	Fall Crop
Yam	176	220	264	352	tiller	crop	Fall Crop

Fish

Fish was the second most difficult item to scrape from the wiki, since again not all of the pages are structured the same. However, we were able identify 4 different pages in which we could write functions to automate.

We start be getting a list of all the different fish in the game.

Code

# making sure that this irl is scrapable
fish <- bow("https://stardewvalleywiki.com/Fish", force = TRUE) 

# scraping table to get a list of all the fish 
result <- scrape(fish) |>
  html_nodes(css = "table") |>
  html_table(header = TRUE, fill = TRUE)

# the correct table for the list of fish, and only keeping the names of the fish column
fishes <- result[[224]][2] 

# however, it is formatted very poorly so we need to tidy it up 
fishes <- fishes |>
  mutate(Fish = strsplit(Fish, " • ", fixed = TRUE)) |>
  unnest(Fish) |>
  # splitting the string since " • " was used to separate all fish
  mutate(Fish = str_replace_all(Fish, " ", "_")) |> 
  distinct(Fish) |>
  # this is a fish that is in the data set twice but with different spacing 
  filter(Fish != "_Super_Cucumber") 

# tibble with the subcategories of the fish and the fish name for joining later
subcategory <- result[[224]] |> 
  dplyr::select(Location = 1, Fish = 2) |> 
  mutate(Fish = strsplit(Fish, " • ", fixed = TRUE)) |> 
  unnest(Fish) |>
  mutate(Fish = str_replace_all(Fish, " ", "_"))

Create our helper functions for fish:

Code

# function for getting the price at a given page and css selector
get_price <- function(page, css_selector) {
  page |>
  html_nodes(css_selector) |>
  html_text()
}

# function for creating a tibble of prices for a given fish this functions output a tibble of our fish and the 4 different prices of the fish dependent on quality

#fish_base_prices takes our fish name,and takes a profession if we specify true or false, as well as the "nthchild_num" value for where the price is being store on that website

fish_base_prices <- function(fish, fisher = FALSE, angler = FALSE, nthchild_num) {
  url <- str_c("https://stardewvalleywiki.com/", fish)
  page <- read_html(url)
  
  qualities <- c("regular", "silver", "gold", "iridium")
  prices <- list()
  
  for (i in seq_along(qualities)) {
    if (fisher) {
      selector <- str_c("tr:nth-child(", nthchild_num,") tr td:nth-child(2) tr:nth-child(", i, ") td+ td")
    } else if (angler) {
      selector <- str_c("tr:nth-child(", nthchild_num,") tr td:nth-child(3) tr:nth-child(", i, ") td+ td")
    } 
    else {
      selector <- str_c("tr:nth-child(", nthchild_num,") tr td:nth-child(1) tr:nth-child(", i, ") td+ td")
    }
    price <- get_price(page, selector)
    prices[[qualities[i]]] <- parse_number(price)
  }
  
  tibble(
    item = fish,
    regular_price = prices$regular,
    silver_price = prices$silver,
    gold_price = prices$gold,
    iridium_price = prices$iridium
  )
}

As well as the function for the fish with a different webpage format.

Code

# this functions output a tibble of our fish and the 2 different prices of the fish dependent on quality

# fish_base_prices takes our fish name, and takes a profession if we specify true or false, as well as the "nthchild_num" value for where the price is being store on that website

fish_base_prices2 <- function(fish, fisher = FALSE, angler = FALSE, nthchild_num) {
  url <- str_c("https://stardewvalleywiki.com/", fish)
  page <- read_html(url)
  
  qualities <- c("regular", "silver", "gold", "iridium")
  prices <- list()
  
  for (i in seq_along(qualities)) {
    if (fisher) {
      selector <- str_c("tr:nth-child(", nthchild_num,") tr td:nth-child(2) tr:nth-child(", i, ") td+ td")
    } else if (angler) {
      selector <- str_c("tr:nth-child(", nthchild_num,") tr td:nth-child(3) tr:nth-child(", i, ") td+ td")
    } 
    else {
      selector <- str_c("tr:nth-child(", nthchild_num,") tr td:nth-child(1) tr:nth-child(", i, ") td+ td")
    }
    price <- get_price(page, selector)
    prices[[qualities[i]]] <- parse_number(price)
  }
  
  tibble(
    item = fish,
    regular_price = prices$regular,
    silver_price = prices$silver,
  )
}

Now, we will load in our fishes lists so for the type of webpage format they have and then apply our function to the fishes to find their prices.

 [1] "Mutant_Carp"      "Radioactive_Carp" "Albacore"         "Anchovy"         
 [5] "Eel"              "Flounder"         "Halibut"          "Herring"         
 [9] "Octopus"          "Pufferfish"       "Red_Mullet"       "Red_Snapper"     
[13] "Sardine"          "Sea_Cucumber"     "Squid"            "Super_Cucumber"  
[17] "Tilapia"          "Tuna"             "Bream"            "Catfish"         
[21] "Chub"             "Dorado"           "Goby"             "Lingcod"         
[25] "Perch"            "Pike"             "Rainbow_Trout"    "Salmon"          
[29] "Shad"             "Smallmouth_Bass"  "Sunfish"          "Tiger_Trout"     
[33] "Walleye"          "Bullhead"         "Carp"             "Largemouth_Bass" 
[37] "Midnight_Carp"    "Sturgeon"         "Woodskip"         "Ghostfish"       
[41] "Ice_Pip"          "Stonefish"        "Sandfish"         "Slimejack"       
[45] "Void_Salmon"      "Blobfish"         "Midnight_Squid"   "Spook_Fish"      
[49] "Blue_Discus"      "Lionfish"         "Stingray"

 [1] "Angler"             "Crimsonfish"        "Glacierfish"       
 [4] "Glacierfish_Jr."    "Legend"             "Legend_II"         
 [7] "Ms._Angler"         "Son_of_Crimsonfish" "Lava_Eel"          
[10] "Scorpion_Carp"

[1] "Clam"   "Cockle" "Mussel" "Oyster"

[1] "Crab"       "Crayfish"   "Lobster"    "Periwinkle" "Shrimp"    
[6] "Snail"

Code

# creating list of tbl's to store prices so that we can bind into one big tibble
fish_prices <- vector("list", length = 12)

# base prices without profession for tr:nth-child(14)
fish_prices[[1]] <- fishfor14 |>
  purrr::map_dfr(~ fish_base_prices(.x, nthchild_num = 14)) |>
  mutate(profession = as.character(NA))

# prices with Fisher profession
fish_prices[[2]] <- fishfor14 |>
  purrr::map_dfr(~ fish_base_prices(.x, fisher = TRUE, nthchild_num = 14)) |>
  mutate(profession = "fisher")

# prices with Angler profession
fish_prices[[3]] <- fishfor14 |>
  purrr::map_dfr(~ fish_base_prices(.x, angler = TRUE, nthchild_num = 14)) |>
  mutate(profession = "angler")

# base prices without profession for tr:nth-child(15)
fish_prices[[4]] <- fishfor15 |>
  purrr::map_dfr(~ fish_base_prices(.x, nthchild_num = 15)) |>
  mutate(profession = as.character(NA))

# prices with Fisher profession
fish_prices[[5]] <- fishfor15 |>
  purrr::map_dfr(~ fish_base_prices(.x, fisher = TRUE, nthchild_num = 15)) |>
  mutate(profession = "fisher")

# prices with Angler profession
fish_prices[[6]] <- fishfor15 |>
  purrr::map_dfr(~ fish_base_prices(.x, angler = TRUE, nthchild_num = 15)) |>
  mutate(profession = "angler")

# base prices without profession for tr:nth-child(10)
fish_prices[[7]] <- fishfor10 |>
  purrr::map_dfr(~ fish_base_prices(.x, nthchild_num = 10)) |>
  mutate(profession = as.character(NA))

# prices with Fisher profession
fish_prices[[8]] <- fishfor10 |>
  purrr::map_dfr(~ fish_base_prices(.x, fisher = TRUE, nthchild_num = 10)) |>
  mutate(profession = "fisher")

# prices with Angler profession
fish_prices[[9]] <- fishfor10 |>
  purrr::map_dfr(~ fish_base_prices(.x, angler = TRUE, nthchild_num = 10)) |>
  mutate(profession = "angler")

# base prices without profession for tr:nth-child(10) but only two qualities
fish_prices[[10]] <- fishleft |>
  purrr::map_dfr(~ fish_base_prices2(.x, nthchild_num = 10)) |>
  mutate(profession = as.character(NA))

# prices with Fisher profession
fish_prices[[11]] <- fishleft |>
  purrr::map_dfr(~ fish_base_prices2(.x, fisher = TRUE, nthchild_num = 10)) |>
  mutate(profession = "fisher")

# prices with Angler profession
fish_prices[[12]] <- fishleft |>
  purrr::map_dfr(~ fish_base_prices2(.x, angler = TRUE, nthchild_num = 10)) |>
  mutate(profession = "angler")

Finally we will take our fish prices and then create one big tibble.

Code

# first tbl in fish prices assigned to our final tibble 
tidy_fish_prices <- fish_prices[[1]] 

# for loop for iterating each tbl in our fish prices list to our final tibble
for (i in 2:12){
  tidy_fish_prices <- bind_rows(tidy_fish_prices, fish_prices[[i]])
}

# viewing and alphabetizing our tidy fish tbl also joining our subcategories and assigning category
tidy_fish_prices <- tidy_fish_prices |>
  left_join(subcategory, join_by(item == Fish)) |>
  mutate(category = "fish") |>
  rename(sub_category = Location) |>
  arrange(item)

# writing our tbl as a csv so that we can join with the other items 
#write.csv(tidy_fish_prices, "fish_prices.csv")

tidy_fish_prices |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	regular_price	silver_price	gold_price	iridium_price	profession	sub_category	category
Albacore	75	93	112	150	NA	The Beach	fish
Albacore	93	116	140	187	fisher	The Beach	fish
Albacore	112	139	168	225	angler	The Beach	fish
Anchovy	30	37	45	60	NA	The Beach	fish
Anchovy	37	46	56	75	fisher	The Beach	fish
Anchovy	45	55	67	90	angler	The Beach	fish
Angler	900	1125	1350	1800	NA	Legendary	fish
Angler	900	1125	1350	1800	NA	River	fish
Angler	1125	1406	1687	2250	fisher	Legendary	fish
Angler	1125	1406	1687	2250	fisher	River	fish
Angler	1350	1687	2025	2700	angler	Legendary	fish
Angler	1350	1687	2025	2700	angler	River	fish
Blobfish	500	625	750	1000	NA	Night Market	fish
Blobfish	625	781	937	1250	fisher	Night Market	fish
Blobfish	750	937	1125	1500	angler	Night Market	fish
Blue_Discus	120	150	180	240	NA	Ginger Island	fish
Blue_Discus	150	187	225	300	fisher	Ginger Island	fish
Blue_Discus	180	225	270	360	angler	Ginger Island	fish
Bream	45	56	67	90	NA	River	fish
Bream	56	70	83	112	fisher	River	fish
Bream	67	84	100	135	angler	River	fish
Bullhead	75	93	112	150	NA	Mountain Lake	fish
Bullhead	93	116	140	187	fisher	Mountain Lake	fish
Bullhead	112	139	168	225	angler	Mountain Lake	fish
Carp	30	37	45	60	NA	Mountain Lake	fish
Carp	30	37	45	60	NA	Secret Woods	fish
Carp	30	37	45	60	NA	Sewers	fish
Carp	30	37	45	60	NA	Mutant Bug Lair	fish
Carp	37	46	56	75	fisher	Mountain Lake	fish
Carp	37	46	56	75	fisher	Secret Woods	fish
Carp	37	46	56	75	fisher	Sewers	fish
Carp	37	46	56	75	fisher	Mutant Bug Lair	fish
Carp	45	55	67	90	angler	Mountain Lake	fish
Carp	45	55	67	90	angler	Secret Woods	fish
Carp	45	55	67	90	angler	Sewers	fish
Carp	45	55	67	90	angler	Mutant Bug Lair	fish
Catfish	200	250	300	400	NA	River	fish
Catfish	200	250	300	400	NA	Secret Woods	fish
Catfish	200	250	300	400	NA	Witch's Swamp	fish
Catfish	250	312	375	500	fisher	River	fish
Catfish	250	312	375	500	fisher	Secret Woods	fish
Catfish	250	312	375	500	fisher	Witch's Swamp	fish
Catfish	300	375	450	600	angler	River	fish
Catfish	300	375	450	600	angler	Secret Woods	fish
Catfish	300	375	450	600	angler	Witch's Swamp	fish
Chub	50	62	75	100	NA	River	fish
Chub	50	62	75	100	NA	Mountain Lake	fish
Chub	62	77	93	125	fisher	River	fish
Chub	62	77	93	125	fisher	Mountain Lake	fish
Chub	75	93	112	150	angler	River	fish
Chub	75	93	112	150	angler	Mountain Lake	fish
Clam	50	62	75	100	NA	Crab Pot	fish
Clam	62	77	93	125	fisher	Crab Pot	fish
Clam	75	93	112	150	angler	Crab Pot	fish
Cockle	50	62	75	100	NA	Crab Pot	fish
Cockle	62	77	93	125	fisher	Crab Pot	fish
Cockle	75	93	112	150	angler	Crab Pot	fish
Crab	100	125	NA	NA	NA	Crab Pot	fish
Crab	125	156	NA	NA	fisher	Crab Pot	fish
Crab	150	187	NA	NA	angler	Crab Pot	fish
Crayfish	75	93	NA	NA	NA	Crab Pot	fish
Crayfish	93	116	NA	NA	fisher	Crab Pot	fish
Crayfish	112	139	NA	NA	angler	Crab Pot	fish
Crimsonfish	1500	1875	2250	3000	NA	Legendary	fish
Crimsonfish	1500	1875	2250	3000	NA	The Beach	fish
Crimsonfish	1875	2343	2812	3750	fisher	Legendary	fish
Crimsonfish	1875	2343	2812	3750	fisher	The Beach	fish
Crimsonfish	2250	2812	3375	4500	angler	Legendary	fish
Crimsonfish	2250	2812	3375	4500	angler	The Beach	fish
Dorado	100	125	150	200	NA	River	fish
Dorado	125	156	187	250	fisher	River	fish
Dorado	150	187	225	300	angler	River	fish
Eel	85	106	127	170	NA	The Beach	fish
Eel	106	132	158	212	fisher	The Beach	fish
Eel	127	159	190	255	angler	The Beach	fish
Flounder	100	125	150	200	NA	The Beach	fish
Flounder	100	125	150	200	NA	Ginger Island	fish
Flounder	125	156	187	250	fisher	The Beach	fish
Flounder	125	156	187	250	fisher	Ginger Island	fish
Flounder	150	187	225	300	angler	The Beach	fish
Flounder	150	187	225	300	angler	Ginger Island	fish
Ghostfish	45	56	67	90	NA	Mines	fish
Ghostfish	56	70	83	112	fisher	Mines	fish
Ghostfish	67	84	100	135	angler	Mines	fish
Glacierfish	1000	1250	1500	2000	NA	Legendary	fish
Glacierfish	1000	1250	1500	2000	NA	River	fish
Glacierfish	1250	1562	1875	2500	fisher	Legendary	fish
Glacierfish	1250	1562	1875	2500	fisher	River	fish
Glacierfish	1500	1875	2250	3000	angler	Legendary	fish
Glacierfish	1500	1875	2250	3000	angler	River	fish
Glacierfish_Jr.	1000	1250	1500	2000	NA	Legendary	fish
Glacierfish_Jr.	1000	1250	1500	2000	NA	River	fish
Glacierfish_Jr.	1250	1562	1875	2500	fisher	Legendary	fish
Glacierfish_Jr.	1250	1562	1875	2500	fisher	River	fish
Glacierfish_Jr.	1500	1875	2250	3000	angler	Legendary	fish
Glacierfish_Jr.	1500	1875	2250	3000	angler	River	fish
Goby	150	187	225	300	NA	River	fish
Goby	187	233	281	375	fisher	River	fish
Goby	225	280	337	450	angler	River	fish
Halibut	80	100	120	160	NA	The Beach	fish
Halibut	100	125	150	200	fisher	The Beach	fish
Halibut	120	150	180	240	angler	The Beach	fish
Herring	30	37	45	60	NA	The Beach	fish
Herring	37	46	56	75	fisher	The Beach	fish
Herring	45	55	67	90	angler	The Beach	fish
Ice_Pip	500	625	750	1000	NA	Mines	fish
Ice_Pip	625	781	937	1250	fisher	Mines	fish
Ice_Pip	750	937	1125	1500	angler	Mines	fish
Largemouth_Bass	100	125	150	200	NA	Mountain Lake	fish
Largemouth_Bass	125	156	187	250	fisher	Mountain Lake	fish
Largemouth_Bass	150	187	225	300	angler	Mountain Lake	fish
Lava_Eel	700	875	1050	1400	NA	Mines	fish
Lava_Eel	700	875	1050	1400	NA	Ginger Island	fish
Lava_Eel	875	1093	1312	1750	fisher	Mines	fish
Lava_Eel	875	1093	1312	1750	fisher	Ginger Island	fish
Lava_Eel	1050	1312	1575	2100	angler	Mines	fish
Lava_Eel	1050	1312	1575	2100	angler	Ginger Island	fish
Legend	5000	6250	7500	10000	NA	Legendary	fish
Legend	5000	6250	7500	10000	NA	Mountain Lake	fish
Legend	6250	7812	9375	12500	fisher	Legendary	fish
Legend	6250	7812	9375	12500	fisher	Mountain Lake	fish
Legend	7500	9375	11250	15000	angler	Legendary	fish
Legend	7500	9375	11250	15000	angler	Mountain Lake	fish
Legend_II	5000	6250	7500	10000	NA	Legendary	fish
Legend_II	5000	6250	7500	10000	NA	Mountain Lake	fish
Legend_II	6250	7812	9375	12500	fisher	Legendary	fish
Legend_II	6250	7812	9375	12500	fisher	Mountain Lake	fish
Legend_II	7500	9375	11250	15000	angler	Legendary	fish
Legend_II	7500	9375	11250	15000	angler	Mountain Lake	fish
Lingcod	120	150	180	240	NA	River	fish
Lingcod	120	150	180	240	NA	Mountain Lake	fish
Lingcod	150	187	225	300	fisher	River	fish
Lingcod	150	187	225	300	fisher	Mountain Lake	fish
Lingcod	180	225	270	360	angler	River	fish
Lingcod	180	225	270	360	angler	Mountain Lake	fish
Lionfish	100	125	150	200	NA	Ginger Island	fish
Lionfish	125	156	187	250	fisher	Ginger Island	fish
Lionfish	150	187	225	300	angler	Ginger Island	fish
Lobster	120	150	NA	NA	NA	Crab Pot	fish
Lobster	150	187	NA	NA	fisher	Crab Pot	fish
Lobster	180	225	NA	NA	angler	Crab Pot	fish
Midnight_Carp	150	187	225	300	NA	Mountain Lake	fish
Midnight_Carp	150	187	225	300	NA	Cindersap Forest Pond	fish
Midnight_Carp	150	187	225	300	NA	Ginger Island	fish
Midnight_Carp	187	233	281	375	fisher	Mountain Lake	fish
Midnight_Carp	187	233	281	375	fisher	Cindersap Forest Pond	fish
Midnight_Carp	187	233	281	375	fisher	Ginger Island	fish
Midnight_Carp	225	280	337	450	angler	Mountain Lake	fish
Midnight_Carp	225	280	337	450	angler	Cindersap Forest Pond	fish
Midnight_Carp	225	280	337	450	angler	Ginger Island	fish
Midnight_Squid	100	125	150	200	NA	Night Market	fish
Midnight_Squid	125	156	187	250	fisher	Night Market	fish
Midnight_Squid	150	187	225	300	angler	Night Market	fish
Ms._Angler	900	1125	1350	1800	NA	Legendary	fish
Ms._Angler	900	1125	1350	1800	NA	River	fish
Ms._Angler	1125	1406	1687	2250	fisher	Legendary	fish
Ms._Angler	1125	1406	1687	2250	fisher	River	fish
Ms._Angler	1350	1687	2025	2700	angler	Legendary	fish
Ms._Angler	1350	1687	2025	2700	angler	River	fish
Mussel	30	37	45	60	NA	Crab Pot	fish
Mussel	37	46	56	75	fisher	Crab Pot	fish
Mussel	45	55	67	90	angler	Crab Pot	fish
Mutant_Carp	1000	1250	1500	2000	NA	Legendary	fish
Mutant_Carp	1000	1250	1500	2000	NA	Sewers	fish
Mutant_Carp	1250	1562	1875	2500	fisher	Legendary	fish
Mutant_Carp	1250	1562	1875	2500	fisher	Sewers	fish
Mutant_Carp	1500	1875	2250	3000	angler	Legendary	fish
Mutant_Carp	1500	1875	2250	3000	angler	Sewers	fish
Octopus	150	187	225	300	NA	The Beach	fish
Octopus	150	187	225	300	NA	Night Market	fish
Octopus	150	187	225	300	NA	Ginger Island	fish
Octopus	187	233	281	375	fisher	The Beach	fish
Octopus	187	233	281	375	fisher	Night Market	fish
Octopus	187	233	281	375	fisher	Ginger Island	fish
Octopus	225	280	337	450	angler	The Beach	fish
Octopus	225	280	337	450	angler	Night Market	fish
Octopus	225	280	337	450	angler	Ginger Island	fish
Oyster	40	50	60	80	NA	Crab Pot	fish
Oyster	50	62	75	100	fisher	Crab Pot	fish
Oyster	60	75	90	120	angler	Crab Pot	fish
Perch	55	68	82	110	NA	River	fish
Perch	55	68	82	110	NA	Mountain Lake	fish
Perch	55	68	82	110	NA	Cindersap Forest Pond	fish
Perch	68	85	102	137	fisher	River	fish
Perch	68	85	102	137	fisher	Mountain Lake	fish
Perch	68	85	102	137	fisher	Cindersap Forest Pond	fish
Perch	82	102	123	165	angler	River	fish
Perch	82	102	123	165	angler	Mountain Lake	fish
Perch	82	102	123	165	angler	Cindersap Forest Pond	fish
Periwinkle	20	25	NA	NA	NA	Crab Pot	fish
Periwinkle	25	31	NA	NA	fisher	Crab Pot	fish
Periwinkle	30	37	NA	NA	angler	Crab Pot	fish
Pike	100	125	150	200	NA	River	fish
Pike	100	125	150	200	NA	Cindersap Forest Pond	fish
Pike	125	156	187	250	fisher	River	fish
Pike	125	156	187	250	fisher	Cindersap Forest Pond	fish
Pike	150	187	225	300	angler	River	fish
Pike	150	187	225	300	angler	Cindersap Forest Pond	fish
Pufferfish	200	250	300	400	NA	The Beach	fish
Pufferfish	200	250	300	400	NA	Ginger Island	fish
Pufferfish	250	312	375	500	fisher	The Beach	fish
Pufferfish	250	312	375	500	fisher	Ginger Island	fish
Pufferfish	300	375	450	600	angler	The Beach	fish
Pufferfish	300	375	450	600	angler	Ginger Island	fish
Radioactive_Carp	1000	1250	1500	2000	NA	Legendary	fish
Radioactive_Carp	1000	1250	1500	2000	NA	Sewers	fish
Radioactive_Carp	1250	1562	1875	2500	fisher	Legendary	fish
Radioactive_Carp	1250	1562	1875	2500	fisher	Sewers	fish
Radioactive_Carp	1500	1875	2250	3000	angler	Legendary	fish
Radioactive_Carp	1500	1875	2250	3000	angler	Sewers	fish
Rainbow_Trout	65	81	97	130	NA	River	fish
Rainbow_Trout	65	81	97	130	NA	Mountain Lake	fish
Rainbow_Trout	81	101	121	162	fisher	River	fish
Rainbow_Trout	81	101	121	162	fisher	Mountain Lake	fish
Rainbow_Trout	97	121	145	195	angler	River	fish
Rainbow_Trout	97	121	145	195	angler	Mountain Lake	fish
Red_Mullet	75	93	112	150	NA	The Beach	fish
Red_Mullet	93	116	140	187	fisher	The Beach	fish
Red_Mullet	112	139	168	225	angler	The Beach	fish
Red_Snapper	50	62	75	100	NA	The Beach	fish
Red_Snapper	62	77	93	125	fisher	The Beach	fish
Red_Snapper	75	93	112	150	angler	The Beach	fish
Salmon	75	93	112	150	NA	River	fish
Salmon	93	116	140	187	fisher	River	fish
Salmon	112	139	168	225	angler	River	fish
Sandfish	75	93	112	150	NA	Desert	fish
Sandfish	93	116	140	187	fisher	Desert	fish
Sandfish	112	139	168	225	angler	Desert	fish
Sardine	40	50	60	80	NA	The Beach	fish
Sardine	50	62	75	100	fisher	The Beach	fish
Sardine	60	75	90	120	angler	The Beach	fish
Scorpion_Carp	150	187	225	300	NA	Desert	fish
Scorpion_Carp	187	233	281	375	fisher	Desert	fish
Scorpion_Carp	225	280	337	450	angler	Desert	fish
Sea_Cucumber	75	93	112	150	NA	The Beach	fish
Sea_Cucumber	75	93	112	150	NA	Night Market	fish
Sea_Cucumber	93	116	140	187	fisher	The Beach	fish
Sea_Cucumber	93	116	140	187	fisher	Night Market	fish
Sea_Cucumber	112	139	168	225	angler	The Beach	fish
Sea_Cucumber	112	139	168	225	angler	Night Market	fish
Shad	60	75	90	120	NA	River	fish
Shad	75	93	112	150	fisher	River	fish
Shad	90	112	135	180	angler	River	fish
Shrimp	60	75	NA	NA	NA	Crab Pot	fish
Shrimp	75	93	NA	NA	fisher	Crab Pot	fish
Shrimp	90	112	NA	NA	angler	Crab Pot	fish
Slimejack	100	125	150	200	NA	Mutant Bug Lair	fish
Slimejack	125	156	187	250	fisher	Mutant Bug Lair	fish
Slimejack	150	187	225	300	angler	Mutant Bug Lair	fish
Smallmouth_Bass	50	62	75	100	NA	River	fish
Smallmouth_Bass	50	62	75	100	NA	Cindersap Forest Pond	fish
Smallmouth_Bass	62	77	93	125	fisher	River	fish
Smallmouth_Bass	62	77	93	125	fisher	Cindersap Forest Pond	fish
Smallmouth_Bass	75	93	112	150	angler	River	fish
Smallmouth_Bass	75	93	112	150	angler	Cindersap Forest Pond	fish
Snail	65	81	NA	NA	NA	Crab Pot	fish
Snail	81	101	NA	NA	fisher	Crab Pot	fish
Snail	97	121	NA	NA	angler	Crab Pot	fish
Son_of_Crimsonfish	1500	1875	2250	3000	NA	Legendary	fish
Son_of_Crimsonfish	1500	1875	2250	3000	NA	The Beach	fish
Son_of_Crimsonfish	1875	2343	2812	3750	fisher	Legendary	fish
Son_of_Crimsonfish	1875	2343	2812	3750	fisher	The Beach	fish
Son_of_Crimsonfish	2250	2812	3375	4500	angler	Legendary	fish
Son_of_Crimsonfish	2250	2812	3375	4500	angler	The Beach	fish
Spook_Fish	220	275	330	440	NA	Night Market	fish
Spook_Fish	275	343	412	550	fisher	Night Market	fish
Spook_Fish	330	412	495	660	angler	Night Market	fish
Squid	80	100	120	160	NA	The Beach	fish
Squid	100	125	150	200	fisher	The Beach	fish
Squid	120	150	180	240	angler	The Beach	fish
Stingray	180	225	270	360	NA	Ginger Island	fish
Stingray	225	281	337	450	fisher	Ginger Island	fish
Stingray	270	337	405	540	angler	Ginger Island	fish
Stonefish	300	375	450	600	NA	Mines	fish
Stonefish	375	468	562	750	fisher	Mines	fish
Stonefish	450	562	675	900	angler	Mines	fish
Sturgeon	200	250	300	400	NA	Mountain Lake	fish
Sturgeon	250	312	375	500	fisher	Mountain Lake	fish
Sturgeon	300	375	450	600	angler	Mountain Lake	fish
Sunfish	30	37	45	60	NA	River	fish
Sunfish	37	46	56	75	fisher	River	fish
Sunfish	45	55	67	90	angler	River	fish
Super_Cucumber	250	312	375	500	NA	The Beach	fish
Super_Cucumber	250	312	375	500	NA	Night Market	fish
Super_Cucumber	312	390	468	625	fisher	The Beach	fish
Super_Cucumber	312	390	468	625	fisher	Night Market	fish
Super_Cucumber	375	468	562	750	angler	The Beach	fish
Super_Cucumber	375	468	562	750	angler	Night Market	fish
Tiger_Trout	150	187	225	300	NA	River	fish
Tiger_Trout	187	233	281	375	fisher	River	fish
Tiger_Trout	225	280	337	450	angler	River	fish
Tilapia	75	93	112	150	NA	The Beach	fish
Tilapia	75	93	112	150	NA	Ginger Island	fish
Tilapia	93	116	140	187	fisher	The Beach	fish
Tilapia	93	116	140	187	fisher	Ginger Island	fish
Tilapia	112	139	168	225	angler	The Beach	fish
Tilapia	112	139	168	225	angler	Ginger Island	fish
Tuna	100	125	150	200	NA	The Beach	fish
Tuna	100	125	150	200	NA	Ginger Island	fish
Tuna	125	156	187	250	fisher	The Beach	fish
Tuna	125	156	187	250	fisher	Ginger Island	fish
Tuna	150	187	225	300	angler	The Beach	fish
Tuna	150	187	225	300	angler	Ginger Island	fish
Void_Salmon	150	187	225	300	NA	Witch's Swamp	fish
Void_Salmon	187	233	281	375	fisher	Witch's Swamp	fish
Void_Salmon	225	280	337	450	angler	Witch's Swamp	fish
Walleye	105	131	157	210	NA	River	fish
Walleye	105	131	157	210	NA	Mountain Lake	fish
Walleye	105	131	157	210	NA	Cindersap Forest Pond	fish
Walleye	131	163	196	262	fisher	River	fish
Walleye	131	163	196	262	fisher	Mountain Lake	fish
Walleye	131	163	196	262	fisher	Cindersap Forest Pond	fish
Walleye	157	196	235	315	angler	River	fish
Walleye	157	196	235	315	angler	Mountain Lake	fish
Walleye	157	196	235	315	angler	Cindersap Forest Pond	fish
Woodskip	75	93	112	150	NA	Secret Woods	fish
Woodskip	93	116	140	187	fisher	Secret Woods	fish
Woodskip	112	139	168	225	angler	Secret Woods	fish

Animal Products

Animal products was one of the easier items to scrape since we were able to scrape the data from a table.

Code

#first be polite and check that we can scrape it 
robotstxt::paths_allowed("https://stardewvalleywiki.com/Animal_Products_Profitability")


 stardewvalleywiki.com

[1] TRUE

Code

session <- bow("https://stardewvalleywiki.com/Animal_Products_Profitability", force = TRUE)

#take the second table, because that is the one we are interested in
result_animals <- scrape(session) |>
  html_nodes(css = "table") |> 
  html_table(header = TRUE, fill = TRUE)

sd_animal_prices <- result_animals[[2]]

After scraping, all all we have to do is clean up our tibble since it isn’t in the format we want it to be to join with the rest of our items.

Code

#clean up the sd_animal_prices tibble
tidy_sd_animal_price <- sd_animal_prices |>
  clean_names()|>
  dplyr::select(item, 
         profession, 
         quality, 
         sell_price) |> #select only the columns we want
  group_by(item, profession)|>
  pivot_wider(names_from = quality, 
              values_from = sell_price, 
              names_glue = "{quality}_price",
              values_fn = mean)|>
  clean_names()|>
  mutate(category = "animal product",
         profession = ifelse(profession == "—", NA, profession))

#write the final version to a csv
#write.csv(tidy_sd_animal_price, "animal_product_prices.csv")

tidy_sd_animal_price |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	profession	regular_price	silver_price	gold_price	iridium_price	category
Egg	NA	50	62	75	100	animal product
Egg	Rancher	60	75	90	120	animal product
Egg	Artisan	50	62	75	100	animal product
Large Egg	NA	95	118	142	190	animal product
Large Egg	Rancher	114	142	171	228	animal product
Large Egg	Artisan	95	118	142	190	animal product
Void Egg	NA	65	81	97	130	animal product
Void Egg	Rancher	78	97	117	156	animal product
Void Egg	Artisan	65	81	97	130	animal product
Duck Egg	NA	95	118	142	190	animal product
Duck Egg	Rancher	114	142	171	228	animal product
Duck Egg	Artisan	95	118	142	190	animal product
Wool	NA	340	425	510	680	animal product
Wool	Rancher	408	510	612	816	animal product
Wool	Artisan	340	425	510	680	animal product
Dinosaur Egg	NA	350	437	525	700	animal product
Dinosaur Egg	Rancher	350	437	525	700	animal product
Dinosaur Egg	Artisan	350	437	525	700	animal product
Dinosaur Egg	Treasure Appraisal Guide and Artisan	1050	1311	1575	2100	animal product
Golden Egg	NA	500	625	750	1000	animal product
Golden Egg	Rancher	600	750	900	1200	animal product
Golden Egg	Artisan	500	625	750	1000	animal product
Ostrich Egg	NA	600	750	900	1200	animal product
Ostrich Egg	Rancher	720	900	1080	1440	animal product
Ostrich Egg	Artisan	600	750	900	1200	animal product
Milk	NA	125	156	187	250	animal product
Milk	Rancher	150	187	225	300	animal product
Milk	Artisan	125	156	187	250	animal product
Large Milk	NA	190	237	285	380	animal product
Large Milk	Rancher	228	285	342	456	animal product
Large Milk	Artisan	190	237	285	380	animal product
Goat Milk	NA	225	281	337	450	animal product
Goat Milk	Rancher	270	337	405	540	animal product
Goat Milk	Artisan	225	281	337	450	animal product
Large Goat Milk	NA	345	431	517	690	animal product
Large Goat Milk	Rancher	414	517	621	828	animal product
Large Goat Milk	Artisan	345	431	517	690	animal product
Truffle	NA	625	781	937	1250	animal product
Truffle	Rancher	625	781	937	1250	animal product
Truffle	Artisan	625	781	937	1250	animal product

Minerals

Minerals was one of the easier items to scrape since we were able to scrape the data from a table. However assigning the category and subcategories is what made the process a little more tedious.

Code

# first be polite and check that we can scrape it 
robotstxt::paths_allowed("https://stardewvalleywiki.com/Minerals")


 stardewvalleywiki.com

[1] TRUE

Code

session <- bow("https://stardewvalleywiki.com/Minerals", force = TRUE)

result_minerals <- scrape(session) |>
  html_nodes(css = "table") |> 
  html_table(header = TRUE, fill = TRUE)
# interested in tables 1-4

Again, after collecting our data, all we have to do is clean it up to join with our other categories.

Code

# this function takes a scraped minerals table and preps it for joining with other datasets
tidy_minerals <- function(data, sub_cat){
  data|>
  clean_names()|>
  mutate(item = name,
         category = "mineral",
         sub_category = sub_cat)|>
  rename(regular_sell_price = sell_price)|>
  pivot_longer(
    cols = c(gemologist_sell_price,
             regular_sell_price),
    names_to = "profession",
    values_to = "sell_price"
  )|>
  dplyr::select(item, 
         profession, 
         sell_price,
         category,
         sub_category)|>
  mutate(sell_price = as.numeric(str_extract(sell_price, '(?<=data-sort-value=")\\d+')),
         profession = ifelse(profession == "gemologist_sell_price",
                             "gemologist", NA))
  
 
}

# use function for the 1-3 tables using a for loop
minerals_tbl <- vector("list", length = 4)
mineral_sub_cat <- c("foraged mineral",
                     "gem",
                     "geode mineral",
                     "geode")
for (i in 1:3){
  minerals_tbl[[i]] <- tidy_minerals(result_minerals[[i]], mineral_sub_cat[i])
  
}

# clean up the variable names so that it is ready for the row bind.
# make sure the category is all mineral, and the sub_category is correct
minerals_tbl[[4]]<- result_minerals[[4]]|>
  clean_names()|>
  mutate(item = name,
         category = "mineral",
         sub_category = "geode",
         sell_price = as.numeric(str_extract(sell_price, '(?<=data-sort-value=")\\d+')),
         profession = NA)|>
  dplyr::select(item, sell_price, category, sub_category, profession)

tidy_sd_minerals_price <- bind_rows(minerals_tbl)

Now writing minerals to a csv just in case the website changes or updates.

Code

#write.csv(tidy_sd_minerals_price, "minerals_prices.csv")

tidy_sd_minerals_price |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	profession	sell_price	category	sub_category
Quartz	gemologist	32	mineral	foraged mineral
Quartz	NA	25	mineral	foraged mineral
Earth Crystal	gemologist	65	mineral	foraged mineral
Earth Crystal	NA	50	mineral	foraged mineral
Frozen Tear	gemologist	97	mineral	foraged mineral
Frozen Tear	NA	75	mineral	foraged mineral
Fire Quartz	gemologist	130	mineral	foraged mineral
Fire Quartz	NA	100	mineral	foraged mineral
Emerald	gemologist	325	mineral	gem
Emerald	NA	250	mineral	gem
Aquamarine	gemologist	234	mineral	gem
Aquamarine	NA	180	mineral	gem
Ruby	gemologist	325	mineral	gem
Ruby	NA	250	mineral	gem
Amethyst	gemologist	130	mineral	gem
Amethyst	NA	100	mineral	gem
Topaz	gemologist	104	mineral	gem
Topaz	NA	80	mineral	gem
Jade	gemologist	260	mineral	gem
Jade	NA	200	mineral	gem
Diamond	gemologist	974	mineral	gem
Diamond	NA	750	mineral	gem
Prismatic Shard	gemologist	2600	mineral	gem
Prismatic Shard	NA	2000	mineral	gem
Tigerseye	gemologist	357	mineral	geode mineral
Tigerseye	NA	275	mineral	geode mineral
Opal	gemologist	195	mineral	geode mineral
Opal	NA	150	mineral	geode mineral
Fire Opal	gemologist	455	mineral	geode mineral
Fire Opal	NA	350	mineral	geode mineral
Alamite	gemologist	195	mineral	geode mineral
Alamite	NA	150	mineral	geode mineral
Bixite	gemologist	390	mineral	geode mineral
Bixite	NA	300	mineral	geode mineral
Baryte	gemologist	65	mineral	geode mineral
Baryte	NA	50	mineral	geode mineral
Aerinite	gemologist	162	mineral	geode mineral
Aerinite	NA	125	mineral	geode mineral
Calcite	gemologist	97	mineral	geode mineral
Calcite	NA	75	mineral	geode mineral
Dolomite	gemologist	390	mineral	geode mineral
Dolomite	NA	300	mineral	geode mineral
Esperite	gemologist	130	mineral	geode mineral
Esperite	NA	100	mineral	geode mineral
Fluorapatite	gemologist	260	mineral	geode mineral
Fluorapatite	NA	200	mineral	geode mineral
Geminite	gemologist	195	mineral	geode mineral
Geminite	NA	150	mineral	geode mineral
Helvite	gemologist	585	mineral	geode mineral
Helvite	NA	450	mineral	geode mineral
Jamborite	gemologist	195	mineral	geode mineral
Jamborite	NA	150	mineral	geode mineral
Jagoite	gemologist	149	mineral	geode mineral
Jagoite	NA	115	mineral	geode mineral
Kyanite	gemologist	325	mineral	geode mineral
Kyanite	NA	250	mineral	geode mineral
Lunarite	gemologist	260	mineral	geode mineral
Lunarite	NA	200	mineral	geode mineral
Malachite	gemologist	130	mineral	geode mineral
Malachite	NA	100	mineral	geode mineral
Neptunite	gemologist	520	mineral	geode mineral
Neptunite	NA	400	mineral	geode mineral
Lemon Stone	gemologist	260	mineral	geode mineral
Lemon Stone	NA	200	mineral	geode mineral
Nekoite	gemologist	104	mineral	geode mineral
Nekoite	NA	80	mineral	geode mineral
Orpiment	gemologist	104	mineral	geode mineral
Orpiment	NA	80	mineral	geode mineral
Petrified Slime	gemologist	156	mineral	geode mineral
Petrified Slime	NA	120	mineral	geode mineral
Thunder Egg	gemologist	130	mineral	geode mineral
Thunder Egg	NA	100	mineral	geode mineral
Pyrite	gemologist	156	mineral	geode mineral
Pyrite	NA	120	mineral	geode mineral
Ocean Stone	gemologist	286	mineral	geode mineral
Ocean Stone	NA	220	mineral	geode mineral
Ghost Crystal	gemologist	260	mineral	geode mineral
Ghost Crystal	NA	200	mineral	geode mineral
Jasper	gemologist	195	mineral	geode mineral
Jasper	NA	150	mineral	geode mineral
Celestine	gemologist	162	mineral	geode mineral
Celestine	NA	125	mineral	geode mineral
Marble	gemologist	143	mineral	geode mineral
Marble	NA	110	mineral	geode mineral
Sandstone	gemologist	78	mineral	geode mineral
Sandstone	NA	60	mineral	geode mineral
Granite	gemologist	97	mineral	geode mineral
Granite	NA	75	mineral	geode mineral
Basalt	gemologist	227	mineral	geode mineral
Basalt	NA	175	mineral	geode mineral
Limestone	gemologist	19	mineral	geode mineral
Limestone	NA	15	mineral	geode mineral
Soapstone	gemologist	156	mineral	geode mineral
Soapstone	NA	120	mineral	geode mineral
Hematite	gemologist	195	mineral	geode mineral
Hematite	NA	150	mineral	geode mineral
Mudstone	gemologist	32	mineral	geode mineral
Mudstone	NA	25	mineral	geode mineral
Obsidian	gemologist	260	mineral	geode mineral
Obsidian	NA	200	mineral	geode mineral
Slate	gemologist	110	mineral	geode mineral
Slate	NA	85	mineral	geode mineral
Fairy Stone	gemologist	325	mineral	geode mineral
Fairy Stone	NA	250	mineral	geode mineral
Star Shards	gemologist	650	mineral	geode mineral
Star Shards	NA	500	mineral	geode mineral
Geode	NA	50	mineral	geode
Frozen Geode	NA	100	mineral	geode
Magma Geode	NA	150	mineral	geode
Omni Geode	NA	0	mineral	geode

Combined Dataset

We then merge together all of the data sets for each of the 4 categories: crops, fish, animal products, and minerals.

Code

# binding rows for all of different categories 
stardew_items <- bind_rows(crop_prices, 
                           tidy_sd_animal_price, 
                           tidy_sd_minerals_price,
                           tidy_fish_prices)

#write.csv(stardew_items, "stardew_items.csv")

stardew_items |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	regular_price	silver_price	gold_price	iridium_price	profession	category	sub_category	sell_price
Amaranth	150	187	225	300	NA	crop	Fall Crop	NA
Amaranth	165	205	247	330	tiller	crop	Fall Crop	NA
Ancient_Fruit	550	687	825	1100	NA	crop	Special Crop	NA
Ancient_Fruit	605	755	907	1210	tiller	crop	Special Crop	NA
Apple	100	125	150	200	NA	crop	NA	NA
Apple	110	137	165	220	tiller	crop	NA	NA
Apricot	50	62	75	100	NA	crop	NA	NA
Apricot	55	68	82	110	tiller	crop	NA	NA
Artichoke	160	200	240	320	NA	crop	Fall Crop	NA
Artichoke	176	220	264	352	tiller	crop	Fall Crop	NA
Banana	150	187	225	300	NA	crop	NA	NA
Banana	165	205	247	330	tiller	crop	NA	NA
Beet	100	125	150	200	NA	crop	Fall Crop	NA
Beet	110	137	165	220	tiller	crop	Fall Crop	NA
Blackberry	20	25	30	40	NA	crop	NA	NA
Blue_Jazz	50	62	75	100	NA	crop	Spring Crop	NA
Blue_Jazz	55	68	82	110	tiller	crop	Spring Crop	NA
Blueberry	50	62	75	100	NA	crop	Summer Crop	NA
Blueberry	55	68	82	110	tiller	crop	Summer Crop	NA
Bok_Choy	80	100	120	160	NA	crop	Fall Crop	NA
Bok_Choy	88	110	132	176	tiller	crop	Fall Crop	NA
Broccoli	70	87	105	140	NA	crop	Fall Crop	NA
Broccoli	77	95	115	154	tiller	crop	Fall Crop	NA
Cactus_Fruit	75	93	112	150	NA	crop	Special Crop	NA
Cactus_Fruit	82	102	123	165	NA	crop	Special Crop	NA
Carrot	35	43	52	70	NA	crop	Spring Crop	NA
Carrot	38	47	57	77	tiller	crop	Spring Crop	NA
Cauliflower	175	218	262	350	NA	crop	Spring Crop	NA
Cauliflower	192	239	288	385	tiller	crop	Spring Crop	NA
Cherry	80	100	120	160	NA	crop	NA	NA
Cherry	88	110	132	176	tiller	crop	NA	NA
Corn	50	62	75	100	NA	crop	Summer Crop	NA
Corn	50	62	75	100	NA	crop	Fall Crop	NA
Corn	55	68	82	110	tiller	crop	Summer Crop	NA
Corn	55	68	82	110	tiller	crop	Fall Crop	NA
Cranberries	75	93	112	150	NA	crop	Fall Crop	NA
Cranberries	82	102	123	165	tiller	crop	Fall Crop	NA
Crystal_Fruit	150	187	225	300	NA	crop	NA	NA
Eggplant	60	75	90	120	NA	crop	Fall Crop	NA
Eggplant	66	82	99	132	tiller	crop	Fall Crop	NA
Fairy_Rose	290	362	435	580	NA	crop	Fall Crop	NA
Fairy_Rose	319	398	478	638	tiller	crop	Fall Crop	NA
Fiddlehead_Fern	90	112	135	180	NA	crop	NA	NA
Fiddlehead_Fern	99	123	148	198	tiller	crop	NA	NA
Garlic	60	75	90	120	NA	crop	Spring Crop	NA
Garlic	66	82	99	132	tiller	crop	Spring Crop	NA
Grape	80	100	120	160	NA	crop	Fall Crop	NA
Grape	88	110	132	176	NA	crop	Fall Crop	NA
Green_Bean	40	50	60	80	NA	crop	Spring Crop	NA
Green_Bean	44	55	66	88	tiller	crop	Spring Crop	NA
Hops	25	31	37	50	NA	crop	Summer Crop	NA
Hops	27	34	40	55	tiller	crop	Summer Crop	NA
Hot_Pepper	40	50	60	80	NA	crop	Summer Crop	NA
Hot_Pepper	44	55	66	88	tiller	crop	Summer Crop	NA
Kale	110	137	165	220	NA	crop	Spring Crop	NA
Kale	121	150	181	242	tiller	crop	Spring Crop	NA
Mango	130	162	195	260	NA	crop	NA	NA
Mango	143	178	214	286	tiller	crop	NA	NA
Melon	250	312	375	500	NA	crop	Summer Crop	NA
Melon	275	343	412	550	tiller	crop	Summer Crop	NA
Orange	100	125	150	200	NA	crop	NA	NA
Orange	110	137	165	220	tiller	crop	NA	NA
Parsnip	35	43	52	70	NA	crop	Spring Crop	NA
Parsnip	38	47	57	77	tiller	crop	Spring Crop	NA
Peach	140	175	210	280	NA	crop	NA	NA
Peach	154	192	231	308	tiller	crop	NA	NA
Pineapple	300	375	450	600	NA	crop	Special Crop	NA
Pineapple	330	412	495	660	tiller	crop	Special Crop	NA
Pomegranate	140	175	210	280	NA	crop	NA	NA
Pomegranate	154	192	231	308	tiller	crop	NA	NA
Poppy	140	175	210	280	NA	crop	Summer Crop	NA
Poppy	154	192	231	308	tiller	crop	Summer Crop	NA
Potato	80	100	120	160	NA	crop	Spring Crop	NA
Potato	88	110	132	176	tiller	crop	Spring Crop	NA
Powdermelon	60	75	90	120	NA	crop	Winter Crop	NA
Powdermelon	66	82	99	132	tiller	crop	Winter Crop	NA
Pumpkin	320	400	480	640	NA	crop	Fall Crop	NA
Pumpkin	352	440	528	704	tiller	crop	Fall Crop	NA
Qi_Fruit	1	NA	NA	NA	NA	crop	Special Crop	NA
Qi_Fruit	1	NA	NA	NA	NA	crop	Special Crop	NA
Radish	90	112	135	180	NA	crop	Summer Crop	NA
Radish	99	123	148	198	tiller	crop	Summer Crop	NA
Red_Cabbage	260	325	390	520	NA	crop	Summer Crop	NA
Red_Cabbage	286	357	429	572	tiller	crop	Summer Crop	NA
Rhubarb	220	275	330	440	NA	crop	Spring Crop	NA
Rhubarb	242	302	363	484	tiller	crop	Spring Crop	NA
Spice_Berry	80	100	120	160	NA	crop	NA	NA
Starfruit	750	937	1125	1500	NA	crop	Summer Crop	NA
Starfruit	825	1030	1237	1650	tiller	crop	Summer Crop	NA
Strawberry	120	150	180	240	NA	crop	Spring Crop	NA
Strawberry	132	165	198	264	tiller	crop	Spring Crop	NA
Summer_Spangle	90	112	135	180	NA	crop	Summer Crop	NA
Summer_Spangle	99	123	148	198	tiller	crop	Summer Crop	NA
Summer_Squash	45	56	67	90	NA	crop	Summer Crop	NA
Summer_Squash	49	61	73	99	tiller	crop	Summer Crop	NA
Sunflower	80	100	120	160	NA	crop	Summer Crop	NA
Sunflower	80	100	120	160	NA	crop	Fall Crop	NA
Sunflower	88	110	132	176	tiller	crop	Summer Crop	NA
Sunflower	88	110	132	176	tiller	crop	Fall Crop	NA
Taro_Root	100	125	150	200	NA	crop	Special Crop	NA
Taro_Root	110	137	165	220	tiller	crop	Special Crop	NA
Tea_Leaves	50	NA	NA	NA	NA	crop	Special Crop	NA
Tea_Leaves	55	NA	NA	NA	NA	crop	Special Crop	NA
Tomato	60	75	90	120	NA	crop	Summer Crop	NA
Tomato	66	82	99	132	tiller	crop	Summer Crop	NA
Tulip	30	37	45	60	NA	crop	Spring Crop	NA
Tulip	33	40	49	66	tiller	crop	Spring Crop	NA
Unmilled_Rice	30	37	45	60	NA	crop	Spring Crop	NA
Unmilled_Rice	33	40	49	66	tiller	crop	Spring Crop	NA
Wheat	25	31	37	50	NA	crop	Summer Crop	NA
Wheat	25	31	37	50	NA	crop	Fall Crop	NA
Wheat	27	34	40	55	tiller	crop	Summer Crop	NA
Wheat	27	34	40	55	tiller	crop	Fall Crop	NA
Wild_Plum	80	100	120	160	NA	crop	NA	NA
Yam	160	200	240	320	NA	crop	Fall Crop	NA
Yam	176	220	264	352	tiller	crop	Fall Crop	NA
Egg	50	62	75	100	NA	animal product	NA	NA
Egg	60	75	90	120	Rancher	animal product	NA	NA
Egg	50	62	75	100	Artisan	animal product	NA	NA
Large Egg	95	118	142	190	NA	animal product	NA	NA
Large Egg	114	142	171	228	Rancher	animal product	NA	NA
Large Egg	95	118	142	190	Artisan	animal product	NA	NA
Void Egg	65	81	97	130	NA	animal product	NA	NA
Void Egg	78	97	117	156	Rancher	animal product	NA	NA
Void Egg	65	81	97	130	Artisan	animal product	NA	NA
Duck Egg	95	118	142	190	NA	animal product	NA	NA
Duck Egg	114	142	171	228	Rancher	animal product	NA	NA
Duck Egg	95	118	142	190	Artisan	animal product	NA	NA
Wool	340	425	510	680	NA	animal product	NA	NA
Wool	408	510	612	816	Rancher	animal product	NA	NA
Wool	340	425	510	680	Artisan	animal product	NA	NA
Dinosaur Egg	350	437	525	700	NA	animal product	NA	NA
Dinosaur Egg	350	437	525	700	Rancher	animal product	NA	NA
Dinosaur Egg	350	437	525	700	Artisan	animal product	NA	NA
Dinosaur Egg	1050	1311	1575	2100	Treasure Appraisal Guide and Artisan	animal product	NA	NA
Golden Egg	500	625	750	1000	NA	animal product	NA	NA
Golden Egg	600	750	900	1200	Rancher	animal product	NA	NA
Golden Egg	500	625	750	1000	Artisan	animal product	NA	NA
Ostrich Egg	600	750	900	1200	NA	animal product	NA	NA
Ostrich Egg	720	900	1080	1440	Rancher	animal product	NA	NA
Ostrich Egg	600	750	900	1200	Artisan	animal product	NA	NA
Milk	125	156	187	250	NA	animal product	NA	NA
Milk	150	187	225	300	Rancher	animal product	NA	NA
Milk	125	156	187	250	Artisan	animal product	NA	NA
Large Milk	190	237	285	380	NA	animal product	NA	NA
Large Milk	228	285	342	456	Rancher	animal product	NA	NA
Large Milk	190	237	285	380	Artisan	animal product	NA	NA
Goat Milk	225	281	337	450	NA	animal product	NA	NA
Goat Milk	270	337	405	540	Rancher	animal product	NA	NA
Goat Milk	225	281	337	450	Artisan	animal product	NA	NA
Large Goat Milk	345	431	517	690	NA	animal product	NA	NA
Large Goat Milk	414	517	621	828	Rancher	animal product	NA	NA
Large Goat Milk	345	431	517	690	Artisan	animal product	NA	NA
Truffle	625	781	937	1250	NA	animal product	NA	NA
Truffle	625	781	937	1250	Rancher	animal product	NA	NA
Truffle	625	781	937	1250	Artisan	animal product	NA	NA
Quartz	NA	NA	NA	NA	gemologist	mineral	foraged mineral	32
Quartz	NA	NA	NA	NA	NA	mineral	foraged mineral	25
Earth Crystal	NA	NA	NA	NA	gemologist	mineral	foraged mineral	65
Earth Crystal	NA	NA	NA	NA	NA	mineral	foraged mineral	50
Frozen Tear	NA	NA	NA	NA	gemologist	mineral	foraged mineral	97
Frozen Tear	NA	NA	NA	NA	NA	mineral	foraged mineral	75
Fire Quartz	NA	NA	NA	NA	gemologist	mineral	foraged mineral	130
Fire Quartz	NA	NA	NA	NA	NA	mineral	foraged mineral	100
Emerald	NA	NA	NA	NA	gemologist	mineral	gem	325
Emerald	NA	NA	NA	NA	NA	mineral	gem	250
Aquamarine	NA	NA	NA	NA	gemologist	mineral	gem	234
Aquamarine	NA	NA	NA	NA	NA	mineral	gem	180
Ruby	NA	NA	NA	NA	gemologist	mineral	gem	325
Ruby	NA	NA	NA	NA	NA	mineral	gem	250
Amethyst	NA	NA	NA	NA	gemologist	mineral	gem	130
Amethyst	NA	NA	NA	NA	NA	mineral	gem	100
Topaz	NA	NA	NA	NA	gemologist	mineral	gem	104
Topaz	NA	NA	NA	NA	NA	mineral	gem	80
Jade	NA	NA	NA	NA	gemologist	mineral	gem	260
Jade	NA	NA	NA	NA	NA	mineral	gem	200
Diamond	NA	NA	NA	NA	gemologist	mineral	gem	974
Diamond	NA	NA	NA	NA	NA	mineral	gem	750
Prismatic Shard	NA	NA	NA	NA	gemologist	mineral	gem	2600
Prismatic Shard	NA	NA	NA	NA	NA	mineral	gem	2000
Tigerseye	NA	NA	NA	NA	gemologist	mineral	geode mineral	357
Tigerseye	NA	NA	NA	NA	NA	mineral	geode mineral	275
Opal	NA	NA	NA	NA	gemologist	mineral	geode mineral	195
Opal	NA	NA	NA	NA	NA	mineral	geode mineral	150
Fire Opal	NA	NA	NA	NA	gemologist	mineral	geode mineral	455
Fire Opal	NA	NA	NA	NA	NA	mineral	geode mineral	350
Alamite	NA	NA	NA	NA	gemologist	mineral	geode mineral	195
Alamite	NA	NA	NA	NA	NA	mineral	geode mineral	150
Bixite	NA	NA	NA	NA	gemologist	mineral	geode mineral	390
Bixite	NA	NA	NA	NA	NA	mineral	geode mineral	300
Baryte	NA	NA	NA	NA	gemologist	mineral	geode mineral	65
Baryte	NA	NA	NA	NA	NA	mineral	geode mineral	50
Aerinite	NA	NA	NA	NA	gemologist	mineral	geode mineral	162
Aerinite	NA	NA	NA	NA	NA	mineral	geode mineral	125
Calcite	NA	NA	NA	NA	gemologist	mineral	geode mineral	97
Calcite	NA	NA	NA	NA	NA	mineral	geode mineral	75
Dolomite	NA	NA	NA	NA	gemologist	mineral	geode mineral	390
Dolomite	NA	NA	NA	NA	NA	mineral	geode mineral	300
Esperite	NA	NA	NA	NA	gemologist	mineral	geode mineral	130
Esperite	NA	NA	NA	NA	NA	mineral	geode mineral	100
Fluorapatite	NA	NA	NA	NA	gemologist	mineral	geode mineral	260
Fluorapatite	NA	NA	NA	NA	NA	mineral	geode mineral	200
Geminite	NA	NA	NA	NA	gemologist	mineral	geode mineral	195
Geminite	NA	NA	NA	NA	NA	mineral	geode mineral	150
Helvite	NA	NA	NA	NA	gemologist	mineral	geode mineral	585
Helvite	NA	NA	NA	NA	NA	mineral	geode mineral	450
Jamborite	NA	NA	NA	NA	gemologist	mineral	geode mineral	195
Jamborite	NA	NA	NA	NA	NA	mineral	geode mineral	150
Jagoite	NA	NA	NA	NA	gemologist	mineral	geode mineral	149
Jagoite	NA	NA	NA	NA	NA	mineral	geode mineral	115
Kyanite	NA	NA	NA	NA	gemologist	mineral	geode mineral	325
Kyanite	NA	NA	NA	NA	NA	mineral	geode mineral	250
Lunarite	NA	NA	NA	NA	gemologist	mineral	geode mineral	260
Lunarite	NA	NA	NA	NA	NA	mineral	geode mineral	200
Malachite	NA	NA	NA	NA	gemologist	mineral	geode mineral	130
Malachite	NA	NA	NA	NA	NA	mineral	geode mineral	100
Neptunite	NA	NA	NA	NA	gemologist	mineral	geode mineral	520
Neptunite	NA	NA	NA	NA	NA	mineral	geode mineral	400
Lemon Stone	NA	NA	NA	NA	gemologist	mineral	geode mineral	260
Lemon Stone	NA	NA	NA	NA	NA	mineral	geode mineral	200
Nekoite	NA	NA	NA	NA	gemologist	mineral	geode mineral	104
Nekoite	NA	NA	NA	NA	NA	mineral	geode mineral	80
Orpiment	NA	NA	NA	NA	gemologist	mineral	geode mineral	104
Orpiment	NA	NA	NA	NA	NA	mineral	geode mineral	80
Petrified Slime	NA	NA	NA	NA	gemologist	mineral	geode mineral	156
Petrified Slime	NA	NA	NA	NA	NA	mineral	geode mineral	120
Thunder Egg	NA	NA	NA	NA	gemologist	mineral	geode mineral	130
Thunder Egg	NA	NA	NA	NA	NA	mineral	geode mineral	100
Pyrite	NA	NA	NA	NA	gemologist	mineral	geode mineral	156
Pyrite	NA	NA	NA	NA	NA	mineral	geode mineral	120
Ocean Stone	NA	NA	NA	NA	gemologist	mineral	geode mineral	286
Ocean Stone	NA	NA	NA	NA	NA	mineral	geode mineral	220
Ghost Crystal	NA	NA	NA	NA	gemologist	mineral	geode mineral	260
Ghost Crystal	NA	NA	NA	NA	NA	mineral	geode mineral	200
Jasper	NA	NA	NA	NA	gemologist	mineral	geode mineral	195
Jasper	NA	NA	NA	NA	NA	mineral	geode mineral	150
Celestine	NA	NA	NA	NA	gemologist	mineral	geode mineral	162
Celestine	NA	NA	NA	NA	NA	mineral	geode mineral	125
Marble	NA	NA	NA	NA	gemologist	mineral	geode mineral	143
Marble	NA	NA	NA	NA	NA	mineral	geode mineral	110
Sandstone	NA	NA	NA	NA	gemologist	mineral	geode mineral	78
Sandstone	NA	NA	NA	NA	NA	mineral	geode mineral	60
Granite	NA	NA	NA	NA	gemologist	mineral	geode mineral	97
Granite	NA	NA	NA	NA	NA	mineral	geode mineral	75
Basalt	NA	NA	NA	NA	gemologist	mineral	geode mineral	227
Basalt	NA	NA	NA	NA	NA	mineral	geode mineral	175
Limestone	NA	NA	NA	NA	gemologist	mineral	geode mineral	19
Limestone	NA	NA	NA	NA	NA	mineral	geode mineral	15
Soapstone	NA	NA	NA	NA	gemologist	mineral	geode mineral	156
Soapstone	NA	NA	NA	NA	NA	mineral	geode mineral	120
Hematite	NA	NA	NA	NA	gemologist	mineral	geode mineral	195
Hematite	NA	NA	NA	NA	NA	mineral	geode mineral	150
Mudstone	NA	NA	NA	NA	gemologist	mineral	geode mineral	32
Mudstone	NA	NA	NA	NA	NA	mineral	geode mineral	25
Obsidian	NA	NA	NA	NA	gemologist	mineral	geode mineral	260
Obsidian	NA	NA	NA	NA	NA	mineral	geode mineral	200
Slate	NA	NA	NA	NA	gemologist	mineral	geode mineral	110
Slate	NA	NA	NA	NA	NA	mineral	geode mineral	85
Fairy Stone	NA	NA	NA	NA	gemologist	mineral	geode mineral	325
Fairy Stone	NA	NA	NA	NA	NA	mineral	geode mineral	250
Star Shards	NA	NA	NA	NA	gemologist	mineral	geode mineral	650
Star Shards	NA	NA	NA	NA	NA	mineral	geode mineral	500
Geode	NA	NA	NA	NA	NA	mineral	geode	50
Frozen Geode	NA	NA	NA	NA	NA	mineral	geode	100
Magma Geode	NA	NA	NA	NA	NA	mineral	geode	150
Omni Geode	NA	NA	NA	NA	NA	mineral	geode	0
Albacore	75	93	112	150	NA	fish	The Beach	NA
Albacore	93	116	140	187	fisher	fish	The Beach	NA
Albacore	112	139	168	225	angler	fish	The Beach	NA
Anchovy	30	37	45	60	NA	fish	The Beach	NA
Anchovy	37	46	56	75	fisher	fish	The Beach	NA
Anchovy	45	55	67	90	angler	fish	The Beach	NA
Angler	900	1125	1350	1800	NA	fish	Legendary	NA
Angler	900	1125	1350	1800	NA	fish	River	NA
Angler	1125	1406	1687	2250	fisher	fish	Legendary	NA
Angler	1125	1406	1687	2250	fisher	fish	River	NA
Angler	1350	1687	2025	2700	angler	fish	Legendary	NA
Angler	1350	1687	2025	2700	angler	fish	River	NA
Blobfish	500	625	750	1000	NA	fish	Night Market	NA
Blobfish	625	781	937	1250	fisher	fish	Night Market	NA
Blobfish	750	937	1125	1500	angler	fish	Night Market	NA
Blue_Discus	120	150	180	240	NA	fish	Ginger Island	NA
Blue_Discus	150	187	225	300	fisher	fish	Ginger Island	NA
Blue_Discus	180	225	270	360	angler	fish	Ginger Island	NA
Bream	45	56	67	90	NA	fish	River	NA
Bream	56	70	83	112	fisher	fish	River	NA
Bream	67	84	100	135	angler	fish	River	NA
Bullhead	75	93	112	150	NA	fish	Mountain Lake	NA
Bullhead	93	116	140	187	fisher	fish	Mountain Lake	NA
Bullhead	112	139	168	225	angler	fish	Mountain Lake	NA
Carp	30	37	45	60	NA	fish	Mountain Lake	NA
Carp	30	37	45	60	NA	fish	Secret Woods	NA
Carp	30	37	45	60	NA	fish	Sewers	NA
Carp	30	37	45	60	NA	fish	Mutant Bug Lair	NA
Carp	37	46	56	75	fisher	fish	Mountain Lake	NA
Carp	37	46	56	75	fisher	fish	Secret Woods	NA
Carp	37	46	56	75	fisher	fish	Sewers	NA
Carp	37	46	56	75	fisher	fish	Mutant Bug Lair	NA
Carp	45	55	67	90	angler	fish	Mountain Lake	NA
Carp	45	55	67	90	angler	fish	Secret Woods	NA
Carp	45	55	67	90	angler	fish	Sewers	NA
Carp	45	55	67	90	angler	fish	Mutant Bug Lair	NA
Catfish	200	250	300	400	NA	fish	River	NA
Catfish	200	250	300	400	NA	fish	Secret Woods	NA
Catfish	200	250	300	400	NA	fish	Witch's Swamp	NA
Catfish	250	312	375	500	fisher	fish	River	NA
Catfish	250	312	375	500	fisher	fish	Secret Woods	NA
Catfish	250	312	375	500	fisher	fish	Witch's Swamp	NA
Catfish	300	375	450	600	angler	fish	River	NA
Catfish	300	375	450	600	angler	fish	Secret Woods	NA
Catfish	300	375	450	600	angler	fish	Witch's Swamp	NA
Chub	50	62	75	100	NA	fish	River	NA
Chub	50	62	75	100	NA	fish	Mountain Lake	NA
Chub	62	77	93	125	fisher	fish	River	NA
Chub	62	77	93	125	fisher	fish	Mountain Lake	NA
Chub	75	93	112	150	angler	fish	River	NA
Chub	75	93	112	150	angler	fish	Mountain Lake	NA
Clam	50	62	75	100	NA	fish	Crab Pot	NA
Clam	62	77	93	125	fisher	fish	Crab Pot	NA
Clam	75	93	112	150	angler	fish	Crab Pot	NA
Cockle	50	62	75	100	NA	fish	Crab Pot	NA
Cockle	62	77	93	125	fisher	fish	Crab Pot	NA
Cockle	75	93	112	150	angler	fish	Crab Pot	NA
Crab	100	125	NA	NA	NA	fish	Crab Pot	NA
Crab	125	156	NA	NA	fisher	fish	Crab Pot	NA
Crab	150	187	NA	NA	angler	fish	Crab Pot	NA
Crayfish	75	93	NA	NA	NA	fish	Crab Pot	NA
Crayfish	93	116	NA	NA	fisher	fish	Crab Pot	NA
Crayfish	112	139	NA	NA	angler	fish	Crab Pot	NA
Crimsonfish	1500	1875	2250	3000	NA	fish	Legendary	NA
Crimsonfish	1500	1875	2250	3000	NA	fish	The Beach	NA
Crimsonfish	1875	2343	2812	3750	fisher	fish	Legendary	NA
Crimsonfish	1875	2343	2812	3750	fisher	fish	The Beach	NA
Crimsonfish	2250	2812	3375	4500	angler	fish	Legendary	NA
Crimsonfish	2250	2812	3375	4500	angler	fish	The Beach	NA
Dorado	100	125	150	200	NA	fish	River	NA
Dorado	125	156	187	250	fisher	fish	River	NA
Dorado	150	187	225	300	angler	fish	River	NA
Eel	85	106	127	170	NA	fish	The Beach	NA
Eel	106	132	158	212	fisher	fish	The Beach	NA
Eel	127	159	190	255	angler	fish	The Beach	NA
Flounder	100	125	150	200	NA	fish	The Beach	NA
Flounder	100	125	150	200	NA	fish	Ginger Island	NA
Flounder	125	156	187	250	fisher	fish	The Beach	NA
Flounder	125	156	187	250	fisher	fish	Ginger Island	NA
Flounder	150	187	225	300	angler	fish	The Beach	NA
Flounder	150	187	225	300	angler	fish	Ginger Island	NA
Ghostfish	45	56	67	90	NA	fish	Mines	NA
Ghostfish	56	70	83	112	fisher	fish	Mines	NA
Ghostfish	67	84	100	135	angler	fish	Mines	NA
Glacierfish	1000	1250	1500	2000	NA	fish	Legendary	NA
Glacierfish	1000	1250	1500	2000	NA	fish	River	NA
Glacierfish	1250	1562	1875	2500	fisher	fish	Legendary	NA
Glacierfish	1250	1562	1875	2500	fisher	fish	River	NA
Glacierfish	1500	1875	2250	3000	angler	fish	Legendary	NA
Glacierfish	1500	1875	2250	3000	angler	fish	River	NA
Glacierfish_Jr.	1000	1250	1500	2000	NA	fish	Legendary	NA
Glacierfish_Jr.	1000	1250	1500	2000	NA	fish	River	NA
Glacierfish_Jr.	1250	1562	1875	2500	fisher	fish	Legendary	NA
Glacierfish_Jr.	1250	1562	1875	2500	fisher	fish	River	NA
Glacierfish_Jr.	1500	1875	2250	3000	angler	fish	Legendary	NA
Glacierfish_Jr.	1500	1875	2250	3000	angler	fish	River	NA
Goby	150	187	225	300	NA	fish	River	NA
Goby	187	233	281	375	fisher	fish	River	NA
Goby	225	280	337	450	angler	fish	River	NA
Halibut	80	100	120	160	NA	fish	The Beach	NA
Halibut	100	125	150	200	fisher	fish	The Beach	NA
Halibut	120	150	180	240	angler	fish	The Beach	NA
Herring	30	37	45	60	NA	fish	The Beach	NA
Herring	37	46	56	75	fisher	fish	The Beach	NA
Herring	45	55	67	90	angler	fish	The Beach	NA
Ice_Pip	500	625	750	1000	NA	fish	Mines	NA
Ice_Pip	625	781	937	1250	fisher	fish	Mines	NA
Ice_Pip	750	937	1125	1500	angler	fish	Mines	NA
Largemouth_Bass	100	125	150	200	NA	fish	Mountain Lake	NA
Largemouth_Bass	125	156	187	250	fisher	fish	Mountain Lake	NA
Largemouth_Bass	150	187	225	300	angler	fish	Mountain Lake	NA
Lava_Eel	700	875	1050	1400	NA	fish	Mines	NA
Lava_Eel	700	875	1050	1400	NA	fish	Ginger Island	NA
Lava_Eel	875	1093	1312	1750	fisher	fish	Mines	NA
Lava_Eel	875	1093	1312	1750	fisher	fish	Ginger Island	NA
Lava_Eel	1050	1312	1575	2100	angler	fish	Mines	NA
Lava_Eel	1050	1312	1575	2100	angler	fish	Ginger Island	NA
Legend	5000	6250	7500	10000	NA	fish	Legendary	NA
Legend	5000	6250	7500	10000	NA	fish	Mountain Lake	NA
Legend	6250	7812	9375	12500	fisher	fish	Legendary	NA
Legend	6250	7812	9375	12500	fisher	fish	Mountain Lake	NA
Legend	7500	9375	11250	15000	angler	fish	Legendary	NA
Legend	7500	9375	11250	15000	angler	fish	Mountain Lake	NA
Legend_II	5000	6250	7500	10000	NA	fish	Legendary	NA
Legend_II	5000	6250	7500	10000	NA	fish	Mountain Lake	NA
Legend_II	6250	7812	9375	12500	fisher	fish	Legendary	NA
Legend_II	6250	7812	9375	12500	fisher	fish	Mountain Lake	NA
Legend_II	7500	9375	11250	15000	angler	fish	Legendary	NA
Legend_II	7500	9375	11250	15000	angler	fish	Mountain Lake	NA
Lingcod	120	150	180	240	NA	fish	River	NA
Lingcod	120	150	180	240	NA	fish	Mountain Lake	NA
Lingcod	150	187	225	300	fisher	fish	River	NA
Lingcod	150	187	225	300	fisher	fish	Mountain Lake	NA
Lingcod	180	225	270	360	angler	fish	River	NA
Lingcod	180	225	270	360	angler	fish	Mountain Lake	NA
Lionfish	100	125	150	200	NA	fish	Ginger Island	NA
Lionfish	125	156	187	250	fisher	fish	Ginger Island	NA
Lionfish	150	187	225	300	angler	fish	Ginger Island	NA
Lobster	120	150	NA	NA	NA	fish	Crab Pot	NA
Lobster	150	187	NA	NA	fisher	fish	Crab Pot	NA
Lobster	180	225	NA	NA	angler	fish	Crab Pot	NA
Midnight_Carp	150	187	225	300	NA	fish	Mountain Lake	NA
Midnight_Carp	150	187	225	300	NA	fish	Cindersap Forest Pond	NA
Midnight_Carp	150	187	225	300	NA	fish	Ginger Island	NA
Midnight_Carp	187	233	281	375	fisher	fish	Mountain Lake	NA
Midnight_Carp	187	233	281	375	fisher	fish	Cindersap Forest Pond	NA
Midnight_Carp	187	233	281	375	fisher	fish	Ginger Island	NA
Midnight_Carp	225	280	337	450	angler	fish	Mountain Lake	NA
Midnight_Carp	225	280	337	450	angler	fish	Cindersap Forest Pond	NA
Midnight_Carp	225	280	337	450	angler	fish	Ginger Island	NA
Midnight_Squid	100	125	150	200	NA	fish	Night Market	NA
Midnight_Squid	125	156	187	250	fisher	fish	Night Market	NA
Midnight_Squid	150	187	225	300	angler	fish	Night Market	NA
Ms._Angler	900	1125	1350	1800	NA	fish	Legendary	NA
Ms._Angler	900	1125	1350	1800	NA	fish	River	NA
Ms._Angler	1125	1406	1687	2250	fisher	fish	Legendary	NA
Ms._Angler	1125	1406	1687	2250	fisher	fish	River	NA
Ms._Angler	1350	1687	2025	2700	angler	fish	Legendary	NA
Ms._Angler	1350	1687	2025	2700	angler	fish	River	NA
Mussel	30	37	45	60	NA	fish	Crab Pot	NA
Mussel	37	46	56	75	fisher	fish	Crab Pot	NA
Mussel	45	55	67	90	angler	fish	Crab Pot	NA
Mutant_Carp	1000	1250	1500	2000	NA	fish	Legendary	NA
Mutant_Carp	1000	1250	1500	2000	NA	fish	Sewers	NA
Mutant_Carp	1250	1562	1875	2500	fisher	fish	Legendary	NA
Mutant_Carp	1250	1562	1875	2500	fisher	fish	Sewers	NA
Mutant_Carp	1500	1875	2250	3000	angler	fish	Legendary	NA
Mutant_Carp	1500	1875	2250	3000	angler	fish	Sewers	NA
Octopus	150	187	225	300	NA	fish	The Beach	NA
Octopus	150	187	225	300	NA	fish	Night Market	NA
Octopus	150	187	225	300	NA	fish	Ginger Island	NA
Octopus	187	233	281	375	fisher	fish	The Beach	NA
Octopus	187	233	281	375	fisher	fish	Night Market	NA
Octopus	187	233	281	375	fisher	fish	Ginger Island	NA
Octopus	225	280	337	450	angler	fish	The Beach	NA
Octopus	225	280	337	450	angler	fish	Night Market	NA
Octopus	225	280	337	450	angler	fish	Ginger Island	NA
Oyster	40	50	60	80	NA	fish	Crab Pot	NA
Oyster	50	62	75	100	fisher	fish	Crab Pot	NA
Oyster	60	75	90	120	angler	fish	Crab Pot	NA
Perch	55	68	82	110	NA	fish	River	NA
Perch	55	68	82	110	NA	fish	Mountain Lake	NA
Perch	55	68	82	110	NA	fish	Cindersap Forest Pond	NA
Perch	68	85	102	137	fisher	fish	River	NA
Perch	68	85	102	137	fisher	fish	Mountain Lake	NA
Perch	68	85	102	137	fisher	fish	Cindersap Forest Pond	NA
Perch	82	102	123	165	angler	fish	River	NA
Perch	82	102	123	165	angler	fish	Mountain Lake	NA
Perch	82	102	123	165	angler	fish	Cindersap Forest Pond	NA
Periwinkle	20	25	NA	NA	NA	fish	Crab Pot	NA
Periwinkle	25	31	NA	NA	fisher	fish	Crab Pot	NA
Periwinkle	30	37	NA	NA	angler	fish	Crab Pot	NA
Pike	100	125	150	200	NA	fish	River	NA
Pike	100	125	150	200	NA	fish	Cindersap Forest Pond	NA
Pike	125	156	187	250	fisher	fish	River	NA
Pike	125	156	187	250	fisher	fish	Cindersap Forest Pond	NA
Pike	150	187	225	300	angler	fish	River	NA
Pike	150	187	225	300	angler	fish	Cindersap Forest Pond	NA
Pufferfish	200	250	300	400	NA	fish	The Beach	NA
Pufferfish	200	250	300	400	NA	fish	Ginger Island	NA
Pufferfish	250	312	375	500	fisher	fish	The Beach	NA
Pufferfish	250	312	375	500	fisher	fish	Ginger Island	NA
Pufferfish	300	375	450	600	angler	fish	The Beach	NA
Pufferfish	300	375	450	600	angler	fish	Ginger Island	NA
Radioactive_Carp	1000	1250	1500	2000	NA	fish	Legendary	NA
Radioactive_Carp	1000	1250	1500	2000	NA	fish	Sewers	NA
Radioactive_Carp	1250	1562	1875	2500	fisher	fish	Legendary	NA
Radioactive_Carp	1250	1562	1875	2500	fisher	fish	Sewers	NA
Radioactive_Carp	1500	1875	2250	3000	angler	fish	Legendary	NA
Radioactive_Carp	1500	1875	2250	3000	angler	fish	Sewers	NA
Rainbow_Trout	65	81	97	130	NA	fish	River	NA
Rainbow_Trout	65	81	97	130	NA	fish	Mountain Lake	NA
Rainbow_Trout	81	101	121	162	fisher	fish	River	NA
Rainbow_Trout	81	101	121	162	fisher	fish	Mountain Lake	NA
Rainbow_Trout	97	121	145	195	angler	fish	River	NA
Rainbow_Trout	97	121	145	195	angler	fish	Mountain Lake	NA
Red_Mullet	75	93	112	150	NA	fish	The Beach	NA
Red_Mullet	93	116	140	187	fisher	fish	The Beach	NA
Red_Mullet	112	139	168	225	angler	fish	The Beach	NA
Red_Snapper	50	62	75	100	NA	fish	The Beach	NA
Red_Snapper	62	77	93	125	fisher	fish	The Beach	NA
Red_Snapper	75	93	112	150	angler	fish	The Beach	NA
Salmon	75	93	112	150	NA	fish	River	NA
Salmon	93	116	140	187	fisher	fish	River	NA
Salmon	112	139	168	225	angler	fish	River	NA
Sandfish	75	93	112	150	NA	fish	Desert	NA
Sandfish	93	116	140	187	fisher	fish	Desert	NA
Sandfish	112	139	168	225	angler	fish	Desert	NA
Sardine	40	50	60	80	NA	fish	The Beach	NA
Sardine	50	62	75	100	fisher	fish	The Beach	NA
Sardine	60	75	90	120	angler	fish	The Beach	NA
Scorpion_Carp	150	187	225	300	NA	fish	Desert	NA
Scorpion_Carp	187	233	281	375	fisher	fish	Desert	NA
Scorpion_Carp	225	280	337	450	angler	fish	Desert	NA
Sea_Cucumber	75	93	112	150	NA	fish	The Beach	NA
Sea_Cucumber	75	93	112	150	NA	fish	Night Market	NA
Sea_Cucumber	93	116	140	187	fisher	fish	The Beach	NA
Sea_Cucumber	93	116	140	187	fisher	fish	Night Market	NA
Sea_Cucumber	112	139	168	225	angler	fish	The Beach	NA
Sea_Cucumber	112	139	168	225	angler	fish	Night Market	NA
Shad	60	75	90	120	NA	fish	River	NA
Shad	75	93	112	150	fisher	fish	River	NA
Shad	90	112	135	180	angler	fish	River	NA
Shrimp	60	75	NA	NA	NA	fish	Crab Pot	NA
Shrimp	75	93	NA	NA	fisher	fish	Crab Pot	NA
Shrimp	90	112	NA	NA	angler	fish	Crab Pot	NA
Slimejack	100	125	150	200	NA	fish	Mutant Bug Lair	NA
Slimejack	125	156	187	250	fisher	fish	Mutant Bug Lair	NA
Slimejack	150	187	225	300	angler	fish	Mutant Bug Lair	NA
Smallmouth_Bass	50	62	75	100	NA	fish	River	NA
Smallmouth_Bass	50	62	75	100	NA	fish	Cindersap Forest Pond	NA
Smallmouth_Bass	62	77	93	125	fisher	fish	River	NA
Smallmouth_Bass	62	77	93	125	fisher	fish	Cindersap Forest Pond	NA
Smallmouth_Bass	75	93	112	150	angler	fish	River	NA
Smallmouth_Bass	75	93	112	150	angler	fish	Cindersap Forest Pond	NA
Snail	65	81	NA	NA	NA	fish	Crab Pot	NA
Snail	81	101	NA	NA	fisher	fish	Crab Pot	NA
Snail	97	121	NA	NA	angler	fish	Crab Pot	NA
Son_of_Crimsonfish	1500	1875	2250	3000	NA	fish	Legendary	NA
Son_of_Crimsonfish	1500	1875	2250	3000	NA	fish	The Beach	NA
Son_of_Crimsonfish	1875	2343	2812	3750	fisher	fish	Legendary	NA
Son_of_Crimsonfish	1875	2343	2812	3750	fisher	fish	The Beach	NA
Son_of_Crimsonfish	2250	2812	3375	4500	angler	fish	Legendary	NA
Son_of_Crimsonfish	2250	2812	3375	4500	angler	fish	The Beach	NA
Spook_Fish	220	275	330	440	NA	fish	Night Market	NA
Spook_Fish	275	343	412	550	fisher	fish	Night Market	NA
Spook_Fish	330	412	495	660	angler	fish	Night Market	NA
Squid	80	100	120	160	NA	fish	The Beach	NA
Squid	100	125	150	200	fisher	fish	The Beach	NA
Squid	120	150	180	240	angler	fish	The Beach	NA
Stingray	180	225	270	360	NA	fish	Ginger Island	NA
Stingray	225	281	337	450	fisher	fish	Ginger Island	NA
Stingray	270	337	405	540	angler	fish	Ginger Island	NA
Stonefish	300	375	450	600	NA	fish	Mines	NA
Stonefish	375	468	562	750	fisher	fish	Mines	NA
Stonefish	450	562	675	900	angler	fish	Mines	NA
Sturgeon	200	250	300	400	NA	fish	Mountain Lake	NA
Sturgeon	250	312	375	500	fisher	fish	Mountain Lake	NA
Sturgeon	300	375	450	600	angler	fish	Mountain Lake	NA
Sunfish	30	37	45	60	NA	fish	River	NA
Sunfish	37	46	56	75	fisher	fish	River	NA
Sunfish	45	55	67	90	angler	fish	River	NA
Super_Cucumber	250	312	375	500	NA	fish	The Beach	NA
Super_Cucumber	250	312	375	500	NA	fish	Night Market	NA
Super_Cucumber	312	390	468	625	fisher	fish	The Beach	NA
Super_Cucumber	312	390	468	625	fisher	fish	Night Market	NA
Super_Cucumber	375	468	562	750	angler	fish	The Beach	NA
Super_Cucumber	375	468	562	750	angler	fish	Night Market	NA
Tiger_Trout	150	187	225	300	NA	fish	River	NA
Tiger_Trout	187	233	281	375	fisher	fish	River	NA
Tiger_Trout	225	280	337	450	angler	fish	River	NA
Tilapia	75	93	112	150	NA	fish	The Beach	NA
Tilapia	75	93	112	150	NA	fish	Ginger Island	NA
Tilapia	93	116	140	187	fisher	fish	The Beach	NA
Tilapia	93	116	140	187	fisher	fish	Ginger Island	NA
Tilapia	112	139	168	225	angler	fish	The Beach	NA
Tilapia	112	139	168	225	angler	fish	Ginger Island	NA
Tuna	100	125	150	200	NA	fish	The Beach	NA
Tuna	100	125	150	200	NA	fish	Ginger Island	NA
Tuna	125	156	187	250	fisher	fish	The Beach	NA
Tuna	125	156	187	250	fisher	fish	Ginger Island	NA
Tuna	150	187	225	300	angler	fish	The Beach	NA
Tuna	150	187	225	300	angler	fish	Ginger Island	NA
Void_Salmon	150	187	225	300	NA	fish	Witch's Swamp	NA
Void_Salmon	187	233	281	375	fisher	fish	Witch's Swamp	NA
Void_Salmon	225	280	337	450	angler	fish	Witch's Swamp	NA
Walleye	105	131	157	210	NA	fish	River	NA
Walleye	105	131	157	210	NA	fish	Mountain Lake	NA
Walleye	105	131	157	210	NA	fish	Cindersap Forest Pond	NA
Walleye	131	163	196	262	fisher	fish	River	NA
Walleye	131	163	196	262	fisher	fish	Mountain Lake	NA
Walleye	131	163	196	262	fisher	fish	Cindersap Forest Pond	NA
Walleye	157	196	235	315	angler	fish	River	NA
Walleye	157	196	235	315	angler	fish	Mountain Lake	NA
Walleye	157	196	235	315	angler	fish	Cindersap Forest Pond	NA
Woodskip	75	93	112	150	NA	fish	Secret Woods	NA
Woodskip	93	116	140	187	fisher	fish	Secret Woods	NA
Woodskip	112	139	168	225	angler	fish	Secret Woods	NA

Additional Data

Seeds

While working on our shiny app we realized that we needed additional data for crops involving the seed data for the crop because it consisted of growth time which is how long the crop takes to grow.

Code

# make sure can scrape
seed <- bow("https://stardewvalleywiki.com/Potato_Seeds", force = TRUE)

result <- scrape(seed) |>
  html_nodes(css = "table") |>
  html_table(header = TRUE, fill = TRUE)

seeds <- result[[4]][2] #table of the seeds so we can use that list

seeds <- seeds |>
  mutate(Seed = strsplit(`Seeds, Starters, and Saplings`, " • ", fixed = TRUE)) |>
  unnest(Seed) |>
  mutate(Seed = str_replace_all(Seed, " ", "_")) |>
  distinct(Seed) |>
  filter(Seed != "Coffee_Beans")

Like our other categories we created a function to scrape the seed data.

Code

get_growth <- function(page, css_selector) {
  page |>
  html_nodes(css_selector) |>
  html_text()
}

# function for growth time
seeddeets <- function(seed) {
  url <- str_c("https://stardewvalleywiki.com/", seed)
    page <- read_html(url)
    growth_time <- get_growth(page, "tr:nth-child(6) #infoboxdetail")
    general_store <- get_growth(page, "tr:nth-child(10) #infoboxdetail .no-wrap")
    jojamart <- get_growth(page, "tr:nth-child(11) #infoboxdetail .no-wrap")
    oasis <- get_growth(page, "tr:nth-child(12) #infoboxdetail , .no-wrap+ #infoboxdetail .no-wrap")
    item <- seed
    
    seedinfo_tbl <- tibble(
      item = item,
      growth_time = parse_number(growth_time),
      general_store = parse_number(general_store), 
      jojamart = parse_number(jojamart),
      #oasis = parse_number(oasis)
    )
}

# list of all seeds
seeds_list <- as.vector(seeds$Seed)

details <- purrr::map(seeds_list, seeddeets)

draft_seed <- bind_rows(details) |>
  arrange(item)

# check which seeds didn't work
empty_indices <- which(sapply(details, function(tbl) nrow(tbl) == 0))

# assign to list
seeds_needed <- seeds_list[empty_indices]

Another function for the seeds needed from above.

Code

# function for growth time
seeddeets2 <- function(seed) {
  url <- str_c("https://stardewvalleywiki.com/", seed)
    page <- read_html(url)
    growth_time <- get_growth(page, "tr:nth-child(6) #infoboxdetail")
    general_store <- get_growth(page, "tr:nth-child(10) #infoboxdetail")
    jojamart <- get_growth(page, "tr:nth-child(11) #infoboxdetail")
    item <- seed
    
    seedinfo_tbl <- tibble(
      item = item,
      growth_time = parse_number(growth_time),
      general_store = parse_number(str_extract(general_store, "[0-9]+")), 
      jojamart = parse_number(jojamart)
      )}

details2 <- purrr::map(seeds_needed, seeddeets2)

draft_seed2 <- bind_rows(details2) |>
  arrange(item)

empty_indices2 <- which(sapply(details2, function(tbl) nrow(tbl) == 0))

# seeds needed again
seeds_needed2 <- seeds_needed[empty_indices2]

#bind together rows since no more seeds needed
seed_details <- bind_rows(details, details2) |>
  arrange(item)

After collecting all the information we found that we weren’t able to just join the crops dataset with our seed details since the names are very off, for example we aren’t able to join Amarath_Seeds with Amarath since it has the seeds at the end or Apples with Apple_Saplings, or Pepper_Seeds with Hot_Pepper, so we had to manually look at our data and string replace lots of items that would’ve ended up lost in the join.

Code

# manually change names so we can join together with crops later.
seed_deets <- seed_details |>
  mutate(item = str_replace(item, "_Seeds?", ""),
         item = str_replace(item, "_Saplings?", ""),
         item = str_replace(item, "_Bulb", ""),
         item = str_replace(item, "_Starter", ""),
         item = str_replace(item, "_Shoots?", ""),
         item = str_replace(item, "_Tuber", ""),
         item = str_replace(item, "_Bean", "_Fruit"),
         item = str_replace(item, "Cactus", "Cactus_Fruit"),
         item = str_replace(item, "Fairy", "Fairy_Rose"),
         item = str_replace(item, "Jazz", "Blue_Jazz"),
         item = str_replace(item, "Tea", "Tea_Leaves"),
         item = str_replace(item, "Taro", "Taro_Root"),
         item = str_replace(item, "Spangle", "Summer_Spangle"),
         item = str_replace(item, "Rare", "Sweet_Gem_Berry"),
         item = str_replace(item, "Bean", "Green_Bean"),
         item = str_replace(item, "Ancient", "Ancient_Fruit"),
         item = str_replace(item, "Pepper", "Hot_Pepper"),
         item = str_replace(item, "Rice", "Unmilled_Rice"))

oasis <- data.frame(
    item = c("Cactus_Fruit", "Rhubarb", "Starfruit", "Beet"),
    oasis_price = c(150, 100, 400, 20)
  )

seed_deets <- seed_deets|>
  left_join(oasis, join_by(item))

#write.csv(seed_deets, "seed_deets.csv")

seed_deets |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	growth_time	general_store	jojamart	oasis_price
Acorn	NA	NA	NA	NA
Amaranth	7	70	87	NA
Ancient_Fruit	28	NA	NA	NA
Apple	28	4000	NA	NA
Apricot	28	2000	NA	NA
Artichoke	8	30	NA	NA
Banana	28	NA	NA	NA
Green_Bean	10	60	75	NA
Beet	6	NA	NA	20
Blue_Grass	NA	NA	NA	NA
Blueberry	13	80	NA	NA
Bok_Choy	4	50	62	NA
Broccoli	8	NA	NA	NA
Cactus_Fruit	12	NA	NA	150
Carrot	3	NA	NA	NA
Cauliflower	12	80	100	NA
Cherry	28	3400	NA	NA
Corn	14	150	187	NA
Cranberry	7	240	300	NA
Eggplant	5	20	25	NA
Fairy_Rose	12	200	250	NA
Fall	7	NA	NA	NA
Fiber	7	NA	NA	NA
Garlic	4	40	NA	NA
Grape	10	60	75	NA
Grass	NA	100	125	NA
Hops	11	60	75	NA
Blue_Jazz	7	30	37	NA
Kale	6	70	87	NA
Mahogany	NA	NA	NA	NA
Mango	28	NA	NA	NA
Maple	NA	NA	NA	NA
Melon	12	80	100	NA
Mixed_Flower	NA	NA	NA	NA
Mixed	NA	NA	NA	NA
Mossy	NA	NA	NA	NA
Mushroom_Tree	NA	NA	NA	NA
Mystic_Tree	NA	NA	NA	NA
Orange	28	4000	NA	NA
Parsnip	4	20	25	NA
Peach	28	6000	NA	NA
Hot_Pepper	5	40	50	NA
Pine_Cone	NA	NA	NA	NA
Pineapple	14	NA	NA	NA
Pomegranate	28	6000	NA	NA
Poppy	7	100	125	NA
Potato	6	50	62	NA
Powdermelon	7	NA	NA	NA
Pumpkin	13	100	125	NA
Qi_Fruit	4	NA	NA	NA
Radish	6	40	50	NA
Sweet_Gem_Berry	24	NA	NA	NA
Red_Cabbage	9	100	NA	NA
Rhubarb	13	NA	NA	100
Unmilled_Rice	8	40	NA	NA
Summer_Spangle	8	50	62	NA
Spring	7	NA	NA	NA
Starfruit	13	NA	NA	400
Strawberry	8	NA	NA	NA
Summer	7	NA	NA	NA
Summer_Squash	6	NA	NA	NA
Sunflower	8	200	125	NA
Taro_Root	10	NA	NA	NA
Tea_Leaves	20	NA	NA	NA
Tomato	11	50	62	NA
Tulip	6	20	25	NA
Wheat	4	10	12	NA
Winter	7	NA	NA	NA
Yam	10	60	75	NA

Animal Origins

We also wanted the origins of where a product came, this took two steps, first scraping the animal products table and then joining it with another table, we also set the profession instead of NA to be none and did not pivot it for future use in our app.

Code

animaltable <- bow("https://stardewvalleywiki.com/Animal_Products_Profitability", force = TRUE)

result <- scrape(animaltable) |>
  html_nodes(css = "table") |>
  html_table(header = TRUE, fill = TRUE)

animal_table <- result[[2]] 

animal_table <- animal_table |>
  clean_names() |>
  mutate(profession = ifelse(profession == "—", "none", profession)) |>
  filter(profession != "Treasure Appraisal Guide and  Artisan")

animal_table |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	quality	profession	sell_price	processed_item	processed_item_quality	processed_item_sell_price	profit_increase
Egg	Regular	none	50	Mayonnaise	Regular	190	380%
Egg	Silver	none	62	Mayonnaise	Regular	190	306%
Egg	Gold	none	75	Mayonnaise	Regular	190	253%
Egg	Iridium	none	100	Mayonnaise	Regular	190	190%
Egg	Regular	Rancher	60	Mayonnaise	Regular	228	380%
Egg	Silver	Rancher	75	Mayonnaise	Regular	228	304%
Egg	Gold	Rancher	90	Mayonnaise	Regular	228	253%
Egg	Iridium	Rancher	120	Mayonnaise	Regular	228	190%
Egg	Regular	Artisan	50	Mayonnaise	Regular	266	532%
Egg	Silver	Artisan	62	Mayonnaise	Regular	266	429%
Egg	Gold	Artisan	75	Mayonnaise	Regular	266	355%
Egg	Iridium	Artisan	100	Mayonnaise	Regular	266	266%
Large Egg	Regular	none	95	Mayonnaise	Gold	285	300%
Large Egg	Silver	none	118	Mayonnaise	Gold	285	242%
Large Egg	Gold	none	142	Mayonnaise	Gold	285	201%
Large Egg	Iridium	none	190	Mayonnaise	Gold	285	150%
Large Egg	Regular	Rancher	114	Mayonnaise	Gold	342	300%
Large Egg	Silver	Rancher	142	Mayonnaise	Gold	342	241%
Large Egg	Gold	Rancher	171	Mayonnaise	Gold	342	200%
Large Egg	Iridium	Rancher	228	Mayonnaise	Gold	342	150%
Large Egg	Regular	Artisan	95	Mayonnaise	Gold	399	420%
Large Egg	Silver	Artisan	118	Mayonnaise	Gold	399	338%
Large Egg	Gold	Artisan	142	Mayonnaise	Gold	399	281%
Large Egg	Iridium	Artisan	190	Mayonnaise	Gold	399	210%
Void Egg	Regular	none	65	Void Mayonnaise	Regular	275	423%
Void Egg	Silver	none	81	Void Mayonnaise	Regular	275	340%
Void Egg	Gold	none	97	Void Mayonnaise	Regular	275	284%
Void Egg	Iridium	none	130	Void Mayonnaise	Regular	275	212%
Void Egg	Regular	Rancher	78	Void Mayonnaise	Regular	330	423%
Void Egg	Silver	Rancher	97	Void Mayonnaise	Regular	330	340%
Void Egg	Gold	Rancher	117	Void Mayonnaise	Regular	330	282%
Void Egg	Iridium	Rancher	156	Void Mayonnaise	Regular	330	212%
Void Egg	Regular	Artisan	65	Void Mayonnaise	Regular	385	592%
Void Egg	Silver	Artisan	81	Void Mayonnaise	Regular	385	475%
Void Egg	Gold	Artisan	97	Void Mayonnaise	Regular	385	397%
Void Egg	Iridium	Artisan	130	Void Mayonnaise	Regular	385	296%
Duck Egg	Regular	none	95	Duck Mayonnaise	Regular	375	395%
Duck Egg	Silver	none	118	Duck Mayonnaise	Regular	375	318%
Duck Egg	Gold	none	142	Duck Mayonnaise	Regular	375	264%
Duck Egg	Iridium	none	190	Duck Mayonnaise	Regular	375	197%
Duck Egg	Regular	Rancher	114	Duck Mayonnaise	Regular	450	395%
Duck Egg	Silver	Rancher	142	Duck Mayonnaise	Regular	450	317%
Duck Egg	Gold	Rancher	171	Duck Mayonnaise	Regular	450	263%
Duck Egg	Iridium	Rancher	228	Duck Mayonnaise	Regular	450	197%
Duck Egg	Regular	Artisan	95	Duck Mayonnaise	Regular	525	553%
Duck Egg	Silver	Artisan	118	Duck Mayonnaise	Regular	525	445%
Duck Egg	Gold	Artisan	142	Duck Mayonnaise	Regular	525	370%
Duck Egg	Iridium	Artisan	190	Duck Mayonnaise	Regular	525	276%
Wool	Regular	none	340	Cloth (1)	Regular	470	138%
Wool	Silver	none	425	Cloth (1)	Regular	470	111%
Wool	Silver	none	425	Cloth (2)	Regular	940	221%
Wool	Gold	none	510	Cloth (1)	Regular	470	92%
Wool	Gold	none	510	Cloth (2)	Regular	940	184%
Wool	Iridium	none	680	Cloth (2)	Regular	940	138%
Wool	Regular	Rancher	408	Cloth (1)	Regular	564	138%
Wool	Regular	Rancher	408	Cloth (2)	Regular	1128	276%
Wool	Silver	Rancher	510	Cloth (1)	Regular	564	111%
Wool	Silver	Rancher	510	Cloth (2)	Regular	1128	221%
Wool	Gold	Rancher	612	Cloth (1)	Regular	564	92%
Wool	Gold	Rancher	612	Cloth (2)	Regular	1128	184%
Wool	Iridium	Rancher	816	Cloth (2)	Regular	1128	138%
Wool	Regular	Artisan	340	Cloth (1)	Regular	658	194%
Wool	Regular	Artisan	340	Cloth (2)	Regular	1316	387%
Wool	Silver	Artisan	425	Cloth (1)	Regular	658	155%
Wool	Silver	Artisan	425	Cloth (2)	Regular	1316	310%
Wool	Gold	Artisan	510	Cloth (1)	Regular	658	129%
Wool	Gold	Artisan	510	Cloth (2)	Regular	1316	258%
Wool	Iridium	Artisan	680	Cloth (2)	Regular	1316	194%
Dinosaur Egg	Regular	none	350	Dinosaur Mayonnaise	Regular	800	229%
Dinosaur Egg	Silver	none	437	Dinosaur Mayonnaise	Regular	800	183%
Dinosaur Egg	Gold	none	525	Dinosaur Mayonnaise	Regular	800	152%
Dinosaur Egg	Iridium	none	700	Dinosaur Mayonnaise	Regular	800	114%
Dinosaur Egg	Regular	Rancher	350	Dinosaur Mayonnaise	Regular	960	274%
Dinosaur Egg	Silver	Rancher	437	Dinosaur Mayonnaise	Regular	960	220%
Dinosaur Egg	Gold	Rancher	525	Dinosaur Mayonnaise	Regular	960	183%
Dinosaur Egg	Iridium	Rancher	700	Dinosaur Mayonnaise	Regular	960	137%
Dinosaur Egg	Regular	Artisan	350	Dinosaur Mayonnaise	Regular	1120	320%
Dinosaur Egg	Silver	Artisan	437	Dinosaur Mayonnaise	Regular	1120	256%
Dinosaur Egg	Gold	Artisan	525	Dinosaur Mayonnaise	Regular	1120	213%
Dinosaur Egg	Iridium	Artisan	700	Dinosaur Mayonnaise	Regular	1120	160%
Golden Egg	Regular	none	500	Mayonnaise (3)	Gold	855	171%
Golden Egg	Silver	none	625	Mayonnaise (3)	Gold	855	137%
Golden Egg	Gold	none	750	Mayonnaise (3)	Gold	855	114%
Golden Egg	Iridium	none	1000	Mayonnaise (3)	Gold	855	86%
Golden Egg	Regular	Rancher	600	Mayonnaise (3)	Gold	1026	171%
Golden Egg	Silver	Rancher	750	Mayonnaise (3)	Gold	1026	137%
Golden Egg	Gold	Rancher	900	Mayonnaise (3)	Gold	1026	114%
Golden Egg	Iridium	Rancher	1200	Mayonnaise (3)	Gold	1026	86%
Golden Egg	Regular	Artisan	500	Mayonnaise (3)	Gold	1197	239%
Golden Egg	Silver	Artisan	625	Mayonnaise (3)	Gold	1197	192%
Golden Egg	Gold	Artisan	750	Mayonnaise (3)	Gold	1197	160%
Golden Egg	Iridium	Artisan	1000	Mayonnaise (3)	Gold	1197	120%
Ostrich Egg	Regular	none	600	Mayonnaise (10)	Regular	1900	317%
Ostrich Egg	Silver	none	750	Mayonnaise (10)	Silver	2370	316%
Ostrich Egg	Gold	none	900	Mayonnaise (10)	Gold	2850	317%
Ostrich Egg	Iridium	none	1200	Mayonnaise (10)	Iridium	3800	317%
Ostrich Egg	Regular	Rancher	720	Mayonnaise (10)	Regular	2280	317%
Ostrich Egg	Silver	Rancher	900	Mayonnaise (10)	Silver	2840	316%
Ostrich Egg	Gold	Rancher	1080	Mayonnaise (10)	Gold	3420	317%
Ostrich Egg	Iridium	Rancher	1440	Mayonnaise (10)	Iridium	4560	317%
Ostrich Egg	Regular	Artisan	600	Mayonnaise (10)	Regular	2660	443%
Ostrich Egg	Silver	Artisan	750	Mayonnaise (10)	Silver	3310	441%
Ostrich Egg	Gold	Artisan	900	Mayonnaise (10)	Gold	3990	443%
Ostrich Egg	Iridium	Artisan	1200	Mayonnaise (10)	Iridium	5320	443%
Milk	Regular	none	125	Cheese	Regular	230	184%
Milk	Regular	none	125	Cheese	Silver	287	230%
Milk	Regular	none	125	Cheese	Gold	345	276%
Milk	Regular	none	125	Cheese	Iridium	460	368%
Milk	Silver	none	156	Cheese	Regular	230	147%
Milk	Silver	none	156	Cheese	Silver	287	184%
Milk	Silver	none	156	Cheese	Gold	345	221%
Milk	Silver	none	156	Cheese	Iridium	460	295%
Milk	Gold	none	187	Cheese	Regular	230	123%
Milk	Gold	none	187	Cheese	Silver	287	153%
Milk	Gold	none	187	Cheese	Gold	345	184%
Milk	Gold	none	187	Cheese	Iridium	460	246%
Milk	Iridium	none	250	Cheese	Regular	230	92%
Milk	Iridium	none	250	Cheese	Silver	287	115%
Milk	Iridium	none	250	Cheese	Gold	345	138%
Milk	Iridium	none	250	Cheese	Iridium	460	184%
Milk	Regular	Rancher	150	Cheese	Regular	276	184%
Milk	Regular	Rancher	150	Cheese	Silver	345	230%
Milk	Regular	Rancher	150	Cheese	Gold	414	276%
Milk	Regular	Rancher	150	Cheese	Iridium	552	368%
Milk	Silver	Rancher	187	Cheese	Regular	276	148%
Milk	Silver	Rancher	187	Cheese	Silver	345	184%
Milk	Silver	Rancher	187	Cheese	Gold	414	221%
Milk	Silver	Rancher	187	Cheese	Iridium	552	295%
Milk	Gold	Rancher	225	Cheese	Regular	276	123%
Milk	Gold	Rancher	225	Cheese	Silver	345	153%
Milk	Gold	Rancher	225	Cheese	Gold	414	184%
Milk	Gold	Rancher	225	Cheese	Iridium	552	245%
Milk	Iridium	Rancher	300	Cheese	Regular	276	92%
Milk	Iridium	Rancher	300	Cheese	Silver	345	115%
Milk	Iridium	Rancher	300	Cheese	Gold	414	138%
Milk	Iridium	Rancher	300	Cheese	Iridium	552	184%
Milk	Regular	Artisan	125	Cheese	Regular	322	258%
Milk	Regular	Artisan	125	Cheese	Silver	402	322%
Milk	Regular	Artisan	125	Cheese	Gold	483	386%
Milk	Regular	Artisan	125	Cheese	Iridium	644	515%
Milk	Silver	Artisan	156	Cheese	Regular	322	206%
Milk	Silver	Artisan	156	Cheese	Silver	402	258%
Milk	Silver	Artisan	156	Cheese	Gold	483	310%
Milk	Silver	Artisan	156	Cheese	Iridium	644	413%
Milk	Gold	Artisan	187	Cheese	Regular	322	172%
Milk	Gold	Artisan	187	Cheese	Silver	402	215%
Milk	Gold	Artisan	187	Cheese	Gold	483	258%
Milk	Gold	Artisan	187	Cheese	Iridium	644	344%
Milk	Iridium	Artisan	250	Cheese	Regular	322	129%
Milk	Iridium	Artisan	250	Cheese	Silver	402	161%
Milk	Iridium	Artisan	250	Cheese	Gold	483	193%
Milk	Iridium	Artisan	250	Cheese	Iridium	644	258%
Large Milk	Regular	none	190	Cheese	Gold	345	182%
Large Milk	Regular	none	190	Cheese	Iridium	460	242%
Large Milk	Silver	none	237	Cheese	Gold	345	146%
Large Milk	Silver	none	237	Cheese	Iridium	460	194%
Large Milk	Gold	none	285	Cheese	Gold	345	121%
Large Milk	Gold	none	285	Cheese	Iridium	460	161%
Large Milk	Iridium	none	380	Cheese	Gold	345	91%
Large Milk	Iridium	none	380	Cheese	Iridium	460	121%
Large Milk	Regular	Rancher	228	Cheese	Gold	414	182%
Large Milk	Regular	Rancher	228	Cheese	Iridium	552	242%
Large Milk	Silver	Rancher	285	Cheese	Gold	414	145%
Large Milk	Silver	Rancher	285	Cheese	Iridium	552	194%
Large Milk	Gold	Rancher	342	Cheese	Gold	414	121%
Large Milk	Gold	Rancher	342	Cheese	Iridium	552	161%
Large Milk	Iridium	Rancher	456	Cheese	Gold	414	91%
Large Milk	Iridium	Rancher	456	Cheese	Iridium	552	121%
Large Milk	Regular	Artisan	190	Cheese	Gold	483	254%
Large Milk	Regular	Artisan	190	Cheese	Iridium	644	339%
Large Milk	Silver	Artisan	237	Cheese	Gold	483	204%
Large Milk	Silver	Artisan	237	Cheese	Iridium	644	272%
Large Milk	Gold	Artisan	285	Cheese	Gold	483	169%
Large Milk	Gold	Artisan	285	Cheese	Iridium	644	226%
Large Milk	Iridium	Artisan	380	Cheese	Gold	483	127%
Large Milk	Iridium	Artisan	380	Cheese	Iridium	644	169%
Goat Milk	Regular	none	225	Goat Cheese	Regular	400	178%
Goat Milk	Regular	none	225	Goat Cheese	Silver	500	222%
Goat Milk	Regular	none	225	Goat Cheese	Gold	600	267%
Goat Milk	Regular	none	225	Goat Cheese	Iridium	800	356%
Goat Milk	Silver	none	281	Goat Cheese	Regular	400	142%
Goat Milk	Silver	none	281	Goat Cheese	Silver	500	178%
Goat Milk	Silver	none	281	Goat Cheese	Gold	600	214%
Goat Milk	Silver	none	281	Goat Cheese	Iridium	800	285%
Goat Milk	Gold	none	337	Goat Cheese	Regular	400	119%
Goat Milk	Gold	none	337	Goat Cheese	Silver	500	148%
Goat Milk	Gold	none	337	Goat Cheese	Gold	600	178%
Goat Milk	Gold	none	337	Goat Cheese	Iridium	800	237%
Goat Milk	Iridium	none	450	Goat Cheese	Regular	400	89%
Goat Milk	Iridium	none	450	Goat Cheese	Silver	500	111%
Goat Milk	Iridium	none	450	Goat Cheese	Gold	600	133%
Goat Milk	Iridium	none	450	Goat Cheese	Iridium	800	178%
Goat Milk	Regular	Rancher	270	Goat Cheese	Regular	480	178%
Goat Milk	Regular	Rancher	270	Goat Cheese	Silver	600	222%
Goat Milk	Regular	Rancher	270	Goat Cheese	Gold	720	267%
Goat Milk	Regular	Rancher	270	Goat Cheese	Iridium	960	356%
Goat Milk	Silver	Rancher	337	Goat Cheese	Regular	480	142%
Goat Milk	Silver	Rancher	337	Goat Cheese	Silver	600	178%
Goat Milk	Silver	Rancher	337	Goat Cheese	Gold	720	214%
Goat Milk	Silver	Rancher	337	Goat Cheese	Iridium	960	285%
Goat Milk	Gold	Rancher	405	Goat Cheese	Regular	480	118%
Goat Milk	Gold	Rancher	405	Goat Cheese	Silver	600	148%
Goat Milk	Gold	Rancher	405	Goat Cheese	Gold	720	178%
Goat Milk	Gold	Rancher	405	Goat Cheese	Iridium	960	237%
Goat Milk	Iridium	Rancher	540	Goat Cheese	Regular	480	89%
Goat Milk	Iridium	Rancher	540	Goat Cheese	Silver	600	111%
Goat Milk	Iridium	Rancher	540	Goat Cheese	Gold	720	133%
Goat Milk	Iridium	Rancher	540	Goat Cheese	Iridium	960	178%
Goat Milk	Regular	Artisan	225	Goat Cheese	Regular	560	249%
Goat Milk	Regular	Artisan	225	Goat Cheese	Silver	700	311%
Goat Milk	Regular	Artisan	225	Goat Cheese	Gold	840	373%
Goat Milk	Regular	Artisan	225	Goat Cheese	Iridium	1120	498%
Goat Milk	Silver	Artisan	281	Goat Cheese	Regular	560	199%
Goat Milk	Silver	Artisan	281	Goat Cheese	Silver	700	249%
Goat Milk	Silver	Artisan	281	Goat Cheese	Gold	840	299%
Goat Milk	Silver	Artisan	281	Goat Cheese	Iridium	1120	399%
Goat Milk	Gold	Artisan	337	Goat Cheese	Regular	560	166%
Goat Milk	Gold	Artisan	337	Goat Cheese	Silver	700	208%
Goat Milk	Gold	Artisan	337	Goat Cheese	Gold	840	249%
Goat Milk	Gold	Artisan	337	Goat Cheese	Iridium	1120	332%
Goat Milk	Iridium	Artisan	450	Goat Cheese	Regular	560	124%
Goat Milk	Iridium	Artisan	450	Goat Cheese	Silver	700	156%
Goat Milk	Iridium	Artisan	450	Goat Cheese	Gold	840	187%
Goat Milk	Iridium	Artisan	450	Goat Cheese	Iridium	1120	249%
Large Goat Milk	Regular	none	345	Goat Cheese	Gold	600	174%
Large Goat Milk	Regular	none	345	Goat Cheese	Iridium	800	232%
Large Goat Milk	Silver	none	431	Goat Cheese	Gold	600	139%
Large Goat Milk	Silver	none	431	Goat Cheese	Iridium	800	186%
Large Goat Milk	Gold	none	517	Goat Cheese	Gold	600	116%
Large Goat Milk	Gold	none	517	Goat Cheese	Iridium	800	155%
Large Goat Milk	Iridium	none	690	Goat Cheese	Gold	600	97%
Large Goat Milk	Iridium	none	690	Goat Cheese	Iridium	800	116%
Large Goat Milk	Regular	Rancher	414	Goat Cheese	Gold	720	174%
Large Goat Milk	Regular	Rancher	414	Goat Cheese	Iridium	960	232%
Large Goat Milk	Silver	Rancher	517	Goat Cheese	Gold	720	139%
Large Goat Milk	Silver	Rancher	517	Goat Cheese	Iridium	960	186%
Large Goat Milk	Gold	Rancher	621	Goat Cheese	Gold	720	116%
Large Goat Milk	Gold	Rancher	621	Goat Cheese	Iridium	960	155%
Large Goat Milk	Iridium	Rancher	828	Goat Cheese	Gold	720	87%
Large Goat Milk	Iridium	Rancher	828	Goat Cheese	Iridium	960	116%
Large Goat Milk	Regular	Artisan	345	Goat Cheese	Gold	840	243%
Large Goat Milk	Regular	Artisan	345	Goat Cheese	Iridium	1120	325%
Large Goat Milk	Silver	Artisan	431	Goat Cheese	Gold	840	195%
Large Goat Milk	Silver	Artisan	431	Goat Cheese	Iridium	1120	260%
Large Goat Milk	Gold	Artisan	517	Goat Cheese	Gold	840	162%
Large Goat Milk	Gold	Artisan	517	Goat Cheese	Iridium	1120	217%
Large Goat Milk	Iridium	Artisan	690	Goat Cheese	Gold	840	122%
Large Goat Milk	Iridium	Artisan	690	Goat Cheese	Iridium	1120	162%
Truffle	Regular	none	625	Truffle Oil	Regular	1065	170%
Truffle	Silver	none	781	Truffle Oil	Regular	1065	136%
Truffle	Gold	none	937	Truffle Oil	Regular	1065	114%
Truffle	Iridium	none	1250	Truffle Oil	Regular	1065	85%
Truffle	Regular	Rancher	625	Truffle Oil	Regular	1065	170%
Truffle	Silver	Rancher	781	Truffle Oil	Regular	1065	136%
Truffle	Gold	Rancher	937	Truffle Oil	Regular	1065	114%
Truffle	Iridium	Rancher	1250	Truffle Oil	Regular	1065	85%
Truffle	Regular	Artisan	625	Truffle Oil	Regular	1491	239%
Truffle	Silver	Artisan	781	Truffle Oil	Regular	1491	191%
Truffle	Gold	Artisan	937	Truffle Oil	Regular	1491	159%
Truffle	Iridium	Artisan	1250	Truffle Oil	Regular	1491	119%

This data below was collected from another table and then intensely formatted with string functions so that we could then join the animal to the product it produced.

Code

animalasso <- bow("https://stardewvalleywiki.com/Animals", force = TRUE)

result <- scrape(animalasso) |>
  html_nodes(css = "table") |>
  html_table(header = TRUE, fill = TRUE)

animal_asso <- result[[14]][2]

animal_n_items <- animal_asso |>
  clean_names() |>
  mutate(animals_and_produce = strsplit(animals_and_produce, ") • ", fixed = TRUE)) |>
  unnest(animals_and_produce) |>
  filter(row_number() != 14) |>
  mutate(animal = str_extract(animals_and_produce, "^[^(]+"),
         product = str_extract(animals_and_produce, "\\(.*")) |>
  dplyr::select(animal, product) |>
  mutate(animal = str_replace(animal, " ", "_"),
         animal = str_replace(animal, " ", ""),
         animal = str_replace(animal, "_$", ""),
         product = str_replace(product, "\\(", ""),
         product = str_replace(product, "\\)", ""),
         product = strsplit(product, " • ", fixed = TRUE)) |>
  unnest(product)

full_animal_table <- animal_table |>
  left_join(animal_n_items, join_by(item == product), relationship =
  "many-to-many")

#write_csv(full_animal_table, "full_animal_table.csv")

full_animal_table |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	quality	profession	sell_price	processed_item	processed_item_quality	processed_item_sell_price	profit_increase	animal
Egg	Regular	none	50	Mayonnaise	Regular	190	380%	Chicken
Egg	Silver	none	62	Mayonnaise	Regular	190	306%	Chicken
Egg	Gold	none	75	Mayonnaise	Regular	190	253%	Chicken
Egg	Iridium	none	100	Mayonnaise	Regular	190	190%	Chicken
Egg	Regular	Rancher	60	Mayonnaise	Regular	228	380%	Chicken
Egg	Silver	Rancher	75	Mayonnaise	Regular	228	304%	Chicken
Egg	Gold	Rancher	90	Mayonnaise	Regular	228	253%	Chicken
Egg	Iridium	Rancher	120	Mayonnaise	Regular	228	190%	Chicken
Egg	Regular	Artisan	50	Mayonnaise	Regular	266	532%	Chicken
Egg	Silver	Artisan	62	Mayonnaise	Regular	266	429%	Chicken
Egg	Gold	Artisan	75	Mayonnaise	Regular	266	355%	Chicken
Egg	Iridium	Artisan	100	Mayonnaise	Regular	266	266%	Chicken
Large Egg	Regular	none	95	Mayonnaise	Gold	285	300%	Chicken
Large Egg	Silver	none	118	Mayonnaise	Gold	285	242%	Chicken
Large Egg	Gold	none	142	Mayonnaise	Gold	285	201%	Chicken
Large Egg	Iridium	none	190	Mayonnaise	Gold	285	150%	Chicken
Large Egg	Regular	Rancher	114	Mayonnaise	Gold	342	300%	Chicken
Large Egg	Silver	Rancher	142	Mayonnaise	Gold	342	241%	Chicken
Large Egg	Gold	Rancher	171	Mayonnaise	Gold	342	200%	Chicken
Large Egg	Iridium	Rancher	228	Mayonnaise	Gold	342	150%	Chicken
Large Egg	Regular	Artisan	95	Mayonnaise	Gold	399	420%	Chicken
Large Egg	Silver	Artisan	118	Mayonnaise	Gold	399	338%	Chicken
Large Egg	Gold	Artisan	142	Mayonnaise	Gold	399	281%	Chicken
Large Egg	Iridium	Artisan	190	Mayonnaise	Gold	399	210%	Chicken
Void Egg	Regular	none	65	Void Mayonnaise	Regular	275	423%	Void_Chicken
Void Egg	Silver	none	81	Void Mayonnaise	Regular	275	340%	Void_Chicken
Void Egg	Gold	none	97	Void Mayonnaise	Regular	275	284%	Void_Chicken
Void Egg	Iridium	none	130	Void Mayonnaise	Regular	275	212%	Void_Chicken
Void Egg	Regular	Rancher	78	Void Mayonnaise	Regular	330	423%	Void_Chicken
Void Egg	Silver	Rancher	97	Void Mayonnaise	Regular	330	340%	Void_Chicken
Void Egg	Gold	Rancher	117	Void Mayonnaise	Regular	330	282%	Void_Chicken
Void Egg	Iridium	Rancher	156	Void Mayonnaise	Regular	330	212%	Void_Chicken
Void Egg	Regular	Artisan	65	Void Mayonnaise	Regular	385	592%	Void_Chicken
Void Egg	Silver	Artisan	81	Void Mayonnaise	Regular	385	475%	Void_Chicken
Void Egg	Gold	Artisan	97	Void Mayonnaise	Regular	385	397%	Void_Chicken
Void Egg	Iridium	Artisan	130	Void Mayonnaise	Regular	385	296%	Void_Chicken
Duck Egg	Regular	none	95	Duck Mayonnaise	Regular	375	395%	Duck
Duck Egg	Silver	none	118	Duck Mayonnaise	Regular	375	318%	Duck
Duck Egg	Gold	none	142	Duck Mayonnaise	Regular	375	264%	Duck
Duck Egg	Iridium	none	190	Duck Mayonnaise	Regular	375	197%	Duck
Duck Egg	Regular	Rancher	114	Duck Mayonnaise	Regular	450	395%	Duck
Duck Egg	Silver	Rancher	142	Duck Mayonnaise	Regular	450	317%	Duck
Duck Egg	Gold	Rancher	171	Duck Mayonnaise	Regular	450	263%	Duck
Duck Egg	Iridium	Rancher	228	Duck Mayonnaise	Regular	450	197%	Duck
Duck Egg	Regular	Artisan	95	Duck Mayonnaise	Regular	525	553%	Duck
Duck Egg	Silver	Artisan	118	Duck Mayonnaise	Regular	525	445%	Duck
Duck Egg	Gold	Artisan	142	Duck Mayonnaise	Regular	525	370%	Duck
Duck Egg	Iridium	Artisan	190	Duck Mayonnaise	Regular	525	276%	Duck
Wool	Regular	none	340	Cloth (1)	Regular	470	138%	Rabbit
Wool	Regular	none	340	Cloth (1)	Regular	470	138%	Sheep
Wool	Silver	none	425	Cloth (1)	Regular	470	111%	Rabbit
Wool	Silver	none	425	Cloth (1)	Regular	470	111%	Sheep
Wool	Silver	none	425	Cloth (2)	Regular	940	221%	Rabbit
Wool	Silver	none	425	Cloth (2)	Regular	940	221%	Sheep
Wool	Gold	none	510	Cloth (1)	Regular	470	92%	Rabbit
Wool	Gold	none	510	Cloth (1)	Regular	470	92%	Sheep
Wool	Gold	none	510	Cloth (2)	Regular	940	184%	Rabbit
Wool	Gold	none	510	Cloth (2)	Regular	940	184%	Sheep
Wool	Iridium	none	680	Cloth (2)	Regular	940	138%	Rabbit
Wool	Iridium	none	680	Cloth (2)	Regular	940	138%	Sheep
Wool	Regular	Rancher	408	Cloth (1)	Regular	564	138%	Rabbit
Wool	Regular	Rancher	408	Cloth (1)	Regular	564	138%	Sheep
Wool	Regular	Rancher	408	Cloth (2)	Regular	1128	276%	Rabbit
Wool	Regular	Rancher	408	Cloth (2)	Regular	1128	276%	Sheep
Wool	Silver	Rancher	510	Cloth (1)	Regular	564	111%	Rabbit
Wool	Silver	Rancher	510	Cloth (1)	Regular	564	111%	Sheep
Wool	Silver	Rancher	510	Cloth (2)	Regular	1128	221%	Rabbit
Wool	Silver	Rancher	510	Cloth (2)	Regular	1128	221%	Sheep
Wool	Gold	Rancher	612	Cloth (1)	Regular	564	92%	Rabbit
Wool	Gold	Rancher	612	Cloth (1)	Regular	564	92%	Sheep
Wool	Gold	Rancher	612	Cloth (2)	Regular	1128	184%	Rabbit
Wool	Gold	Rancher	612	Cloth (2)	Regular	1128	184%	Sheep
Wool	Iridium	Rancher	816	Cloth (2)	Regular	1128	138%	Rabbit
Wool	Iridium	Rancher	816	Cloth (2)	Regular	1128	138%	Sheep
Wool	Regular	Artisan	340	Cloth (1)	Regular	658	194%	Rabbit
Wool	Regular	Artisan	340	Cloth (1)	Regular	658	194%	Sheep
Wool	Regular	Artisan	340	Cloth (2)	Regular	1316	387%	Rabbit
Wool	Regular	Artisan	340	Cloth (2)	Regular	1316	387%	Sheep
Wool	Silver	Artisan	425	Cloth (1)	Regular	658	155%	Rabbit
Wool	Silver	Artisan	425	Cloth (1)	Regular	658	155%	Sheep
Wool	Silver	Artisan	425	Cloth (2)	Regular	1316	310%	Rabbit
Wool	Silver	Artisan	425	Cloth (2)	Regular	1316	310%	Sheep
Wool	Gold	Artisan	510	Cloth (1)	Regular	658	129%	Rabbit
Wool	Gold	Artisan	510	Cloth (1)	Regular	658	129%	Sheep
Wool	Gold	Artisan	510	Cloth (2)	Regular	1316	258%	Rabbit
Wool	Gold	Artisan	510	Cloth (2)	Regular	1316	258%	Sheep
Wool	Iridium	Artisan	680	Cloth (2)	Regular	1316	194%	Rabbit
Wool	Iridium	Artisan	680	Cloth (2)	Regular	1316	194%	Sheep
Dinosaur Egg	Regular	none	350	Dinosaur Mayonnaise	Regular	800	229%	Dinosaur
Dinosaur Egg	Silver	none	437	Dinosaur Mayonnaise	Regular	800	183%	Dinosaur
Dinosaur Egg	Gold	none	525	Dinosaur Mayonnaise	Regular	800	152%	Dinosaur
Dinosaur Egg	Iridium	none	700	Dinosaur Mayonnaise	Regular	800	114%	Dinosaur
Dinosaur Egg	Regular	Rancher	350	Dinosaur Mayonnaise	Regular	960	274%	Dinosaur
Dinosaur Egg	Silver	Rancher	437	Dinosaur Mayonnaise	Regular	960	220%	Dinosaur
Dinosaur Egg	Gold	Rancher	525	Dinosaur Mayonnaise	Regular	960	183%	Dinosaur
Dinosaur Egg	Iridium	Rancher	700	Dinosaur Mayonnaise	Regular	960	137%	Dinosaur
Dinosaur Egg	Regular	Artisan	350	Dinosaur Mayonnaise	Regular	1120	320%	Dinosaur
Dinosaur Egg	Silver	Artisan	437	Dinosaur Mayonnaise	Regular	1120	256%	Dinosaur
Dinosaur Egg	Gold	Artisan	525	Dinosaur Mayonnaise	Regular	1120	213%	Dinosaur
Dinosaur Egg	Iridium	Artisan	700	Dinosaur Mayonnaise	Regular	1120	160%	Dinosaur
Golden Egg	Regular	none	500	Mayonnaise (3)	Gold	855	171%	Golden_Chicken
Golden Egg	Silver	none	625	Mayonnaise (3)	Gold	855	137%	Golden_Chicken
Golden Egg	Gold	none	750	Mayonnaise (3)	Gold	855	114%	Golden_Chicken
Golden Egg	Iridium	none	1000	Mayonnaise (3)	Gold	855	86%	Golden_Chicken
Golden Egg	Regular	Rancher	600	Mayonnaise (3)	Gold	1026	171%	Golden_Chicken
Golden Egg	Silver	Rancher	750	Mayonnaise (3)	Gold	1026	137%	Golden_Chicken
Golden Egg	Gold	Rancher	900	Mayonnaise (3)	Gold	1026	114%	Golden_Chicken
Golden Egg	Iridium	Rancher	1200	Mayonnaise (3)	Gold	1026	86%	Golden_Chicken
Golden Egg	Regular	Artisan	500	Mayonnaise (3)	Gold	1197	239%	Golden_Chicken
Golden Egg	Silver	Artisan	625	Mayonnaise (3)	Gold	1197	192%	Golden_Chicken
Golden Egg	Gold	Artisan	750	Mayonnaise (3)	Gold	1197	160%	Golden_Chicken
Golden Egg	Iridium	Artisan	1000	Mayonnaise (3)	Gold	1197	120%	Golden_Chicken
Ostrich Egg	Regular	none	600	Mayonnaise (10)	Regular	1900	317%	Ostrich
Ostrich Egg	Silver	none	750	Mayonnaise (10)	Silver	2370	316%	Ostrich
Ostrich Egg	Gold	none	900	Mayonnaise (10)	Gold	2850	317%	Ostrich
Ostrich Egg	Iridium	none	1200	Mayonnaise (10)	Iridium	3800	317%	Ostrich
Ostrich Egg	Regular	Rancher	720	Mayonnaise (10)	Regular	2280	317%	Ostrich
Ostrich Egg	Silver	Rancher	900	Mayonnaise (10)	Silver	2840	316%	Ostrich
Ostrich Egg	Gold	Rancher	1080	Mayonnaise (10)	Gold	3420	317%	Ostrich
Ostrich Egg	Iridium	Rancher	1440	Mayonnaise (10)	Iridium	4560	317%	Ostrich
Ostrich Egg	Regular	Artisan	600	Mayonnaise (10)	Regular	2660	443%	Ostrich
Ostrich Egg	Silver	Artisan	750	Mayonnaise (10)	Silver	3310	441%	Ostrich
Ostrich Egg	Gold	Artisan	900	Mayonnaise (10)	Gold	3990	443%	Ostrich
Ostrich Egg	Iridium	Artisan	1200	Mayonnaise (10)	Iridium	5320	443%	Ostrich
Milk	Regular	none	125	Cheese	Regular	230	184%	Cow
Milk	Regular	none	125	Cheese	Silver	287	230%	Cow
Milk	Regular	none	125	Cheese	Gold	345	276%	Cow
Milk	Regular	none	125	Cheese	Iridium	460	368%	Cow
Milk	Silver	none	156	Cheese	Regular	230	147%	Cow
Milk	Silver	none	156	Cheese	Silver	287	184%	Cow
Milk	Silver	none	156	Cheese	Gold	345	221%	Cow
Milk	Silver	none	156	Cheese	Iridium	460	295%	Cow
Milk	Gold	none	187	Cheese	Regular	230	123%	Cow
Milk	Gold	none	187	Cheese	Silver	287	153%	Cow
Milk	Gold	none	187	Cheese	Gold	345	184%	Cow
Milk	Gold	none	187	Cheese	Iridium	460	246%	Cow
Milk	Iridium	none	250	Cheese	Regular	230	92%	Cow
Milk	Iridium	none	250	Cheese	Silver	287	115%	Cow
Milk	Iridium	none	250	Cheese	Gold	345	138%	Cow
Milk	Iridium	none	250	Cheese	Iridium	460	184%	Cow
Milk	Regular	Rancher	150	Cheese	Regular	276	184%	Cow
Milk	Regular	Rancher	150	Cheese	Silver	345	230%	Cow
Milk	Regular	Rancher	150	Cheese	Gold	414	276%	Cow
Milk	Regular	Rancher	150	Cheese	Iridium	552	368%	Cow
Milk	Silver	Rancher	187	Cheese	Regular	276	148%	Cow
Milk	Silver	Rancher	187	Cheese	Silver	345	184%	Cow
Milk	Silver	Rancher	187	Cheese	Gold	414	221%	Cow
Milk	Silver	Rancher	187	Cheese	Iridium	552	295%	Cow
Milk	Gold	Rancher	225	Cheese	Regular	276	123%	Cow
Milk	Gold	Rancher	225	Cheese	Silver	345	153%	Cow
Milk	Gold	Rancher	225	Cheese	Gold	414	184%	Cow
Milk	Gold	Rancher	225	Cheese	Iridium	552	245%	Cow
Milk	Iridium	Rancher	300	Cheese	Regular	276	92%	Cow
Milk	Iridium	Rancher	300	Cheese	Silver	345	115%	Cow
Milk	Iridium	Rancher	300	Cheese	Gold	414	138%	Cow
Milk	Iridium	Rancher	300	Cheese	Iridium	552	184%	Cow
Milk	Regular	Artisan	125	Cheese	Regular	322	258%	Cow
Milk	Regular	Artisan	125	Cheese	Silver	402	322%	Cow
Milk	Regular	Artisan	125	Cheese	Gold	483	386%	Cow
Milk	Regular	Artisan	125	Cheese	Iridium	644	515%	Cow
Milk	Silver	Artisan	156	Cheese	Regular	322	206%	Cow
Milk	Silver	Artisan	156	Cheese	Silver	402	258%	Cow
Milk	Silver	Artisan	156	Cheese	Gold	483	310%	Cow
Milk	Silver	Artisan	156	Cheese	Iridium	644	413%	Cow
Milk	Gold	Artisan	187	Cheese	Regular	322	172%	Cow
Milk	Gold	Artisan	187	Cheese	Silver	402	215%	Cow
Milk	Gold	Artisan	187	Cheese	Gold	483	258%	Cow
Milk	Gold	Artisan	187	Cheese	Iridium	644	344%	Cow
Milk	Iridium	Artisan	250	Cheese	Regular	322	129%	Cow
Milk	Iridium	Artisan	250	Cheese	Silver	402	161%	Cow
Milk	Iridium	Artisan	250	Cheese	Gold	483	193%	Cow
Milk	Iridium	Artisan	250	Cheese	Iridium	644	258%	Cow
Large Milk	Regular	none	190	Cheese	Gold	345	182%	Cow
Large Milk	Regular	none	190	Cheese	Iridium	460	242%	Cow
Large Milk	Silver	none	237	Cheese	Gold	345	146%	Cow
Large Milk	Silver	none	237	Cheese	Iridium	460	194%	Cow
Large Milk	Gold	none	285	Cheese	Gold	345	121%	Cow
Large Milk	Gold	none	285	Cheese	Iridium	460	161%	Cow
Large Milk	Iridium	none	380	Cheese	Gold	345	91%	Cow
Large Milk	Iridium	none	380	Cheese	Iridium	460	121%	Cow
Large Milk	Regular	Rancher	228	Cheese	Gold	414	182%	Cow
Large Milk	Regular	Rancher	228	Cheese	Iridium	552	242%	Cow
Large Milk	Silver	Rancher	285	Cheese	Gold	414	145%	Cow
Large Milk	Silver	Rancher	285	Cheese	Iridium	552	194%	Cow
Large Milk	Gold	Rancher	342	Cheese	Gold	414	121%	Cow
Large Milk	Gold	Rancher	342	Cheese	Iridium	552	161%	Cow
Large Milk	Iridium	Rancher	456	Cheese	Gold	414	91%	Cow
Large Milk	Iridium	Rancher	456	Cheese	Iridium	552	121%	Cow
Large Milk	Regular	Artisan	190	Cheese	Gold	483	254%	Cow
Large Milk	Regular	Artisan	190	Cheese	Iridium	644	339%	Cow
Large Milk	Silver	Artisan	237	Cheese	Gold	483	204%	Cow
Large Milk	Silver	Artisan	237	Cheese	Iridium	644	272%	Cow
Large Milk	Gold	Artisan	285	Cheese	Gold	483	169%	Cow
Large Milk	Gold	Artisan	285	Cheese	Iridium	644	226%	Cow
Large Milk	Iridium	Artisan	380	Cheese	Gold	483	127%	Cow
Large Milk	Iridium	Artisan	380	Cheese	Iridium	644	169%	Cow
Goat Milk	Regular	none	225	Goat Cheese	Regular	400	178%	Goat
Goat Milk	Regular	none	225	Goat Cheese	Silver	500	222%	Goat
Goat Milk	Regular	none	225	Goat Cheese	Gold	600	267%	Goat
Goat Milk	Regular	none	225	Goat Cheese	Iridium	800	356%	Goat
Goat Milk	Silver	none	281	Goat Cheese	Regular	400	142%	Goat
Goat Milk	Silver	none	281	Goat Cheese	Silver	500	178%	Goat
Goat Milk	Silver	none	281	Goat Cheese	Gold	600	214%	Goat
Goat Milk	Silver	none	281	Goat Cheese	Iridium	800	285%	Goat
Goat Milk	Gold	none	337	Goat Cheese	Regular	400	119%	Goat
Goat Milk	Gold	none	337	Goat Cheese	Silver	500	148%	Goat
Goat Milk	Gold	none	337	Goat Cheese	Gold	600	178%	Goat
Goat Milk	Gold	none	337	Goat Cheese	Iridium	800	237%	Goat
Goat Milk	Iridium	none	450	Goat Cheese	Regular	400	89%	Goat
Goat Milk	Iridium	none	450	Goat Cheese	Silver	500	111%	Goat
Goat Milk	Iridium	none	450	Goat Cheese	Gold	600	133%	Goat
Goat Milk	Iridium	none	450	Goat Cheese	Iridium	800	178%	Goat
Goat Milk	Regular	Rancher	270	Goat Cheese	Regular	480	178%	Goat
Goat Milk	Regular	Rancher	270	Goat Cheese	Silver	600	222%	Goat
Goat Milk	Regular	Rancher	270	Goat Cheese	Gold	720	267%	Goat
Goat Milk	Regular	Rancher	270	Goat Cheese	Iridium	960	356%	Goat
Goat Milk	Silver	Rancher	337	Goat Cheese	Regular	480	142%	Goat
Goat Milk	Silver	Rancher	337	Goat Cheese	Silver	600	178%	Goat
Goat Milk	Silver	Rancher	337	Goat Cheese	Gold	720	214%	Goat
Goat Milk	Silver	Rancher	337	Goat Cheese	Iridium	960	285%	Goat
Goat Milk	Gold	Rancher	405	Goat Cheese	Regular	480	118%	Goat
Goat Milk	Gold	Rancher	405	Goat Cheese	Silver	600	148%	Goat
Goat Milk	Gold	Rancher	405	Goat Cheese	Gold	720	178%	Goat
Goat Milk	Gold	Rancher	405	Goat Cheese	Iridium	960	237%	Goat
Goat Milk	Iridium	Rancher	540	Goat Cheese	Regular	480	89%	Goat
Goat Milk	Iridium	Rancher	540	Goat Cheese	Silver	600	111%	Goat
Goat Milk	Iridium	Rancher	540	Goat Cheese	Gold	720	133%	Goat
Goat Milk	Iridium	Rancher	540	Goat Cheese	Iridium	960	178%	Goat
Goat Milk	Regular	Artisan	225	Goat Cheese	Regular	560	249%	Goat
Goat Milk	Regular	Artisan	225	Goat Cheese	Silver	700	311%	Goat
Goat Milk	Regular	Artisan	225	Goat Cheese	Gold	840	373%	Goat
Goat Milk	Regular	Artisan	225	Goat Cheese	Iridium	1120	498%	Goat
Goat Milk	Silver	Artisan	281	Goat Cheese	Regular	560	199%	Goat
Goat Milk	Silver	Artisan	281	Goat Cheese	Silver	700	249%	Goat
Goat Milk	Silver	Artisan	281	Goat Cheese	Gold	840	299%	Goat
Goat Milk	Silver	Artisan	281	Goat Cheese	Iridium	1120	399%	Goat
Goat Milk	Gold	Artisan	337	Goat Cheese	Regular	560	166%	Goat
Goat Milk	Gold	Artisan	337	Goat Cheese	Silver	700	208%	Goat
Goat Milk	Gold	Artisan	337	Goat Cheese	Gold	840	249%	Goat
Goat Milk	Gold	Artisan	337	Goat Cheese	Iridium	1120	332%	Goat
Goat Milk	Iridium	Artisan	450	Goat Cheese	Regular	560	124%	Goat
Goat Milk	Iridium	Artisan	450	Goat Cheese	Silver	700	156%	Goat
Goat Milk	Iridium	Artisan	450	Goat Cheese	Gold	840	187%	Goat
Goat Milk	Iridium	Artisan	450	Goat Cheese	Iridium	1120	249%	Goat
Large Goat Milk	Regular	none	345	Goat Cheese	Gold	600	174%	Goat
Large Goat Milk	Regular	none	345	Goat Cheese	Iridium	800	232%	Goat
Large Goat Milk	Silver	none	431	Goat Cheese	Gold	600	139%	Goat
Large Goat Milk	Silver	none	431	Goat Cheese	Iridium	800	186%	Goat
Large Goat Milk	Gold	none	517	Goat Cheese	Gold	600	116%	Goat
Large Goat Milk	Gold	none	517	Goat Cheese	Iridium	800	155%	Goat
Large Goat Milk	Iridium	none	690	Goat Cheese	Gold	600	97%	Goat
Large Goat Milk	Iridium	none	690	Goat Cheese	Iridium	800	116%	Goat
Large Goat Milk	Regular	Rancher	414	Goat Cheese	Gold	720	174%	Goat
Large Goat Milk	Regular	Rancher	414	Goat Cheese	Iridium	960	232%	Goat
Large Goat Milk	Silver	Rancher	517	Goat Cheese	Gold	720	139%	Goat
Large Goat Milk	Silver	Rancher	517	Goat Cheese	Iridium	960	186%	Goat
Large Goat Milk	Gold	Rancher	621	Goat Cheese	Gold	720	116%	Goat
Large Goat Milk	Gold	Rancher	621	Goat Cheese	Iridium	960	155%	Goat
Large Goat Milk	Iridium	Rancher	828	Goat Cheese	Gold	720	87%	Goat
Large Goat Milk	Iridium	Rancher	828	Goat Cheese	Iridium	960	116%	Goat
Large Goat Milk	Regular	Artisan	345	Goat Cheese	Gold	840	243%	Goat
Large Goat Milk	Regular	Artisan	345	Goat Cheese	Iridium	1120	325%	Goat
Large Goat Milk	Silver	Artisan	431	Goat Cheese	Gold	840	195%	Goat
Large Goat Milk	Silver	Artisan	431	Goat Cheese	Iridium	1120	260%	Goat
Large Goat Milk	Gold	Artisan	517	Goat Cheese	Gold	840	162%	Goat
Large Goat Milk	Gold	Artisan	517	Goat Cheese	Iridium	1120	217%	Goat
Large Goat Milk	Iridium	Artisan	690	Goat Cheese	Gold	840	122%	Goat
Large Goat Milk	Iridium	Artisan	690	Goat Cheese	Iridium	1120	162%	Goat
Truffle	Regular	none	625	Truffle Oil	Regular	1065	170%	Pig
Truffle	Silver	none	781	Truffle Oil	Regular	1065	136%	Pig
Truffle	Gold	none	937	Truffle Oil	Regular	1065	114%	Pig
Truffle	Iridium	none	1250	Truffle Oil	Regular	1065	85%	Pig
Truffle	Regular	Rancher	625	Truffle Oil	Regular	1065	170%	Pig
Truffle	Silver	Rancher	781	Truffle Oil	Regular	1065	136%	Pig
Truffle	Gold	Rancher	937	Truffle Oil	Regular	1065	114%	Pig
Truffle	Iridium	Rancher	1250	Truffle Oil	Regular	1065	85%	Pig
Truffle	Regular	Artisan	625	Truffle Oil	Regular	1491	239%	Pig
Truffle	Silver	Artisan	781	Truffle Oil	Regular	1491	191%	Pig
Truffle	Gold	Artisan	937	Truffle Oil	Regular	1491	159%	Pig
Truffle	Iridium	Artisan	1250	Truffle Oil	Regular	1491	119%	Pig

Wrangling:

Crops

Additional wrangling had to be done because our app wouldn’t work if there were NA values, so instead of NA values for if an item wasn’t sold at a store we set the values to zero. However, we first worked with our crops dataset, we needed to join the grow times and add more information.

Code

# zero out everything with crop prices and create crop prices2
crop_prices2 <- crop_prices |>
  left_join(seed_deets, join_by(item)) |>
  mutate(profession = replace_na(profession, "none"),
         sub_category = replace_na(sub_category, "Special Crop"),
         growth_time = replace_na(growth_time, 0),
         general_store = replace_na(general_store, 0),
         jojamart = replace_na(jojamart, 0),
         oasis_price = replace_na(oasis_price, 0)) |>
  filter(!item %in% c("Qi_Fruit", "Tea_Leaves"))

#write.csv(crop_prices2, "crop_prices2.csv")

An issue we ran into was that some plants drop multiple crops when harvested so for calculating the profit we had to take that into account as well. For those specific crops we made a new data frame and specified how many crops they drop. Another issue was that some plants can regrow, so you only have to buy the seed and plant the seed once in a season so planting these early on so that they can continue produce crops throughout the season. After finally accounting for these things we are able to join our data together and ultimately create a gold per day column for each quality of crop.

Code

regrow <- as.data.frame(
  list(item = c("Ancient Fruit", "Blueberry", "Broccoli", "Cactus Fruit", "Coffee Bean",
             "Corn", "Cranberries", "Eggplant", "Grape", "Green Bean", "Hops", "Hot Pepper",
             "Pineapple", "Strawberry", "Summer Squash", "Tea Leaves", "Tomato"),
    crops_per_harvest = c(1, 3, 1, 1, 4, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)))

regrow <- regrow|>
  mutate(can_regrow = "TRUE")
  
crop_prices3 <- crop_prices2 |>
  mutate(
    season = str_replace(sub_category, " Crop", ""),
    seed_price = ifelse(general_store != 0, 
                        general_store, 
                        ifelse(oasis_price != 0, oasis_price, 0)),
    seed_price = ifelse(item == "Strawberry", 100, seed_price)
  ) |>
  left_join(regrow, join_by(item)) |>
  mutate(
    crops_per_harvest = ifelse(is.na(crops_per_harvest), 1, crops_per_harvest),
    can_regrow = ifelse(is.na(can_regrow), FALSE, TRUE)
  ) |>
  mutate(
    regular_gold_per_day = round(((regular_price * crops_per_harvest) - seed_price) / growth_time, 3),
    silver_gold_per_day = round(((silver_price * crops_per_harvest) - seed_price) / growth_time, 3),
    gold_gold_per_day = round(((gold_price * crops_per_harvest) - seed_price) / growth_time, 3),
    iridium_gold_per_day = round(((iridium_price * crops_per_harvest) - seed_price) / growth_time, 3)
  )

#write.csv(crop_prices3, "final_crop_prices.csv")

crop_prices3 |>
  # kable for nice table in html
  kable() |>
    kable_styling(full_width = FALSE) |>
    scroll_box(width = "100%", height = "200px")

item	regular_price	silver_price	gold_price	iridium_price	profession	category	sub_category	growth_time	general_store	jojamart	oasis_price	season	seed_price	crops_per_harvest	can_regrow	regular_gold_per_day	silver_gold_per_day	gold_gold_per_day	iridium_gold_per_day
Amaranth	150	187	225	300	none	crop	Fall Crop	7	70	87	0	Fall	70	1	FALSE	11.429	16.714	22.143	32.857
Amaranth	165	205	247	330	tiller	crop	Fall Crop	7	70	87	0	Fall	70	1	FALSE	13.571	19.286	25.286	37.143
Ancient_Fruit	550	687	825	1100	none	crop	Special Crop	28	0	0	0	Special	0	1	FALSE	19.643	24.536	29.464	39.286
Ancient_Fruit	605	755	907	1210	tiller	crop	Special Crop	28	0	0	0	Special	0	1	FALSE	21.607	26.964	32.393	43.214
Apple	100	125	150	200	none	crop	Special Crop	28	4000	0	0	Special	4000	1	FALSE	-139.286	-138.393	-137.500	-135.714
Apple	110	137	165	220	tiller	crop	Special Crop	28	4000	0	0	Special	4000	1	FALSE	-138.929	-137.964	-136.964	-135.000
Apricot	50	62	75	100	none	crop	Special Crop	28	2000	0	0	Special	2000	1	FALSE	-69.643	-69.214	-68.750	-67.857
Apricot	55	68	82	110	tiller	crop	Special Crop	28	2000	0	0	Special	2000	1	FALSE	-69.464	-69.000	-68.500	-67.500
Artichoke	160	200	240	320	none	crop	Fall Crop	8	30	0	0	Fall	30	1	FALSE	16.250	21.250	26.250	36.250
Artichoke	176	220	264	352	tiller	crop	Fall Crop	8	30	0	0	Fall	30	1	FALSE	18.250	23.750	29.250	40.250
Banana	150	187	225	300	none	crop	Special Crop	28	0	0	0	Special	0	1	FALSE	5.357	6.679	8.036	10.714
Banana	165	205	247	330	tiller	crop	Special Crop	28	0	0	0	Special	0	1	FALSE	5.893	7.321	8.821	11.786
Beet	100	125	150	200	none	crop	Fall Crop	6	0	0	20	Fall	20	1	FALSE	13.333	17.500	21.667	30.000
Beet	110	137	165	220	tiller	crop	Fall Crop	6	0	0	20	Fall	20	1	FALSE	15.000	19.500	24.167	33.333
Blackberry	20	25	30	40	none	crop	Special Crop	0	0	0	0	Special	0	1	FALSE	Inf	Inf	Inf	Inf
Blue_Jazz	50	62	75	100	none	crop	Spring Crop	7	30	37	0	Spring	30	1	FALSE	2.857	4.571	6.429	10.000
Blue_Jazz	55	68	82	110	tiller	crop	Spring Crop	7	30	37	0	Spring	30	1	FALSE	3.571	5.429	7.429	11.429
Blueberry	50	62	75	100	none	crop	Summer Crop	13	80	0	0	Summer	80	3	TRUE	5.385	8.154	11.154	16.923
Blueberry	55	68	82	110	tiller	crop	Summer Crop	13	80	0	0	Summer	80	3	TRUE	6.538	9.538	12.769	19.231
Bok_Choy	80	100	120	160	none	crop	Fall Crop	4	50	62	0	Fall	50	1	FALSE	7.500	12.500	17.500	27.500
Bok_Choy	88	110	132	176	tiller	crop	Fall Crop	4	50	62	0	Fall	50	1	FALSE	9.500	15.000	20.500	31.500
Broccoli	70	87	105	140	none	crop	Fall Crop	8	0	0	0	Fall	0	1	TRUE	8.750	10.875	13.125	17.500
Broccoli	77	95	115	154	tiller	crop	Fall Crop	8	0	0	0	Fall	0	1	TRUE	9.625	11.875	14.375	19.250
Cactus_Fruit	75	93	112	150	none	crop	Special Crop	12	0	0	150	Special	150	1	FALSE	-6.250	-4.750	-3.167	0.000
Cactus_Fruit	82	102	123	165	none	crop	Special Crop	12	0	0	150	Special	150	1	FALSE	-5.667	-4.000	-2.250	1.250
Carrot	35	43	52	70	none	crop	Spring Crop	3	0	0	0	Spring	0	1	FALSE	11.667	14.333	17.333	23.333
Carrot	38	47	57	77	tiller	crop	Spring Crop	3	0	0	0	Spring	0	1	FALSE	12.667	15.667	19.000	25.667
Cauliflower	175	218	262	350	none	crop	Spring Crop	12	80	100	0	Spring	80	1	FALSE	7.917	11.500	15.167	22.500
Cauliflower	192	239	288	385	tiller	crop	Spring Crop	12	80	100	0	Spring	80	1	FALSE	9.333	13.250	17.333	25.417
Cherry	80	100	120	160	none	crop	Special Crop	28	3400	0	0	Special	3400	1	FALSE	-118.571	-117.857	-117.143	-115.714
Cherry	88	110	132	176	tiller	crop	Special Crop	28	3400	0	0	Special	3400	1	FALSE	-118.286	-117.500	-116.714	-115.143
Corn	50	62	75	100	none	crop	Summer Crop	14	150	187	0	Summer	150	1	TRUE	-7.143	-6.286	-5.357	-3.571
Corn	50	62	75	100	none	crop	Fall Crop	14	150	187	0	Fall	150	1	TRUE	-7.143	-6.286	-5.357	-3.571
Corn	55	68	82	110	tiller	crop	Summer Crop	14	150	187	0	Summer	150	1	TRUE	-6.786	-5.857	-4.857	-2.857
Corn	55	68	82	110	tiller	crop	Fall Crop	14	150	187	0	Fall	150	1	TRUE	-6.786	-5.857	-4.857	-2.857
Cranberries	75	93	112	150	none	crop	Fall Crop	0	0	0	0	Fall	0	2	TRUE	Inf	Inf	Inf	Inf
Cranberries	82	102	123	165	tiller	crop	Fall Crop	0	0	0	0	Fall	0	2	TRUE	Inf	Inf	Inf	Inf
Crystal_Fruit	150	187	225	300	none	crop	Special Crop	0	0	0	0	Special	0	1	FALSE	Inf	Inf	Inf	Inf
Eggplant	60	75	90	120	none	crop	Fall Crop	5	20	25	0	Fall	20	1	TRUE	8.000	11.000	14.000	20.000
Eggplant	66	82	99	132	tiller	crop	Fall Crop	5	20	25	0	Fall	20	1	TRUE	9.200	12.400	15.800	22.400
Fairy_Rose	290	362	435	580	none	crop	Fall Crop	12	200	250	0	Fall	200	1	FALSE	7.500	13.500	19.583	31.667
Fairy_Rose	319	398	478	638	tiller	crop	Fall Crop	12	200	250	0	Fall	200	1	FALSE	9.917	16.500	23.167	36.500
Fiddlehead_Fern	90	112	135	180	none	crop	Special Crop	0	0	0	0	Special	0	1	FALSE	Inf	Inf	Inf	Inf
Fiddlehead_Fern	99	123	148	198	tiller	crop	Special Crop	0	0	0	0	Special	0	1	FALSE	Inf	Inf	Inf	Inf
Garlic	60	75	90	120	none	crop	Spring Crop	4	40	0	0	Spring	40	1	FALSE	5.000	8.750	12.500	20.000
Garlic	66	82	99	132	tiller	crop	Spring Crop	4	40	0	0	Spring	40	1	FALSE	6.500	10.500	14.750	23.000
Grape	80	100	120	160	none	crop	Fall Crop	10	60	75	0	Fall	60	1	TRUE	2.000	4.000	6.000	10.000
Grape	88	110	132	176	none	crop	Fall Crop	10	60	75	0	Fall	60	1	TRUE	2.800	5.000	7.200	11.600
Green_Bean	40	50	60	80	none	crop	Spring Crop	10	60	75	0	Spring	60	1	FALSE	-2.000	-1.000	0.000	2.000
Green_Bean	44	55	66	88	tiller	crop	Spring Crop	10	60	75	0	Spring	60	1	FALSE	-1.600	-0.500	0.600	2.800
Hops	25	31	37	50	none	crop	Summer Crop	11	60	75	0	Summer	60	1	TRUE	-3.182	-2.636	-2.091	-0.909
Hops	27	34	40	55	tiller	crop	Summer Crop	11	60	75	0	Summer	60	1	TRUE	-3.000	-2.364	-1.818	-0.455
Hot_Pepper	40	50	60	80	none	crop	Summer Crop	5	40	50	0	Summer	40	1	FALSE	0.000	2.000	4.000	8.000
Hot_Pepper	44	55	66	88	tiller	crop	Summer Crop	5	40	50	0	Summer	40	1	FALSE	0.800	3.000	5.200	9.600
Kale	110	137	165	220	none	crop	Spring Crop	6	70	87	0	Spring	70	1	FALSE	6.667	11.167	15.833	25.000
Kale	121	150	181	242	tiller	crop	Spring Crop	6	70	87	0	Spring	70	1	FALSE	8.500	13.333	18.500	28.667
Mango	130	162	195	260	none	crop	Special Crop	28	0	0	0	Special	0	1	FALSE	4.643	5.786	6.964	9.286
Mango	143	178	214	286	tiller	crop	Special Crop	28	0	0	0	Special	0	1	FALSE	5.107	6.357	7.643	10.214
Melon	250	312	375	500	none	crop	Summer Crop	12	80	100	0	Summer	80	1	FALSE	14.167	19.333	24.583	35.000
Melon	275	343	412	550	tiller	crop	Summer Crop	12	80	100	0	Summer	80	1	FALSE	16.250	21.917	27.667	39.167
Orange	100	125	150	200	none	crop	Special Crop	28	4000	0	0	Special	4000	1	FALSE	-139.286	-138.393	-137.500	-135.714
Orange	110	137	165	220	tiller	crop	Special Crop	28	4000	0	0	Special	4000	1	FALSE	-138.929	-137.964	-136.964	-135.000
Parsnip	35	43	52	70	none	crop	Spring Crop	4	20	25	0	Spring	20	1	FALSE	3.750	5.750	8.000	12.500
Parsnip	38	47	57	77	tiller	crop	Spring Crop	4	20	25	0	Spring	20	1	FALSE	4.500	6.750	9.250	14.250
Peach	140	175	210	280	none	crop	Special Crop	28	6000	0	0	Special	6000	1	FALSE	-209.286	-208.036	-206.786	-204.286
Peach	154	192	231	308	tiller	crop	Special Crop	28	6000	0	0	Special	6000	1	FALSE	-208.786	-207.429	-206.036	-203.286
Pineapple	300	375	450	600	none	crop	Special Crop	14	0	0	0	Special	0	1	TRUE	21.429	26.786	32.143	42.857
Pineapple	330	412	495	660	tiller	crop	Special Crop	14	0	0	0	Special	0	1	TRUE	23.571	29.429	35.357	47.143
Pomegranate	140	175	210	280	none	crop	Special Crop	28	6000	0	0	Special	6000	1	FALSE	-209.286	-208.036	-206.786	-204.286
Pomegranate	154	192	231	308	tiller	crop	Special Crop	28	6000	0	0	Special	6000	1	FALSE	-208.786	-207.429	-206.036	-203.286
Poppy	140	175	210	280	none	crop	Summer Crop	7	100	125	0	Summer	100	1	FALSE	5.714	10.714	15.714	25.714
Poppy	154	192	231	308	tiller	crop	Summer Crop	7	100	125	0	Summer	100	1	FALSE	7.714	13.143	18.714	29.714
Potato	80	100	120	160	none	crop	Spring Crop	6	50	62	0	Spring	50	1	FALSE	5.000	8.333	11.667	18.333
Potato	88	110	132	176	tiller	crop	Spring Crop	6	50	62	0	Spring	50	1	FALSE	6.333	10.000	13.667	21.000
Powdermelon	60	75	90	120	none	crop	Winter Crop	7	0	0	0	Winter	0	1	FALSE	8.571	10.714	12.857	17.143
Powdermelon	66	82	99	132	tiller	crop	Winter Crop	7	0	0	0	Winter	0	1	FALSE	9.429	11.714	14.143	18.857
Pumpkin	320	400	480	640	none	crop	Fall Crop	13	100	125	0	Fall	100	1	FALSE	16.923	23.077	29.231	41.538
Pumpkin	352	440	528	704	tiller	crop	Fall Crop	13	100	125	0	Fall	100	1	FALSE	19.385	26.154	32.923	46.462
Radish	90	112	135	180	none	crop	Summer Crop	6	40	50	0	Summer	40	1	FALSE	8.333	12.000	15.833	23.333
Radish	99	123	148	198	tiller	crop	Summer Crop	6	40	50	0	Summer	40	1	FALSE	9.833	13.833	18.000	26.333
Red_Cabbage	260	325	390	520	none	crop	Summer Crop	9	100	0	0	Summer	100	1	FALSE	17.778	25.000	32.222	46.667
Red_Cabbage	286	357	429	572	tiller	crop	Summer Crop	9	100	0	0	Summer	100	1	FALSE	20.667	28.556	36.556	52.444
Rhubarb	220	275	330	440	none	crop	Spring Crop	13	0	0	100	Spring	100	1	FALSE	9.231	13.462	17.692	26.154
Rhubarb	242	302	363	484	tiller	crop	Spring Crop	13	0	0	100	Spring	100	1	FALSE	10.923	15.538	20.231	29.538
Spice_Berry	80	100	120	160	none	crop	Special Crop	0	0	0	0	Special	0	1	FALSE	Inf	Inf	Inf	Inf
Starfruit	750	937	1125	1500	none	crop	Summer Crop	13	0	0	400	Summer	400	1	FALSE	26.923	41.308	55.769	84.615
Starfruit	825	1030	1237	1650	tiller	crop	Summer Crop	13	0	0	400	Summer	400	1	FALSE	32.692	48.462	64.385	96.154
Strawberry	120	150	180	240	none	crop	Spring Crop	8	0	0	0	Spring	100	1	TRUE	2.500	6.250	10.000	17.500
Strawberry	132	165	198	264	tiller	crop	Spring Crop	8	0	0	0	Spring	100	1	TRUE	4.000	8.125	12.250	20.500
Summer_Spangle	90	112	135	180	none	crop	Summer Crop	8	50	62	0	Summer	50	1	FALSE	5.000	7.750	10.625	16.250
Summer_Spangle	99	123	148	198	tiller	crop	Summer Crop	8	50	62	0	Summer	50	1	FALSE	6.125	9.125	12.250	18.500
Summer_Squash	45	56	67	90	none	crop	Summer Crop	6	0	0	0	Summer	0	1	FALSE	7.500	9.333	11.167	15.000
Summer_Squash	49	61	73	99	tiller	crop	Summer Crop	6	0	0	0	Summer	0	1	FALSE	8.167	10.167	12.167	16.500
Sunflower	80	100	120	160	none	crop	Summer Crop	8	200	125	0	Summer	200	1	FALSE	-15.000	-12.500	-10.000	-5.000
Sunflower	80	100	120	160	none	crop	Fall Crop	8	200	125	0	Fall	200	1	FALSE	-15.000	-12.500	-10.000	-5.000
Sunflower	88	110	132	176	tiller	crop	Summer Crop	8	200	125	0	Summer	200	1	FALSE	-14.000	-11.250	-8.500	-3.000
Sunflower	88	110	132	176	tiller	crop	Fall Crop	8	200	125	0	Fall	200	1	FALSE	-14.000	-11.250	-8.500	-3.000
Taro_Root	100	125	150	200	none	crop	Special Crop	10	0	0	0	Special	0	1	FALSE	10.000	12.500	15.000	20.000
Taro_Root	110	137	165	220	tiller	crop	Special Crop	10	0	0	0	Special	0	1	FALSE	11.000	13.700	16.500	22.000
Tomato	60	75	90	120	none	crop	Summer Crop	11	50	62	0	Summer	50	1	TRUE	0.909	2.273	3.636	6.364
Tomato	66	82	99	132	tiller	crop	Summer Crop	11	50	62	0	Summer	50	1	TRUE	1.455	2.909	4.455	7.455
Tulip	30	37	45	60	none	crop	Spring Crop	6	20	25	0	Spring	20	1	FALSE	1.667	2.833	4.167	6.667
Tulip	33	40	49	66	tiller	crop	Spring Crop	6	20	25	0	Spring	20	1	FALSE	2.167	3.333	4.833	7.667
Unmilled_Rice	30	37	45	60	none	crop	Spring Crop	8	40	0	0	Spring	40	1	FALSE	-1.250	-0.375	0.625	2.500
Unmilled_Rice	33	40	49	66	tiller	crop	Spring Crop	8	40	0	0	Spring	40	1	FALSE	-0.875	0.000	1.125	3.250
Wheat	25	31	37	50	none	crop	Summer Crop	4	10	12	0	Summer	10	1	FALSE	3.750	5.250	6.750	10.000
Wheat	25	31	37	50	none	crop	Fall Crop	4	10	12	0	Fall	10	1	FALSE	3.750	5.250	6.750	10.000
Wheat	27	34	40	55	tiller	crop	Summer Crop	4	10	12	0	Summer	10	1	FALSE	4.250	6.000	7.500	11.250
Wheat	27	34	40	55	tiller	crop	Fall Crop	4	10	12	0	Fall	10	1	FALSE	4.250	6.000	7.500	11.250
Wild_Plum	80	100	120	160	none	crop	Special Crop	0	0	0	0	Special	0	1	FALSE	Inf	Inf	Inf	Inf
Yam	160	200	240	320	none	crop	Fall Crop	10	60	75	0	Fall	60	1	FALSE	10.000	14.000	18.000	26.000
Yam	176	220	264	352	tiller	crop	Fall Crop	10	60	75	0	Fall	60	1	FALSE	11.600	16.000	20.400	29.200

NA Professions

Similar to the NA values for if the seed wasn’t sold at the mart, our app wouldn’t run if there were NA values for the profession, so for every category we will update the NA value with “none”

Code

final_minerals_prices <- tidy_sd_minerals_price |>
  mutate(profession = replace_na(profession, "none"))
#write_csv(final_minerals_prices, "final_minerals_prices.csv")

fish_prices <- tidy_fish_prices |>
  mutate(profession = replace_na(profession, "none"))
#write_csv(fish_prices, "fish_prices.csv")

Fish Map

Lastly, we need the data for creating our map for the locations of the fish.

Code

line_thick = 0.05
width = 1224
height = 742

# Draw a rectangle that defines the shape of map
map_int <- rbind(
  c(0, 0),
  c(0, height),
  c(width, height),
  c(width, 0),
  c(0,0)
  )

# Draw a rectangle that defines the map exterior
map_ext <- rbind(
  c(0-line_thick, 0-line_thick),
  c(0-line_thick, height + line_thick),
  c(width + line_thick, height + line_thick),
  c(width + line_thick, 0-line_thick),
  c(0-line_thick, 0-line_thick)
  )

# Define a sfg polygon object in sf by subtracting interior from exterior
map_shape <- st_polygon(list(map_ext, map_int))

# verify sfg class of polygon
#class(map_shape)

# save shapefile as rds
#saveRDS(map_shape, "projects/archived_folder/stardew_folder/stardew_data_folder/map_shape.rds")

# load the image as a raster
#img <- brick("projects/archived_folder/stardew_folder/stardew_data_folder/stardewmap.png") 

# inspect the image dimensions
#print(img)

# extract bounds(xmin, xmax, ymin, ymax)
#bounds <- extent(img)
#print(bounds)

# create image map df with center map pixel size
stardewmap_df <- data.frame(
  x = 612, 
  y = 371, 
  image = "stardewmap.png"
)

# write it in csv form 
#write_csv(stardewmap_df, "projects/archived_folder/stardew_folder/stardew_data_folder/stardewmap_df.csv")
#stardewmap_df <-read_csv("projects/archived_folder/stardew_folder/stardew_data_folder/stardewmap_df.csv")

# testing map
ggplot() +
  geom_sf(data = map_shape) +
  geom_image(data = stardewmap_df, aes(x, y, image = image), size = 1.496)

Now that we have our map, we want to specify the x and y coodinates of our location, we did this by creating a new data frame with these locations.

Code

# get data ready
xy <- data.frame(
    sub_category = c("The Beach", "River", "Night Market", "Ginger Island", "Mountain Lake", "Secret Woods", "Sewers", "Mutant Bug Lair", "Witch's Swamp", "Crab Pot", "Mines", "Cindersap Forest Pond", "Desert"),
    x = c(850, 850, 800, 1150, 900, 200, 725, 725, 210, 400, 900, 300, 20),
    y = c(120, 300, 100, 50, 550, 400, 260, 260, 305, 390, 610, 300, 710)
  )

# write in our x and y coordinates
#write_csv(xy, "projects/archived_folder/stardew_data_folder/xy.csv")
#read_csv("projects/archived_folder/stardew_data_folder/xy.csv")

fish_prices_sf <- fish_prices |>
  left_join(xy, join_by(sub_category)) |>
  filter(!is.na(x)) |>
  mutate(x = ifelse(item == "Angler", 815, x),
         y = ifelse(item == "Angler", 500, y),
         x = ifelse(item == "Ms._Angler", 815, x),
         y = ifelse(item == "Ms._Angler", 500, y),
         x = ifelse(item == "Crimson", 805, x),
         y = ifelse(item == "Crimson", 70, y),
         x = ifelse(item == "Son_of_Crimsonfish", 805, x),
         y = ifelse(item == "Son_of_Crimsonfish", 70, y),
         ) |>  
  st_as_sf(coords = c("x", "y"))

# save shapefile
#saveRDS(fish_prices_sf, "projects/archived_folder/stardew_data_folder/fish_prices_sf.rds")
#fish_prices_sf <- readRDS("data/fish_prices_sf.rds")

Finally, we have all the information needed to make our app work.