In tpemartin/econDV2:

ntpu_restaurants_fbf <- jsonlite::fromJSON("C:/Users/user/Desktop/RRR/learning~R/learning R class/final/ntpu_restaurants.json", simplifyDataFrame = T)
ntpu_restaurants_obo <- jsonlite::fromJSON("C:/Users/user/Desktop/RRR/learning~R/learning R class/final/ntpu_restaurants.json", simplifyDataFrame = F)

View(ntpu_restaurants_fbf)
View(ntpu_restaurants_obo)

營業狀態

businessStatus <- function(){
  cal <- list()
  rstudioapi::showPrompt('', message="Operational or not.\n(T or F)") -> status
if(status){
statusCheck <- ntpu_restaurants_fbf |>
  subset(business_status == "OPERATIONAL")
} else{
statusCheck <- ntpu_restaurants_fbf |>  subset(business_status == "CLOSED_TEMPORARILY")
}

cal$total <- length(statusCheck$name)
cal$percentage <- round(cal$total/60*100, 2)

View(statusCheck$name)
cal
}
businessStatus()

物價水平

priceLevel <- function(){
  cal <- list()
  rstudioapi::showPrompt('', message="Input the price level value you want.\n(1 or 2)") -> price

priceLevel <- c()
priceLevel <- 
  ntpu_restaurants_fbf |> subset(price_level==price)

cal$total <- length(priceLevel$name)
cal$percentage <- round(cal$total/60*100, 2)

View(priceLevel$name)
cal
}
priceLevel()

評論星數

rating <- function(){
  cal <- list()
  rstudioapi::showPrompt('', message="Input the lowest rating value you want.") -> value

rating_higherThanOrEqualToValue <- ntpu_restaurants_fbf[which(as.numeric(ntpu_restaurants_fbf$rating) >= as.numeric(value)), c("name", "rating")]

print(glue::glue("The following are those restaurants whose rating are higher than or equal to {value}."))

for (.x in seq_along(rating_higherThanOrEqualToValue$name)) {
  print(rating_higherThanOrEqualToValue$name[[.x]])
  print(rating_higherThanOrEqualToValue$rating[[.x]])
}

cal$total <- length(rating_higherThanOrEqualToValue$name)
cal$percentage <- round(cal$total/60*100, 2)

View(rating_higherThanOrEqualToValue)
cal
}
rating()

道路

vicinity <- function(){
  roadName <- list(c("Dade Road", "大德路"), c("Daguan Road", "大觀路"), c("Daxue Road", "大學路"), c("Dayi Road", "大義路"), c("Guoji 1st Street", "ˇ國際一街"), c("Guoji 2nd Street", "國際二街"), c("Guoxue Street", "國學街"), c("Xuefu Road", "學府路"), c("Xueqin Road", "學勤路"))
restaurantOnRoad <- list()
restaurantOnRoadDetail <- list()
cal <- list()

rstudioapi::showPrompt('', message="Input the road you want to go to.\n(using english)") -> destination
rstudioapi::showPrompt('', message="Detail?\n(T or F)") -> showDetail

for(.x in seq_along(roadName)){
  if(destination == roadName[[.x]][[1]]){
    destination == roadName[[.x]][[1]]
    pick1 <- ntpu_restaurants_fbf$vicinity |> stringr::str_detect(roadName[[.x]][[1]])
    pick2 <- ntpu_restaurants_fbf$vicinity |> stringr::str_detect(roadName[[.x]][[2]])
    restaurantOnRoad[[destination]] <- ntpu_restaurants_fbf[pick1 | pick2, c("name", "rating", "vicinity")]
    restaurantOnRoadDetail[[destination]] <- ntpu_restaurants_fbf[pick1 | pick2, ]
  }
}

if(showDetail){
  View(restaurantOnRoadDetail[[destination]])
} else{
  View(restaurantOnRoad[[destination]])
}

cal$total <- length(restaurantOnRoad[[1]]$name)
cal$percentage <- round(cal$total/60*100, 2)

cal
}
vicinity()

評論總數

ratingsTotal <- function(){
  cal <- list()
  rstudioapi::showPrompt('', message="Input the lowest ratings total value you want.") -> totalValue

ratingTotal_higherThanOrEqualToValue <- ntpu_restaurants_fbf[which(
  as.numeric(ntpu_restaurants_fbf$user_ratings_total) >= as.numeric(totalValue)), c("name", "user_ratings_total")]

print(glue::glue(
  "The following are those restaurants whose rating total value are higher than or equal to {totalValue}.")
  )

for (.x in seq_along(ratingTotal_higherThanOrEqualToValue$name)) {
  print(ratingTotal_higherThanOrEqualToValue$name[[.x]])
  print(ratingTotal_higherThanOrEqualToValue$rating[[.x]])
}

cal$total <- length(
  ratingTotal_higherThanOrEqualToValue$name)
cal$percentage <- round(cal$total/60*100, 2)

View(ratingTotal_higherThanOrEqualToValue)
cal
}
ratingsTotal()

評論總數分級

ntpu_restaurants_fbf$user_ratings_total <- 
  as.numeric(ntpu_restaurants_fbf$user_ratings_total)

max(ntpu_restaurants_fbf$user_ratings_total, na.rm = T)

ntpuMaximalValues <- c(0, 500, 1000, 1500, 2000, 2500)

ntpu_ratingTotal <- cut(
  ntpu_restaurants_fbf$user_ratings_total, 
  ntpuMaximalValues3,
  include.lowest = TRUE
  )

View(table(ntpu_ratingTotal, useNA = "always"))
mean(ntpu_restaurants_fbf$user_ratings_total, na.rm = T)
max(ntpu_restaurants_fbf$user_ratings_total, na.rm = T)

tpemartin/econDV2 documentation built on Aug. 6, 2023, 11:46 p.m.