Assignment

Your task is to choose one of the New York Times APIs, construct an interface in R to read in the JSON data, and transform it to an R dataframe.

My Take

I am sure that every publishing executive has a dashboard that shows how the books on the NY Times are performing. While the code below calls the NY Times API and gets the data from the “Combined Print and E-Book Fiction” list, I am sure this is just one square on the publisher’s NY Times Bestseller Dashboard. I am sure they have squares for each list on the NY Times Best Sellers list on thier Dashboard.

Create the Dashboard Tile

library(httr)
library(ggplot2)
library(knitr)


#Call API and store payload
api_key <- readLines("api_key.txt") [[1]]
base_url <- "https://api.nytimes.com/svc/books/v3/lists//.json"
query_list = list( `api-key`=api_key, list="combined-print-and-e-book-fiction")
response <- GET(base_url, query=query_list)
payload <- content(response)

book_names <- vector()
weeks_on_list <- vector()
current_rank <- vector()
prev_rank <- vector()
 
#Loop through books on the best sellers list
for ( i in 1: 20) {
  book_names <- c( payload$results[[i]]$book_details[[1]]$title, book_names) 
  weeks_on_list <- c(  as.numeric  (payload$results[[i]]$weeks_on_list), weeks_on_list   )
  current_rank <- c(  as.numeric  (payload$results[[i]]$rank), current_rank   )
  prev_rank <- c(  as.numeric  (payload$results[[i]]$rank_last_week), prev_rank   )
}

#Create a dataframe
books_df = data.frame(
  book_names = book_names,
  weeks_on_list = weeks_on_list,
  current_rank = current_rank,
  prev_rank = prev_rank
  )

#Freeze data frame so books show up in ggplot in the correct order
books_df$book_names <- factor(books_df$book_names, levels = books_df$book_names)


#Add derived column showing direction of the book
rising_falling_static <- ifelse ( current_rank >prev_rank , "Rising", 
                                  ifelse( current_rank == prev_rank, "No Change", "Falling" ))
books_df <- cbind(books_df,rising_falling_static )
books_df$rising_falling_static <- factor(books_df$rising_falling_static)

kable(books_df)

book_names	weeks_on_list	current_rank	prev_rank	rising_falling_static
THE UNDERGROUND RAILROAD	0	20	0	Rising
MILK AND HONEY	0	19	0	Rising
THE FIX UP	0	18	0	Rising
GOING DOWN FAST	0	17	0	Rising
THE WOMAN IN CABIN 10	0	16	0	Rising
TODAY WILL BE DIFFERENT	2	15	9	Rising
WOMAN OF GOD	3	14	12	Rising
THE LIGHT BETWEEN OCEANS	15	13	13	No Change
THE TRESPASSER	2	12	4	Rising
PRECIOUS AND GRACE	1	11	0	Rising
MISSING	2	10	3	Rising
COMMONWEALTH	5	9	8	Rising
INFERNO	32	8	10	Falling
HOME	4	7	5	Rising
CRIMSON DEATH	1	6	0	Rising
A MAN CALLED OVE	21	5	6	Falling
TWO BY TWO	2	4	2	Rising
SMALL GREAT THINGS	1	3	0	Rising
VINCE FLYNN: ORDER TO KILL	1	2	0	Rising
THE GIRL ON THE TRAIN	86	1	1	No Change

 ggplot( data = books_df, aes  (x = book_names, y=weeks_on_list,
                                fill=rising_falling_static )) + 
   geom_bar(stat="identity") + 
   coord_flip() +
   scale_fill_manual(values=c("#ff0000", "#ffff00", "#00ff00")) + 
   xlab("Book Title") + 
   ylab("Weeks on List") +
   ggtitle ("NY Times Best Seller Dashboard") +
   theme(legend.position="bottom") +
   guides(fill=guide_legend(title="Direction of Change Since Last Week:"))

CUNY-DATA-607-WebAPIs

Raphael Nash

10/23/2016

Assignment

My Take

Create the Dashboard Tile