DATA607_Assignment_9

Assignment - Web APIs

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 into an R DataFrame.

We will need to use libraries httr, jsonlite, and dplyr to extract the data from API from JSON format to R Dataframe

library(httr)
library(jsonlite)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats   1.0.0     ✔ readr     2.1.5
## ✔ ggplot2   3.5.1     ✔ stringr   1.5.1
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.1

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter()  masks stats::filter()
## ✖ purrr::flatten() masks jsonlite::flatten()
## ✖ dplyr::lag()     masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Sign up for the NY Times developer apis and activate an API key for the API accessing. I choose the books API and from the API documentation get the base url and use it to build out API call.

# Define API key and endpoint
api_key <- "PR6ullqlzC8T72wCHIUWBbqkTQWAgRRe"
base_url <- "https://api.nytimes.com/svc/books/v3/lists/full-overview.json"

Get the response with the url constructed and check the response code

# Construct the full URL with query parameters
url <- paste0(base_url, "?", "&api-key=", api_key) %>% print()

## [1] "https://api.nytimes.com/svc/books/v3/lists/full-overview.json?&api-key=PR6ullqlzC8T72wCHIUWBbqkTQWAgRRe"

# Make the GET request
response <- GET(url)

# Check if the request was successful
if (status_code(response) != 200) {
  stop("API request failed!")
  }

Parse the response data into json format then convert it to dataframe.

# Parse the JSON response into a list
json_data <- fromJSON(content(response, "text", encoding = "UTF-8"))

# Extract JSON to dataframe
book_lists <- json_data$results$lists %>% as.data.frame()
books <- json_data$results$lists$books
# Empty dataframe for books
books_df <- data.frame(counter = integer(),
                       title = character(), 
                       author = character(), 
                       rank = integer(), 
                       last_rank = integer(),
                       publisher = character(),
                       stringsAsFactors = FALSE)
# create an identifier for join later
book_lists <- book_lists %>% mutate(counter = 1:18)

# parsing the list of books
item <- 1
for (book in books) {
  dataf <- data.frame(
    counter = item,
    title = book$title,
    author = book$author,
    rank = book$rank,
    last_rank = book$rank_last_week,
    publisher = book$publisher,
    stringsAsFactors = FALSE
  )
  books_df <- rbind(books_df, dataf)
  item <- item+1
  }

# Create data frame for best sellers
best_sellers <- left_join(books_df, book_lists %>% select(counter, list_id,list_name,updated)) %>% select(-counter)

## Joining with `by = join_by(counter)`

Analysis

# Which author was on the best seller list the most times
best_author <- best_sellers %>% 
  count(author) %>%
  arrange(desc(n)) %>%
  head(6)

best_author

##             author n
## 1  Freida McFadden 6
## 2   Kristin Hannah 6
## 3   Rebecca Yarros 5
## 4    Sarah J. Maas 5
## 5       Dav Pilkey 4
## 6 Malcolm Gladwell 4

best_sellers %>% 
  filter(author %in% best_author$author) %>% 
  ggplot(aes(x = author)) +
  geom_bar()

# Which publisher produced the most best sellers
best_publisher <- best_sellers %>% 
  count(publisher) %>% 
  arrange(desc(n)) %>% 
  head(3)

best_publisher

##            publisher  n
## 1         Scholastic 15
## 2              Crown  9
## 3 Random House Audio  9

best_sellers %>% 
  filter(publisher %in% best_publisher$publisher) %>% 
  ggplot(aes(x = publisher)) +
  geom_bar()

Conslusion

Freida McFadden and Kristin Hannah authored the most best sellers for different categories as of the list from December. Scholastic is the publisher that published the most best sellers.