In this assignment we will demonstrate how to fetch and analyze books data from the New York Times Books API. The list we’re interested in is “Hardcover Fiction,” and we will transform the JSON response into an R data frame.
# Function to fetch and transform NY Times Books data
get_nyt_books_data <- function(api_key, list_name = "hardcover-fiction") {
# Construct the URL
url <- paste0("https://api.nytimes.com/svc/books/v3/lists.json?list=", list_name, "&api-key=", api_key)
# Make the GET request
response <- GET(url, accept("application/json"))
if (status_code(response) == 200) {
json_data <- content(response, as = "text", encoding = "UTF-8")
data <- fromJSON(json_data, flatten = TRUE)
# Extract book details into a separate data frame
books_details_df <- data$results %>%
mutate(book_details = map(book_details, ~ .x %>%
as.data.frame() %>%
select(title, author))) %>%
unnest(book_details)
#select and work with columns directly
books_summary <- books_details_df %>%
select(rank, title, author, weeks_on_list)
print(books_summary)
} else {
books_df <- NULL
print("Failed to fetch data from the API.")
}
}
api_key <- "gYMvXAooRmMGPCBIAj8ADZAIT0pBzW97"
books_data <- get_nyt_books_data(api_key)## # A tibble: 15 × 4
## rank title author weeks_on_list
## <int> <chr> <chr> <int>
## 1 1 IN TOO DEEP Lee Child and Andrew Child 1
## 2 2 BLOODGUARD Cecy Robson 1
## 3 3 THE WAITING Michael Connelly 2
## 4 4 COUNTING MIRACLES Nicholas Sparks 5
## 5 5 THE WOMEN Kristin Hannah 38
## 6 6 IRON FLAME Rebecca Yarros 51
## 7 7 ABSOLUTION Jeff VanderMeer 1
## 8 8 INTERMEZZO Sally Rooney 5
## 9 9 HERE ONE MOMENT Liane Moriarty 7
## 10 10 MEMORIALS Richard Chizmar 1
## 11 11 THE GOD OF THE WOODS Liz Moore 17
## 12 12 THE STARS ARE DYING Chloe C. Peñaranda 3
## 13 13 JAMES Percival Everett 17
## 14 14 FOURTH WING Rebecca Yarros 74
## 15 15 ALL THE COLORS OF THE DARK Chris Whitaker 15The data fetched from the New York Times Books API has been converted into a data frame and displayed below
head(books_data)## # A tibble: 6 × 4
## rank title author weeks_on_list
## <int> <chr> <chr> <int>
## 1 1 IN TOO DEEP Lee Child and Andrew Child 1
## 2 2 BLOODGUARD Cecy Robson 1
## 3 3 THE WAITING Michael Connelly 2
## 4 4 COUNTING MIRACLES Nicholas Sparks 5
## 5 5 THE WOMEN Kristin Hannah 38
## 6 6 IRON FLAME Rebecca Yarros 51Now that the data is loaded, lets perform some analysis.
# Summarize the data
summary(books_data)## rank title author weeks_on_list
## Min. : 1.0 Length:15 Length:15 Min. : 1.00
## 1st Qu.: 4.5 Class :character Class :character 1st Qu.: 1.50
## Median : 8.0 Mode :character Mode :character Median : 5.00
## Mean : 8.0 Mean :15.87
## 3rd Qu.:11.5 3rd Qu.:17.00
## Max. :15.0 Max. :74.00# Check unique book titles
unique(books_data$title)## [1] "IN TOO DEEP" "BLOODGUARD"
## [3] "THE WAITING" "COUNTING MIRACLES"
## [5] "THE WOMEN" "IRON FLAME"
## [7] "ABSOLUTION" "INTERMEZZO"
## [9] "HERE ONE MOMENT" "MEMORIALS"
## [11] "THE GOD OF THE WOODS" "THE STARS ARE DYING"
## [13] "JAMES" "FOURTH WING"
## [15] "ALL THE COLORS OF THE DARK"This assignment shows how to interface with an external API, parse JSON data, and transform it into an R data frame for further analysis. The data can be used for various visualizations and analyses in R.