Data607_Web_API

Introduction: The New York Times web site provides a rich set of APIs (link: https://developer.nytimes.com/apis). For this assignment, my 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. Here, I chose the movie critics JSON data for all reviewer from New York Times Movie Review APIs.

Loading libraries

library(jsonlite)
library(httr)
library(ggplot2)
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

Constructing an interface with required API and checking the response

# link to the API output as a JSON file
url_json <- "https://api.nytimes.com/svc/movies/v2/critics/all.json?api-key=VAhjWqxLrMQTPsvIOYxaH7gFuKWE79en"
#get the raw json into R
resp <- GET(url_json)
resp

## Response [https://api.nytimes.com/svc/movies/v2/critics/all.json?api-key=VAhjWqxLrMQTPsvIOYxaH7gFuKWE79en]
##   Date: 2022-10-30 20:31
##   Status: 200
##   Content-Type: application/json; charset=utf-8
##   Size: 13.9 kB

Reading movie critics JSON data and converting it into a R dataframe

critics_data<- fromJSON(rawToChar(resp$content))%>% data.frame
glimpse(critics_data)

## Rows: 82
## Columns: 9
## $ status               <chr> "OK", "OK", "OK", "OK", "OK", "OK", "OK", "OK", "…
## $ copyright            <chr> "Copyright (c) 2022 The New York Times Company. A…
## $ num_results          <int> 82, 82, 82, 82, 82, 82, 82, 82, 82, 82, 82, 82, 8…
## $ results.display_name <chr> "A. O. Scott", "Renata Adler", "Robert Alden", "E…
## $ results.sort_name    <chr> "A. O. Scott", "Adler, Renata", "Alden, Robert", …
## $ results.status       <chr> "full-time", "part-time", "", "part-time", "part-…
## $ results.bio          <chr> "A. O. Scott joined The New York Times as a film …
## $ results.seo_name     <chr> "A-O-Scott", "Renata-Adler", "Robert-Alden", "Eug…
## $ results.multimedia   <df[,1]> <data.frame[26 x 1]>

Data tidying and subsetting

#Renaming two columns
critics_data<-rename(critics_data,critic_name=results.display_name,critic_status=results.status)
#Sub setting data frame with new column names
critics_data1<-select(critics_data,critic_name,critic_status)
head(critics_data1)

##          critic_name critic_status
## 1        A. O. Scott     full-time
## 2       Renata Adler     part-time
## 3       Robert Alden              
## 4      Eugene Archer     part-time
## 5        Miriam Bale     part-time
## 6 Felicity Barringer     part-time

#Replace empty value with NA in critic_status column
critics_data1$critic_status[critics_data1$critic_status==''] <- NA
head(critics_data1)

##          critic_name critic_status
## 1        A. O. Scott     full-time
## 2       Renata Adler     part-time
## 3       Robert Alden          <NA>
## 4      Eugene Archer     part-time
## 5        Miriam Bale     part-time
## 6 Felicity Barringer     part-time

#Finding critics status count data
critics_status_count_data <- critics_data1 %>% count(critic_status)
critics_status_count_data

##   critic_status  n
## 1     full-time  3
## 2     part-time 56
## 3          <NA> 23

Plotting critics status based on their occuring number

ggplot(data=critics_status_count_data, aes(x=critic_status, y=n)) +
  geom_bar(stat="identity") + 
    labs(
      x = "Critic Status",
      y = "Number of Critic Status",
      title = "The number of critic status"
    ) + 
    coord_flip()

Conclusion: In this assignment, I chose movie critics data for all reviewer from New York Times Movie Review API.I collected JSON data through a API connection and transformed that JSON data into a R data frame. Finally, I plotted a bar graph to see the critics status based on their occuring numbers.