Data from APIs

Google Trends API

Explanation of service

Google Trends is a platform that helps compare search popularity between different subjects during a time frame that one can set. The reason why I chose this platform is because I wanted to see how brand popularity has affected the shoe market after Nike stopped selling to common retailers. One way that this platform can be used for would be to see trends in seasons to understand during what seasons a topic is more popular or what products.

Set Up

The Google Trends API is very easy to use, to be able to access it one has to install the gtrendsR package.

After installing the package one has to use the library(gtrendsR) command.

# Load packages
library(tidyverse) # All the tidy things

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.2     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.0
✔ ggplot2   3.4.3     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

# New Package 
library(gtrendsR)  # Provides interface for receiving and displaying Google Trends                        info 

Demonstration

One of the functions that this package has is that one can compare the popularity of any subject and select the region that you would like to target. An example of this is shown below where I compare the brands Nike, Adidas, New Balance, and Puma in the United States to observe its popularity over the past 4 years. With this information one can use the tidyverse to be able to create new visuals to help explain information.

res <- gtrends(c("Nike", "Adidas", "New Balance", "Puma"), geo = c("US"))

plot(res)