[Free] Google Trends Data Mining Using R

Building an automated solution to download Google Trends data for a large number of terms. – Free Course

Added on July 28, 2023 IT & Software 2 min read

What you’ll learn

• Set up your own process in R to autonomously download and process large amounts of Google Trends data.
• Automate various tasks used in a day to day life of a data scientist through R.
• Understand each line of code used in the course and how it fits in the bigger picture of a live project.
• Two independent approaches used in the course to access Trends data will reinforce the concept of building R solutions from scratch. In one approach, we will exclusively use Base R methods, and in other, learn how to work with R packages.
• You will be able to run various windows commands from R e.g. copy, rename, delete files on hard disc etc
• Use Window’s Task Scheduler to have desktop run R in batch mode on recurring basis.
• Your R toolbox will become much more diverse and applicable to a wide range of future projects.

Requirements

• No prerequisites, previous exposure to R and windows work environment will be helpful..
• You will need access to R, Windows, Google account, Chrome.

Description

Google Trends is a new tool in a Data Scientist or a Marketing Analyst’s tool box. It provides data that could be quite useful when assessing trend in general public interest in a particular product or an array of products. Trends data essentially gives us a way to assess how often a particular search was performed on world’s most popular search engine.

However, Google Trends only allows a simultaneous search of up to five terms, also it does not provide data through a dedicated API. This course describes two processes in R which could be employed to circumvent both of these issues. First process stitches together R and Windows batch system. Second, utilize gtrendsR package. In both case we set up an automated process.

The course begins by describing Google Trends data itself, and then various R functions relevant to build the automated solution. In the third section, we apply the knowledge from previous sections to build a complete end to end solution.

By the end of the course, we will better understand how R could be employed in more automated manner with minimum human involvement. Additionally, better appreciate the power of Google Trends data to provide a greater understanding of the way the world around us functions.

Author(s): Sanjeev Baniwal Ph.D.