Google Trends Data Mining Using R
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Google Trends Data Mining Using R

Building an automated solution to download Google Trends data for a large number of terms.
3.9 (11 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
228 students enrolled
Last updated 2/2017
English
Current price: $10 Original price: $35 Discount: 71% off
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Includes:
  • 2 hours on-demand video
  • 5 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I 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.
View Curriculum
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.

Who is the target audience?
  • Those wanting to retrieve and explore large amounts of Google Trends data.
  • Students with beginner level of R understanding and those wanting to join course which is not typical beginner's curriculum. We will stay focused on using R to automate a software process.
  • We will NOT deal with any statistics here!
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Curriculum For This Course
14 Lectures
01:44:35
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Introduction to Google Trends web Search engine
1 Lecture 06:31
  • Introduction to Google Trends as a tool for deriving interesting insights about the world around us.
  • Understand the layout of Trends data.
  • Bottlenecks associate with Google Trends website.
Preview 06:31
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Understanding R functions one at a time
9 Lectures 01:10:56
  • Import and Export of text files using read.table and read.csv functions.
  • Export R data files using write.csv and write.table functions.
  • Address various commonly faced issues.
Import Export of txt and csv files
08:02

  • Create data frames.
  • Create calculated variables.
  • Change variable names in an existing data frame.
Data Frames in R Part 1
05:54

Data Frames in R Part 2
09:07

Use systems command to:

  • Create Directories.
  • Copy multiple files.
  • Rename files.
  • Use wild cards (characters) in these functions to allows selection of files with a particular characteristic.

Reinforce the concepts for lapply and do.call functions to read in multiple files and stack them using rbind function.

Performing system functions using R
12:44

  • Create list objects and sub set them.
  • Distinguish between lapply and do.call functions.
  • Combine lapply and do.call functions to achieve desired outcomes.
Preview 07:10

  • Conceptualize the manual steps and how to automate them using R.
  • Capture the string that is submitted to Google Trends servers from Chrome's 'Inspect Element' Tools menu.
  • Set up a batch script to open Chrome and download a particular response from a server.



Review Windows Batch processes
08:03

  • Use R to write a .bat (batch) file.
  • Execute batch files from R.
Write a Windows Batch process from R
04:52

Combinding the power of Batch files with R "For loops"
09:50

  • Understand the concept of Anchor term and its role as 'equalizer' of data across search terms.
  • learn to identify an Anchor term from the collection of search terms.
  • Modify an existing batch file to include two search item simultaneously.
  • Create a Pivot chart in Excel to visualize the data.


Use of an Anchor search term to enable comparative analysis of Trends data
05:14
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Bringing it all together: Setting up the automated R process.
2 Lectures 15:04
  • Put together all the functions described above in the context of a bigger project.
  • Set up a file as a repository for search terms used in a project.
  • Use for loop to iterate over all the search terms to create and execute batch files specifically created for each search term.
Automating a Google Trends data download.
08:14

  • Set up your first automated task using Task Scheduler, Batch file, and a R script.
  • Precautions needed when downloading data for a large number of terms on a slow internet or machine.
  • Override a scheduled task in Windows Scheduler.
Scheduling Trends Data Download using R script, .bat, and Task Scheduler
06:50
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Section 4: Using gTrendsR package
2 Lectures 12:04
  • Understand different options offered by gTrendsR package to access Trends data.
  • Use various options in gtrends() such as query vector, geographical area, start date , end date,  resolution etc.
  • Dissect the list object returned by gtrends() after querying Google Trends.
Getting started with gTrendsR package
05:12

Use gTrendsR to download large amounts of data
06:52
About the Instructor
Sanjeev Baniwal  Ph.D.
3.9 Average rating
11 Reviews
228 Students
1 Course
Data Scientist

I have played at the forefront of data analytics for the last 15 or so years. Until 2010, I worked at University of Southern California, Los Angeles as Assistant Professor and then moved to The Nielsen Company to join Analytics team focused in Social Media and Entertainment space.  I am interested in using the power of Big Data to understand basic human behaviour when making a choice. 

Apart from Data Science, my interests include Baseball, Cricket, and Hiking.