Articles by AbdulMajedRaja RS

Analyse Google Trends Search Data in R using {gtrendsR}

June 7, 2020 | AbdulMajedRaja RS

As much as Google is popular for searching information on the web, Google can also provide information (meta) about those searches. Google Search Insights can be extremely helpful in Marketing Analytics, Market Research, Understanding Customer Demands, Trends and so on. While usual Market Researches or someone interested in Google Search ...
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Easy ggplot2 Theme customization with {ggeasy}

April 21, 2020 | AbdulMajedRaja RS

In this post, We’ll learn about {ggeasy} an R package by Jonathan Carroll. The goal of {ggeasy} is to help R programmers make ggplot2 theme customizations with simple-easy English functions. (much easier than playing with theme()) We use dataset generated by {fakir} for this tutorial. Youtube: https://youtu.be/...
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Android Smartphone Analysis in R [Code + Video]

April 12, 2020 | AbdulMajedRaja RS

In this post, We’ll learn how to take analyse your Android Smartphone usage data. Steps: Download your MyActivity Data from Google Takeout - https://takeout.google.com/ (after Selecting json format - instead of the default html format) When the download is available, save the zip file and unzip ...
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Scrape HTML Table using rvest

April 8, 2020 | AbdulMajedRaja RS

In this tutorial, we’ll see how to scrape an HTML table from Wikipedia and process the data for finding insights in it (or naively, to build a data visualization plot). Youtube - https://youtu.be/KCUj7JQKOJA Why? Most of the times, As a Data Scientist or Data Analyst, ... [Read more...]

How to create Bar Race Animation Charts in R

January 7, 2020 | AbdulMajedRaja RS

Bar Race Animation Charts have started going Viral on Social Media leaving a lot of Data Enthusiasts wondering how are these Bar Race Animation Charts made. The objective of this post is to explain how to build such Bar Race Animation Charts using R — R with the power of versatile ...
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Handling Missing Values in R using tidyr

September 22, 2019 | AbdulMajedRaja RS

In this post, We’ll see 3 functions from tidyr that’s useful for handling Missing Values (NAs) in the dataset. Please note: This post isn’t going to be about Missing Value Imputation. tidyr According to the documentation of tidyr, The goal of tidyr is to help you create tidy ... [Read more...]
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