R is meant for Data analytics and it is no longer a secret!. No other language can serve better than R when it comes to analytics and statistical computations. In recent years the careers in R are rising than ever before. If you wish to be your career in analytics and started to learn R, then these are the best projects on R programming for you. 

Why R for Analytics?

R language is specifically made for statistical analysis and computations. The R has many inbuilt features, packages, and tools which facilitate the precise analysis of data.

Since the rise of Big Data, tons of data is being generating every alternative minute and companies are investing big in aspects like Data science, Machine learning, Big data, Data mining, engineering, analytics and more to get some crucial insights and boost their profits.

Being an analytical friendly language, R has got greater importance in the analytics industry than any other programming language. With its data storing, wrangling, processing, modeling features, R is impeccable for data analytics.

Let’s dive into our gathered choices of best 5 Projects on R programming for you.

1. Sentiment Analysis (Social Media)

projects on R

Today, social media are the leading sources of data collection. Billions of people are using social media every day and tons of data is generating and stored in their databases.

The sentiment analysis is the process of analyzing the given works and sensing the nature of reaction such as positive, negative, sab, excited, angry, and more. The categories in this may be binary as well as multiple.

So using the R language we can analyze the words and find the sentiment of the people through their words. This will help you to get good knowledge over the data mining and analyzing techniques using the R language.

Project Details with Code: Sentiment Analysis

2. Movie Recommendation System


Whether you are learning Machine learning, Data Science, and Data analytics, the recommendation systems are not going to leave you. These are just like the default projects for most of the data-heavy technologies.

If you ever watched Netflix, or browsed on Amazon web store, after your watch or purchase, you will get similar movies and products in front of you respectively. Did you ever thought about how???

Recommendation Engines!!!

Yes, online platforms such as streaming sites, E-commerce sites and more will use the recommendation engines to push similar products at you to increase the chances of purchase.

In the R, you can make use of packages like ggplot2, data.table, and importantly recommender lab for this project. It will be simple and you will get a lot of exposure to algorithms and classification techniques as well.

Project Details with Code: Movie recommendation Engine

3. Uber Data Analysis

projects on R

Uber is one of the premium Cab service providers across the globe. You can get a dataset names ‘Uber pickups in New York City’, on which you have to perform the data analysis techniques and visualize the results to ease the storytelling purpose at the end of the project.

R has many packages for good looking visualizations. You can use tidyverse, Viridis, hrbrthemes, ggplot2, and more packages to create compelling visualization effects.

In this project, you have to analyse the customer behaviour with the Uber services in New York city to draw key inferences.

Project Details with Code: Uber data analysis

4. Customer segmentation

projects on R

The segmentation problems are one of the best projects to work on. If any company wants to run a campaign, a promotional activity or to launch specific offers to a particular group of people then you should need customer segmentation.

Customer segmentation is one of the most widely used techniques by the companies as they can launch effective marketing activities without wasting their time on other things.

Project Details with Code: Customer segmentation

5. Credit Card Fraud detection

projects on R

Well, the most important sector deals with a huge amount of data in the banking/finance sector. As the world is growing digitally, all the transactions are happening through online mode, and people who use credit and debit cards also increasing day by day.

This also raised the issue of credit card frauds. You can use R language for building a model, analysing the data to get the unusual transaction data and its details.

Well, You can use algorithms like regressors, Classifiers, and more. You have to import the data, process it, analyze it, and build a model that identifies the frauds made using the credit cards.

Project Details with Code: Credit card fraud detection

Things to know before you start

There are specific steps involved in a data analysis project. so we have provided 6 crucial steps for your project on R programming.

  • Problem statement
  • The Data collection
  • Cleaning of Data
  • Data analysis
  • Modelling
  • Optimisation and Deployment

Conclusion – Projects on R

The need for the R language is in high demand in the data analytics field. We all know how powerful R is. Any mathematical computations and statistical modeling are the key features of the R language.

You can choose the projects on R of your choice from the list. That’s all for now. Happy Data analysis!!!

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