Coral Bleaching Analysis Visualisation — Tableau or R ggplot?

Coral Bleaching Analysis Visualisation — Tableau or R ggplot?

Comparing the effectiveness of Tableau and R ggplot to deliver the key messages in Coral Bleaching Analysis. This article will look into this, and hopefully arrive at a common consensus for all.

Tableau and R are two common data visualisation tools where the former is known for it’s simple and beginner-friendly functions, and the latter for it’s extensive user interaction possibilities. How do we decide which visualisation tool is easier to implement or more effective in conveying the key insights to the relevant stakeholders? This article will look into this, and hopefully arrive at a common consensus for all.

Dataset

The dataset we will be using contains Coral Bleaching percentages located in Great Barrier Reef from 2010 to 2017. There’s a total of 5 different coral types, mainly Blue Corals, Hard Corals, Sea Fans, Sea Pens and_ Soft Corals_. 8 different sites/locations along with their latitudes and longitudes situated in Great Barrier Reef has been provided.

Image for post

Image by author — R output of first 6 records in dataset

Key Message

In every data visualisation we build, there must be a key message we wish to deliver to the relevant stakeholders so that appropriate actions can be taken as supported by these data insights. In this dataset, we wish to address the following questions:

1. In which year and which type of coral bleaching was the worst from 2010 to 2017?

2. How does the location of the site affects bleaching on the different coral types?

data-visualization data-analysis r tableau data-science

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

Data Cleaning in R for Data Science

A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.

Tableau Data Analysis Tips and Tricks

Tableau Data Analysis Tips and Tricks. Master the one of the most powerful data analytics tool with some handy shortcut and tricks.

Exploratory Data Analysis is a significant part of Data Science

Data science is omnipresent to advanced statistical and machine learning methods. For whatever length of time that there is data to analyse, the need to investigate is obvious.

Data Analysis and Visualization of scraped data from IMDb with R

TV Series that Geeks (and not so geeks) love

50 Data Science Jobs That Opened Just Last Week

Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.