Learn how to create better charts and find hidden insights in time series using appropriate aspect ratios for your line plots.

One of the most overlooked aspects of creating charts is the use of incorrect aspect ratios. Even in photography, changing the aspect ratio makes the photograph look skewed. Here, it is easy to rectify the aspect ratio. But is it that easy when creating charts?

Let’s compare three plots and…


Leveraging the extensions of the ggplot2 package on stepping up the visualizations.

On a single glance, when you look at a visualization, few things pop out, which may vary from person to person. Those eye-catching features can be the charts or images, colors used, text style, or even the background. If you are into data visualization and familiar with principles for creating…


Tips on how and when to choose bar charts over line plots when visualizing time-series data

Data visualization is a powerful tool for communicating information to a broader audience. This means apart from using the right color scheme, font size, and font type; using a proper chart type to depict the data is also important.

The focus of this article, as clear from the title, is…


Automate reading, writing, merging, and splitting multiple Excel files using R

One of the beauties of the data analytics field is its openness to multiple tools. The field has already shown that knowledge of one single tool is a handicap. In order to survive and grow in this field, you ought to be:

Jack of all trades and master of some


Key takeaways from the works of DataViz legends.

Here I discuss six guiding principles that I find very effective for creating good visualizations. Some are learned from experience/observations and others by the teaching of the pioneers of data visualizations.

“Good design is a lot like clear thinking made visual.”
Edward Tufte

This is not an exhaustive list…


A hands-on tutorial to get you to start creating maps with R.

Maps are one of the widely read and understood visualizations that keep getting more and more traction. Since the start of the pandemic, the maps caught my attention again after a gap of more than two decades. The…


Step by step guide to animate two different styles of bar charts

Data visualizations in the form of plot and infographics are the way to convey stories. The stories are appealing to the masses if they have substance to them and are self-explanatory. The reason infographics or presentations are more popular than a mere plot because they convey a story and are…


Opening up a plethora of R functionalities to Excel users with BERT add-in.

Excel has been the go-to data analytics tool for businesses for the last three decades. Excel provides built-in tools to conduct statistical analysis, creating budgets, forecasting, dashboards, data plotting, etc. And then there are add-ins to fill in the analytical gap or improve performance.

For me, Excel had been a…


Basic concepts covered from data prep to connecting UI and server to publishing the app online

Shiny is one of the powerful tools in the hand of data analysts and data scientists to develop web-based applications and interactive data visualizations. The Shiny app consists of two important functions: UI and the server function. …


Tee, exposition, and assignment pipe operators for clean code writing

Apart from hosting the main pipe operator %>% used by the Tidyverse community, the magrittr package in Tidyverse holds a few other pipe operators. The %>% pipe is widely used for data manipulations and is automatically loaded with Tidyverse.

The pipe operator is used to execute multiple operations that are…

Abhinav Malasi

Passionate about Dataviz | Mathviz | Machine Learning using R. In quest to help SME’s to leverage the power of data.

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