Visualisation in research is an important element in distilling the key points of technical information to make it understandable. I love the ggplot2 R package and have used it for research publications but found myself wondering if there were other R packages that could plot statistical results easily.
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After a tumultuous year which was 2021, I thought I’d start the year with a bit of reflection in 2022. Eventually I decided that I’d write a seemingly generic post on reasons to start learning R except I wanted to unwrap what were my reasons on how exactly I ended up learning R to begin with.
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“A picture is worth a thousand words.” R doesn’t need to be used only for purely data manipulation and analysis. I had used a number of data visualisation packages in R to help a client with suitable visuals.
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While I have developed and published interactive dashboards on my website, I started thinking about the practicalities of creating dashboards for business reporting only. It occurred to me that, yes, large-scale reporting tools such as Tableau and Power BI that are amazing at producing self-service dashboards but organisations still rely on conventional reporting methods through the means of creating documents presenting findings from analyses.
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