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In my daily job I am quite often presented with specific tasks to make sense of a dataset and make recommendations for future action.

Excel has been my primary tool to work through data and present the findings. However, recently I came to realise that in addition to data analysis I spend a considerable amount of time  trying to visualise and summarise the information graphically. It is quite burdensome and requires good grasp of VBA to be able to create summary graphs for a number of different facets in the data. An example of such a challenge would be a request to create a report showing graphically sales by product group over the past 24 months in each of the 15 regions.

Then one day I came across the R – Project for Statistical Computing – a free software environment for statistical computing and graphics. Fully knowing statistics is not my strongest asset, the examples I saw where fairly neat in design and seemed to be relatively easy to create.

It has to be said that after deciding to explore R’s graphing capabilities further it turned out to be a bit more complicated than I envisaged when I set out to learn more about R.

After some additional research, I arrived on the website of ggplot2 – “ggplot2 is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and none of the bad parts. It takes care of many of the fiddly details that make plotting a hassle (like drawing legends) as well as providing a powerful model of graphics that makes it easy to produce complex multi-layered graphics.”

The principle of building plots layer by layer seemed very intuitive to me, and a decision was made to take up R again, this time with a focus on creating plots with ggplot2.

This blog is a humble attempt to document my journey in reproducing some of the charts found on the internet, with a special focus on the charts I would need to create in my daily job using Excel. This being said, I will also post on other topics of interest I pick up on my journey of learning R.


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