We are going to be using formattable on the Imagine Austin Indicators dataset. A lot of other open data portals do not make it this easy to find and download data from. I’ve been playing around with it somewhat frequently and I’m really impressed with the consistency of design and features per data set. It’s a website designed to make facilitate easy access to open government data. #Set a few color variables to make our table more visually appealingįor our tutorial we are going to be using a data set from the Austin Open Data Portal. # Install the relevant libraries - do this one time If you are in Watson Studio, enter the following code into a cell (or multiple cells), highlight the cell and hit the “run cell” button. We are also going to assign a few custom color variables that we will use when setting the colors on our table. We need to install and load them in your environment so that we can call upon them later. R packages contain a grouping of R data functions and code that can be used to perform your analysis. If you’d like to get started with R in IBM Watson Studio, please have a look at the tutorial I wrote. Or we can use a free, hosted, multi-language collaboration environment like Watson Studio. We can use something like R Studio for a local analytics on our personal computer. In terms of setting up the R working environment, we have a couple of options open to us. I’m going to walk you through a step-by-step example of using the formattable R package to make your data frame more presentable for data storytelling. But it got me thinking why can’t tables be treated as a first class data visualization too? Tables need a little pizazz as much as the next data object!Įnter the r package formattable! The formattable package is used to transform vectors and data frames into more readable and impactful tabular formats. But what happens with you need to visualize the raw numbers? Do you open up the data set in the viewer and screenshot? Do you save the summarized data set locally and add a bit of formatting in excel? That’s what I used to do with my R summary tables. Because of this I am completely hooked on a variety of data visualization packages and tooling. I love a good visualization to assist in telling the story of your data.
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