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Copy file name to clipboardExpand all lines: _episodes/00-the-why-of-interactivity.md
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@@ -7,16 +7,16 @@ questions:
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- "How will interacting with data change this understanding?"
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objectives:
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- "To understand the difference between static and interactive figures"
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- "Consider"
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- "To consider which aspects of your data would work with some user interaction"
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keypoints:
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- "Consider the message you want to convey or story you want to tell. Is it clearer with interactivity?"
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- "Data types are often best suited to certain certain dimensions, (timeseries as a continuous x-axis, rather than coloured groups)"
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- "A plot or figure should make sense without needing to use interactivity"
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- "Consider the message you want to convey or story you want to tell. Is it clearer with some interactivity?"
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- "Data types are often best suited to certain certain dimensions (for example timeseries as a continuous x-axis, rather than coloured groups)"
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- "A plot or figure should make sense without needing to use the interactivity"
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- "If a plot changes then titles and labels need to change too, or they will be inaccurate or misleading"
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---
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## Why plot?
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The goal of research is to improve our understanding of the world, but that increase in knowledge is small if that understanding doesn't spread.
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The goal of research is to improve our understanding of the world, but that overall increase in knowledge is small if that understanding doesn't spread.
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Humans benefit from visual representation of data to see patterns and plotting data has become an essential part of the researcher's toolbox for communication.
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{: .discussion}
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## Choices in analysis and presentation
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Producing a figure will often decide on the story you want to tell, or the pattern you wish to highlight in your data. You have to decide which variables in your data (group, treatment, location, time, amount)to map to the available visual dimensions (x-y-z position / colour / symbols / etc).
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Producing a figure will often depend on the story you want to tell, or the pattern you wish to highlight in your data.
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You have to decide which variables in your data (group, treatment, location, time, amount)to map to the available visual dimensions (x-y-z position / colour / symbols / etc).
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Modern sources of data often present aditional problems, those of density and complexity, that require further choices relating to aggregation and ommission. All of these aspects require choices and this can force a certain interpretation on your audience, a limit what you can show.
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Modern sources of data often present additional problems, those of density and complexity, that require further choices relating to aggregation and ommission. All of these aspects require choices and this can force a certain interpretation on your audience, a limit what you can show.
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Interactivity gives the reader/user a chance to explore the data in ways a static (non-interactive) plot does not. It can also help you and your collaborators understand your data better.
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>
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> These are summariazed at [PyViz.org](https://pyviz.org/tools.html).
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>
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> Many of the tools described are developed with specific use cases in mind, whereas others are intentionally more basic and adaptable. Some are focused on particular issues, such as choices of colour or aggregation of data. There is a lot here to explore...
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> Many of the tools described are developed with specific users in mind, whereas others are intentionally more basic and adaptable. Some are focused on particular issues, such as choices of colour or the aggregation of data. There is a lot here to explore...
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{: .callout}
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### The steps for constructing our interactive data visualization
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