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@@ -40,16 +40,18 @@ By the end of the chapter, readers will be able to do the following:
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- bar plots
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- histogram plots
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- Given a data set and a question, select from the above plot types and use Python to create a visualization that best answers the question.
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- Given a visualization and a question, evaluate the effectiveness of the visualization and suggest improvements to better answer the question.
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- Evaluate the effectiveness of a visualization and suggest improvements to better answer a given question.
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- Referring to the visualization, communicate the conclusions in non-technical terms.
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- Identify rules of thumb for creating effective visualizations.
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- Define the two key aspects of altair charts:
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- graphical marks
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- encoding channels
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- Use the altair library in Python to create and refine the above visualizations using:
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- graphical marks: `mark_point`, `mark_line`, `mark_bar`
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- Use the `altair` library in Python to create and refine the above visualizations using:
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- graphical marks: `mark_point`, `mark_line`, `mark_circle`, `mark_bar`, `mark_rule`
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- encoding channels: `x`, `y`, `color`, `shape`
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- labeling: `title`
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- transformations: `scale`
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- subplots: `facet`
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- Define the two key aspects of `altair` charts:
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- graphical marks
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- encoding channels
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- Describe the difference in raster and vector output formats.
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- Use `chart.save()` to save visualizations in `.png` and `.svg` format.
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