Document the data options #1539
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doc/ref/plot_options/data.ipynb
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| "source": [ | |||
| "## `by`\n", | |||
| "\n", | |||
| "Text TBD." | |||
| "The `by` option allows you to group your data based on one or more categorical variables. By specifying a column name (or a list of column names) with `by`, the plot automatically separates the data into groups. This makes it easier to compare different subsets of your data in a single visualization. For instance, in the penguin dataset, grouping by 'species' column creates separate overlays (or subplots when using `subplots=True`) for each species." | |||
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Let's indicate that an NdOverlay is returned normally and a NdLayout when subplots=True. NdOverlay and NdLayout should link to their relevant page in HoloViews using intersphinx cross-references.
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@Azaya89 I had a quick look and that's a great start!! The documentation is going to be so much better with that new content, really looking forward to it. One comment is that so far the page is tabular-centric. Instead of using the term column maybe it'd be best to use a more generic term like variable or dimension. Having some xarray examples would be nice too. Other than that, I've left a few comments.
doc/ref/plot_options/data.ipynb
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| @@ -19,7 +19,7 @@ | |||
| "source": [ | |||
| "## `by`\n", | |||
| "\n", | |||
| "Text TBD." | |||
| "The `by` option allows you to group your data based on one or more categorical variables. By specifying a column name (or a list of column names) with `by`, the plot automatically separates the data into groups. This makes it easier to compare different subsets of your data in a single visualization. For instance, in the penguin dataset, grouping by 'species' column creates separate overlays (or subplots when using `subplots=True`) for each species." | |||
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hvPlot users are often confused with by, groupby, and color. Let's keep in mind we should make it clear in the reference how they differ (I also think we will have specific how-tos for that).
doc/ref/plot_options/data.ipynb
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| "\n", | ||
| "df = hvsampledata.penguins(\"pandas\")\n", | ||
| "\n", | ||
| "df.hvplot.scatter(x='bill_length_mm', y='bill_depth_mm', by='species', subplots=True).cols(1)" |
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I'd say either add a note to explain cols(1) or keep it simple without calling it.
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OK. Chose to remove it instead, heh.
doc/ref/plot_options/data.ipynb
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| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "The `fields` option lets you rename or transform your dataset’s dimensions before plotting. If your data contains column names that aren’t descriptive or need minor adjustments for clarity, you can use `fields` to rename them or apply simple transformations. This can help to make your plots more understandable and tailored to your needs." |
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What sort of transformation can one do?
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Looked a bit at the converter.py file and it seems you can also assign metadata as well. Will update that section.
doc/ref/plot_options/data.ipynb
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| "metadata": {}, | ||
| "source": [ | ||
| "## `kind`\n", | ||
| "The kind option determines the type of plot to generate from your data. By specifying a plot kind (such as ‘line’, ‘scatter’, or ‘bar’), you tell hvPlot which plot to create. The default is 'line', which generates a line plot. Changing the `kind` parameter lets you quickly experiment with different visual representations without altering your data." |
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It's the default for tabular data but not for xarray.
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Oh? Will look into it then...
doc/ref/plot_options/data.ipynb
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| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "The label option allows you to specify a custom name for your dataset that appears in the plot title or legend." |
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There's the title plot option that has a somewhat similar effect. It'd be nice to explain when label should be used over title.
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I'm not sure yet what the answer to this is. Will look into it more...
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| "source": [ | |||
| "## `by`\n", | |||
| "\n", | |||
| "Text TBD." | |||
| "The `by` option allows you to group your data based on one or more categorical variables. By specifying a dimension name (or a list of dimension names) with `by`, the plot automatically separates the data into groups, making it easier to compare different subsets in a single visualization. By default, an :class:holoviews.NdOverlay is returned, overlaying all groups in one plot. However, when you set `subplots=True`, a :class:holoviews.NdLayout is returned instead, arranging the groups as separate subplots." | |||
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The :class:holoviews.... inter-sphinx tag did not build correctly in my local build, so I'm not sure I did it correctly.
| "outputs": [], | ||
| "source": [ | ||
| "import hvplot.pandas # noqa\n", | ||
| "from bokeh.sampledata.sea_surface_temperature import sea_surface_temperature as sst\n", |
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This seemed like a good enough dataset for this example, but I'm open to using something else from hvsampledata
fixes #1538
This PR documents the
Data Optionsin the new API reference guide.