hvplot_docs/Customization.md

```python
import hvplot
import hvplot.pandas  # noqa
```

The hvPlot API is closely modeled on the pandas plot API but also diverges in certain cases, either to improve consistency or to provide additional functionality. This section will outline the valid options to control the axes of a plot, to control datashading and to modify the style of a plot. To look these options up interactively you may either use the tab-completion machinery in IPython or the Jupyter notebook, e.g.:

```python
df.hvplot.line(<TAB>
```

OR use the help method:

```
hvplot.help('line')
```

## Generic options

The generic set of options which may apply to all plot types include:

    clim: tuple
        Lower and upper bound of the color scale
    cnorm (default='linear'): str
        Color scaling which must be one of 'linear', 'log' or 'eq_hist'
    colorbar (default=False): boolean
        Enables a colorbar
    fontscale: number
        Scales the size of all fonts by the same amount, e.g. fontscale=1.5
        enlarges all fonts (title, xticks, labels etc.) by 50%
    fontsize: number or dict
        Set title, label and legend text to the same fontsize. Finer control
        by using a dict: {'title': '15pt', 'ylabel': '5px', 'ticks': 20}
    flip_xaxis/flip_yaxis: boolean
        Whether to flip the axis left to right or up and down respectively
    grid (default=False): boolean
        Whether to show a grid
    hover : boolean
        Whether to show hover tooltips, default is True unless datashade is
        True in which case hover is False by default
    hover_cols (default=[]): list or str
        Additional columns to add to the hover tool or 'all' which will
        includes all columns (including indexes if use_index is True).
    invert (default=False): boolean
        Swaps x- and y-axis
    frame_width/frame_height: int
        The width and height of the data area of the plot
    legend (default=True): boolean or str
        Whether to show a legend, or a legend position
        ('top', 'bottom', 'left', 'right')
    logx/logy (default=False): boolean
        Enables logarithmic x- and y-axis respectively
    logz (default=False): boolean
        Enables logarithmic colormapping
    loglog (default=False): boolean
        Enables logarithmic x- and y-axis
    max_width/max_height: int
        The maximum width and height of the plot for responsive modes
    min_width/min_height: int
        The minimum width and height of the plot for responsive modes
    padding: number or tuple
        Fraction by which to increase auto-ranged extents to make
        datapoints more visible around borders. Supports tuples to
        specify different amount of padding for x- and y-axis and
        tuples of tuples to specify different amounts of padding for
        upper and lower bounds.
    responsive: boolean
        Whether the plot should responsively resize depending on the
        size of the browser. Responsive mode will only work if at
        least one dimension of the plot is left undefined, e.g. when
        width and height or width and aspect are set the plot is set
        to a fixed size, ignoring any responsive option.
    rot: number
        Rotates the axis ticks along the x-axis by the specified
        number of degrees.
    shared_axes (default=True): boolean
        Whether to link axes between plots
    transforms (default={}): dict
        A dictionary of HoloViews dim transforms to apply before plotting
    title (default=''): str
        Title for the plot
    tools (default=[]): list
        List of tool instances or strings (e.g. ['tap', box_select'])
    xaxis/yaxis: str or None
        Whether to show the x/y-axis and whether to place it at the
        'top'/'bottom' and 'left'/'right' respectively.
    xformatter/yformatter (default=None): str or TickFormatter
        Formatter for the x-axis and y-axis (accepts printf formatter,
        e.g. '%.3f', and bokeh TickFormatter)
    xlabel/ylabel/clabel (default=None): str
        Axis labels for the x-axis, y-axis, and colorbar
    xlim/ylim (default=None): tuple or list
        Plot limits of the x- and y-axis
    xticks/yticks (default=None): int or list
        Ticks along x- and y-axis specified as an integer, list of
        ticks positions, or list of tuples of the tick positions and labels
    width (default=700)/height (default=300): int
        The width and height of the plot in pixels
    attr_labels (default=None): bool
        Whether to use an xarray object's attributes as labels, defaults to
        None to allow best effort without throwing a warning. Set to True
        to see warning if the attrs can't be found, set to False to disable
        the behavior.
    sort_date (default=True): bool
        Whether to sort the x-axis by date before plotting
    symmetric (default=None): bool
        Whether the data are symmetric around zero. If left unset, the data
        will be checked for symmetry as long as the size is less than
        ``check_symmetric_max``.
    check_symmetric_max (default=1000000):
        Size above which to stop checking for symmetry by default on the data.

## Datashading options

In addition to regular plot options hvplot also exposes options for dealing with large data:

    aggregator (default=None):
        Aggregator to use when applying rasterize or datashade operation
        (valid options include 'mean', 'count', 'min', 'max' and more, and
        datashader reduction objects)
    dynamic (default=True):
        Whether to return a dynamic plot which sends updates on widget and
        zoom/pan events or whether all the data should be embedded
        (warning: for large groupby operations embedded data can become
        very large if dynamic=False)
    datashade (default=False):
        Whether to apply rasterization and shading using datashader
        library returning an RGB object
    dynspread (default=False):
        Allows plots generated with datashade=True to increase the point
        size to make sparse regions more visible
    rasterize (default=False):
        Whether to apply rasterization using the datashader library
        returning an aggregated Image
    x_sampling/y_sampling (default=None):
        Specifies the smallest allowed sampling interval along the x/y axis.

## Geographic options

When dealing with geographic data, there are a number of options that become available. See the [geographic section](Geographic_Data.ipynb) for more information on working with geographic data:

    coastline (default=False):
        Whether to display a coastline on top of the plot, setting
        coastline='10m'/'50m'/'110m' specifies a specific scale.
    crs (default=None):
        Coordinate reference system of the data specified as Cartopy
        CRS object, proj.4 string or EPSG code.
    features (default=None): dict or list
        A list of features or a dictionary of features and the scale
        at which to render it. Available features include 'borders',
        'coastline', 'lakes', 'land', 'ocean', 'rivers' and 'states'.
        Available scales include '10m'/'50m'/'110m'.
    geo (default=False):
        Whether the plot should be treated as geographic (and assume
        PlateCarree, i.e. lat/lon coordinates).
    global_extent (default=False):
        Whether to expand the plot extent to span the whole globe.
    project (default=False):
        Whether to project the data before plotting (adds initial
        overhead but avoids projecting data when plot is dynamically
        updated).
    tiles (default=False):
        Whether to overlay the plot on a tile source. Tiles sources
        can be selected by name or a tiles object or class can be passed,
        the default is 'Wikipedia'.

## Kind options

Each type of plot may have a number of options to visual attributes specific to that plot type. In general these are provided in the docstring of the plot type, which can be viewed using ``help`` method:


```python
hvplot.help('scatter', generic=False, style=False)
```

## Styling options

Beyond the options specific to each plot type (or ``kind``) it is also possible to customize each component in detail, exposing all the options bokeh exposes. These usually include options to color the line and fill color, alpha and style. To see the full listing we can once again use the ``help`` method:


```python
hvplot.help('line', docstring=False, generic=False)
```

In general, the objects returned by hvPlot are regular HoloViews objects, which can be overlaid, laid out, composed and customized like all other HoloViews objects.  The [HoloViews](https://holoviews.org) website explains all the functionality available, but what's on this hvPlot website should be enough to get you up and running for typical usage.