```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( ``` 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.