diff --git a/doc/conf.py b/doc/conf.py index 25d627a16..751cf38f8 100644 --- a/doc/conf.py +++ b/doc/conf.py @@ -232,6 +232,7 @@ 'numpy': ('https://numpy.org/doc/stable/', None), 'xarray': ('https://docs.xarray.dev/en/stable/', None), 'pyproj': ('https://pyproj4.github.io/pyproj/stable/', None), + 'python': ('https://docs.python.org/3', None), } # To avoid this warning diff --git a/hvplot/plotting/core.py b/hvplot/plotting/core.py index 298556d22..282205c24 100644 --- a/hvplot/plotting/core.py +++ b/hvplot/plotting/core.py @@ -133,9 +133,9 @@ def explorer(self, x=None, y=None, **kwds): Parameters ---------- - x : string, optional + x : str, optional The coordinate variable along the x-axis - y : string, optional + y : str, optional The coordinate variable along the y-axis **kwds : optional Additional keywords arguments typically passed to hvplot's call. @@ -162,13 +162,13 @@ class hvPlotTabular(hvPlotBase): Parameters ---------- - x : string, optional + x : str, optional Field name(s) to draw x-positions from. If not specified, the index is used. - y : string or list, optional + y : str or list, optional Field name(s) to draw y-positions from. If not specified, all numerical fields are used. - kind : string, optional + kind : str, optional The kind of plot to generate, e.g. 'area', 'bar', 'line', 'scatter' etc. To see the available plots run `print(df.hvplot.__all__)`. **kwds : optional @@ -257,7 +257,11 @@ class hvPlotTabular(hvPlotBase): def line(self, x=None, y=None, **kwds): """ - The `line` plot connects the points with a continuous curve. + Create a line plot that connects data points with continuous curves. + + A line plot displays data as a series of data points connected by + straight line segments. It is commonly used to visualize trends and + changes over continuous variables such as time. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.line.html @@ -265,18 +269,18 @@ def line(self, x=None, y=None, **kwds): Parameters ---------- - x : string, optional + x : str, optional Field name(s) to draw x-positions from. If not specified, the index is used. Can refer to continuous and categorical data. - y : string or list, optional + y : str or list of str, optional Field name(s) to draw y-positions from. If not specified, all numerical fields are used. - by : string, optional + by : str or list of str, optional A single column or list of columns to group by. All the subgroups are visualized. - groupby: string, list, optional + groupby : str or list of str, optional A single field or list of fields to group and filter by. Adds one or more widgets to select the subgroup(s) to visualize. - color : str or array-like, optional. + color : str or list of str, optional. The color for each of the series. Possible values are: A single color string referred to by name, RGB or RGBA code, for instance 'red' or @@ -287,15 +291,16 @@ def line(self, x=None, y=None, **kwds): filled in green or yellow, alternatively. If there is only a single series to be plotted, then only the first color from the color list will be used. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('line')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Curve` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Curve` or Panel object + A HoloViews Curve element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -304,7 +309,6 @@ def line(self, x=None, y=None, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/line.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Curve.html - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.line.html @@ -317,10 +321,11 @@ def line(self, x=None, y=None, **kwds): def step(self, x=None, y=None, where='mid', **kwds): """ - The `step` plot connects the points with piece-wise constant curves. + Create a step plot that connects data points with piece-wise constant curves. - The `step` plot can be used pretty much anytime the `line` plot might be used, and has many - of the same options available. + A step plot displays data using horizontal and vertical line segments, + creating a stepped appearance. It is useful for visualizing discrete + changes in data values over continuous intervals. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.step.html @@ -328,40 +333,41 @@ def step(self, x=None, y=None, where='mid', **kwds): Parameters ---------- - x : string, optional + x : str, optional Field name(s) to draw x-positions from. If not specified, the index is - used. Must refer to continuous data. Not categorical data. - y : string or list, optional + used. Must refer to continuous data, not categorical data. + y : str or list of str, optional Field name(s) to draw y-positions from. If not specified, all numerical fields are used. - by : string, optional - A single field or list of fields to group by. All the subgroups are visualized. - groupby: string, list, optional - A single field or list of fields to group and filter by. Adds one or more widgets to + by : str or list of str, optional + Field name(s) to group by. All subgroups are visualized separately. + groupby : str or list of str, optional + Field name(s) to group and filter by. Adds one or more widgets to select the subgroup(s) to visualize. - where: string, optional - Controls the transition point of the step along the x-axis. One of - ``'mid'``, ``'pre'``, ``'post'``. Default is ``'mid'``. - color : str or array-like, optional. - The color for each of the series. Possible values are: + where : {'mid', 'pre', 'post'}, default 'mid' + Controls the transition point of the step along the x-axis: - A single color string referred to by name, RGB or RGBA code, for instance 'red' or - '#a98d19. + - 'mid': Steps are centered on x values + - 'pre': Steps extend left from x values + - 'post': Steps extend right from x values + color : str or list of str, optional + Color(s) for the step series. Can be: - A sequence of color strings referred to by name, RGB or RGBA code, which will be used - for each series recursively. For instance ['green','yellow'] each field's line will be - filled in green or yellow, alternatively. If there is only a single series to be - plotted, then only the first color from the color list will be used. + - A single color string (name, RGB, or RGBA code), e.g., 'red' or '#a98d19' + - A sequence of color strings used recursively for each series + + For multiple series, colors are applied cyclically. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('step')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Curve` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Curve` or Panel object + A HoloViews Curve element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -370,7 +376,6 @@ def step(self, x=None, y=None, where='mid', **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/step.html - HoloViews: https://holoviews.org/gallery/demos/bokeh/step_chart.html - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.line.html (use `draw_style='step'`) @@ -381,10 +386,11 @@ def step(self, x=None, y=None, where='mid', **kwds): def scatter(self, x=None, y=None, **kwds): """ - The `scatter` plot visualizes your points as markers in 2D space. You can visualize - one more dimension by using colors. + Create a scatter plot that displays data points as markers in 2D space. - The `scatter` plot is a good first way to plot data with non continuous axes. + A scatter plot uses individual markers to represent data points, making it + ideal for exploring relationships between two continuous variables and + identifying patterns, correlations, or outliers in the data. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.scatter.html @@ -392,44 +398,40 @@ def scatter(self, x=None, y=None, **kwds): Parameters ---------- - x : string, optional + x : str, optional Field name(s) to draw x-positions from. If not specified, the index is used. Can refer to continuous and categorical data. - y : string or list, optional + y : str or list of str, optional Field name(s) to draw y-positions from. If not specified, all numerical fields are used. - marker : string, optional - The marker shape depends on the activated plotting backend: + marker : str, optional + The marker shape. Options depend on the plotting backend: - - Bokeh: Bokeh marker styles and a subset of Matplotlib styles, e.g. - ``'circle'`` (default), ``'dot'``, ``'cross'``, ``'x'``, ``'square'`` - for Bokeh markers and ``'+'``, ``'x'``, ``'s'`` for Matplotlib- - compatible markers. + - Bokeh: 'circle' (default), 'dot', 'cross', 'x', 'square', etc. See https://docs.bokeh.org/en/latest/docs/examples/basic/scatters/markertypes.html - for the list of Bokeh markers. - - Matplotlib: Any supported marker, e.g. ``'s'`` (square), ``'x'`` - (cross), ``'+'``, etc. - See https://matplotlib.org/stable/api/markers_api.html for the list - of Matplotlib markers. - c : string, optional - A color or a field name to draw the color of the marker from. Alias of - ``color``. - s : int, optional, also available as 'size' - The size of the marker. - scale: number, optional - Scaling factor to apply to point scaling. Default is 1. - logz : bool - Whether to apply log scaling to the z-axis. Default is False. + for the complete list of Bokeh markers. + - Matplotlib: 's' (square), 'x' (cross), '+', 'o' (circle), etc. + See https://matplotlib.org/stable/api/markers_api.html + for the complete list of Matplotlib markers. + c : str, optional + Field name to color markers by, or a single color name. Alias for ``color``. + s : int, optional + Size of the markers. Also available as 'size'. + scale : float, default 1.0 + Scaling factor to apply to marker sizing. + logz : bool, default False + Whether to apply log scaling to the color axis. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('scatter')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Scatter` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Scatter` or Panel object + A HoloViews Scatter element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -438,7 +440,6 @@ def scatter(self, x=None, y=None, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/examples/basic/scatters/color_scatter.html - HoloViews: https://holoviews.org/reference/elements/matplotlib/Scatter.html - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.scatter.html @@ -451,8 +452,11 @@ def scatter(self, x=None, y=None, **kwds): def area(self, x=None, y=None, y2=None, stacked=True, **kwds): """ - The `area` plot can be used to color the area under a line or to color the space between two - lines. + Create an area plot that fills the region between curves and axes. + + An area plot displays quantitative data by filling the area between a curve + and the axis (or between two curves). It is useful for showing cumulative + totals, part-to-whole relationships, and trends over continuous data. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.area.html @@ -460,25 +464,28 @@ def area(self, x=None, y=None, y2=None, stacked=True, **kwds): Parameters ---------- - x : string, optional + x : str, optional Field name(s) to draw x-positions from. If not specified, the index is used. Can refer to continuous and categorical data. - y : string, optional - Field name to draw the first y-position from - y2 : string, optional - Field name to draw the second y-position from - stacked : boolean, optional - Whether to stack multiple areas. Default is True. + y : str, optional + Field name for the primary y-positions that define the area boundary. + y2 : str, optional + Field name for secondary y-positions. When specified, the area is + filled between ``y`` and ``y2`` curves. + stacked : bool, default True + Whether to stack multiple areas on top of each other. When False, + areas are overlaid with transparency. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('area')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Area` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Area` or Panel object + A HoloViews Area element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -487,7 +494,6 @@ def area(self, x=None, y=None, y2=None, stacked=True, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/user_guide/basic/areas.html#directed-areas - HoloViews: https://holoviews.org/reference/elements/matplotlib/Area.html - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.area.html @@ -511,25 +517,26 @@ def errorbars(self, x=None, y=None, yerr1=None, yerr2=None, **kwds): Parameters ---------- - x : string, optional + x : str, optional Field name to draw the x-position from. If not specified, the index is used. Can refer to continuous and categorical data. - y : string, optional - Field name to draw the y-position from - yerr1 : string, optional - Field name to draw symmetric / negative errors from - yerr2 : string, optional - Field name to draw positive errors from + y : str, optional + Field name to draw the y-position from. + yerr1 : str, optional + Field name to draw symmetric / negative errors from. + yerr2 : str, optional + Field name to draw positive errors from. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('errorbars')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.ErrorBars` / Panel object + :class:`holoviews:holoviews.element.ErrorBars` or Panel object + A HoloViews ErrorBars element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -538,7 +545,6 @@ def errorbars(self, x=None, y=None, yerr1=None, yerr2=None, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/examples/basic/annotations/whisker.html - HoloViews: https://holoviews.org/reference/elements/bokeh/ErrorBars.html - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.errorbar.html @@ -558,29 +564,29 @@ def ohlc(self, x=None, y=None, **kwds): Parameters ---------- - x : string, optional + x : str, optional Field name to draw x coordinates from. If not specified, the index is used. Normally refers to date values. y : list or tuple, optional - Field names of the OHLC fields. Default is ["open", "high", "low", "close"] - bar_width: number, optional + Field names of the OHLC fields. Default is ["open", "high", "low", "close"]. + bar_width : float, optional Bar width. Default is 0.5. - line_color : string, optional - The line color. Default is black - pos_color : string, optional + line_color : str, optional + The line color. Default is black. + pos_color : str, optional The color indicating a positive change. Default is green. - neg_color : string, optional + neg_color : str, optional The color indicating a negative change. Default is red. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('ohlc')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Rectangles` / Panel object + :class:`holoviews:holoviews.element.Rectangles` or Panel object You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -589,7 +595,6 @@ def ohlc(self, x=None, y=None, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/examples/topics/timeseries/candlestick.html - Matplotlib: https://www.statology.org/matplotlib-python-candlestick-chart/ - Plotly: https://plotly.com/python/ohlc-charts/ @@ -611,35 +616,36 @@ def heatmap(self, x=None, y=None, C=None, colorbar=True, logz=False, **kwds): Parameters ---------- - x : string, optional + x : str, optional Field name to draw x-positions from. In the data as an array case, setting x to None assumes drawing x labels from the column names, which can be explicitly declared by setting x to ``'columns'``. Can refer to continuous and categorical data. - y : string, optional + y : str, optional Field name to draw y-positions from. In the data as an array case, setting y to None assumes drawing y labels from the index, which can be explicitly declared by setting y to ``'index'`` or to the index name. Can refer to continuous and categorical data. - C : string, optional + C : str, optional Field to draw heatmap color from. If not specified a simple count will be used. - colorbar: boolean, optional + colorbar : bool, optional Whether to display a colorbar. Default is True. - logz : bool + logz : bool, optional Whether to apply log scaling to the z-axis. Default is False. reduce_function : function, optional Function to compute statistics for heatmap, for example ``np.mean``. If omitted, no aggregation is applied and duplicate values are dropped. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('heatmap')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.HeatMap` / Panel object + :class:`holoviews:holoviews.element.HeatMap` or Panel object + A HoloViews HeatMap element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -648,7 +654,6 @@ def heatmap(self, x=None, y=None, C=None, colorbar=True, logz=False, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/examples/topics/categorical/heatmap_unemployment.html - HoloViews: https://holoviews.org/reference/elements/bokeh/HeatMap.html - Matplotlib: https://matplotlib.org/stable/gallery/images_contours_and_fields/image_annotated_heatmap.html @@ -680,37 +685,38 @@ def hexbin( Parameters ---------- - x : string, optional + x : str, optional Field name to draw x coordinates from. If not specified, the index is used. - y : string - Field name to draw y-positions from - C : string, optional + y : str + Field name to draw y-positions from. + C : str, optional Field to draw hexbin color from. If not specified a simple count will be used. - colorbar: boolean, optional + colorbar : bool, optional Whether to display a colorbar. Default is True. reduce_function : function, optional Function to compute statistics for hexbins, for example ``np.mean``. Default aggregation is a count of the values in the area. - gridsize: int or tuple, optional + gridsize : int or tuple, optional Number of hexagonal bins along x- and y-axes. Defaults to uniform - sampling along both axes when setting and integer but independent + sampling along both axes when setting an integer but independent bin sampling can be specified a tuple of integers corresponding to the number of bins along each axis. Default is 50. - logz : bool + logz : bool, optional Whether to apply log scaling to the z-axis. Default is False. - min_count : number, optional + min_count : int, optional The display threshold before a bin is shown, by default bins with - a count of less than 1 are hidden + a count of less than 1 are hidden. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('hexbin')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.HexTiles` / Panel object + :class:`holoviews:holoviews.element.HexTiles` or Panel object + A HoloViews HexTiles element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -719,7 +725,6 @@ def hexbin( References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/gallery/hexbin.html - HoloViews: https://holoviews.org/reference/elements/bokeh/HexTiles.html - Plotly: https://plotly.com/python/hexbin-mapbox/ @@ -763,12 +768,12 @@ def bivariate( Parameters ---------- - x : string, optional + x : str, optional Field name to draw x-positions from. If not specified, the index is used. - y : string, optional - Field name to draw y-positions from - colorbar : boolean - Whether to display a colorbar + y : str, optional + Field name to draw y-positions from. + colorbar : bool, optional + Whether to display a colorbar. Default is True. bandwidth : float, optional Allows supplying explicit bandwidth value of the kernel for the density estimate, rather than relying on Scott. Higher value @@ -780,17 +785,17 @@ def bivariate( levels : int or list, optional The number of contour lines to draw or a list of scalar values used to specify the contour levels. Default is 10. - **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('bivariate')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Bivariate` / Panel object + :class:`holoviews:holoviews.element.Bivariate` or Panel object + A HoloViews Bivariate element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -799,7 +804,6 @@ def bivariate( References ---------- - - ggplot: https://bio304-class.github.io/bio304-fall2017/ggplot-bivariate.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Bivariate.html - Plotly: https://plotly.com/python/2d-histogram-contour/ @@ -825,12 +829,11 @@ def bivariate( def bar(self, x=None, y=None, stacked=False, **kwds): """ - A vertical bar plot + Create a vertical bar chart for categorical data comparison. - A `bar` plot represents categorical data with rectangular bars - with heights proportional to the values that they represent. The x-axis - represents the categories and the y axis represents the value scale. - The bars are of equal width which allows for instant comparison of data. + A bar chart displays categorical data using rectangular bars with heights + proportional to the values they represent. It is ideal for comparing + quantities across different categories and showing rankings or differences. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.bar.html @@ -838,34 +841,31 @@ def bar(self, x=None, y=None, stacked=False, **kwds): Parameters ---------- - x : string, optional - Field name to draw x-positions from. If not specified, the index is used. - y : string, optional - Field name to draw y-positions from. If not specified, all numerical + x : str, optional + Field name for categorical x-axis positions. If not specified, the index is used. + y : str or list of str, optional + Field name(s) for bar heights. If not specified, all numerical fields are used. - stacked : bool, optional - If True, creates a stacked bar plot. Default is False. - color : str or array-like, optional. - The color for each of the series. Possible values are: - - The name of the field to draw the colors from. The field can contain numerical values or strings - representing colors. - - A single color string referred to by name, RGB or RGBA code, for instance 'red' or - '#a98d19'. - - A sequence of color strings referred to by name, RGB or RGBA code, which will be used - for each series recursively. For instance ['red', 'green','blue']. + stacked : bool, default False + Whether to stack multiple series on top of each other. When True, + bars are stacked vertically; when False, bars are grouped side-by-side. + color : str or list of str, optional + Color specification for bars. Can be: + + - Field name containing numerical values or color strings + - Single color string (name, RGB, or RGBA code), e.g., 'red' or '#a98d19' + - Sequence of colors applied to each series, e.g., ['red', 'green', 'blue'] **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('bar')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Bars` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Bars` or Panel object + A HoloViews Bars element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -874,7 +874,6 @@ def bar(self, x=None, y=None, stacked=False, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/vbar.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Bars.html - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.bar.html @@ -901,18 +900,24 @@ def barh(self, x=None, y=None, stacked=False, **kwds): Parameters ---------- + x : str, optional + Field name to draw values from. If not specified, the index is used. + y : str, optional + Field name to draw categories from. If not specified, all numerical + columns are used. stacked : bool, optional If True, creates a stacked horizontal bar plot. Default is False. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('barh')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Bars` / Panel object + :class:`holoviews:holoviews.element.Bars` or Panel object + A HoloViews Bars element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -921,7 +926,6 @@ def barh(self, x=None, y=None, stacked=False, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/hbar.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Bars.html - Matplotlib: https://matplotlib.org/stable/gallery/lines_bars_and_markers/barh.html @@ -944,21 +948,22 @@ def box(self, y=None, by=None, **kwds): Parameters ---------- - y : string or sequence + y : str or sequence, optional Field(s) in the *wide* data to compute distribution from. If none is provided all numerical fields will be used. - by : string or sequence + by : str or sequence, optional Field in the *long* data to group by. - kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + **kwds : optional + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('box')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.BoxWhisker` / Panel object + :class:`holoviews:holoviews.element.BoxWhisker` or Panel object + A HoloViews BoxWhisker element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -989,21 +994,22 @@ def violin(self, y=None, by=None, **kwds): Parameters ---------- - y : string or sequence + y : str or sequence, optional Field(s) in the *wide* data to compute distribution from. If none is provided all numerical fields will be used. - by : string or sequence + by : str or sequence, optional Field in the *long* data to group by. - kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + **kwds : optional + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('violin')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Violin` / Panel object + :class:`holoviews:holoviews.element.Violin` or Panel object + A HoloViews Violin element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1012,7 +1018,6 @@ def violin(self, y=None, by=None, **kwds): References ---------- - - Seaborn: https://seaborn.pydata.org/generated/seaborn.violinplot.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Violin.html - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.violinplot.html @@ -1025,7 +1030,11 @@ def hist( self, y=None, by=None, bins=20, bin_range=None, normed=False, cumulative=False, **kwds ): """ - A `histogram` displays an approximate representation of the distribution of continuous data. + Create a histogram that displays the distribution of continuous data. + + A histogram represents the frequency distribution of data by dividing it + into bins and showing the count or density for each bin. It is fundamental + for understanding the shape, central tendency, and spread of data distributions. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.hist.html @@ -1033,40 +1042,42 @@ def hist( Parameters ---------- - y : string or sequence - Field(s) in the *wide* data to compute the distribution(s) from. - Please note the fields should contain continuous data. Not categorical. - by : string or sequence - Field(s) in the *long* data to group by. - bins : int or string or np.ndarray or list or tuple, optional - The number of bins in the histogram, or an explicit set of bin edges - or a method to find the optimal set of bin edges, e.g. 'auto', 'fd', - 'scott' etc. For more documentation on these approaches see the - :func:`numpy.histogram_bin_edges` documentation. Default is 20. - bin_range: tuple, optional - The lower and upper range of the bins. - Default is the minimum and maximum values of the continuous data. - normed : str or bool, optional - Controls normalization behavior. If ``True`` or ``'integral'``, then - ``density=True`` is passed to np.histogram, and the distribution - is normalized such that the integral is unity. If ``False``, - then the frequencies will be raw counts. If ``'height'``, then the - frequencies are normalized such that the max bin height is unity. - Default is False. - cumulative: bool, optional - If True, then a histogram is computed where each bin gives the counts - in that bin plus all bins for smaller values. The last bin gives the - total number of data points. Default is False. - kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + y : str or list of str, optional + Field name(s) to compute distribution from. Should contain continuous + data, not categorical. If not specified, all numerical fields are used. + by : str or list of str, optional + Field name(s) to group data by before computing histograms. + bins : int, str, array-like, default 20 + Bin specification. Can be: + + - int: Number of equal-width bins + - str: Method for automatic bin selection ('auto', 'fd', 'scott', etc.) + - array-like: Explicit bin edges + + See :func:`numpy.histogram_bin_edges` for automatic methods. + bin_range : tuple, optional + Lower and upper range of bins as (min, max). If not specified, + uses the data range. + normed : bool or str, default False + Normalization mode: + + - False: Raw frequency counts + - True or 'integral': Density normalized so integral equals 1 + - 'height': Normalized so maximum bin height equals 1 + cumulative : bool, default False + If True, compute cumulative histogram where each bin represents + the count up to that bin. + **kwds : optional + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('hist')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Histogram` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Histogram` or Panel object + A HoloViews Histogram element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1081,7 +1092,6 @@ def hist( References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/examples/topics/stats/histogram.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Histogram.html - Pandas: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.hist.html @@ -1118,10 +1128,10 @@ def kde(self, y=None, by=None, **kwds): Parameters ---------- - y : string or sequence + y : str or sequence, optional Field(s) in the data to compute distribution on. If not specified all numerical fields are used. - by : string or sequence + by : str or sequence, optional Field(s) in the data to group by. bandwidth : float, optional Allows supplying explicit bandwidth value of the kernel for the @@ -1129,22 +1139,23 @@ def kde(self, y=None, by=None, **kwds): yields smoother contours. Default is None. cut : float, optional Draw the estimate to cut * bw from the extreme data points. Default is 3. - filled : + filled : bool, optional Whether the bivariate contours should be filled. Default is True. bw_method : optional Not supported. ind : optional Not supported. - kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + **kwds : optional + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('kde')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Distribution` / Panel object + :class:`holoviews:holoviews.element.Distribution` or Panel object + A HoloViews Distribution element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1159,7 +1170,6 @@ def kde(self, y=None, by=None, **kwds): References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/Distribution.html - Pandas: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.kde.html - Plotly: https://plotly.com/python/distplot/ @@ -1189,18 +1199,19 @@ def table(self, columns=None, **kwds): Parameters ---------- - columns : string or sequence + columns : str or sequence, optional The field(s) to display as columns. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('table')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Table` / Panel object + :class:`holoviews:holoviews.element.Table` or Panel object + A HoloViews Table element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1209,7 +1220,6 @@ def table(self, columns=None, **kwds): References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/Table.html - Plotly: https://plotly.com/python/table/ - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.table.html @@ -1223,16 +1233,19 @@ def dataset(self, columns=None, **kwds): Parameters ---------- + columns : str or sequence, optional + The field(s) to include in the dataset. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('dataset')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Dataset` / Panel object + :class:`holoviews:holoviews.element.Dataset` or Panel object + A HoloViews Dataset element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1241,7 +1254,6 @@ def dataset(self, columns=None, **kwds): References ---------- - - HoloViews Tabular: https://holoviews.org/getting_started/Tabular_Datasets.html - HoloViews Gridded: https://holoviews.org/getting_started/Gridded_Datasets.html """ @@ -1271,31 +1283,32 @@ def points(self, x=None, y=None, **kwds): Parameters ---------- - x : string, optional + x : str, optional The coordinate variable along the x-axis. Default is the first numeric field. - y : string, optional + y : str, optional The coordinate variable along the y-axis. Default is the second numeric field. - c : string, optional - The dimension to color the points by - s : int, optional, also available as 'size' - The size of the marker - marker : string, optional + c : str, optional + The dimension to color the points by. + s : int, optional + The size of the marker. Also available as 'size'. + marker : str, optional The marker shape specified above can be any supported by matplotlib, e.g. s, d, o etc. See https://matplotlib.org/stable/api/markers_api.html. - scale: number, optional + scale : float, optional Scaling factor to apply to point scaling. Default is 1. - logz : bool + logz : bool, optional Whether to apply log scaling to the z-axis. Default is False. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('points')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Points` / Panel object + :class:`holoviews:holoviews.element.Points` or Panel object + A HoloViews Points element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1304,16 +1317,17 @@ def points(self, x=None, y=None, **kwds): References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/Points.html """ return self(x, y, kind='points', **kwds) def vectorfield(self, x=None, y=None, angle=None, mag=None, **kwds): """ - vectorfield visualizes vectors given by the (``x``, ``y``) starting point, - a magnitude (``mag``) and an `angle`. A ``vectorfield`` plot is also known - as a ``quiver`` plot. + Create a vector field plot showing direction and magnitude at each point. + + A vector field plot (also known as a quiver plot) displays vectors at + specified coordinates, each defined by a magnitude and angle. It is useful + for visualizing flow fields, gradients, forces, or any directional data. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.vectorfield.html @@ -1321,24 +1335,26 @@ def vectorfield(self, x=None, y=None, angle=None, mag=None, **kwds): Parameters ---------- - x : string - Field name to draw x-positions from - y : string - Field name to draw y-positions from - mag : string - Magnitude. - angle : string - Angle in radians. + x : str, required + Field name for x-coordinates of vector origins. + y : str, required + Field name for y-coordinates of vector origins. + angle : str, required + Field name containing vector angles in radians. The angle is measured + counterclockwise from the positive x-axis. + mag : str, required + Field name containing vector magnitudes (lengths). **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('vectorfield')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.VectorField` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.VectorField` or Panel object + A HoloViews VectorField element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1347,7 +1363,6 @@ def vectorfield(self, x=None, y=None, angle=None, mag=None, **kwds): References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/VectorField.html - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.quiver.html - Plotly: https://plotly.com/python/quiver-plots/ @@ -1357,7 +1372,12 @@ def vectorfield(self, x=None, y=None, angle=None, mag=None, **kwds): def polygons(self, x=None, y=None, c=None, **kwds): """ - Polygon plot for geopandas dataframes. + Create a polygon plot for visualizing geometric shapes and regions. + + A polygon plot displays closed geometric shapes defined by their boundary + coordinates. It is commonly used with geographic data (e.g., GeoPandas + GeoDataFrames) to visualize administrative boundaries, regions, or any + other area-based data. Reference: https://hvplot.holoviz.org/ref/api/manual/hvplot.hvPlot.polygons.html @@ -1365,20 +1385,28 @@ def polygons(self, x=None, y=None, c=None, **kwds): Parameters ---------- - c : string, optional - The dimension to color the polygons by - logz : bool - Enables logarithmic colormapping. Default is False. + x : str, optional + Field name for x-coordinates. For GeoPandas data, this is typically + handled automatically from geometry columns. + y : str, optional + Field name for y-coordinates. For GeoPandas data, this is typically + handled automatically from geometry columns. + c : str, optional + Field name to color polygons by. Can be numerical (for continuous + color mapping) or categorical (for discrete colors). + logz : bool, default False + Whether to apply logarithmic scaling to the color mapping. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('polygons')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Polygons` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Polygons` or Panel object + A HoloViews Polygons element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1406,16 +1434,23 @@ def paths(self, x=None, y=None, c=None, **kwds): Parameters ---------- + x : str, optional + Field name to draw x-coordinates from. If not specified, the index is used. + y : str, optional + Field name to draw y-coordinates from. + c : str, optional + Field to color the paths by. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('paths')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Path` / Panel object + :class:`holoviews:holoviews.element.Path` or Panel object + A HoloViews Path element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1424,7 +1459,6 @@ def paths(self, x=None, y=None, c=None, **kwds): References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/Path.html """ return self(x, y, c=c, kind='paths', **kwds) @@ -1442,24 +1476,25 @@ def labels(self, x=None, y=None, text=None, **kwds): Parameters ---------- - x : string, optional - The coordinate variable along the x-axis - y : string, optional - The coordinate variable along the y-axis - text : string, optional + x : str, optional + The coordinate variable along the x-axis. + y : str, optional + The coordinate variable along the y-axis. + text : str, optional The column to draw the text labels from; it's also possible to provide a template string containing the column names to automatically format the text, e.g. "{col1}, {col2}". **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments are documented in :ref:`plot-options`. Run ``hvplot.help('labels')`` for the full method documentation. Returns ------- - :class:`holoviews:holoviews.element.Labels` / Panel object + :class:`holoviews:holoviews.element.Labels` or Panel object + A HoloViews Labels element or Panel object if using Panel widgets. You can `print` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1468,7 +1503,6 @@ def labels(self, x=None, y=None, text=None, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/text.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Labels.html - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.text.html#matplotlib.pyplot.text @@ -1624,13 +1658,13 @@ class hvPlot(hvPlotTabular): Parameters ---------- - x : string, optional + x : str, optional Field name(s) to draw x-positions from. If not specified, the index is used. - y : string or list, optional + y : str or list, optional Field name(s) to draw y-positions from. If not specified, all numerical fields are used. - kind : string, optional + kind : str, optional The kind of plot to generate, e.g. 'area', 'bar', 'line', 'scatter' etc. To see the available plots run `print(df.hvplot.__all__)`. **kwds : optional @@ -1727,13 +1761,13 @@ def image(self, x=None, y=None, z=None, colorbar=True, **kwds): Parameters ---------- - x : string, optional + x : str, optional The coordinate variable along the x-axis - y : string, optional + y : str, optional The coordinate variable along the y-axis - z : string, optional + z : str, optional The data variable to plot - colorbar: boolean + colorbar: bool Whether to display a colorbar **kwds : optional Additional keywords arguments are documented in :ref:`plot-options`. @@ -1741,7 +1775,7 @@ def image(self, x=None, y=None, z=None, colorbar=True, **kwds): Returns ------- - :class:`holoviews:holoviews.element.Image` / Panel object + :class:`holoviews:holoviews.element.Image` or Panel object You can `print` the object to study its composition and run: .. code-block:: @@ -1753,7 +1787,6 @@ def image(self, x=None, y=None, z=None, colorbar=True, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/examples/topics/images/image.html - HoloViews: https://holoviews.org/reference/elements/bokeh/Image.html - Matplotlib: https://matplotlib.org/stable/tutorials/introductory/images.html @@ -1774,16 +1807,16 @@ def rgb(self, x=None, y=None, z=None, bands=None, **kwds): Parameters ---------- - x : string, optional + x : str, optional The coordinate variable along the x-axis. By default the third coordinate of the dataset. - y : string, optional + y : str, optional The coordinate variable along the y-axis. By default the second coordinate of the dataset. - bands : string, optional + bands : str, optional The coordinate variable to draw the RGB channels from. By default the first coordinate of the dataset. - z : string, optional + z : str, optional The data variable to plot **kwds : optional Additional keywords arguments are documented in :ref:`plot-options`. @@ -1791,7 +1824,7 @@ def rgb(self, x=None, y=None, z=None, bands=None, **kwds): Returns ------- - :class:`holoviews:holoviews.element.RGB` / Panel object + :class:`holoviews:holoviews.element.RGB` or Panel object You can `print` the object to study its composition and run: .. code-block:: @@ -1803,7 +1836,6 @@ def rgb(self, x=None, y=None, z=None, bands=None, **kwds): References ---------- - - Bokeh: https://docs.bokeh.org/en/latest/docs/reference/models/glyphs/image_rgba.html - HoloViews: https://holoviews.org/reference/elements/bokeh/RGB.html - Matplotlib: https://matplotlib.org/stable/tutorials/introductory/images.html @@ -1830,13 +1862,13 @@ def quadmesh(self, x=None, y=None, z=None, colorbar=True, **kwds): Parameters ---------- - x : string, optional + x : str, optional The coordinate variable along the x-axis - y : string, optional + y : str, optional The coordinate variable along the y-axis - z : string, optional + z : str, optional The data variable to plot - colorbar: boolean + colorbar: bool Whether to display a colorbar **kwds : optional Additional keywords arguments are documented in :ref:`plot-options`. @@ -1844,7 +1876,7 @@ def quadmesh(self, x=None, y=None, z=None, colorbar=True, **kwds): Returns ------- - :class:`holoviews:holoviews.element.QuadMesh` / Panel object + :class:`holoviews:holoviews.element.QuadMesh` or Panel object You can `print` the object to study its composition and run: .. code-block:: @@ -1856,7 +1888,6 @@ def quadmesh(self, x=None, y=None, z=None, colorbar=True, **kwds): References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/QuadMesh.html """ return self(x, y, z=z, kind='quadmesh', colorbar=colorbar, **kwds) @@ -1874,13 +1905,13 @@ def contour(self, x=None, y=None, z=None, colorbar=True, levels=5, logz=False, * Parameters ---------- - x : string, optional + x : str, optional The coordinate variable along the x-axis - y : string, optional + y : str, optional The coordinate variable along the y-axis - z : string, optional + z : str, optional The data variable to plot - colorbar: boolean, optional + colorbar: bool, optional Whether to display a colorbar. Default is True. levels: int or list, optional The number of contour lines to draw or a list of scalar values used @@ -1893,7 +1924,7 @@ def contour(self, x=None, y=None, z=None, colorbar=True, levels=5, logz=False, * Returns ------- - :class:`holoviews:holoviews.element.Contours` / Panel object + :class:`holoviews:holoviews.element.Contours` or Panel object You can `print` the object to study its composition and run: .. code-block:: @@ -1909,7 +1940,6 @@ def contour(self, x=None, y=None, z=None, colorbar=True, levels=5, logz=False, * References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/Contours.html - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html - Plotly: https://plotly.com/python/contour-plots/ @@ -1918,27 +1948,34 @@ def contour(self, x=None, y=None, z=None, colorbar=True, levels=5, logz=False, * def contourf(self, x=None, y=None, z=None, colorbar=True, levels=5, logz=False, **kwds): """ - Filled contour plot + Create a filled contour plot for gridded data visualization. + + A filled contour plot displays smooth color-filled regions representing + different value ranges in 2D scalar fields. It is useful for visualizing + continuous data distributions, topographic maps, or any gridded data + where you want to show smooth transitions between values. + + Reference: https://hvplot.holoviz.org/reference/xarray/contourf.html - Reference. https://hvplot.holoviz.org/reference/xarray/contourf.html + Plotting options: https://hvplot.holoviz.org/ref/plotting_options/index.html Parameters ---------- - x : string, optional - The coordinate variable along the x-axis - y : string, optional - The coordinate variable along the y-axis - z : string, optional - The data variable to plot - colorbar: boolean - Whether to display a colorbar - levels: int, optional - The number of contour lines to draw or a list of scalar values used - to specify the contour levels. Default is 5 - logz: bool, optional - Whether to apply log scaling to the z-axis. Default is False + x : str, optional + Field name for the x-axis coordinate variable. + y : str, optional + Field name for the y-axis coordinate variable. + z : str, optional + Field name for the data variable to plot as filled contours. + colorbar : bool, default True + Whether to display a colorbar showing the value-to-color mapping. + levels : int or list, default 5 + Number of contour levels to draw, or explicit list of scalar values + defining the contour boundaries. + logz : bool, default False + Whether to apply logarithmic scaling to the z-axis values. **kwds : optional - Additional keywords arguments are documented in :ref:`plot-options`. + Additional keyword arguments documented in :ref:`plot-options`. Run ``hvplot.help('contourf')`` for the full method documentation. See Also @@ -1947,10 +1984,11 @@ def contourf(self, x=None, y=None, z=None, colorbar=True, levels=5, logz=False, Returns ------- - :class:`holoviews:holoviews.element.Contours` / Panel object - You can `print` the object to study its composition and run: + :class:`holoviews:holoviews.element.Contours` or Panel object + A HoloViews Contours element or Panel object if using Panel widgets. + You can ``print`` the object to study its composition and run: - .. code-block:: + .. code-block:: python import holoviews as hv hv.help(the_holoviews_object) @@ -1959,7 +1997,6 @@ def contourf(self, x=None, y=None, z=None, colorbar=True, levels=5, logz=False, References ---------- - - HoloViews: https://holoviews.org/reference/elements/bokeh/Contours.html - Matplotlib: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.contour.html - Plotly: https://plotly.com/python/contour-plots/