from warnings import warn from ._core import make_figure from ._doc import make_docstring import plotly.graph_objs as go _wide_mode_xy_append = [ "Either `x` or `y` can optionally be a list of column references or array_likes, ", "in which case the data will be treated as if it were 'wide' rather than 'long'.", ] _cartesian_append_dict = dict(x=_wide_mode_xy_append, y=_wide_mode_xy_append) def scatter( data_frame=None, x=None, y=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, orientation=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map=None, opacity=None, size_max=None, marginal_x=None, marginal_y=None, trendline=None, trendline_options=None, trendline_color_override=None, trendline_scope="trace", log_x=False, log_y=False, range_x=None, range_y=None, render_mode="auto", title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a scatter plot, each row of `data_frame` is represented by a symbol mark in 2D space. """ return make_figure(args=locals(), constructor=go.Scatter) scatter.__doc__ = make_docstring(scatter, append_dict=_cartesian_append_dict) def density_contour( data_frame=None, x=None, y=None, z=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, orientation=None, color_discrete_sequence=None, color_discrete_map=None, marginal_x=None, marginal_y=None, trendline=None, trendline_options=None, trendline_color_override=None, trendline_scope="trace", log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, histnorm=None, nbinsx=None, nbinsy=None, text_auto=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a density contour plot, rows of `data_frame` are grouped together into contour marks to visualize the 2D distribution of an aggregate function `histfunc` (e.g. the count or sum) of the value `z`. """ return make_figure( args=locals(), constructor=go.Histogram2dContour, trace_patch=dict( contours=dict(coloring="none"), histfunc=histfunc, histnorm=histnorm, nbinsx=nbinsx, nbinsy=nbinsy, xbingroup="x", ybingroup="y", ), ) density_contour.__doc__ = make_docstring( density_contour, append_dict=dict( x=_wide_mode_xy_append, y=_wide_mode_xy_append, z=[ "For `density_heatmap` and `density_contour` these values are used as the inputs to `histfunc`.", ], histfunc=["The arguments to this function are the values of `z`."], ), ) def density_heatmap( data_frame=None, x=None, y=None, z=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, orientation=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, marginal_x=None, marginal_y=None, opacity=None, log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, histnorm=None, nbinsx=None, nbinsy=None, text_auto=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a density heatmap, rows of `data_frame` are grouped together into colored rectangular tiles to visualize the 2D distribution of an aggregate function `histfunc` (e.g. the count or sum) of the value `z`. """ return make_figure( args=locals(), constructor=go.Histogram2d, trace_patch=dict( histfunc=histfunc, histnorm=histnorm, nbinsx=nbinsx, nbinsy=nbinsy, xbingroup="x", ybingroup="y", ), ) density_heatmap.__doc__ = make_docstring( density_heatmap, append_dict=dict( x=_wide_mode_xy_append, y=_wide_mode_xy_append, z=[ "For `density_heatmap` and `density_contour` these values are used as the inputs to `histfunc`.", ], histfunc=[ "The arguments to this function are the values of `z`.", ], ), ) def line( data_frame=None, x=None, y=None, line_group=None, color=None, line_dash=None, symbol=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, orientation=None, color_discrete_sequence=None, color_discrete_map=None, line_dash_sequence=None, line_dash_map=None, symbol_sequence=None, symbol_map=None, markers=False, log_x=False, log_y=False, range_x=None, range_y=None, line_shape=None, render_mode="auto", title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a 2D line plot, each row of `data_frame` is represented as a vertex of a polyline mark in 2D space. """ return make_figure(args=locals(), constructor=go.Scatter) line.__doc__ = make_docstring(line, append_dict=_cartesian_append_dict) def area( data_frame=None, x=None, y=None, line_group=None, color=None, pattern_shape=None, symbol=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, pattern_shape_sequence=None, pattern_shape_map=None, symbol_sequence=None, symbol_map=None, markers=False, orientation=None, groupnorm=None, log_x=False, log_y=False, range_x=None, range_y=None, line_shape=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a stacked area plot, each row of `data_frame` is represented as a vertex of a polyline mark in 2D space. The area between successive polylines is filled. """ return make_figure( args=locals(), constructor=go.Scatter, trace_patch=dict(stackgroup=1, mode="lines", groupnorm=groupnorm), ) area.__doc__ = make_docstring(area, append_dict=_cartesian_append_dict) def bar( data_frame=None, x=None, y=None, color=None, pattern_shape=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, text=None, base=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, pattern_shape_sequence=None, pattern_shape_map=None, range_color=None, color_continuous_midpoint=None, opacity=None, orientation=None, barmode="relative", log_x=False, log_y=False, range_x=None, range_y=None, text_auto=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a bar plot, each row of `data_frame` is represented as a rectangular mark. """ return make_figure( args=locals(), constructor=go.Bar, trace_patch=dict(textposition="auto"), layout_patch=dict(barmode=barmode), ) bar.__doc__ = make_docstring(bar, append_dict=_cartesian_append_dict) def timeline( data_frame=None, x_start=None, x_end=None, y=None, color=None, pattern_shape=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, text=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, pattern_shape_sequence=None, pattern_shape_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, range_x=None, range_y=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a timeline plot, each row of `data_frame` is represented as a rectangular mark on an x axis of type `date`, spanning from `x_start` to `x_end`. """ return make_figure( args=locals(), constructor="timeline", trace_patch=dict(textposition="auto", orientation="h"), layout_patch=dict(barmode="overlay"), ) timeline.__doc__ = make_docstring(timeline) def histogram( data_frame=None, x=None, y=None, color=None, pattern_shape=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, pattern_shape_sequence=None, pattern_shape_map=None, marginal=None, opacity=None, orientation=None, barmode="relative", barnorm=None, histnorm=None, log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, cumulative=None, nbins=None, text_auto=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a histogram, rows of `data_frame` are grouped together into a rectangular mark to visualize the 1D distribution of an aggregate function `histfunc` (e.g. the count or sum) of the value `y` (or `x` if `orientation` is `'h'`). """ return make_figure( args=locals(), constructor=go.Histogram, trace_patch=dict( histnorm=histnorm, histfunc=histfunc, cumulative=dict(enabled=cumulative), ), layout_patch=dict(barmode=barmode, barnorm=barnorm), ) histogram.__doc__ = make_docstring( histogram, append_dict=dict( x=["If `orientation` is `'h'`, these values are used as inputs to `histfunc`."] + _wide_mode_xy_append, y=["If `orientation` is `'v'`, these values are used as inputs to `histfunc`."] + _wide_mode_xy_append, histfunc=[ "The arguments to this function are the values of `y` (`x`) if `orientation` is `'v'` (`'h'`).", ], ), ) def ecdf( data_frame=None, x=None, y=None, color=None, text=None, line_dash=None, symbol=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, animation_frame=None, animation_group=None, markers=False, lines=True, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, line_dash_sequence=None, line_dash_map=None, symbol_sequence=None, symbol_map=None, marginal=None, opacity=None, orientation=None, ecdfnorm="probability", ecdfmode="standard", render_mode="auto", log_x=False, log_y=False, range_x=None, range_y=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a Empirical Cumulative Distribution Function (ECDF) plot, rows of `data_frame` are sorted by the value `x` (or `y` if `orientation` is `'h'`) and their cumulative count (or the cumulative sum of `y` if supplied and `orientation` is `h`) is drawn as a line. """ return make_figure(args=locals(), constructor=go.Scatter) ecdf.__doc__ = make_docstring( ecdf, append_dict=dict( x=[ "If `orientation` is `'h'`, the cumulative sum of this argument is plotted rather than the cumulative count." ] + _wide_mode_xy_append, y=[ "If `orientation` is `'v'`, the cumulative sum of this argument is plotted rather than the cumulative count." ] + _wide_mode_xy_append, ), ) def violin( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, orientation=None, violinmode=None, log_x=False, log_y=False, range_x=None, range_y=None, points=None, box=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a violin plot, rows of `data_frame` are grouped together into a curved mark to visualize their distribution. """ return make_figure( args=locals(), constructor=go.Violin, trace_patch=dict( points=points, box=dict(visible=box), scalegroup=True, x0=" ", y0=" ", ), layout_patch=dict(violinmode=violinmode), ) violin.__doc__ = make_docstring(violin, append_dict=_cartesian_append_dict) def box( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, orientation=None, boxmode=None, log_x=False, log_y=False, range_x=None, range_y=None, points=None, notched=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a box plot, rows of `data_frame` are grouped together into a box-and-whisker mark to visualize their distribution. Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second quartile (Q2) is marked by a line inside the box. By default, the whiskers correspond to the box' edges +/- 1.5 times the interquartile range (IQR: Q3-Q1), see "points" for other options. """ return make_figure( args=locals(), constructor=go.Box, trace_patch=dict(boxpoints=points, notched=notched, x0=" ", y0=" "), layout_patch=dict(boxmode=boxmode), ) box.__doc__ = make_docstring(box, append_dict=_cartesian_append_dict) def strip( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, orientation=None, stripmode=None, log_x=False, log_y=False, range_x=None, range_y=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a strip plot each row of `data_frame` is represented as a jittered mark within categories. """ return make_figure( args=locals(), constructor=go.Box, trace_patch=dict( boxpoints="all", pointpos=0, hoveron="points", fillcolor="rgba(255,255,255,0)", line={"color": "rgba(255,255,255,0)"}, x0=" ", y0=" ", ), layout_patch=dict(boxmode=stripmode), ) strip.__doc__ = make_docstring(strip, append_dict=_cartesian_append_dict) def scatter_3d( data_frame=None, x=None, y=None, z=None, color=None, symbol=None, size=None, text=None, hover_name=None, hover_data=None, custom_data=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, error_z=None, error_z_minus=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, size_max=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map=None, opacity=None, log_x=False, log_y=False, log_z=False, range_x=None, range_y=None, range_z=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a 3D scatter plot, each row of `data_frame` is represented by a symbol mark in 3D space. """ return make_figure(args=locals(), constructor=go.Scatter3d) scatter_3d.__doc__ = make_docstring(scatter_3d) def line_3d( data_frame=None, x=None, y=None, z=None, color=None, line_dash=None, text=None, line_group=None, symbol=None, hover_name=None, hover_data=None, custom_data=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, error_z=None, error_z_minus=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, line_dash_sequence=None, line_dash_map=None, symbol_sequence=None, symbol_map=None, markers=False, log_x=False, log_y=False, log_z=False, range_x=None, range_y=None, range_z=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a 3D line plot, each row of `data_frame` is represented as a vertex of a polyline mark in 3D space. """ return make_figure(args=locals(), constructor=go.Scatter3d) line_3d.__doc__ = make_docstring(line_3d) def scatter_ternary( data_frame=None, a=None, b=None, c=None, color=None, symbol=None, size=None, text=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map=None, opacity=None, size_max=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a ternary scatter plot, each row of `data_frame` is represented by a symbol mark in ternary coordinates. """ return make_figure(args=locals(), constructor=go.Scatterternary) scatter_ternary.__doc__ = make_docstring(scatter_ternary) def line_ternary( data_frame=None, a=None, b=None, c=None, color=None, line_dash=None, line_group=None, symbol=None, hover_name=None, hover_data=None, custom_data=None, text=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, line_dash_sequence=None, line_dash_map=None, symbol_sequence=None, symbol_map=None, markers=False, line_shape=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a ternary line plot, each row of `data_frame` is represented as a vertex of a polyline mark in ternary coordinates. """ return make_figure(args=locals(), constructor=go.Scatterternary) line_ternary.__doc__ = make_docstring(line_ternary) def scatter_polar( data_frame=None, r=None, theta=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, custom_data=None, text=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map=None, opacity=None, direction="clockwise", start_angle=90, size_max=None, range_r=None, range_theta=None, log_r=False, render_mode="auto", title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a polar scatter plot, each row of `data_frame` is represented by a symbol mark in polar coordinates. """ return make_figure(args=locals(), constructor=go.Scatterpolar) scatter_polar.__doc__ = make_docstring(scatter_polar) def line_polar( data_frame=None, r=None, theta=None, color=None, line_dash=None, hover_name=None, hover_data=None, custom_data=None, line_group=None, text=None, symbol=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, line_dash_sequence=None, line_dash_map=None, symbol_sequence=None, symbol_map=None, markers=False, direction="clockwise", start_angle=90, line_close=False, line_shape=None, render_mode="auto", range_r=None, range_theta=None, log_r=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a polar line plot, each row of `data_frame` is represented as a vertex of a polyline mark in polar coordinates. """ return make_figure(args=locals(), constructor=go.Scatterpolar) line_polar.__doc__ = make_docstring(line_polar) def bar_polar( data_frame=None, r=None, theta=None, color=None, pattern_shape=None, hover_name=None, hover_data=None, custom_data=None, base=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, pattern_shape_sequence=None, pattern_shape_map=None, range_color=None, color_continuous_midpoint=None, barnorm=None, barmode="relative", direction="clockwise", start_angle=90, range_r=None, range_theta=None, log_r=False, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a polar bar plot, each row of `data_frame` is represented as a wedge mark in polar coordinates. """ return make_figure( args=locals(), constructor=go.Barpolar, layout_patch=dict(barnorm=barnorm, barmode=barmode), ) bar_polar.__doc__ = make_docstring(bar_polar) def choropleth( data_frame=None, lat=None, lon=None, locations=None, locationmode=None, geojson=None, featureidkey=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, projection=None, scope=None, center=None, fitbounds=None, basemap_visible=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a choropleth map, each row of `data_frame` is represented by a colored region mark on a map. """ if locationmode == "country names": warn( "The library used by the *country names* `locationmode` option is changing in an upcoming version. " "Country names in existing plots may not work in the new version. " "To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.", DeprecationWarning, stacklevel=2, ) return make_figure( args=locals(), constructor=go.Choropleth, trace_patch=dict(locationmode=locationmode), ) choropleth.__doc__ = make_docstring(choropleth) def scatter_geo( data_frame=None, lat=None, lon=None, locations=None, locationmode=None, geojson=None, featureidkey=None, color=None, text=None, symbol=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, size=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map=None, opacity=None, size_max=None, projection=None, scope=None, center=None, fitbounds=None, basemap_visible=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a geographic scatter plot, each row of `data_frame` is represented by a symbol mark on a map. """ if locationmode == "country names": warn( "The library used by the *country names* `locationmode` option is changing in an upcoming version. " "Country names in existing plots may not work in the new version. " "To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.", DeprecationWarning, stacklevel=2, ) return make_figure( args=locals(), constructor=go.Scattergeo, trace_patch=dict(locationmode=locationmode), ) scatter_geo.__doc__ = make_docstring(scatter_geo) def line_geo( data_frame=None, lat=None, lon=None, locations=None, locationmode=None, geojson=None, featureidkey=None, color=None, line_dash=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, line_group=None, symbol=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, line_dash_sequence=None, line_dash_map=None, symbol_sequence=None, symbol_map=None, markers=False, projection=None, scope=None, center=None, fitbounds=None, basemap_visible=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a geographic line plot, each row of `data_frame` is represented as a vertex of a polyline mark on a map. """ return make_figure( args=locals(), constructor=go.Scattergeo, trace_patch=dict(locationmode=locationmode), ) line_geo.__doc__ = make_docstring(line_geo) def scatter_map( data_frame=None, lat=None, lon=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, size=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, size_max=None, zoom=8, center=None, map_style=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a scatter map, each row of `data_frame` is represented by a symbol mark on the map. """ return make_figure(args=locals(), constructor=go.Scattermap) scatter_map.__doc__ = make_docstring(scatter_map) def choropleth_map( data_frame=None, geojson=None, featureidkey=None, locations=None, color=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, zoom=8, center=None, map_style=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a choropleth map, each row of `data_frame` is represented by a colored region on the map. """ return make_figure(args=locals(), constructor=go.Choroplethmap) choropleth_map.__doc__ = make_docstring(choropleth_map) def density_map( data_frame=None, lat=None, lon=None, z=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, zoom=8, center=None, map_style=None, radius=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a density map, each row of `data_frame` contributes to the intensity of the color of the region around the corresponding point on the map. """ return make_figure( args=locals(), constructor=go.Densitymap, trace_patch=dict(radius=radius) ) density_map.__doc__ = make_docstring(density_map) def line_map( data_frame=None, lat=None, lon=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, line_group=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, zoom=8, center=None, map_style=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a line map, each row of `data_frame` is represented as a vertex of a polyline mark on the map. """ return make_figure(args=locals(), constructor=go.Scattermap) line_map.__doc__ = make_docstring(line_map) def scatter_mapbox( data_frame=None, lat=None, lon=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, size=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, size_max=None, zoom=8, center=None, mapbox_style=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ *scatter_mapbox* is deprecated! Use *scatter_map* instead. Learn more at: https://plotly.com/python/mapbox-to-maplibre/ In a Mapbox scatter plot, each row of `data_frame` is represented by a symbol mark on a Mapbox map. """ warn( "*scatter_mapbox* is deprecated!" + " Use *scatter_map* instead." + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", stacklevel=2, category=DeprecationWarning, ) return make_figure(args=locals(), constructor=go.Scattermapbox) scatter_mapbox.__doc__ = make_docstring(scatter_mapbox) def choropleth_mapbox( data_frame=None, geojson=None, featureidkey=None, locations=None, color=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, zoom=8, center=None, mapbox_style=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ *choropleth_mapbox* is deprecated! Use *choropleth_map* instead. Learn more at: https://plotly.com/python/mapbox-to-maplibre/ In a Mapbox choropleth map, each row of `data_frame` is represented by a colored region on a Mapbox map. """ warn( "*choropleth_mapbox* is deprecated!" + " Use *choropleth_map* instead." + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", stacklevel=2, category=DeprecationWarning, ) return make_figure(args=locals(), constructor=go.Choroplethmapbox) choropleth_mapbox.__doc__ = make_docstring(choropleth_mapbox) def density_mapbox( data_frame=None, lat=None, lon=None, z=None, hover_name=None, hover_data=None, custom_data=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, zoom=8, center=None, mapbox_style=None, radius=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ *density_mapbox* is deprecated! Use *density_map* instead. Learn more at: https://plotly.com/python/mapbox-to-maplibre/ In a Mapbox density map, each row of `data_frame` contributes to the intensity of the color of the region around the corresponding point on the map """ warn( "*density_mapbox* is deprecated!" + " Use *density_map* instead." + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", stacklevel=2, category=DeprecationWarning, ) return make_figure( args=locals(), constructor=go.Densitymapbox, trace_patch=dict(radius=radius) ) density_mapbox.__doc__ = make_docstring(density_mapbox) def line_mapbox( data_frame=None, lat=None, lon=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, line_group=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, zoom=8, center=None, mapbox_style=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ *line_mapbox* is deprecated! Use *line_map* instead. Learn more at: https://plotly.com/python/mapbox-to-maplibre/ In a Mapbox line plot, each row of `data_frame` is represented as a vertex of a polyline mark on a Mapbox map. """ warn( "*line_mapbox* is deprecated!" + " Use *line_map* instead." + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", stacklevel=2, category=DeprecationWarning, ) return make_figure(args=locals(), constructor=go.Scattermapbox) line_mapbox.__doc__ = make_docstring(line_mapbox) def scatter_matrix( data_frame=None, dimensions=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, custom_data=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map=None, opacity=None, size_max=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a scatter plot matrix (or SPLOM), each row of `data_frame` is represented by a multiple symbol marks, one in each cell of a grid of 2D scatter plots, which plot each pair of `dimensions` against each other. """ return make_figure( args=locals(), constructor=go.Splom, layout_patch=dict(dragmode="select") ) scatter_matrix.__doc__ = make_docstring(scatter_matrix) def parallel_coordinates( data_frame=None, dimensions=None, color=None, labels=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a parallel coordinates plot, each row of `data_frame` is represented by a polyline mark which traverses a set of parallel axes, one for each of the `dimensions`. """ return make_figure(args=locals(), constructor=go.Parcoords) parallel_coordinates.__doc__ = make_docstring(parallel_coordinates) def parallel_categories( data_frame=None, dimensions=None, color=None, labels=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, title=None, subtitle=None, template=None, width=None, height=None, dimensions_max_cardinality=50, ) -> go.Figure: """ In a parallel categories (or parallel sets) plot, each row of `data_frame` is grouped with other rows that share the same values of `dimensions` and then plotted as a polyline mark through a set of parallel axes, one for each of the `dimensions`. """ return make_figure(args=locals(), constructor=go.Parcats) parallel_categories.__doc__ = make_docstring(parallel_categories) def pie( data_frame=None, names=None, values=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, color_discrete_sequence=None, color_discrete_map=None, hover_name=None, hover_data=None, custom_data=None, category_orders=None, labels=None, title=None, subtitle=None, template=None, width=None, height=None, opacity=None, hole=None, ) -> go.Figure: """ In a pie plot, each row of `data_frame` is represented as a sector of a pie. """ if color_discrete_sequence is not None: layout_patch = {"piecolorway": color_discrete_sequence} else: layout_patch = {} return make_figure( args=locals(), constructor=go.Pie, trace_patch=dict(showlegend=(names is not None), hole=hole), layout_patch=layout_patch, ) pie.__doc__ = make_docstring( pie, override_dict=dict( hole=[ "float", "Sets the fraction of the radius to cut out of the pie." "Use this to make a donut chart.", ], ), ) def sunburst( data_frame=None, names=None, values=None, parents=None, path=None, ids=None, color=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, color_discrete_sequence=None, color_discrete_map=None, hover_name=None, hover_data=None, custom_data=None, labels=None, title=None, subtitle=None, template=None, width=None, height=None, branchvalues=None, maxdepth=None, ) -> go.Figure: """ A sunburst plot represents hierarchial data as sectors laid out over several levels of concentric rings. """ if color_discrete_sequence is not None: layout_patch = {"sunburstcolorway": color_discrete_sequence} else: layout_patch = {} if path is not None and (ids is not None or parents is not None): raise ValueError( "Either `path` should be provided, or `ids` and `parents`." "These parameters are mutually exclusive and cannot be passed together." ) if path is not None and branchvalues is None: branchvalues = "total" return make_figure( args=locals(), constructor=go.Sunburst, trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), layout_patch=layout_patch, ) sunburst.__doc__ = make_docstring(sunburst) def treemap( data_frame=None, names=None, values=None, parents=None, ids=None, path=None, color=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, color_discrete_sequence=None, color_discrete_map=None, hover_name=None, hover_data=None, custom_data=None, labels=None, title=None, subtitle=None, template=None, width=None, height=None, branchvalues=None, maxdepth=None, ) -> go.Figure: """ A treemap plot represents hierarchial data as nested rectangular sectors. """ if color_discrete_sequence is not None: layout_patch = {"treemapcolorway": color_discrete_sequence} else: layout_patch = {} if path is not None and (ids is not None or parents is not None): raise ValueError( "Either `path` should be provided, or `ids` and `parents`." "These parameters are mutually exclusive and cannot be passed together." ) if path is not None and branchvalues is None: branchvalues = "total" return make_figure( args=locals(), constructor=go.Treemap, trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), layout_patch=layout_patch, ) treemap.__doc__ = make_docstring(treemap) def icicle( data_frame=None, names=None, values=None, parents=None, path=None, ids=None, color=None, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, color_discrete_sequence=None, color_discrete_map=None, hover_name=None, hover_data=None, custom_data=None, labels=None, title=None, subtitle=None, template=None, width=None, height=None, branchvalues=None, maxdepth=None, ) -> go.Figure: """ An icicle plot represents hierarchial data with adjoined rectangular sectors that all cascade from root down to leaf in one direction. """ if color_discrete_sequence is not None: layout_patch = {"iciclecolorway": color_discrete_sequence} else: layout_patch = {} if path is not None and (ids is not None or parents is not None): raise ValueError( "Either `path` should be provided, or `ids` and `parents`." "These parameters are mutually exclusive and cannot be passed together." ) if path is not None and branchvalues is None: branchvalues = "total" return make_figure( args=locals(), constructor=go.Icicle, trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), layout_patch=layout_patch, ) icicle.__doc__ = make_docstring(icicle) def funnel( data_frame=None, x=None, y=None, color=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, hover_name=None, hover_data=None, custom_data=None, text=None, animation_frame=None, animation_group=None, category_orders=None, labels=None, color_discrete_sequence=None, color_discrete_map=None, opacity=None, orientation=None, log_x=False, log_y=False, range_x=None, range_y=None, title=None, subtitle=None, template=None, width=None, height=None, ) -> go.Figure: """ In a funnel plot, each row of `data_frame` is represented as a rectangular sector of a funnel. """ return make_figure(args=locals(), constructor=go.Funnel) funnel.__doc__ = make_docstring(funnel, append_dict=_cartesian_append_dict) def funnel_area( data_frame=None, names=None, values=None, color=None, color_discrete_sequence=None, color_discrete_map=None, hover_name=None, hover_data=None, custom_data=None, labels=None, title=None, subtitle=None, template=None, width=None, height=None, opacity=None, ) -> go.Figure: """ In a funnel area plot, each row of `data_frame` is represented as a trapezoidal sector of a funnel. """ if color_discrete_sequence is not None: layout_patch = {"funnelareacolorway": color_discrete_sequence} else: layout_patch = {} return make_figure( args=locals(), constructor=go.Funnelarea, trace_patch=dict(showlegend=(names is not None)), layout_patch=layout_patch, ) funnel_area.__doc__ = make_docstring(funnel_area)