high-level interface for data visualization — 6.6.0 documentation
scatter([data_frame, x, y, color, symbol, …])
In a scatter plot, each row of data_frame is represented by a symbol
scatter_3d([data_frame, x, y, z, color, …])
In a 3D scatter plot, each row of data_frame is represented by a
scatter_polar([data_frame, r, theta, color, …])
In a polar scatter plot, each row of data_frame is represented by a
scatter_ternary([data_frame, a, b, c, …])
In a ternary scatter plot, each row of data_frame is represented by a
scatter_map([data_frame, lat, lon, color, …])
In a scatter map, each row of data_frame is represented by a
scatter_mapbox([data_frame, lat, lon, …])
scatter_mapbox is deprecated! Use scatter_map instead.
scatter_geo([data_frame, lat, lon, …])
In a geographic scatter plot, each row of data_frame is represented
line([data_frame, x, y, line_group, color, …])
In a 2D line plot, each row of data_frame is represented as a vertex of
line_3d([data_frame, x, y, z, color, …])
In a 3D line plot, each row of data_frame is represented as a vertex of
line_polar([data_frame, r, theta, color, …])
In a polar line plot, each row of data_frame is represented as a
line_ternary([data_frame, a, b, c, color, …])
In a ternary line plot, each row of data_frame is represented as
line_map([data_frame, lat, lon, color, …])
In a line map, each row of data_frame is represented as
line_mapbox([data_frame, lat, lon, color, …])
line_mapbox is deprecated! Use line_map instead.
line_geo([data_frame, lat, lon, locations, …])
In a geographic line plot, each row of data_frame is represented as
area([data_frame, x, y, line_group, color, …])
In a stacked area plot, each row of data_frame is represented as
bar([data_frame, x, y, color, …])
In a bar plot, each row of data_frame is represented as a rectangular
timeline([data_frame, x_start, x_end, y, …])
In a timeline plot, each row of data_frame is represented as a rectangular
bar_polar([data_frame, r, theta, color, …])
In a polar bar plot, each row of data_frame is represented as a wedge
violin([data_frame, x, y, color, facet_row, …])
In a violin plot, rows of data_frame are grouped together into a
box([data_frame, x, y, color, facet_row, …])
In a box plot, rows of data_frame are grouped together into a
ecdf([data_frame, x, y, color, text, …])
In a Empirical Cumulative Distribution Function (ECDF) plot, rows of data_frame
strip([data_frame, x, y, color, facet_row, …])
In a strip plot each row of data_frame is represented as a jittered
histogram([data_frame, x, y, color, …])
In a histogram, rows of data_frame are grouped together into a
pie([data_frame, names, values, color, …])
In a pie plot, each row of data_frame is represented as a sector of a
treemap([data_frame, names, values, …])
A treemap plot represents hierarchial data as nested rectangular
sunburst([data_frame, names, values, …])
A sunburst plot represents hierarchial data as sectors laid out over
icicle([data_frame, names, values, parents, …])
An icicle plot represents hierarchial data with adjoined rectangular
funnel([data_frame, x, y, color, facet_row, …])
In a funnel plot, each row of data_frame is represented as a
funnel_area([data_frame, names, values, …])
In a funnel area plot, each row of data_frame is represented as a
scatter_matrix([data_frame, dimensions, …])
In a scatter plot matrix (or SPLOM), each row of data_frame is
parallel_coordinates([data_frame, …])
In a parallel coordinates plot, each row of data_frame is represented
parallel_categories([data_frame, …])
In a parallel categories (or parallel sets) plot, each row of
choropleth([data_frame, lat, lon, …])
In a choropleth map, each row of data_frame is represented by a
choropleth_map([data_frame, geojson, …])
In a choropleth map, each row of data_frame is represented by a
choropleth_mapbox([data_frame, geojson, …])
choropleth_mapbox is deprecated! Use choropleth_map instead.
density_contour([data_frame, x, y, z, …])
In a density contour plot, rows of data_frame are grouped together
density_heatmap([data_frame, x, y, z, …])
In a density heatmap, rows of data_frame are grouped together into
density_map([data_frame, lat, lon, z, …])
In a density map, each row of data_frame contributes to the intensity of
density_mapbox([data_frame, lat, lon, z, …])
density_mapbox is deprecated! Use density_map instead.
imshow(img[, zmin, zmax, origin, labels, x, …])
Display an image, i.e. data on a 2D regular raster.
set_mapbox_access_token(token)
- param token
A Mapbox token to be used in
plotly.express.scatter_mapboxandplotly.express.line_mapboxfigures. See https://docs.mapbox.com/help/how-mapbox-works/access-tokens/ for more details
Extracts fit statistics for trendlines (when applied to figures generated with the trendline argument set to "ols").