plotly.express.scatter_geo

plotly.express.scatter_geo(data_frame=None, lat=None, lon=None, locations=None, locationmode=None, color=None, text=None, hover_name=None, hover_data=None, custom_data=None, size=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, opacity=None, size_max=None, projection=None, scope=None, center=None, title=None, template=None, width=None, height=None)

In a geographic scatter plot, each row of data_frame is represented by a symbol mark on a map.

Parameters
  • data_frame (DataFrame or array-like or dict) – This argument needs to be passed for column names (and not keyword names) to be used. Array-like and dict are tranformed internally to a pandas DataFrame. Optional: if missing, a DataFrame gets constructed under the hood using the other arguments.

  • lat (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to position marks according to latitude on a map.

  • lon (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to position marks according to longitude on a map.

  • locations (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are to be interpreted according to locationmode and mapped to longitude/latitude.

  • locationmode (str) – One of ‘ISO-3’, ‘USA-states’, or ‘country names’ Determines the set of locations used to match entries in locations to regions on the map.

  • color (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign color to marks.

  • text (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like appear in the figure as text labels.

  • hover_name (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like appear in bold in the hover tooltip.

  • hover_data (list of str or int, or Series or array-like) – Either names of columns in data_frame, or pandas Series, or array_like objects Values from these columns appear as extra data in the hover tooltip.

  • custom_data (list of str or int, or Series or array-like) – Either names of columns in data_frame, or pandas Series, or array_like objects Values from these columns are extra data, to be used in widgets or Dash callbacks for example. This data is not user-visible but is included in events emitted by the figure (lasso selection etc.)

  • size (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign mark sizes.

  • animation_frame (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to assign marks to animation frames.

  • animation_group (str or int or Series or array-like) – Either a name of a column in data_frame, or a pandas Series or array_like object. Values from this column or array_like are used to provide object-constancy across animation frames: rows with matching `animation_group`s will be treated as if they describe the same object in each frame.

  • category_orders (dict with str keys and list of str values (default {})) – By default, in Python 3.6+, the order of categorical values in axes, legends and facets depends on the order in which these values are first encountered in data_frame (and no order is guaranteed by default in Python below 3.6). This parameter is used to force a specific ordering of values per column. The keys of this dict should correspond to column names, and the values should be lists of strings corresponding to the specific display order desired.

  • labels (dict with str keys and str values (default {})) – By default, column names are used in the figure for axis titles, legend entries and hovers. This parameter allows this to be overridden. The keys of this dict should correspond to column names, and the values should correspond to the desired label to be displayed.

  • color_discrete_sequence (list of str) – Strings should define valid CSS-colors. When color is set and the values in the corresponding column are not numeric, values in that column are assigned colors by cycling through color_discrete_sequence in the order described in category_orders, unless the value of color is a key in color_discrete_map. Various useful color sequences are available in the plotly_express.colors submodules, specifically plotly_express.colors.qualitative.

  • color_discrete_map (dict with str keys and str values (default {})) – String values should define valid CSS-colors Used to override color_discrete_sequence to assign a specific colors to marks corresponding with specific values. Keys in color_discrete_map should be values in the column denoted by color.

  • color_continuous_scale (list of str) – Strings should define valid CSS-colors This list is used to build a continuous color scale when the column denoted by color contains numeric data. Various useful color scales are available in the plotly_express.colors submodules, specifically plotly_express.colors.sequential, plotly_express.colors.diverging and plotly_express.colors.cyclical.

  • range_color (list of two numbers) – If provided, overrides auto-scaling on the continuous color scale.

  • color_continuous_midpoint (number (default None)) – If set, computes the bounds of the continuous color scale to have the desired midpoint. Setting this value is recommended when using plotly_express.colors.diverging color scales as the inputs to color_continuous_scale.

  • opacity (float) – Value between 0 and 1. Sets the opacity for markers.

  • size_max (int (default 20)) – Set the maximum mark size when using size.

  • projection (str) – One of 'equirectangular', 'mercator', 'orthographic', 'natural earth', 'kavrayskiy7', 'miller', 'robinson', 'eckert4', 'azimuthal equal area', 'azimuthal equidistant', 'conic equal area', 'conic conformal', 'conic equidistant', 'gnomonic', 'stereographic', 'mollweide', 'hammer', 'transverse mercator', 'albers usa', 'winkel tripel', 'aitoff', or 'sinusoidal'`Default depends on `scope.

  • scope (str (default 'world').) – One of 'world', 'usa', 'europe', 'asia', 'africa', 'north america', or 'south america')Default is 'world' unless projection is set to 'albers usa', which forces 'usa'.

  • center (dict) – Dict keys are 'lat' and 'lon' Sets the center point of the map.

  • title (str) – The figure title.

  • template (or dict or plotly.graph_objects.layout.Template instance) – The figure template name or definition.

  • width (int (default None)) – The figure width in pixels.

  • height (int (default 600)) – The figure height in pixels.

Returns

Return type

A Figure object.