import plotly.express as px
px.choropleth_map?
Signature:
px.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,
 template=None,
 width=None,
 height=None,
) -> plotly.graph_objs._figure.Figure
Docstring:
 In a choropleth map, each row of `data_frame` is represented by a
 colored region on the 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 transformed internally to a
 pandas DataFrame. Optional: if missing, a DataFrame gets constructed
 under the hood using the other arguments.
geojson: GeoJSON-formatted dict
 Must contain a Polygon feature collection, with IDs, which are
 references from `locations`.
featureidkey: str (default: `'id'`)
 Path to field in GeoJSON feature object with which to match the values
 passed in to `locations`.The most common alternative to the default is
 of the form `'properties.<key>`.
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.
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.
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: str, or list of str or int, or Series or array-like, or dict
 Either a name or list of names of columns in `data_frame`, or pandas
 Series, or array_like objects or a dict with column names as keys, with
 values True (for default formatting) False (in order to remove this
 column from hover information), or a formatting string, for example
 ':.3f' or '|%a' or list-like data to appear in the hover tooltip or
 tuples with a bool or formatting string as first element, and list-like
 data to appear in hover as second element Values from these columns
 appear as extra data in the hover tooltip.
custom_data: str, or list of str or int, or Series or array-like
 Either name or list of 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.)
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`. Alternatively, if the
 values of `color` are valid colors, the string `'identity'` may be
 passed to cause them to be used directly.
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.
zoom: int (default `8`)
 Between 0 and 20. Sets map zoom level.
center: dict
 Dict keys are `'lat'` and `'lon'` Sets the center point of the map.
map_style: str (default `'basic'`)
 Identifier of base map style. Allowed values are `'basic'`, `'carto-
 darkmatter'`, `'carto-darkmatter-nolabels'`, `'carto-positron'`,
 `'carto-positron-nolabels'`, `'carto-voyager'`, `'carto-voyager-
 nolabels'`, `'dark'`, `'light'`, `'open-street-map'`, `'outdoors'`,
 `'satellite'`, `'satellite-streets'`, `'streets'`, `'white-bg'`.
title: str
 The figure title.
template: str or dict or plotly.graph_objects.layout.Template instance
 The figure template name (must be a key in plotly.io.templates) or
 definition.
width: int (default `None`)
 The figure width in pixels.
height: int (default `None`)
 The figure height in pixels.
Returns
-------
 plotly.graph_objects.Figure
File: ~/venv312/lib/python3.12/site-packages/plotly/express/_chart_types.py
Type: function