plotly.express.treemap¶plotly.express.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) → plotly.graph_objects._figure.Figure¶A treemap plot represents hierarchial data as nested rectangular sectors.
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.
names (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 as
labels for sectors.
values (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
set values associated to sectors.
parents (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 as
parents in sunburst and treemap charts.
ids (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
set ids of sectors
path (list of str or int, or Series or array-like) – Either names of columns in data_frame, or pandas Series, or
array_like objects List of columns names or columns of a rectangular
dataframe defining the hierarchy of sectors, from root to leaves. An
error is raised if path AND ids or parents is passed
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.
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.
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.
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.)
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.
title (str) – The figure title.
subtitle (str) – The figure subtitle.
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.
branchvalues (str) – ‘total’ or ‘remainder’ Determines how the items in values are summed.
Whenset to ‘total’, items in values are taken to be valueof all its
descendants. When set to ‘remainder’, itemsin values corresponding to
the root and the branches:sectors are taken to be the extra part not
part of thesum of the values at their leaves.
maxdepth (int) – Positive integer Sets the number of rendered sectors from any given
level. Set maxdepth to -1 to render all thelevels in the hierarchy.