plotly.express.bar¶plotly.express.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) → plotly.graph_objects._figure.Figure¶In a bar plot, each row of
data_frameis represented as a rectangular mark.
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.
x (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 along the x axis in cartesian coordinates. 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’.
y (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 along the y axis in cartesian coordinates. 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’.
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.
pattern_shape (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 pattern shapes to marks.
facet_row (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 facetted subplots in the vertical direction.
facet_col (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 facetted subplots in the horizontal direction.
facet_col_wrap (int) – Maximum number of facet columns. Wraps the column variable at this
width, so that the column facets span multiple rows. Ignored if 0, and
forced to 0 if facet_row or a marginal is set.
facet_row_spacing (float between 0 and 1) – Spacing between facet rows, in paper units. Default is 0.03 or 0.07 when facet_col_wrap is used.
facet_col_spacing (float between 0 and 1) – Spacing between facet columns, in paper units Default is 0.02.
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.)
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.
base (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 the base of the bar.
error_x (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
size x-axis error bars. If error_x_minus is None, error bars will
be symmetrical, otherwise error_x is used for the positive direction
only.
error_x_minus (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
size x-axis error bars in the negative direction. Ignored if error_x
is None.
error_y (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
size y-axis error bars. If error_y_minus is None, error bars will
be symmetrical, otherwise error_y is used for the positive direction
only.
error_y_minus (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
size y-axis error bars in the negative direction. Ignored if error_y
is None.
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.
pattern_shape_sequence (list of str) – Strings should define valid plotly.js patterns-shapes. When
pattern_shape is set, values in that column are assigned
patterns-shapes by cycling through pattern_shape_sequence in the
order described in category_orders, unless the value of
pattern_shape is a key in pattern_shape_map.
pattern_shape_map (dict with str keys and str values (default {})) – Strings values define plotly.js patterns-shapes. Used to override
pattern_shape_sequences to assign a specific patterns-shapes to lines
corresponding with specific values. Keys in pattern_shape_map should
be values in the column denoted by pattern_shape. Alternatively, if
the values of pattern_shape are valid patterns-shapes names, the
string 'identity' may be passed to cause them to be used directly.
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.
orientation (str, one of 'h' for horizontal or 'v' for vertical.) – (default 'v' if x and y are provided and both continuous or both
categorical, otherwise 'v'`(‘h’) if `x`(`y) is categorical and
y`(`x) is continuous, otherwise 'v'`(‘h’) if only `x`(`y) is
provided)
barmode (str (default 'relative')) – One of 'group', 'overlay' or 'relative' In 'relative' mode,
bars are stacked above zero for positive values and below zero for
negative values. In 'overlay' mode, bars are drawn on top of one
another. In 'group' mode, bars are placed beside each other.
log_x (boolean (default False)) – If True, the x-axis is log-scaled in cartesian coordinates.
log_y (boolean (default False)) – If True, the y-axis is log-scaled in cartesian coordinates.
range_x (list of two numbers) – If provided, overrides auto-scaling on the x-axis in cartesian coordinates.
range_y (list of two numbers) – If provided, overrides auto-scaling on the y-axis in cartesian coordinates.
text_auto (bool or string (default False)) – If True or a string, the x or y or z values will be displayed as
text, depending on the orientation A string like '.2f' will be
interpreted as a texttemplate numeric formatting directive.
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.