module

    Objects of this class can be passed to Plotly Express functions that expect column
    identifiers or list-like objects to indicate that this attribute should take on a
    constant value. An optional label can be provided.

    `dict`-like object which acts as if the value for any key is the key itself. Objects
    of this class can be passed in to arguments like `color_discrete_map` to
    use the provided data values as colors, rather than mapping them to colors cycled
    from `color_discrete_sequence`. This works for any `_map` argument to Plotly Express
    functions, such as `line_dash_map` and `symbol_map`.

str(object='') -> str
str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or
errors is specified, then the object must expose a data buffer
that will be decoded using the given encoding and error handler.
Otherwise, returns the result of object.__str__() (if defined)
or repr(object).
encoding defaults to sys.getdefaultencoding().
errors defaults to 'strict'.

    Objects of this class can be passed to Plotly Express functions that expect column
    identifiers or list-like objects to indicate that this attribute should be mapped
    onto integers starting at 0. An optional label can be provided.

    In a stacked area plot, each row of `data_frame` is represented as
    vertex of a polyline mark in 2D space. The area between successive
    polylines is filled.
    
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.
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'.
line_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
    group rows of `data_frame` into lines.
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.
symbol: 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 symbols 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.)
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.
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 0.0.7
    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.
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.
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.
symbol_sequence: list of str
    Strings should define valid plotly.js symbols. When `symbol` is set,
    values in that column are assigned symbols by cycling through
    `symbol_sequence` in the order described in `category_orders`, unless
    the value of `symbol` is a key in `symbol_map`.
symbol_map: dict with str keys and str values (default `{}`)
    String values should define plotly.js symbols Used to override
    `symbol_sequence` to assign a specific symbols to marks corresponding
    with specific values. Keys in `symbol_map` should be values in the
    column denoted by `symbol`. Alternatively, if the values of `symbol`
    are valid symbol names, the string `'identity'` may be passed to cause
    them to be used directly.
markers: boolean (default `False`)
    If `True`, markers are shown on lines.
orientation: str, one of `'h'` for horizontal or `'v'` for vertical. 
    (default `'v'` if `x` and `y` are provided and both continous 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)
groupnorm: str (default `None`)
    One of `'fraction'` or `'percent'`. If `'fraction'`, the value of each
    point is divided by the sum of all values at that location coordinate.
    `'percent'` is the same but multiplied by 100 to show percentages.
    `None` will stack up all values at each location coordinate.
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.
line_shape: str (default `'linear'`)
    One of `'linear'` or `'spline'`.
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

    In a bar plot, each row of `data_frame` is represented as a rectangular
    mark.
    
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.
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 0.0.7
    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 continous 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.
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

    In a polar bar plot, each row of `data_frame` is represented as a wedge
    mark in polar coordinates.
    
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.
r: 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 radial axis in polar coordinates.
theta: 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 angular axis in polar coordinates.
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.
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.)
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.
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`.
barnorm: str (default `None`)
    One of `'fraction'` or `'percent'`. If `'fraction'`, the value of each
    bar is divided by the sum of all values at that location coordinate.
    `'percent'` is the same but multiplied by 100 to show percentages.
    `None` will stack up all values at each location coordinate.
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.
direction: str
    One of '`counterclockwise'` or `'clockwise'`. Default is `'clockwise'`
    Sets the direction in which increasing values of the angular axis are
    drawn.
start_angle: int (default `90`)
    Sets start angle for the angular axis, with 0 being due east and 90
    being due north.
range_r: list of two numbers
    If provided, overrides auto-scaling on the radial axis in polar
    coordinates.
range_theta: list of two numbers
    If provided, overrides auto-scaling on the angular axis in polar
    coordinates.
log_r: boolean (default `False`)
    If `True`, the radial axis is log-scaled in polar coordinates.
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

    In a box plot, rows of `data_frame` are grouped together into a
    box-and-whisker mark to visualize their distribution.

    Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second
    quartile (Q2) is marked by a line inside the box. By default, the
    whiskers correspond to the box' edges +/- 1.5 times the interquartile
    range (IQR: Q3-Q1), see "points" for other options.
    
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.
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.
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 0.0.7
    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.)
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.
orientation: str, one of `'h'` for horizontal or `'v'` for vertical. 
    (default `'v'` if `x` and `y` are provided and both continous 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)
boxmode: str (default `'group'`)
    One of `'group'` or `'overlay'` In `'overlay'` mode, boxes are on drawn
    top of one another. In `'group'` mode, boxes 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.
points: str or boolean (default `'outliers'`)
    One of `'outliers'`, `'suspectedoutliers'`, `'all'`, or `False`. If
    `'outliers'`, only the sample points lying outside the whiskers are
    shown. If `'suspectedoutliers'`, all outlier points are shown and those
    less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted with the
    marker's `'outliercolor'`. If `'outliers'`, only the sample points
    lying outside the whiskers are shown. If `'all'`, all sample points are
    shown. If `False`, no sample points are shown and the whiskers extend
    to the full range of the sample.
notched: boolean (default `False`)
    If `True`, boxes are drawn with notches.
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

    In a choropleth map, each row of `data_frame` is represented by a
    colored region 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 transformed 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.
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>`.
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.
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 0.0.7
    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.)
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`.
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.
fitbounds: str (default `False`).
    One of `False`, `locations` or `geojson`.
basemap_visible: bool
    Force the basemap visibility.
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

    In a Mapbox choropleth map, each row of `data_frame` is represented by a
    colored region on a Mapbox 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.
mapbox_style: str (default `'basic'`, needs Mapbox API token)
    Identifier of base map style, some of which require a Mapbox API token
    to be set using `plotly.express.set_mapbox_access_token()`. Allowed
    values which do not require a Mapbox API token are `'open-street-map'`,
    `'white-bg'`, `'carto-positron'`, `'carto-darkmatter'`, `'stamen-
    terrain'`, `'stamen-toner'`, `'stamen-watercolor'`. Allowed values
    which do require a Mapbox API token are `'basic'`, `'streets'`,
    `'outdoors'`, `'light'`, `'dark'`, `'satellite'`, `'satellite-
    streets'`.
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