viz_utils¶

virtualitics_sdk.utils.viz_utils.create_bar_plot(data_frame, x_axis_key, y_axis_key, plot_title, plot_description='', show_tooltip=True, include_keys_tooltip=None, exclude_keys_tooltip=None, x_axis_orientation=XAxisOrientation.BOTTOM, y_axis_orientation=YAxisOrientation.LEFT, x_axis_scale=PlotAxisScale.AUTO, y_axis_scale=PlotAxisScale.LINEAR, x_axis_label=None, y_axis_label=None, color_by=None, bounds=None, color_by_category=True, show_title=True, show_description=True, colors=None, advanced_tooltip=None, legend=None, lines=None, **kwargs)¶

Generates a Bar Plot for using Virtualitics AI Platform’s Visualization Framework.

Parameters:

data_frame (Union[Dataset, DataFrame]) – The data that should be plotted. NOTE: Rows with NaN will be filtered out.
x_axis_key (str) – The name of the column for the X-Axis.
y_axis_key (str) – The name of the column for the Y-Axis.
plot_title (str) – The title of the plot.
plot_description (str) – The description of the plot, defaults to “”.
show_tooltip (bool) – whether to show the tooltip, defaults to True.
include_keys_tooltip (Optional[List[str]]) – Keys to include on tooltip, defaults to all keys.
exclude_keys_tooltip (Optional[List[str]]) – Keys to exclude on tooltip, defaults to including all keys.
x_axis_orientation (XAxisOrientation) – The orientation of the X-Axis, defaults to XAxisOrientation.BOTTOM.
y_axis_orientation (YAxisOrientation) – The orientation of the Y-Axis, defaults to YAxisOrientation.LEFT.
x_axis_scale (PlotAxisScale) – The scale of the X-Axis, defaults to PlotAxisScale.AUTO.
y_axis_scale (PlotAxisScale) – The scale of the Y-Axis, defaults to PlotAxisScale.LINEAR.
x_axis_label (Optional[str]) – The label for the X-axis, defaults to x_axis_key.
y_axis_label (Optional[str]) – The label for the Y-axis, defaults to y_axis_key.
color_by (Optional[str]) – The column to use to color the plot if coloring, defaults to None (no coloring).
bounds (Optional[Dict[str, List[Union[str, int]]]]) – The bounds of the data range if they should be manually set. This is a dict that contains they key as a string and a list of two numbers as min and max range. A list of strings is also accepted for categorical values, defaults to None. For example {x_axis_key: [0, 100], y_axis_key: [50, 200]}
color_by_category (bool) – When true, the color by axis will be categorical (if set).
show_title (bool)
show_description (bool)
colors (Optional[List[str]]) – The hex color schema a plot should use, defaults to None (Virtualitics AI Platform default colors).
advanced_tooltip (Optional[Callable[[dict], List[Union[Element, str]]]]) – The function to call that creates an advanced tooltip. This functions takes a dict containing the data point and returns a list of elements (Plots, Infographics Tables, Infographics, CustomEvents) or strings which are rendered as markdown, defaults to None
legend (Optional[List[str]]) – A list to represent the order and labels on the legend. Will default to order present in plot data.
lines (Optional[List[Dict[str, Union[LineType, str, Any]]]]) – A list of dictionaries containing information on parameters for the creation of a line on the plot. Each dictionary in the list denotes a different line. The currently supported line types are ‘horizontal’, ‘vertical’, and ‘linear’, where a ‘linear’ line denotes a linear trend line fitted to the data. The dictionary must be specify the line type using a LineType enum and can specify additional parameters relevant each line type. See the constructors for the HorizontalLine, VerticalLine, and OLSTrendLine for more information. For exmaple, a dictionary for a linear trend line could look like: {“type”: LineType.LINEAR, “description”: “My trendline”, “time_series_unit”: pd.Timedelta(“1 hours”)}.

Return type:

Plot

Returns:

A newly created bar plot.

EXAMPLE:

# Imports 
from virtualitics_sdk.utils.viz_utils import create_bar_plot
...
# Example usage
df = pd.read_csv("some/example/path.csv")
ex_bar = create_bar_plot(df, 
                         "sepal.length", 
                         "sepal.width", 
                         "Sepal Length vs. Sepal Width")
card = Card("Example", [ex_bar])

virtualitics_sdk.utils.viz_utils.create_histogram_plot(data_frame, data_column, plot_title, plot_description='', bins='auto', frequency=False, show_tooltip=True, include_keys_tooltip=None, exclude_keys_tooltip=None, x_axis_orientation=XAxisOrientation.BOTTOM, y_axis_orientation=YAxisOrientation.LEFT, x_axis_scale=PlotAxisScale.AUTO, y_axis_scale=PlotAxisScale.LINEAR, x_axis_label=None, y_axis_label=None, color_by=None, bounds=None, color_by_category=True, show_title=True, show_description=True, _id=None, colors=None, advanced_tooltip=None, lines=None, legend=None, **kwargs)¶

Generates a Histogram Plot using Virtualitics AI Platform’s Visualization Framework.

Parameters:

data_frame (Union[Dataset, DataFrame]) – The data that should be plotted. NOTE: Rows with NaN will be filtered out.
data_column (str) – The name of the column whose data will be plotted in the histogram.
plot_title (str) – The title of the plot.
plot_description (str) – The description of the plot, defaults to “”.
bins (Union[int, Sequence[Union[int, float, number]], str]) – If an integer is provided, this is number of bins to to plot in the histogram. If a sequence of numbers is provided, these denote the edges of the bins, including the right most edge. If a string is provided, a binning algorithm is used to determine the number of bins based on the data’s distribution. More details can be found here, defaults to ‘auto’.
frequency (bool) – Determines whether to plot a histogram based on counts or frequency. If False, the histogram is plotted using counts in each bin. If True, uses frequency instead, defaults to False.
show_tooltip (bool) – whether to show the tooltip, defaults to True.
include_keys_tooltip (Optional[List[str]]) – Keys to include on tooltip, defaults to all keys.
exclude_keys_tooltip (Optional[List[str]]) – Keys to exclude on tooltip, defaults to including all keys.
x_axis_orientation (XAxisOrientation) – The orientation of the X-Axis, defaults to XAxisOrientation.BOTTOM.
y_axis_orientation (YAxisOrientation) – The orientation of the Y-Axis, defaults to YAxisOrientation.LEFT.
x_axis_scale (PlotAxisScale) – The scale of the X-Axis, defaults to PlotAxisScale.AUTO.
y_axis_scale (PlotAxisScale) – The scale of the Y-Axis, defaults to PlotAxisScale.LINEAR.
x_axis_label (Optional[str]) – The label for the X-axis, defaults to x_axis_key.
y_axis_label (Optional[str]) – The label for the Y-axis, defaults to y_axis_key.
color_by (Optional[str]) – The column to use to color the plot if coloring, defaults to None (no coloring).
bounds (Optional[Dict[str, List[Union[str, int]]]]) – The bounds of the data range if they should be manually set. This is a dict that contains they key as a string and a list of two numbers as min and max range. A list of strings is also accepted for categorical values, defaults to None. For example {x_axis_key: [0, 100], y_axis_key: [50, 200]}
color_by_category (bool) – When true, the color by axis will be categorical (if set).
show_title (bool)
show_description (bool)
_id (Optional[str]) – The ID of the plot, defaults to None.
colors (Optional[List[str]]) – The hex color schema a plot should use, defaults to None (Virtualitics AI Platform default colors).
advanced_tooltip (Optional[Callable[[dict], List[Union[Element, str]]]]) – The function to call that creatse an advanced tooltip. This functions takes a dict containing the data point and returns a list of elements (Plots, Infographics Tables, Infographics, CustomEvents) or strings which are rendered as markdown, defaults to None
lines (Optional[List[Dict[str, Union[LineType, str, Any]]]]) – A list of dictionaries containing information on parameters for the creation of a line on the plot. Each dictionary in the list denotes a different line. The currently supported line types are ‘horizontal’, ‘vertical’, and ‘linear’, where a ‘linear’ line denotes a linear trend line fitted to the data. The dictionary must be specify the line type using a LineType enum and can specify additional parameters relevant each line type. See the constructors for the HorizontalLine, VerticalLine, and OLSTrendLine for more information. For exmaple, a dictionary for a linear trend line could look like: {“type”: LineType.LINEAR, “description”: “My trendline”, “time_series_unit”: pd.Timedelta(“1 hours”)}.
legend (Optional[List[str]]) – A list to represent the order and labels on the legend. Will default to order present in plot data.

Return type:

Plot

Returns:

A newly created bar plot.

EXAMPLE:

# Imports 
from virtualitics_sdk.utils.viz_utils import create_histogram_plot
. . . 
# Example usage 
df = pd.read_csv("some/example/path.csv")
ex_histogram_plot = create_histogram_plot(df, 
                                          "sepal.length", 
                                          "Sepal Length Distribution",
                                          advanced_tooltip=bar_tooltip)
card = Card("Example",[ex_histogram_plot])

virtualitics_sdk.utils.viz_utils.create_line_plot(data_frame, x_axis_key, y_axis_key, plot_title, plot_description='', show_tooltip=True, include_keys_tooltip=None, exclude_keys_tooltip=None, x_axis_orientation=XAxisOrientation.BOTTOM, y_axis_orientation=YAxisOrientation.LEFT, x_axis_scale=PlotAxisScale.AUTO, y_axis_scale=PlotAxisScale.LINEAR, x_axis_label=None, y_axis_label=None, color_by=None, bounds=None, color_by_category=True, show_title=True, show_description=True, colors=None, advanced_tooltip=None, lines=None, legend=None, **kwargs)¶

Generates a Line Plot for using Virtualitics AI Platform’s Visualization Framework.

Parameters:

data_frame (Union[Dataset, DataFrame]) – The data that should be plotted. NOTE: Rows with NaN will be filtered out.
x_axis_key (str) – The name of the column for the X-Axis.
y_axis_key (str) – The name of the column for the Y-Axis.
plot_title (str) – The title of the plot.
plot_description (str) – The description of the plot, defaults to “”.
show_tooltip (bool) – whether to show the tooltip, defaults to True.
include_keys_tooltip (Optional[List[str]]) – Keys to include on tooltip, defaults to all keys.
exclude_keys_tooltip (Optional[List[str]]) – Keys to exclude on tooltip, defaults to including all keys.
x_axis_orientation (XAxisOrientation) – The orientation of the X-Axis, defaults to XAxisOrientation.BOTTOM.
y_axis_orientation (YAxisOrientation) – The orientation of the Y-Axis, defaults to YAxisOrientation.LEFT.
x_axis_scale (PlotAxisScale) – The scale of the X-Axis, defaults to PlotAxisScale.AUTO.
y_axis_scale (PlotAxisScale) – The scale of the Y-Axis, defaults to PlotAxisScale.LINEAR.
x_axis_label (Optional[str]) – The label for the X-axis, defaults to x_axis_key.
y_axis_label (Optional[str]) – The label for the Y-axis, defaults to y_axis_key.
color_by (Optional[str]) – The column to use to color the plot if coloring, defaults to None (no coloring).
bounds (Optional[Dict[str, List[Union[str, int]]]]) – The bounds of the data range if they should be manually set. This is a dict that contains the key as a string and a list of two numbers as min and max range. A list of strings is also accepted for categorical values, defaults to None. For example {x_axis_key: [0, 100], y_axis_key: [50, 200]}
color_by_category (bool) – When true, the color by axis will be categorical (if set).
show_title (bool)
show_description (bool)
colors (Optional[List[str]]) – The hex color schema a plot should use, defaults to None (Virtualitics AI Platform default colors).
advanced_tooltip (Optional[Callable[[dict], List[Union[Element, str]]]]) – The function to call that creatse an advanced tooltip. This functions takes a dict containing the data point and returns a list of elements (Plots, Infographics Tables, Infographics, CustomEvents) or strings which are rendered as markdown, defaults to None
lines (Optional[List[Dict[str, Union[LineType, str, Any]]]]) – A list of dictionaries containing information on parameters for the creation of a line on the plot. Each dictionary in the list denotes a different line. The currently supported line types are ‘horizontal’, ‘vertical’, and ‘linear’, where a ‘linear’ line denotes a linear trend line fitted to the data. The dictionary must be specify the line type using a LineType enum and can specify additional parameters relevant each line type. See the constructors for the HorizontalLine, VerticalLine, and OLSTrendLine for more information. For exmaple, a dictionary for a linear trend line could look like: {“type”: LineType.LINEAR, “description”: “My trendline”, “time_series_unit”: pd.Timedelta(“1 hours”)}.
legend (Optional[List[str]]) – A list to represent the order and labels on the legend. Will default to order present in plot data.

Return type:

Plot

Returns:

A newly created line plot.

EXAMPLE:

# Imports 
from virtualitics_sdk.utils.viz_utils import create_line_plot
. . . 
df = pd.read_csv("some/example/path.csv")
ex_line_plot = create_line_plot(df, 
                                "sepal.length", 
                                "sepal.width", 
                                "Sepal Length vs. Sepal Width Line")
card = Card("",[ex_line_plot])

The above plot will be displayed as:

virtualitics_sdk.utils.viz_utils.create_plot(plot_type, data_frame, x_axis_key, y_axis_key, plot_title, plot_description='', show_tooltip=True, include_keys_tooltip=None, exclude_keys_tooltip=None, x_axis_orientation=XAxisOrientation.BOTTOM, y_axis_orientation=YAxisOrientation.LEFT, x_axis_scale=PlotAxisScale.AUTO, y_axis_scale=PlotAxisScale.LINEAR, x_axis_label=None, y_axis_label=None, color_by=None, bounds=None, color_by_category=True, show_title=True, show_description=True, colors=None, advanced_tooltip=None, lines=None, legend=None, **kwargs)¶

Generates a Plot for using Virtualitics AI Platforms’s Visualization Framework.

Parameters:

plot_type (PlotType)
data_frame (Union[Dataset, DataFrame]) – The data that should be plotted. NOTE: Rows with NaN will be filtered out.
x_axis_key (str) – The name of the column for the X-Axis.
y_axis_key (str) – The name of the column for the Y-Axis.
plot_title (str) – The title of the plot.
plot_description (str) – The description of the plot, defaults to “”.
show_tooltip (bool) – whether to show the tooltip, defaults to True.
include_keys_tooltip (Optional[List[str]]) – Keys to include on tooltip, defaults to all keys.
exclude_keys_tooltip (Optional[List[str]]) – Keys to exclude on tooltip, defaults to including all keys.
x_axis_orientation (XAxisOrientation) – The orientation of the X-Axis, defaults to XAxisOrientation.BOTTOM.
y_axis_orientation (YAxisOrientation) – The orientation of the Y-Axis, defaults to YAxisOrientation.LEFT.
x_axis_scale (PlotAxisScale) – The scale of the X-Axis, defaults to PlotAxisScale.LINEAR.
y_axis_scale (PlotAxisScale) – The scale of the Y-Axis, defaults to PlotAxisScale.LINEAR.
x_axis_label (Optional[str]) – The label for the X-axis, defaults to the x_axis_key.
y_axis_label (Optional[str]) – The label for the Y-axis, defaults to the y_axis_key.
color_by (Optional[str]) – The column to use to color the plot if coloring. Defaults to None (no coloring).
bounds (Optional[Dict[str, List[Union[str, int]]]]) – The bounds of the data range if they should be manually set. This is a dict that contains they key as a string and a list of two numbers as min and max range. A list of strings is also accepted for categorical values. For example {x_axis_key: [0, 100], y_axis_key: [50, 200]}
color_by_category (bool) – When true, the color by axis will be categorical (if set).
show_title (bool)
show_description (bool)
colors (Optional[List[str]]) – The hex color schema a plot should use, defaults to None (Virtualitics AI Platform default colors).
advanced_tooltip (Optional[Callable[[dict], List[Union[Element, str]]]]) – The function to call that creatse an advanced tooltip. This functions takes a dict containing the data point and returns a list of elements (Plots, Infographics Tables, Infographics, CustomEvents) or strings which are rendered as markdown, defaults to None
lines (Optional[List[Dict[str, Union[LineType, str, Any]]]]) – A list of dictionaries containing information on parameters for the creation of a line on the plot. Each dictionary in the list denotes a different line. The currently supported line types are ‘horizontal’, ‘vertical’, and ‘linear’, where a ‘linear’ line denotes a linear trend line fitted to the data. The dictionary must be specify the line type using a LineType enum and can specify additional parameters relevant each line type. See the constructors for the HorizontalLine, VerticalLine, and OLSTrendLine for more information. For exmaple, a dictionary for a linear trend line could look like: {“type”: LineType.LINEAR, “description”: “My trendline”, “time_series_unit”: pd.Timedelta(“1 hours”)}.
legend (Optional[List[str]]) – A list to represent the order and labels on the legend. Will default to order present in plot data.

Return type:

Plot

Returns:

A Plot with the specification from above.

virtualitics_sdk.utils.viz_utils.create_scatter_plot(data_frame, x_axis_key, y_axis_key, plot_title, plot_description='', show_tooltip=True, include_keys_tooltip=None, exclude_keys_tooltip=None, x_axis_orientation=XAxisOrientation.BOTTOM, y_axis_orientation=YAxisOrientation.LEFT, x_axis_scale=PlotAxisScale.AUTO, y_axis_scale=PlotAxisScale.LINEAR, x_axis_label=None, y_axis_label=None, color_by=None, bounds=None, color_by_category=True, show_title=True, show_description=True, colors=None, advanced_tooltip=None, lines=None, legend=None, **kwargs)¶

Generates a Scatter Plot for using Virtualitics AI Platform’s Visualization Framework.

Parameters:

data_frame (Union[Dataset, DataFrame]) – The data that should be plotted. NOTE: Rows with NaN will be filtered out.
x_axis_key (str) – The name of the column for the X-Axis.
y_axis_key (str) – The name of the column for the Y-Axis.
plot_title (str) – The title of the plot.
plot_description (str) – The description of the plot, defaults to “”.
show_tooltip (bool) – whether to show the tooltip, defaults to True.
include_keys_tooltip (Optional[List[str]]) – Keys to include on tooltip, defaults to all keys.
exclude_keys_tooltip (Optional[List[str]]) – Keys to exclude on tooltip, defaults to including all keys.
x_axis_orientation (XAxisOrientation) – The orientation of the X-Axis, defaults to XAxisOrientation.BOTTOM.
y_axis_orientation (YAxisOrientation) – The orientation of the Y-Axis, defaults to YAxisOrientation.LEFT.
x_axis_scale (PlotAxisScale) – The scale of the X-Axis, defaults to PlotAxisScale.AUTO.
y_axis_scale (PlotAxisScale) – The scale of the Y-Axis, defaults to PlotAxisScale.LINEAR.
x_axis_label (Optional[str]) – The label for the X-axis, defaults to x_axis_key.
y_axis_label (Optional[str]) – The label for the Y-axis, defaults to y_axis_key.
color_by (Optional[str]) – The column to use to color the plot if coloring, defaults to None (no coloring).
bounds (Optional[Dict[str, List[Union[str, int]]]]) – The bounds of the data range if they should be manually set. This is a dict that contains they key as a string and a list of two numbers as min and max range. A list of strings is also accepted for categorical values, defaults to None. For example {x_axis_key: [0, 100], y_axis_key: [50, 200]}
color_by_category (bool) – When true, the color by axis will be categorical (if set).
show_title (bool)
show_description (bool)
colors (Optional[List[str]]) – The hex color schema a plot should use, defaults to None (Virtualitics AI Platform default colors).
advanced_tooltip (Optional[Callable[[dict], List[Union[Element, str]]]]) – The function to call that creatse an advanced tooltip. This functions takes a dict containing the data point and returns a list of elements (Plots, Infographics Tables, Infographics, CustomEvents) or strings which are rendered as markdown, defaults to None
lines (Optional[List[Dict[str, Union[LineType, str, Any]]]]) – A list of dictionaries containing information on parameters for the creation of a line on the plot. Each dictionary in the list denotes a different line. The currently supported line types are ‘horizontal’, ‘vertical’, and ‘linear’, where a ‘linear’ line denotes a linear trend line fitted to the data. The dictionary must be specify the line type using a LineType enum and can specify additional parameters relevant each line type. See the constructors for the HorizontalLine, VerticalLine, and OLSTrendLine for more information. For exmaple, a dictionary for a linear trend line could look like: {“type”: LineType.LINEAR, “description”: “My trendline”, “time_series_unit”: pd.Timedelta(“1 hours”)}.
legend (Optional[List[str]]) – A list to represent the order and labels on the legend. Will default to order present in plot data.

Return type:

Plot

Returns:

A newly created scatter plot.

EXAMPLE:

# Imports 
from virtualitics_sdk.utils.viz_utils import create_scatter_plot
. . . 
df = pd.read_csv("some/example/path.csv")
ex_scatter_plot = create_scatter_plot(df, 
                                      "sepal.length", 
                                      "sepal.width", 
                                      "Sepal Length vs. Sepal Width")
card = Card("",[ex_scatter_plot])

The above plot will be displayed as:

virtualitics_sdk.utils.viz_utils.get_bounds(bounds, key, _data_frame, y_axis_key, data_type, y_axis_scale, plot_type)¶