Autoviz

AutoViz

Interact with dataset visualizations in the Driverless AI server.

create

create(dataset: Dataset) -> Visualization

Creates a dataset visualization.

Parameters:

• dataset (Dataset) –

  The dataset to be visualized.

Returns:

• Visualization –

  Created visualization.

create_async

create_async(dataset: Dataset) -> VisualizationJob

Launches the creation of a dataset visualization.

Parameters:

• dataset (Dataset) –

  The dataset to be visualized.

Returns:

• VisualizationJob –

  Started visualization job.

get

get(key: str) -> Visualization

Retrieves a dataset visualization in the Driverless AI server.

Parameters:

• key (str) –

  The unique ID of the visualization.

Returns:

• Visualization –

  The visualization corresponding to the key.

get_by_name

get_by_name(name: str) -> Optional[Visualization]

Retrieves a dataset visualization by its display name from the Driverless AI server.

Parameters:

• name (str) –

  Name of the visualization.

Returns:

• Optional[Visualization] –

  The visualization with the specified name if it exists, otherwise None.

Beta API

A beta API that is subject to future changes.

gui

gui() -> Hyperlink

Returns the full URL to the AutoViz page in the Driverless AI server.

Returns:

• Hyperlink –

  The full URL to the AutoViz page.

list

list(start_index: int = 0, count: int = None) -> Sequence[Visualization]

Retrieves dataset visualizations in the Driverless AI server.

Parameters:

• start_index (int, default: 0 ) –

  The index of the first visualization to retrieve.

• count (int, default: None ) –

  The maximum number of visualizations to retrieve. If None, retrieves all available visualizations.

Returns:

• Sequence[Visualization] –

  Dataset visualizations.

VisualizationJob

Monitor the creation of a dataset visualization in the Driverless AI server.

key property

key: str

Universally unique key of the entity.

Returns:

• str –

   

name property

name: str

Name of the entity.

Returns:

• str –

   

is_complete

is_complete() -> bool

Whether the job has been completed successfully.

Returns:

• bool –

  True if the job has been completed successfully, otherwise False.

is_running

is_running() -> bool

Whether the job has been scheduled or is running, finishing, or syncing.

Returns:

• bool –

  True if the job has not completed yet, otherwise False.

result

result(silent: bool = False) -> Visualization

Awaits the job's completion before returning the created visualization.

Parameters:

• silent (bool, default: False ) –

  Whether to display status updates or not.

Returns:

• Visualization –

  Created visualization by the job.

status

status(verbose: int = 0) -> str

Returns the status of the job.

Parameters:

• verbose (int, default: 0 ) –
  • 0: A short description.
  • 1: A short description with a progress percentage.
  • 2: A detailed description with a progress percentage.

Returns:

• str –

  Current status of the job.

Visualization

A dataset visualization in the Driverless AI server.

box_plots property

box_plots: Dict[str, List[Dict[str, Any]]]

Disparate box plots and heteroscedastic box plots of the visualization.

Returns:

• Dict[str, List[Dict[str, Any]]] –

  A dictionary with two keys, disparate and heteroscedastic, each containing a list of plots in Vega Lite (v3) format.

custom_plots property

custom_plots: List[CustomPlot]

Custom plots added to the visualization.

Returns:

• List[CustomPlot] –

   

dataset property

dataset: Dataset

Visualized dataset.

Returns:

• Dataset –

   

heatmaps property

heatmaps: Dict[str, Dict[str, Any]]

Data heatmap and Missing values heatmap of the visualization.

Returns:

• Dict[str, Dict[str, Any]] –

  A dictionary with two keys, data_heatmap and missing_values_heatmap, each containing a plot in Vega Lite (v3) format.

histograms property

histograms: Dict[str, List[Dict[str, Any]]]

Spikes, skewed, and gaps histograms of the visualization.

Returns:

• Dict[str, List[Dict[str, Any]]] –

  A dictionary with three keys, spikes, skewed, and gaps, each containing a list of plots in Vega Lite (v3) format.

is_deprecated property

is_deprecated: bool

Whether the visualization was created by an older Driverless AI server version and no longer fully compatible with the current server version.

Returns:

• bool –

  True if not compatible, otherwise False.

key property

key: str

Universally unique key of the entity.

Returns:

• str –

   

log property

log: VisualizationLog

Log file associated with the visualization.

Returns:

• VisualizationLog –

  Log of the visualization.

name property

name: str

Name of the entity.

Returns:

• str –

   

outliers property

outliers: List[Dict[str, Any]]

Outlier plots of the visualization.

Returns:

• List[Dict[str, Any]] –

  Outlier plots in Vega Lite (v3) format.

parallel_coordinates_plot property

parallel_coordinates_plot: Dict[str, Any]

Parallel coordinates plot of the visualization.

Returns:

• Dict[str, Any] –

  Parallel coordinates plot in Vega Lite (v3) format.

recommendations property

recommendations: Optional[Dict[str, Dict[str, str]]]

Recommended feature transformations and deletions based on the visualization analysis.

Returns:

• Optional[Dict[str, Dict[str, str]]] –

  A dictionary with two keys, transforms and deletions, each containing a dictionary of recommended actions for features. Or None if no recommendations are present.

scatter_plot property

scatter_plot: Optional[Dict[str, Any]]

Scatter plot of the visualization.

Returns:

• Optional[Dict[str, Any]] –

  Scatter plot in Vega Lite (v3) format if correlated features exist, otherwise None.

add_bar_chart

add_bar_chart(
    x_variable_name: str,
    y_variable_name: str = "",
    transpose: bool = False,
    mark: str = "bar",
) -> CustomPlot

Adds a custom bar chart to the visualization.

Parameters:

• x_variable_name (str) –

  Column for the X axis.

• y_variable_name (str, default: '' ) –

  Column for the Y axis. If omitted then the number of occurrences is considered.

• transpose (bool, default: False ) –

  Whether to flip axes or not.

• mark (str, default: 'bar' ) –

  The type of mark to use in the chart. Accepts bar for a standard bar chart or point for a Cleveland dot plot.

Returns:

• CustomPlot –

  Added custom bar chart.

add_box_plot

add_box_plot(variable_name: str, transpose: bool = False) -> CustomPlot

Adds a custom box plot to the visualization.

Parameters:

• variable_name (str) –

  The column for the plot.

• transpose (bool, default: False ) –

  Whether to flip axes or not.

Returns:

• CustomPlot –

  Added custom box plot.

add_dot_plot

add_dot_plot(variable_name: str, mark: str = 'point') -> CustomPlot

Adds a custom dot plot to the visualization.

Parameters:

• variable_name (str) –

  The column for the plot.

• mark (str, default: 'point' ) –

  The type of mark to represent each data point in the plot. Accepts point, square, or bar.

Returns:

• CustomPlot –

  Added custom dot plot.

add_grouped_box_plot

add_grouped_box_plot(
    variable_name: str, group_variable_name: str, transpose: bool = False
) -> CustomPlot

Adds a custom grouped box plot to the visualization.

Parameters:

• variable_name (str) –

  The column for the plot.

• group_variable_name (str) –

  The grouping column.

• transpose (bool, default: False ) –

  Whether to flip axes or not.

Returns:

• CustomPlot –

  Added custom grouped box plot.

add_heatmap

add_heatmap(
    variable_names: Optional[List[str]] = None,
    permute: bool = False,
    transpose: bool = False,
    matrix_type: str = "rectangular",
) -> CustomPlot

Adds a custom heatmap to the visualization.

Parameters:

• variable_names (Optional[List[str]], default: None ) –

  Columns for the Heatmap, if omitted then all columns are used.

• permute (bool, default: False ) –

  Whether to permute rows and columns using singular value decomposition (SVD) or not.

• transpose (bool, default: False ) –

  Whether to flip axes or not.

• matrix_type (str, default: 'rectangular' ) –

  The type of matrix to be used. Possible values are rectangular or symmetric.

Returns:

• CustomPlot –

  Added custom heatmap.

add_histogram

add_histogram(
    variable_name: str,
    number_of_bars: int = 0,
    transformation: str = "none",
    mark: str = "bar",
) -> CustomPlot

Adds a custom histogram to the visualization.

Parameters:

• variable_name (str) –

  Column for the histogram.

• number_of_bars (int, default: 0 ) –

  Number of bars in the histogram. If set to 0, the number of bars is automatically determined

• transformation (str, default: 'none' ) –

  A transformation applied to the column. Possible values are none, log or square_root.

• mark (str, default: 'bar' ) –

  The type of mark to use in the histogram. Accepts bar for a standard histogram or area for a density polygon.

Returns:

• CustomPlot –

  Added custom histogram.

add_linear_regression

add_linear_regression(
    x_variable_name: str, y_variable_name: str, mark: str = "point"
) -> CustomPlot

Adds a custom linear regression to the visualization.

Parameters:

• x_variable_name (str) –

  Column for the X axis.

• y_variable_name (str) –

  Column for the Y axis.

• mark (str, default: 'point' ) –

  The type of mark to use in the plot. Accepts point or square.

Returns:

• CustomPlot –

  Added custom linear regression.

add_loess_regression

add_loess_regression(
    x_variable_name: str,
    y_variable_name: str,
    mark: str = "point",
    bandwidth: float = 0.5,
) -> CustomPlot

Adds a custom loess regression to the visualization.

Parameters:

• x_variable_name (str) –

  Column for the X axis.

• y_variable_name (str) –

  Column for the Y axis. If omitted then the number of occurrences is considered.

• mark (str, default: 'point' ) –

  The type of mark to use in the plot. Accepts point or square.

• bandwidth (float, default: 0.5 ) –

  Interval denoting proportion of cases in smoothing window.

Returns:

• CustomPlot –

  Added custom loess regression.

add_parallel_coordinates_plot

add_parallel_coordinates_plot(
    variable_names: List[str] = None,
    permute: bool = False,
    transpose: bool = False,
    cluster: bool = False,
) -> CustomPlot

Adds a custom parallel coordinates plot to the visualization.

Parameters:

• variable_names (List[str], default: None ) –

  Columns for the plot, if omitted then all columns will be used.

• permute (bool, default: False ) –

  Whether to permute rows and columns using singular value decomposition (SVD) or not.

• transpose (bool, default: False ) –

  Whether to flip axes or not.

• cluster (bool, default: False ) –

  Set to True to k-means cluster variables and color the plot by cluster IDs.

Returns:

• CustomPlot –

  Added custom parallel coordinates plot.

add_probability_plot

add_probability_plot(
    x_variable_name: str,
    distribution: str = "normal",
    mark: str = "point",
    transpose: bool = False,
) -> CustomPlot

Adds a custom probability plot to the visualization.

Parameters:

• x_variable_name (str) –

  Column for the X axis.

• distribution (str, default: 'normal' ) –

  Type of distribution. Accepts normal or uniform.

• mark (str, default: 'point' ) –

  The type of mark to use in the plot. Accepts point or square.

• transpose (bool, default: False ) –

  Whether to flip axes or not.

Returns:

• CustomPlot –

  Added custom probability plot.

add_quantile_plot

add_quantile_plot(
    x_variable_name: str,
    y_variable_name: str,
    distribution: str = "normal",
    mark: str = "point",
    transpose: bool = False,
) -> CustomPlot

Adds a custom quantile plot to the visualization.

Parameters:

• x_variable_name (str) –

  Column for the X axis.

• y_variable_name (str) –

  Column for the Y axis.

• distribution (str, default: 'normal' ) –

  Type of distribution. Accepts normal or uniform.

• mark (str, default: 'point' ) –

  The type of mark to use in the plot. Accepts point or square.

• transpose (bool, default: False ) –

  Whether to flip axes or not.

Returns:

• CustomPlot –

  Added custom quantile plot.

add_scatter_plot

add_scatter_plot(
    x_variable_name: str, y_variable_name: str, mark: str = "point"
) -> CustomPlot

Adds a custom scatter plot to the visualization.

Parameters:

• x_variable_name (str) –

  Column for the X axis.

• y_variable_name (str) –

  Column for the Y axis. If omitted then the number of occurrences is considered.

• mark (str, default: 'point' ) –

  The type of mark to use in the plot. Accepts point or square.

Returns:

• CustomPlot –

  Added custom scatter plot.

delete

delete() -> None

Permanently deletes the visualization from the Driverless AI server.

gui

gui() -> Hyperlink

Returns the full URL to the visualization's page in the Driverless AI server.

Returns:

• Hyperlink –

  URL to the visualization page.

remove_custom_plot

remove_custom_plot(custom_plot: CustomPlot) -> None

Removes a previously added custom plot from the visualization.

Parameters:

• custom_plot (CustomPlot) –

  Custom plot to be removed & deleted.

CustomPlot

A custom plot added to a dataset visualization in the Driverless AI server.

key property

key: str

Universally unique key of the entity.

Returns:

• str –

   

name property

name: str

Name of the entity.

Returns:

• str –

   

plot_data property

plot_data: Dict[str, Any]

Plot data of the custom plot.

Returns:

• Dict[str, Any] –

  The plot in Vega Lite (v3) format.

VisualizationLog

The AutoViz log file in the Driverless AI server.

file_name property

file_name: str

Filename of the log file.

Returns:

• str –

   

download

download(
    dst_dir: str = ".",
    dst_file: Optional[str] = None,
    file_system: Optional[AbstractFileSystem] = None,
    overwrite: bool = False,
) -> str

Downloads the log file.

Parameters:

• dst_dir (str, default: '.' ) –

  The path where the log file will be saved.

• dst_file (Optional[str], default: None ) –

  The name of the log file (overrides the default file name).

• file_system (Optional[AbstractFileSystem], default: None ) –

  FSSPEC-based file system to download to instead of the local file system.

• overwrite (bool, default: False ) –

  Whether to overwrite or not if a file already exists.

Returns:

• str –

  Path to the downloaded log file.

head

head(num_lines: int = 50) -> str

Returns the first n lines of the log file.

Parameters:

• num_lines (int, default: 50 ) –

  Number of lines to retrieve.

Returns:

• str –

   

tail

tail(num_lines: int = 50) -> str

Returns the last n lines of the log file.

Parameters:

• num_lines (int, default: 50 ) –

  Number of lines to retrieve.

Returns:

• str –