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) -> Visualization | None
Retrieves a dataset visualization by its display name from the Driverless AI server.
Parameters:
-
name(str) –Name of the visualization.
Returns:
-
Visualization | None–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:
Returns:
-
Sequence[Visualization]–Dataset visualizations.
VisualizationJob ¶
Monitor the creation of a dataset visualization in the Driverless AI server.
is_complete ¶
is_complete() -> bool
Whether the job has been completed successfully.
Returns:
-
bool–Trueif the job has been completed successfully, otherwiseFalse.
is_running ¶
is_running() -> bool
Whether the job has been scheduled or is running, finishing, or syncing.
Returns:
-
bool–Trueif the job has not completed yet, otherwiseFalse.
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.
Visualization ¶
A dataset visualization in the Driverless AI server.
box_plots
property
¶
custom_plots
property
¶
custom_plots: list[CustomPlot]
Custom plots added to the visualization.
Returns:
-
list[CustomPlot]–
heatmaps
property
¶
histograms
property
¶
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–Trueif not compatible, otherwiseFalse.
log
property
¶
log: VisualizationLog
Log file associated with the visualization.
Returns:
-
VisualizationLog–Log of the visualization.
outliers
property
¶
Outlier plots of the visualization.
Returns:
-
list[dict[str, Any]]–Outlier plots in Vega Lite (v3) format.
parallel_coordinates_plot
property
¶
Parallel coordinates plot of the visualization.
Returns:
-
dict[str, Any]–Parallel coordinates plot in Vega Lite (v3) format.
recommendations
property
¶
scatter_plot
property
¶
Scatter plot of the visualization.
Returns:
-
dict[str, Any] | None–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
barfor a standard bar chart orpointfor 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:
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:
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:
Returns:
-
CustomPlot–Added custom grouped box plot.
add_heatmap ¶
add_heatmap(
variable_names: list[str] | None = None,
permute: bool = False,
transpose: bool = False,
matrix_type: str = "rectangular",
) -> CustomPlot
Adds a custom heatmap to the visualization.
Parameters:
-
variable_names(list[str] | None, 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
rectangularorsymmetric.
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,logorsquare_root. -
mark(str, default:'bar') –The type of mark to use in the histogram. Accepts
barfor a standard histogram orareafor 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:
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
pointorsquare. -
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
Trueto 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:
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
normaloruniform. -
mark(str, default:'point') –The type of mark to use in the plot. Accepts
pointorsquare. -
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:
Returns:
-
CustomPlot–Added custom scatter plot.
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.
VisualizationLog ¶
The AutoViz log file in the Driverless AI server.
download ¶
download(
dst_dir: str = ".",
dst_file: str | None = None,
file_system: AbstractFileSystem | None = None,
overwrite: bool = False,
timeout: float = 30,
) -> str
Downloads the log file.
Parameters:
-
dst_dir(str, default:'.') –The path where the log file will be saved.
-
dst_file(str | None, default:None) –The name of the log file (overrides the default file name).
-
file_system(AbstractFileSystem | None, 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.
-
timeout(float, default:30) –Connection timeout in seconds.
Returns:
-
str–Path to the downloaded log file.