sda.dashboard.components.tables#

Table Components.

Components for displaying data in tabular format.

Attributes#

Options

Classes#

DropdownOption

dict() -> new empty dictionary

Functions#

create_table_layout(test_name)

Create table layout for displaying all data points.

create_data_table(df[, page_size])

Create a Dash DataTable from a pandas DataFrame.

get_table_info(df[, selected_rows])

Get table information summary.

Module Contents#

class sda.dashboard.components.tables.DropdownOption#

Bases: TypedDict

dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s

(key, value) pairs

dict(iterable) -> new dictionary initialized as if via:

d = {} for k, v in iterable:

d[k] = v

dict(**kwargs) -> new dictionary initialized with the name=value pairs

in the keyword argument list. For example: dict(one=1, two=2)

label: str#
value: int | str#
sda.dashboard.components.tables.Options#
sda.dashboard.components.tables.create_table_layout(test_name)#

Create table layout for displaying all data points.

Parameters:

test_name (str) – Name of the test to display

Returns:

Complete table layout

Return type:

html.Div

sda.dashboard.components.tables.create_data_table(df, page_size=25)#

Create a Dash DataTable from a pandas DataFrame.

Parameters:

  • df (pd.DataFrame) – Data to display

  • page_size (int, default 25) – Number of rows per page

Returns:

Configured DataTable component

Return type:

dash_table.DataTable

sda.dashboard.components.tables.get_table_info(df, selected_rows=None)#

Get table information summary.

Parameters:

  • df (pd.DataFrame) – Data to analyze

  • selected_rows (List[int], optional) – List of selected row indices

Returns:

Table information summary

Return type:

str