Table

Available in backends: qt

Signals

• changed(object) - Emitted when the widget value changes.
• label_changed(str) - Emitted when the widget label changes.
• native_parent_changed(object) - Emitted with the backend widget when the widget parent changes.

Table

Bases: ValueWidget, _ReadOnlyMixin, MutableMapping[TblKey, list]

A widget to represent columnar or 2D data with headers.

Tables behave like plain dicts, where the keys are column headers and the (list-like) values are column data.

Parameters:

• value ((dict, dataframe, list, array, tuple), default: None ) –

  Table data (and/or header data), in one of the accepted formats:

  • list or list-of-lists : [column_values] or [[row_vals], ..., [row_vals]]
  • dict-of-dicts : {column_header -> {row_header -> value}}
  • dict-of-lists : {column_header -> [column_values]}
  • list-of-row-records : [{column_headers -> value}, ... , {column_headers -> value}]
  • split-dict-of-lists :
  • tuple-of-values : ([values], [row_headers], [column_headers])
  • dict-of-pandas-series : {column_header -> Series(values)}
• index (Collection, default: None ) –

  A sized iterable container of row headers. By default, row headers will be tuple(range(len(data))). Values provided here override any implied in value.

• columns (Collection, default: None ) –

  A sized iterable container of column headers. By default, column headers will be tuple(range(len(data[0]))). Values provided here override any implied in value.

• **kwargs (Unpack[WidgetKwargs], default: {} ) –

  Additional kwargs will be passed to the magicgui.widgets.Widget constructor.

Attributes:

• value (dict) –

  Returns a dict with the keys data, index, and columns ... representing the 2D (list of lists) tabular data, row headers, and column headers, respectively. If set, will clear and update the table using the new data.

• data (DataView) –

  A DataView instance that provides numpy-like indexing (with get/set/delete) onto the 2D data array, For example table.data[0,2] gets the data in the cell of the first row, 3rd column. Works with numpy slice syntax.

• column_headers (tuple) –

  The current column headers. Can be set with a new sequence to change

• row_headers (tuple) –

  The current row headers. Can be set with a new sequence to change

• shape (tuple of int) –

  The shape of the table in (rows, columns).

• size (int) –

  The number of cells in the table.

Methods:

• keys –

  Return a TableHeadersView, providing a view on this table's headers. Use axis='row' for row headers.

• items –

  Return a TableItemsView, providing a view on this table's items, as 2-tuples of (header, data). Use axis='row' for (row_header, row_data)

• clear –

  Clear all table data and headers.

• to_dataframe –

  Returns a pandas dataframe representation of this table. (requires pandas)

• to_dict –

  Return one of many different dict-like representations of table and header data. See docstring of :meth:to_dict for details.

Events

changed Emitted whenever a cell in the table changes. The value will have a dict of information regarding the cell that changed: {'data': x, 'row': int, 'column': int, 'column_header': str, 'row_header': str} CURRENTLY: only emitted on changes in the GUI. not programmatic changes.

column_headers: tuple property writable

Return column headers.

data: DataView property writable

Return DataView object for this table.

row_headers: tuple property writable

Return row headers.

shape: tuple[int, int] property

Return shape of table widget (rows, cols).

size: int property

Return shape of table widget (rows, cols).

value: dict[TblKey, Collection] property writable

Return dict with current data, index, and columns of the widget.

__delitem__(key: TblKey) -> None

Delete a column from the table.

__getitem__(key: TblKey) -> list

Get a column from the table.

__hash__() -> int

Make table hashable.

__iter__() -> Iterator

Yield column headers.

__len__() -> int

Return number of columns.

__new__(value: TableData | None = None, *, index: Collection | None = None, columns: Collection | None = None, **kwargs: Any) -> Table

Just for the signature.

__repr__() -> str

Return string repr.

__setitem__(key: TblKey, v: Collection) -> None

Set a column in the table. If k doesn't exist, make a new column.

clear() -> None

Clear the table.

delete_row(*, index: int | Sequence[int] | None = None, header: Any | Sequence[Any] | None = None) -> None

Delete row(s) by index or header.

Parameters:

• index (int or Sequence[int], default: None ) –

  Index or indices of row(s) to delete.

• header (Any or Sequence[Any], default: None ) –

  Header or headers of row(s) to delete.

items(axis: str = 'column') -> TableItemsView[TblKey, list]

Return a set-like object providing a view on this table's items.

keys(axis: str = 'column') -> HeadersView[TblKey]

Return a set-like object providing a view on this table's headers.

to_dataframe() -> pandas.DataFrame

Convert TableData to dataframe.

to_dict(orient: str = 'dict') -> list | dict

Convert the Table to a dictionary.

The type of the key-value pairs can be customized with the parameters (see below).

Parameters:

• orient (str {'dict', 'list', 'series', 'split', 'records', 'index'}, default: 'dict' ) –

  Determines the type of the values of the dictionary.

  • 'dict' (default) : dict like {column -> {index -> value}}
  • 'list' : dict like {column -> [values]}
  • 'split' : dict like
  • 'records' : list like [{column -> value}, ... , {column -> value}]
  • 'index' : dict like {index -> {column -> value}}
  • 'series' : dict like {column -> Series(values)}