Widget

The ITable widget depends on AnyWidget - a great widget development framework! You can install it with

pip install itables[widget] 

The ITable class accepts the same options as the show method, but the df argument is optional.

from itables.sample_pandas_dfs import get_dict_of_test_dfs from itables.widget import ITable df = get_dict_of_test_dfs()["int_float_str"] table = ITable(df, selected_rows=[0, 2, 5], select=True) table 

Tip

The table shown above does not reflect the initial row selection. This is because the ITable widget was updated with more row selection commands, see below.

The selected_rows traits

The selected_rows attribute of the ITable object provides a view on the rows that have been selected in the table (remember to pass select=True to activate the row selection). You can use it to either retrieve or change the current row selection:

table.selected_rows 

[0, 2, 5] 

table.selected_rows = [3, 4] 

The df property

Use it to retrieve the table data:

table.df.iloc[table.selected_rows] 

	int	float	str
3	3	4.848485	d
4	4	4.797980	e

or to update it

table.df = df.head(6) 

Tip

ITable raises an IndexError if the selected_rows are not consistent with the data. If you need to update both simultaneously, use table.update(df, selected_rows=...), see below.

The caption, style and classes traits

You can update these traits from Python, e.g.

table.caption = "numbers and strings" 

The update method

Last but not least, you can update the ITable arguments simultaneously using the update method:

table.update(df.head(20), selected_rows=[7, 8]) 

Using HTML

An alternative to the widget, if you only want to display the table, is the show function. Below is an example in which we use show to display a different table depending on the value of a drop-down component:

import ipywidgets as widgets from itables import show from itables.sample_dfs import get_dict_of_test_dfs def use_show_in_interactive_output(table_name: str): show( sample_dfs[table_name], caption=table_name, ) sample_dfs = get_dict_of_test_dfs() table_selector = widgets.Dropdown(options=sample_dfs.keys(), value="int_float_str") out = widgets.interactive_output( use_show_in_interactive_output, {"table_name": table_selector} ) widgets.VBox([table_selector, out])