Widget

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_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])
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