Row selection#
The select extension let you select rows (or cells). When you do so, only the selected rows are exported
from itables import init_notebook_mode, show
init_notebook_mode()
Show code cell source
import string
import numpy as np
import pandas as pd
from itables.sample_dfs import get_countries
df = get_countries(html=False)
# Add columns for the searchPanes demo
df["climate_zone"] = np.where(
df["latitude"].abs() < 23.43615,
"Tropical",
np.where(
df["latitude"].abs() < 35,
"Sub-tropical",
# Artic circle is 66.563861 but there is no capital there => using 64
np.where(df["latitude"].abs() < 64, "Temperate", "Frigid"),
),
)
df["hemisphere"] = np.where(df["latitude"] > 0, "North", "South")
wide_df = pd.DataFrame(
{
letter: np.random.normal(size=100)
for letter in string.ascii_lowercase + string.ascii_uppercase
}
)
show(
df,
select=True,
selected_rows=[2, 4, 5],
buttons=["copyHtml5", "csvHtml5", "excelHtml5"],
)
region | country | capital | longitude | latitude | climate_zone | hemisphere | |
---|---|---|---|---|---|---|---|
code | |||||||
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Tip
It is possible to get the updated selected_rows
back in Python but for this you will have to use,
instead of show
, either
the
ITable
Jupyter Widgetthe
interactive_table
Streamlit componentor
DT
in a Shiny app.
Tip
The select
option accept multiple values, as documented here:
select=True
orselect="os"
let you select using single click, shift-click and ctrl-clickselect="single"
let you select a single rowselect="multi"
for single click selection of multiple rows,select="multi+shift"
, …
With select={"style": "os", "items": "cell"}
you can let the user select specific cells,
however cell selection is not taken into account when exporting the data.