Table#
Download this notebook from GitHub (right-click to download).
import hvplot.pandas # noqa
table allows the creation of a holoviews Table element with all the options available on that. It can be very useful especially when paired with other visualizations.
from bokeh.sampledata.autompg import autompg_clean as df
df.head()
| mpg | cyl | displ | hp | weight | accel | yr | origin | name | mfr | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 18.0 | 8 | 307.0 | 130 | 3504 | 12.0 | 70 | North America | chevrolet chevelle malibu | chevrolet |
| 1 | 15.0 | 8 | 350.0 | 165 | 3693 | 11.5 | 70 | North America | buick skylark 320 | buick |
| 2 | 18.0 | 8 | 318.0 | 150 | 3436 | 11.0 | 70 | North America | plymouth satellite | plymouth |
| 3 | 16.0 | 8 | 304.0 | 150 | 3433 | 12.0 | 70 | North America | amc rebel sst | amc |
| 4 | 17.0 | 8 | 302.0 | 140 | 3449 | 10.5 | 70 | North America | ford torino | ford |
df.hvplot.table(columns=['origin', 'name', 'yr'], sortable=True, selectable=True)
Click on the header to sort on the values in a column and on a row to select that column.
This web page was generated from a Jupyter notebook and not all interactivity will work on this website. Right click to download and run locally for full Python-backed interactivity.
Download this notebook from GitHub (right-click to download).