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Pandas DataFrames and Series as interactive datatables!
Install the package with
pip install itables
Activate the interactive mode for all series and dataframes with
from itables import init_notebook_mode
init_notebook_mode(all_interactive=True)or use itables.show to show just one Series or DataFrame as an interactive table.
Since itables==1.0.0, the jquery and datatables.net libraries and CSS are injected in the notebook when you execute init_notebook_mode with its default argument connected=False. Thanks to this the interactive tables will work even without a connection to the internet.
If you prefer to load the libraries dynamically (and keep the notebook lighter), use connected=True when you execute init_notebook_mode.
Read more about itables and advanced use cases in the documentation.
In particular, the show method let you pass custom parameters to datatables.net's DataTable()'s constructor - see the advanced parameters examples.
itables has been tested in the following editors:
You can run our examples notebooks directly on , without having to install anything on your side.
If the table just says "Loading...", then maybe
Please note that if you change the value of the connected argument in the init_notebook_mode cell, you will need to re-execute all the cells that display interactive tables.
If the above does not help, please check out the ChangeLog and decide whether you should upgrade itables.
When the data in a table is larger than maxBytes, which is equal to 64KB by default, itables will display only a subset of the table - one that fits into maxBytes. If you wish, you can deactivate the limit with maxBytes=0, change the value of maxBytes, or similarly set a limit on the number of rows (maxRows, defaults to 0) or columns (maxColumns, defaults to pd.get_option('display.max_columns')).
Note that datatables support server-side processing. At a later stage we may implement support for larger tables using this feature.
from itables.sample_dfs import get_indicators
import itables.options as opt
opt.lengthMenu = [2, 5, 10, 20, 50, 100, 200, 500]
opt.maxBytes = 10000
df = get_indicators()
df.values.nbytes
df
To show the table in full, we can modify the value of maxBytes either locally:
show(df, maxBytes=0)
or globally:
opt.maxBytes = 2 ** 20
df
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