Metadata-Version: 2.1
Name: itables
Version: 0.4.1
Summary: Interactive Tables in Jupyter
Home-page: https://github.com/mwouts/itables
Author: Marc Wouts
Author-email: marc.wouts@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Description-Content-Type: text/markdown
Requires-Dist: IPython
Requires-Dist: pandas

# Pandas DataFrames and Series as Interactive Tables

[![Pypi](https://img.shields.io/pypi/v/itables.svg)](https://pypi.python.org/pypi/itables)
![CI](https://github.com/mwouts/itables/workflows/CI/badge.svg)
[![codecov.io](https://codecov.io/github/mwouts/itables/coverage.svg?branch=main)](https://codecov.io/github/mwouts/itables?branch=main)
[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/mwouts/itables.svg)](https://lgtm.com/projects/g/mwouts/itables/context:python)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Notebook](https://img.shields.io/badge/Binder-Notebook-blue.svg)](https://mybinder.org/v2/gh/mwouts/itables/main?filepath=README.md)
[![Lab](https://img.shields.io/badge/Binder-JupyterLab-blue.svg)](https://mybinder.org/v2/gh/mwouts/itables/main?urlpath=lab/tree/README.md)
<a class="github-button" href="https://github.com/mwouts/itables" data-icon="octicon-star" data-show-count="true" aria-label="Star mwouts/itables on GitHub">Star</a>

Turn pandas DataFrames and Series into interactive [datatables](https://datatables.net) in your notebooks with `import itables.interactive`:

![](https://raw.githubusercontent.com/mwouts/itables/main/demo/itables.gif)

# Quick start

Install the package with

```
pip install itables
```

Activate the interactive mode for all series and dataframes with

```python
from itables import init_notebook_mode
init_notebook_mode(all_interactive=True)
```

```python
import world_bank_data as wb

df = wb.get_countries()
df
```

You don't see any table above? Please either open the [HTML export](https://mwouts.github.io/itables/) of this notebook, or run this README on [Binder](https://mybinder.org/v2/gh/mwouts/itables/main?urlpath=lab/tree/README.md)!


Or display just one series or dataframe as an interactive table with the `show` function.

```python
from itables import show

x = wb.get_series("SP.POP.TOTL", mrv=1, simplify_index=True)
show(x)
```

# Supported environments

`itables` has been tested in the following editors:
- Jupyter Notebook
- Jupyter Lab
- Jupyter nbconvert (i.e. the tables are still interactive in the HTML export of a notebook)
- Google Colab
- VS Code (for both Jupyter Notebooks and Python scripts)
- PyCharm (for Jupyter Notebooks)
- Nteract

# Advanced usage

## Row sorting

Select the order in which the row are sorted with the [datatables' `order`](https://datatables.net/reference/option/order) argument. By default, the rows are sorted according to the first column (`order = [[0, 'asc']]`).

If you want to deactivate the sorting, set `order = []`, either in the `show` method, or as a global option:

```python
import pandas as pd
import itables.options as opt

opt.order = []  # no sorting
pd.DataFrame({'a':[2,1]})
```


## Pagination

### How many rows per page

Select [how many entries](https://datatables.net/examples/advanced_init/length_menu.html) should appear at once in the table with either the `lengthMenu` argument of the `show` function, or with the global option `itables.options.lengthMenu`:

```python
import itables.options as opt

opt.lengthMenu = [2, 5, 10, 20, 50, 100, 200, 500]
df
```

### Show the table in full

Show the table in full with the [`paging` argument](https://datatables.net/reference/option/paging), either in the `show` method, or in the options:

```python
show(df.head(), paging=False)
```

### Scroll

If you prefer to replace the pagination with a [vertical scroll](https://datatables.net/examples/basic_init/scroll_y.html), use for instance

```python
show(df, scrollY="200px", scrollCollapse=True, paging=False)
```

## Table and cell style

Select how your table should look like with the `classes` argument of the `show` function, or by changing `itables.options.classes`. For the list of possible values, see [datatables' default style](https://datatables.net/manual/styling/classes) and [the style examples](https://datatables.net/examples/styling/).

```python
opt.classes = ["display", "nowrap"]
df
```

```python
opt.classes = ["display", "cell-border"]
df
```

## Float precision

Floats are rounded using `pd.options.display.float_format`. Please change that format according to your preference.

```python
import math
import pandas as pd

with pd.option_context("display.float_format", "{:,.2f}".format):
    show(pd.Series([i * math.pi for i in range(1, 6)]))
```

You may also choose to convert floating numbers to strings:

```python
with pd.option_context("display.float_format", "${:,.2f}".format):
    show(pd.Series([i * math.pi for i in range(1, 6)]))
```

## Advanced cell formatting

Datatables allows to set the cell or row style depending on the cell content, with either the [createdRow](https://datatables.net/reference/option/createdRow) or [createdCell](https://datatables.net/reference/option/columns.createdCell) callback. For instance, if we want the cells with negative numbers to be colored in red, we can use the `columnDefs.createdCell` argument as follows:

```python
show(
    pd.DataFrame([[-1, 2, -3, 4, -5], [6, -7, 8, -9, 10]], columns=list("abcde")),
    columnDefs=[
        {
            "targets": "_all",
            "createdCell": """function (td, cellData, rowData, row, col) {
      if ( cellData < 0 ) {
        $(td).css('color', 'red')
      }
    }""",
        }
    ],
    eval_functions=True,
)
```

## Column width

For tables that are larger than the notebook, the `columnDefs` argument allows to specify the desired width. If you wish you can also change the default in `itables.options`.

```python
show(x.to_frame().T, columnDefs=[{"width": "120px", "targets": "_all"}])
```

## Cell alignment

You can use the datatables.net [cell classes](https://datatables.net/manual/styling/classes#Cell-classes) like `dt-left`, `dt-center`, `dt-right` etc to set the cell alignment. Specify it for one table by using the `columnDefs` argument of `show`

```python
show(df, columnDefs=[{"className":"dt-center",  "targets": "_all"}])
```

or globally by setting `opt.columnDefs`:

```python
opt.columnDefs = [{"className":"dt-center", "targets": "_all"}]
df
```

```python
del opt.columnDefs
```

## HTML in cells

```python
import pandas as pd

show(
    pd.Series(
        [
            "<b>bold</b>",
            "<i>italic</i>",
            '<a href="https://github.com/mwouts/itables">link</a>',
        ],
        name="HTML",
    ),
    paging=False,
)
```

## Select rows

Not currently implemented. May be made available at a later stage using the [select](https://datatables.net/extensions/select/) extension for datatables.


## Copy, CSV, PDF and Excel buttons

Not currently implemented. May be made available at a later stage thanks to the [buttons](https://datatables.net/extensions/buttons/) extension for datatable.


## <a name="downsampling"></a> Downsampling

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](https://datatables.net/examples/data_sources/server_side). At a later stage we may implement support for larger tables using this feature.

```python
df = wb.get_indicators().head(500)
opt.maxBytes = 10000
df.values.nbytes
```

```python
df
```

To show the table in full, we can modify the value of `maxBytes` either locally:

```python
show(df, maxBytes=0)
```

or globally:

```python
opt.maxBytes = 2**20
df
```

# References

## DataTables

- DataTables is a plug-in for the jQuery Javascript library. It has a great [documentation](https://datatables.net/manual/), and a large set of [examples](https://datatables.net/examples/index).
- The R package [DT](https://rstudio.github.io/DT/) uses [datatables.net](https://datatables.net/) as the underlying library for both R notebooks and Shiny applications. In addition to the standard functionalities of the library (display, sort, filtering and row selection), RStudio seems to have implemented cell edition.

## Alternatives

ITables uses basic Javascript. It is not a Jupyter widget, which means that it does not allows you to **edit** the content of the dataframe.

If you are looking for Jupyter widgets, have a look at
- [QGrid](https://github.com/quantopian/qgrid) by Quantopian
- [IPyaggrid](https://dgothrek.gitlab.io/ipyaggrid/) by Louis Raison and Olivier Borderies
- [IPySheet](https://github.com/QuantStack/ipysheet) by QuantStack.

If you are looking for a table component that will fit in Dash applications, see [datatable by Dash](https://github.com/plotly/dash-table/).

Please also checkout [D-Tale](https://github.com/man-group/dtale) for exploring your Python DataFrames in the browser, using a local server.

<script async defer src="https://buttons.github.io/buttons.js"></script>


