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https://github.com/finos/ipyregulartable

High performance, editable, stylable datagrids in jupyter and jupyterlab
https://github.com/finos/ipyregulartable

data-table data-visualization dataframe datagrid ipywidgets javascript jupyter jupyter-notebook jupyterlab jupyterlab-extension notebook python table typescript

Last synced: about 2 months ago
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High performance, editable, stylable datagrids in jupyter and jupyterlab

Host: GitHub
URL: https://github.com/finos/ipyregulartable
Owner: finos
License: apache-2.0
Created: 2020-06-15T21:45:08.000Z (about 4 years ago)
Default Branch: main
Last Pushed: 2024-02-05T14:45:34.000Z (5 months ago)
Last Synced: 2024-04-13T21:00:34.766Z (3 months ago)
Topics: data-table, data-visualization, dataframe, datagrid, ipywidgets, javascript, jupyter, jupyter-notebook, jupyterlab, jupyterlab-extension, notebook, python, table, typescript
Language: JavaScript
Homepage:
Size: 7.43 MB
Stars: 99
Watchers: 8
Forks: 14
Open Issues: 11
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
- Authors: AUTHORS

Lists

awesome-jupyter - ipyregulartable - High performance, editable, stylable datagrids in Jupyter. (Tables)
best-of-jupyter - GitHub - 37% open · ⏱️ 05.02.2024): (Interactive Widgets & Visualization)

README

        
























# 

An [ipywidgets](https://github.com/jupyter-widgets/ipywidgets) wrapper of [regular-table](https://github.com/finos/regular-table) for Jupyter.

## Examples

### Two Billion Rows

[Notebook](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/examples/two_billion.ipynb)

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/twobillion.gif)

### Click Events

[Notebook](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/examples/click_events.ipynb)

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/click_events.gif)

### Edit Events

[Notebook](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/examples/edit_events.ipynb)

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/edit_events.gif)

### Styling

[Notebook](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/examples/styling.ipynb)

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/style.gif)

### Pandas Data Model

For interactive/streaming sorting/pivoting/aggregation, take a look at [Perspective](https://github.com/finos/perspective), *Streaming pivot visualization via WebAssembly*, which also leverages [`regular-table`](https://github.com/finos/regular-table).

[Notebook](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/examples/pandas.ipynb)

#### Series

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/pd_series.png)

#### DataFrame

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/pd_df.png)

#### DataFrame - Row Pivots

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/pd_rpivot.png)

#### DataFrame - Column Pivots

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/pd_cpivot.png)

#### DataFrame - Pivot Table

![](https://raw.githubusercontent.com/finos/ipyregulartable/main/docs/img/pd_pt.png)

## Installation

### PyPI

`ipyregulartable` is available on [PyPI](https://pypi.org/project/ipyregulartable/):

```bash

pip install ipyregulartable

```

### Conda

`ipyregulartable` is also available on [conda-forge](https://github.com/conda-forge/ipyregulartable-feedstock):

```bash

conda install -c conda-forge ipyregulartable

```

### Jupyter Server/JupyterLab Extension

```bash

 jupyter labextension install ipyregulartable

 jupyter serverextension enable --py ipyregulartable

```

If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable

the nbextension:

```bash

jupyter nbextension enable --py [--sys-prefix|--user|--system] ipyregulartable

```

## Data Model

It is very easy to construct a custom data model. Just implement the abstract methods on the base `DataModel` class.

```python

class DataModel(with_metaclass(ABCMeta)):

    @abstractmethod

    def editable(self, x, y):

        '''Given an (x,y) coordinate, return if its editable or not'''

    @abstractmethod

    def rows(self):

        '''return total number of rows'''

    @abstractmethod

    def columns(self):

        '''return total number of columns'''

    @abstractmethod

    def dataslice(self, x0, y0, x1, y1):

        '''get slice of data from (x0, y0) to (x1, y1) inclusive'''

```

Any `DataModel` object can be provided as the argument to `RegularTableWidget`. Note that `regular-table` may make probing calls of the form (0, 0, 0, 0) to assess data limits. 

## Development

See [CONTRIBUTING.md](./CONTRIBUTING.md) for guidelines.

## License

This software is licensed under the Apache 2.0 license. See the

[LICENSE](LICENSE) and [AUTHORS](AUTHORS) files for details.