Metadata-Version: 2.1
Name: datagrid
Version: 1.0.4
Summary: Tool for exploring columnar data, including multimedia
Home-page: https://github.com/dsblank/datagrid
Author: DataGrid Development Team
License: MIT License
Keywords: data science,python,machine learning
Platform: Linux
Platform: Mac OS X
Platform: Windows
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Framework :: Jupyter
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: Pillow
Requires-Dist: astor
Requires-Dist: click
Requires-Dist: flask>=2.2
Requires-Dist: flask-caching
Requires-Dist: marko
Requires-Dist: matplotlib
Requires-Dist: nodejs-bin==16.15.1a4
Requires-Dist: numpy
Requires-Dist: psutil
Requires-Dist: pyngrok
Requires-Dist: requests
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: waitress

# datagrid

Create a datagrid of mixed-media items, and log to comet.com.

## Installation

```
pip install datagrid
```

## Example

```python
from comet_ml import start
from datagrid import DataGrid, Image
import random
from PIL import Image as PImage
import requests

experiment = start(project_name="datagrids")

dg = DataGrid(columns=["Image", "Score"])
url = "https://picsum.photos/200/300"
for i in range(100):
    im = PImage.open(requests.get(url, stream=True).raw)
    dg.append([Image(im), random.random()])

dg.log(experiment)
experiment.end()
```

## Visualization

Log into comet.com to see results.

![image](https://github.com/user-attachments/assets/8ef86f1e-2a34-4b36-82d7-fca2929ebc38)
