semvec/pypi-packages huggingface dataset:
datamode 0.0.10
A tool to quickly build data science pipelines
License: Apache 2.0
Keywords: datamode,dataviz,data science,data transformation,feature engineering,data prep,data preparation,data munging,data visualization

# Datamode

[Quickstart](https://datamode.readthedocs.io/en/latest/quickstart.html) |
[Demo](http://bit.ly/datamode-live-demo) |
[Documentation](https://datamode.readthedocs.io/en/latest/) |
[Tutorial](https://datamode.readthedocs.io/en/latest/howtos/)

Datamode is a free, open source tool to quickly build data science pipelines. Our Python data visualization and transformation tool runs directly in Jupyter Notebook. We help you:

- Explore your data
- Reshape your data
- Deploy your data and models to production.

## How will this help me?

You're a data scientist. You deal with messy datasets all the time. You often build custom dataviz to explore your data.
You spend countless hours building and rechecking your data transformation code so that your model is accurate.

Also, you usually have to ask Engineering to deploy your model, or worse, maintain the infrastructure yourself.
When the pipeline or your model break down, you spend a lot of time diagnosing the problem with Engineering.

Datamode can help you with all of that.

## Try it out

Try a live demo: <http://bit.ly/datamode-live-demo>.

Or, go to [Quickstart](https://datamode.readthedocs.io/en/latest/quickstart.html) to try Datamode on your own data.


## Quickstart

You can install Datamode with pip. After that, run the two bottom lines in Jupyter Notebook.

From your command line:

```
pip install -U datamode
jupyter notebook
```

In your Jupyter notebook:

```
# Then run this code in Jupyter:
from datamode.interface import quickshow
quickshow('https://raw.githubusercontent.com/datamode/datasets/master/movies.csv')
```

Note: Datamode currently requires Python 3.6+ (64-bit). If you're having problems installing, see these pages:

- [Install using pip](https://datamode.readthedocs.io/en/latest/quickstart.html#pip)
- [Install using conda](https://datamode.readthedocs.io/en/latest/quickstart.html#conda)
- [Create a Python 3.7 virtualenv](https://datamode.readthedocs.io/en/latest/quickstart.html#virtualenv)
- [Check whether you're running 64-bit Python](https://datamode.readthedocs.io/en/latest/quickstart.html#64bit)


Explore the dataset a little with Datamode, then try it on your own data.

## Documentation

- [Main Datamode documentation](https://datamode.readthedocs.io/)
- [Quickstart](https://datamode.readthedocs.io/en/latest/quickstart.html)
- [Tutorial](https://datamode.readthedocs.io/en/latest/howtos/)
- [Transforms](https://datamode.readthedocs.io/en/latest/transforms.html)
- [Datasources](https://datamode.readthedocs.io/en/latest/datasources.html)
- [FAQ](https://datamode.readthedocs.io/en/latest/faq.html)


## Feedback / Contributing

If you're trying out Datamode, we'd love to hear from you! We're especially interested in what's working/not working for you, and what's missing that you really need.

Email us: feedback@datamode.com.

If you want to contribute, see [Contributing](https://datamode.readthedocs.io/en/latest/contributing.html).