Quickly annotate/label your data using jupyter widgets and pandas.
Project description
Classy Pandas
Quickly annotate/label your data using jupyter widgets and pandas.
Sometimes you have a dataset that you need to label before training your classification models or whatever. If you are already using jupyter and pandas why not do that using some ipywidgets?
Prerequisites
What things you need to install the software and how to install them
pip install pandas
pip install jupyter
pip install ipywidgets
If you are using jupyter lab you will also need to install ipywidgets extension: https://ipywidgets.readthedocs.io/en/latest/user_install.html
Installing
Once you have the above installed simply run:
pip install classypandas
Examples
You can then run the examples in the demo folder in this repository to start labelling! Since the content is displayed as html you can define your column as an html string and have it presented in the screen anyway you want it.
Code:
import pandas as pd
from classypandas import core
df = pd.read_csv('demo.csv')
labels = ['text', 'image', 'other']
classy = core.Classy(df, 'html', 'label', labels)
classy.display()
Preview:
You can then, at any time check your progress:
License
This project is licensed under the MIT License - see the LICENSE.md file for details
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for classypandas-0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 34f951ce04e74ef214232e7bb240e2c60ab1d86f6eb6ec95f552058e3b177df8 |
|
MD5 | 83174cfb1b41fa7e183747bd9cdba539 |
|
BLAKE2b-256 | 35609cc700b9daa3d2cd77e2acefd4824189d307284e172f733bc970febe9d11 |