Dataset Manager

Manage and automatize your datasets for your project with YAML files high integrated with Pandas.

Current Support:

How it Works

This project create a file called identifier.yaml in your dataset directory with these fields:

source: https://raw.githubusercontent.com/pcsanwald/kaggle-titanic/master/train.csv

description: this dataset is a test dataset

format: csv

identifier: is the identifier for dataset reference is the file name with yaml extension.

source: is location from dataset.

description: describe your dataset to remember later.

format: pandas read format following read_<format> as described here: https://pandas.pydata.org/pandas-docs/stable/reference/io.html.

Each dataset is a YAML file inside dataset directory.

Installing

With pip just:

pip install dataset_manager

With conda:

conda install dataset_manager

Using

You can manage your datasets with a list of commands and integrated with Pandas.

List all Datasets

Return a List with all datasets from dataset path

from dataset_manager import DatasetManager

manager = DatasetManager(dataset_path)

manager.list_datasets()

Get one Dataset

Get dataset as Pandas DataFrame and accept Pandas read *args and **kwargs

from dataset_manager import DatasetManager

manager = DatasetManager(dataset_path)

manager.get_dataset(identifier, *args, **kwargs)

Create a Dataset

Create a Dataset inside dataset_path defined

from dataset_manager import DatasetManager

manager = DatasetManager(dataset_path)

manager.create_dataset(identifier, source, description, format_extension)

Remove a Dataset

Remove Dataset from dataset_path

from dataset_manager import DatasetManager

manager = DatasetManager(dataset_path)

manager.remove_dataset(identifier)

Contributing

Just make pull request and be happy!

Let's grow together ;)