Manage and automatize datasets for data science projects.
Project description
Dataset Manager
Manage and automatize your datasets for your project with YAML files.
Create a file name.yaml with content in your dataset directory:
src: https://raw.githubusercontent.com/pcsanwald/kaggle-titanic/master/train.csv
description: this dataset is a test dataset
format: csv
name: is the name for dataset reference is the file name with yaml extension.
src: 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.
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(name, *args, **kwargs)
Create a Dataset
Create a Dataset inside dataset_path defined
from dataset_manager import DatasetManager
manager = DatasetManager(dataset_path)
manager.create_dataset(name, src, description, format_extension)
Remove a Dataset
Remove Dataset from dataset_path
from dataset_manager import DatasetManager
manager = DatasetManager(dataset_path)
manager.remove_dataset(name)
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