Get clean datasets from DataHerb to boost your data science and data analysis projects
A DataHerb Core Service to Create and Load Datasets.
pip install dataherb
Load Data into DataFrame
# Load the package from dataherb.flora import Flora # Initialize Flora service # The Flora service holds all the dataset metadata dataherb = Flora() # Search datasets with keyword(s) geo_datasets = dataherb.search("geo") print(geo_datasets) # Get a specific file from a dataset and load as DataFrame tz_df = dataherb.herb( "geonames_timezone" ).leaves.get( "dataset/geonames_timezone.csv" ).data print(tz_df)
Create Dataset Using Command Line Tool
We provide a template for dataset creation.
Before creating a dataset, it is recommended that the user reads the intro.
Use the following command line tool to create the metadata template.
What is DataHerb
DataHerb is an open data initiative to make the access of open datasets easier.
- A DataHerb or Herb is a dataset. A dataset comes with the data files, and the metadata of the data files.
- A DataHerb Leaf or Leaf is a data file in the DataHerb.
- A Flora is the combination of all the DataHerbs.
In many data projects, finding the right datasets to enhance your data is one of the most time consuming part. DataHerb adds flavor to your data project.
What is DataHerb Flora
We desigined the following workflow to share and index datasets.
This repository is being used for listing of datasets (Listings in DataHerb flora repository).
How to Add Your Dataset
Simply create a
yml file in the
flora folder to link to your dataset repository. Your dataset repository should have a
.dataherb folder and a
metadata.yml file in it.
The indexing part will be done by GitHub Actions.
- Create a conda environment.
- Install requirements:
pip install -r requirements.txt
The documentation for this package is located at
HISTORY.rst is used to list changes of the package.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
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