Skip to main content

Get clean datasets from DataHerb to boost your data science and data analysis projects

Project description


Markdownify
The Python Package for DataHerb

A DataHerb Core Service to Create and Load Datasets.

Install

pip install dataherb

Usage

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.

dataherb create

Understanding DataHerb

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.

DataHerb Workflow

This repository is being used for listing of datasets (Listings in DataHerb flora repository).

How to Add Your Dataset

A Complete Tutorals

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.

Development

  1. Create a conda environment.
  2. Install requirements: pip install -r requirements.txt

Documentation

The documentation for this package is located at docs.

HISTORY.rst is used to list changes of the package.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dataherb-0.0.2.tar.gz (9.9 kB view details)

Uploaded Source

Built Distribution

dataherb-0.0.2-py3-none-any.whl (12.5 kB view details)

Uploaded Python 3

File details

Details for the file dataherb-0.0.2.tar.gz.

File metadata

  • Download URL: dataherb-0.0.2.tar.gz
  • Upload date:
  • Size: 9.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.2.0.post20200210 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.8.1

File hashes

Hashes for dataherb-0.0.2.tar.gz
Algorithm Hash digest
SHA256 3d8bfdd19805197fee45065477452d3d6a45187a3f14aada26ab258c9973ca36
MD5 35876c32ae38364c4221ad31987313dc
BLAKE2b-256 10f12a33ebd5619325770bccc44f6a4f49d726e8871762d9f03ae2a4dd938528

See more details on using hashes here.

File details

Details for the file dataherb-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: dataherb-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 12.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.2.0.post20200210 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.8.1

File hashes

Hashes for dataherb-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 e5f2c66c1a81b8f3e4f41d29cbdcb92a1add757e59d5102b56990d6f76afdb98
MD5 22ebb49a27a58603ca9ba0ef34c95ad5
BLAKE2b-256 16e5b44a160882f66736f860fd03f6263cfbe7e00db10a643ad588115c144ad3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page