|
1 | | -# dataherb-python |
| 1 | +<h1 align="center"> |
| 2 | + <br> |
| 3 | + <a href="https://dataherb.github.io"><img src="https://raw.githubusercontent.com/DataHerb/dataherb.github.io/master/assets/favicon/ms-icon-310x310.png" alt="Markdownify" width="200"></a> |
| 4 | + <br> |
| 5 | + The Python Package for DataHerb |
| 6 | + <br> |
| 7 | +</h1> |
| 8 | + |
| 9 | +<h4 align="center">A <a href="https://dataherb.github.io" target="_blank">DataHerb</a> Core Service to Create and Load Datasets.</h4> |
| 10 | + |
| 11 | +<p align="center"> |
| 12 | + |
| 13 | +</p> |
| 14 | + |
2 | 15 |
|
3 | | -The python toolkit for DataHerb datasets. |
4 | 16 |
|
5 | 17 | ## Install |
6 | 18 |
|
| 19 | +``` |
| 20 | +pip install dataherb |
| 21 | +``` |
| 22 | + |
| 23 | +## Usage |
| 24 | + |
| 25 | +### Load Data into DataFrame |
| 26 | + |
| 27 | +``` |
| 28 | +# Load the package |
| 29 | +from dataherb.flora import Flora |
| 30 | +
|
| 31 | +# Initialize Flora service |
| 32 | +# The Flora service holds all the dataset metadata |
| 33 | +dataherb = Flora() |
| 34 | +
|
| 35 | +# Search datasets with keyword(s) |
| 36 | +geo_datasets = dataherb.search("geo") |
| 37 | +print(geo_datasets) |
| 38 | +
|
| 39 | +# Get a specific file from a dataset and load as DataFrame |
| 40 | +tz_df = dataherb.herb( |
| 41 | + "geonames_timezone" |
| 42 | +).leaves.get( |
| 43 | + "dataset/geonames_timezone.csv" |
| 44 | +).data |
| 45 | +print(tz_df) |
| 46 | +
|
| 47 | +``` |
| 48 | + |
| 49 | + |
| 50 | +### Create Dataset Using Command Line Tool |
| 51 | + |
| 52 | +We provide a template for dataset creation. |
| 53 | + |
| 54 | +> Before creating a dataset, it is recommended that the user reads [the intro](#Understanding-DataHerb). |
| 55 | +
|
| 56 | +Use the following command line tool to create the metadata template. |
| 57 | +```bash |
| 58 | +dataherb create |
| 59 | +``` |
| 60 | + |
| 61 | +## Understanding DataHerb |
| 62 | + |
| 63 | + |
| 64 | +### What is DataHerb |
| 65 | + |
| 66 | +DataHerb is an open data initiative to make the access of open datasets easier. |
| 67 | + |
| 68 | +- A **DataHerb** or **Herb** is a dataset. A dataset comes with the data files, and the metadata of the data files. |
| 69 | +- A **DataHerb Leaf** or **Leaf** is a data file in the DataHerb. |
| 70 | +- A **Flora** is the combination of all the DataHerbs. |
| 71 | + |
| 72 | +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. |
| 73 | + |
| 74 | +### What is DataHerb Flora |
| 75 | + |
| 76 | +We desigined the following workflow to share and index datasets. |
| 77 | + |
| 78 | + |
| 79 | + |
| 80 | +This repository is being used for listing of datasets (Listings in DataHerb flora repository). |
| 81 | + |
| 82 | +### How to Add Your Dataset |
| 83 | + |
| 84 | +> [A Complete **Tutorals**](https://dataherb.github.io/add/) |
| 85 | +
|
| 86 | +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. |
| 87 | + |
| 88 | +The indexing part will be done by [GitHub Actions](https://github.com/DataHerb/dataherb-flora/actions). |
| 89 | + |
7 | 90 |
|
8 | 91 | ## Development |
9 | 92 |
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