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:
```
name: your_dataset_name
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.
*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
```
from dataset_manager import DatasetManager
manager = DatasetManager(dataset_path)
manager.list_datasets() ## return a List with all datasets from dataset path
```
## Get one Dataset
```
from dataset_manager import DatasetManager
manager = DatasetManager(dataset_path)
manager.get_dataset(name) ## Get dataset as Pandas DataFrame
```
Manage and automatize your datasets for your project with YAML files.
Create a file *name.yaml* with content in your dataset directory:
```
name: your_dataset_name
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.
*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
```
from dataset_manager import DatasetManager
manager = DatasetManager(dataset_path)
manager.list_datasets() ## return a List with all datasets from dataset path
```
## Get one Dataset
```
from dataset_manager import DatasetManager
manager = DatasetManager(dataset_path)
manager.get_dataset(name) ## Get dataset as Pandas DataFrame
```
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