Metadata-Version: 2.1
Name: autodatapre
Version: 0.1.10
Summary: The package of Auto-DP ( Automated System for Data Preparation).
Home-page: https://gitee.com/zyyyyyyyyyyyyyyyyyyyyy/auto-dp
Author: 2109835660
Author-email: 2109835660@qq.com
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.7.16
Description-Content-Type: text/markdown
Requires-Dist: torch ==1.13.1
Requires-Dist: pandas ==1.3.5
Requires-Dist: pickleshare ==0.7.5
Requires-Dist: numpy ==1.21.6
Requires-Dist: matplotlib ==3.5.3
Requires-Dist: ipywidgets ==8.1.1
Requires-Dist: scikit-learn ==1.0.2
Requires-Dist: jellyfish ==0.9.0
Requires-Dist: py-stringmatching ==0.4.3
Requires-Dist: py-stringsimjoin ==0.1.0
Requires-Dist: impyute ==0.0.8
Requires-Dist: scipy ==1.7.3
Requires-Dist: seaborn ==0.12.2
Requires-Dist: statsmodels ==0.13.5


# autodatapre

#### Project description
Automated System for Efficient Generation of Data Preparation Pipeline


#### Quick Start

1.  Before running the code, please make sure your Python version is 3.10. 
2.  pip install autodatapre

#### Run Example

1.  AutoDP.testFunction() provide two examples
2.  datasetName=csv_path
    datasetTarget = ''
    runTime = 10
    df = pd.read_csv(datasetName, sep=',', encoding='ISO-8859-1')
    detailResult, preparedDataset = Classifier(df, datasetName, datasetTarget, runTime)
    EnhancedFunction(df, preparedDataset, detailResult, taskType="CLA")
3.  datasetName=csv_path
    datasetTarget = ''
    df = pd.read_csv(datasetName, sep=',', encoding='ISO-8859-1')
    detailResult, preparedDataset = Regressor(df, datasetName, datasetTarget, runTime)
    EnhancedFunction(df, preparedDataset, detailResult, taskType="CLA")
