## normscalers
A package for data normalization including the methods of *MinMaxScaler*, *MaxAbsScaler*, *RobustScaler*, *StandardScaler* and *Normalizer* in Scikit-learning, and *DecimalScaler*. The package can automatically detect the one-hot encoded variables and skip them to be normalized.
## Install
```python
pip install normscaler
```
## use
### (1) import one or more scalers by their names
- MinMaxScaler
- MaxAbsScaler
- RobustScaler
- StandardScaler
- Normalizer
- DecimalScaler
For example, import DecimalScaler by
```python
from normascaler.scaler import DecimalScaler
```
### (2) Use Decimal scaling method
```python
X_train_scaled, X_train_scaled = DecimalScaler(X_train, X-test)
```
### (3) Display the normalized X_train data in Pandas DataFrame
```python
X_train_scaled
```
### (4) Display the normalized X_test data in Pandas DataFrame
```python
X_test_scaled
```
## Documentation
Examples of a Jupyter note in GitHub: https://github.com/shoukewei/normscaler/blob/main/docs/examples.ipynb
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"description": "## normscalers\n\nA package for data normalization including the methods of *MinMaxScaler*, *MaxAbsScaler*, *RobustScaler*, *StandardScaler* and *Normalizer* in Scikit-learning, and *DecimalScaler*. The package can automatically detect the one-hot encoded variables and skip them to be normalized.\n\n## Install \n```python\npip install normscaler\n```\n## use\n\n### (1) import one or more scalers by their names\n\n- MinMaxScaler\n- MaxAbsScaler\n- RobustScaler\n- StandardScaler\n- Normalizer\n- DecimalScaler\n\nFor example, import DecimalScaler by\n```python\nfrom normascaler.scaler import DecimalScaler\n```\n### (2) Use Decimal scaling method\n```python\nX_train_scaled, X_train_scaled = DecimalScaler(X_train, X-test)\n```\n### (3) Display the normalized X_train data in Pandas DataFrame\n```python\nX_train_scaled\n```\n### (4) Display the normalized X_test data in Pandas DataFrame\n```python\nX_test_scaled\n```\n ## Documentation\n Examples of a Jupyter note in GitHub: https://github.com/shoukewei/normscaler/blob/main/docs/examples.ipynb\n",
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