MLData 2.0.0

MLData is used to clean data before machine learning process!

#MLData
MLData, is a project to clean and normalize data for machine learning process.


## How to install
```pip install mldata```




## Usage Example
Usage Example:
```
from mldata import Processor
new_file_path = "outputs/new.csv"
processor = Processor("resource/raw_dataset.csv", target_column="APPROVE/NOT", exclude_column_list=["id"],
category_list=["Work Class", "FnlWgt", "Education", "Maried Status", "Occupation",
"Relationship", "Race", "Gender", "Native Country", "Flag"],
invalid_values=["?", "", "null", None],
positive_tag=1)
processor.normalize()
processor.save_to_file(new_file_path)
```


## API Description
1, Init function
```
Processor(csv_file_path, target_column, exclude_column_list=None, category_list=None, positive_tag=1,
csv_header=0, invalid_values=None)

```
Parameters:
csv_file_path: The origin csv file path
target_column: The column name of the target
exclude_column_list: Columns no need to normalize
category_list: A column name list which are category based columns
positive_tag: The positive tag for the target column value, default value is 1
invalid_values: values in csv not valid, such as "?", "", "null", None

2, Norm the list
```buildoutcfg
Processor.normalize()
```
This function is used to do norm to the csv file.


3, Save result to csv file.
```buildoutcfg
Processor.save_to_file(new_file_name)
```
This function is used to save normalized output to csv file.
Parameters:
new_file_name: The new file name to save the normalized data