navinbarnwal / normalization

This library takes the filename and column as a parameter and return the min_max normalization, zscore normalization, decimal normalization.. Set multiple column as parameter as the requirement. example:- normalization.required_method('__filename__, column_name1, column_name2,....') normalization.min_max_nor('iris.csv', 'sepalwidth', 'sepallength') normalization.zscore_nor('iris.csv', 'sepalwidth') normalization.decimal_nor('iris.csv', 'sepalwidth')

Normalization

Normalization is a data mining technique of data transformation. This package involves 3 methods which can easily be used just by abiding the filename and column name as the parameters, usage example is described at the later section of this description file. The functions included in this library are as follows.

• Min_max_nor
• zscore_nor
• decimal_nor

Example: -

• normalization.required_method('filename, column_name1 , column_name2 ,....')
• normalization.min_max_nor('iris.csv', 'sepalwidth', 'sepallength')
• normalization.zscore_nor('iris.csv', 'sepalwidth')
• normalization.decimal_nor('iris.csv', 'sepalwidth')

Install Dependencies

Normalization uses a some of open source library to work properly:

      1. numpy
      2. array
      3. random
      4. statistics
      5. pandas

And of course Normalization itself is open source with a [MIT Lisence] on GitHub.

Development

Want to contribute? Great!

Normalization uses simple math for fast output. Make a change in your file and instantaneously see your updates!