# Function for normalization
[docs]def standard(data, column, mean=None, std=None, return_param=False):
""" Performs standard normalization.
:param data: Data
:param column: Column to normalize
:param mean: Mean, computed if not specified
:param std: Standard deviation, computed if not specified
:param return_param: if True, mean and std are returned
:return: Normalized data
:rtype: autopandas.AutoData
"""
if not mean and not std:
mean = data[column].mean()
std = data[column].std()
data[column] = (data[column] - mean) / std
if return_param:
return data, (mean, std)
return data
[docs]def min_max(data, column, mini=None, maxi=None, return_param=False):
""" Performs min-max normalization.
:param data: Data
:param column: Column to normalize
:param mini: Minimum, computed if not specified
:param maxi: Maximum, computed if not specified
:param return_param: if True, mean and std are returned
:return: Normalized data
:rtype: autopandas.AutoData
"""
if not mini and not maxi:
mini = data[column].min()
maxi = data[column].max()
data[column] = (data[column] - mini) / (maxi - mini)
if return_param:
return data, (mini, maxi)
return data