normalization in python code example
Example 1: normalize data python
>>> from sklearn import preprocessing
>>>
>>> data = [100, 10, 2, 32, 31, 949]
>>>
>>> preprocessing.normalize([data])
array([[0.10467389, 0.01046739, 0.00209348, 0.03349564, 0.03244891,0.99335519]])
Example 2: data normalization python
from sklearn import preprocessing
normalizer = preprocessing.Normalizer().fit(X_train)
X_train = normalizer.transform(X_train)
X_test = normalizer.transform(X_test)
Example 3: count_values in python
idx.value_counts()
Example 4: inheritence in python
class A:
def feature1(self):
print('Feature 1 in process...')
def feature2(self):
print('Feature 2 in process...')
class B:
def feature3(self):
print('Feature 3 in process...')
def feature4(self):
print ('Feature 4 in process...')
a1 = A()
a1.feature1()
a1.feature2()
a2 = B()
a2.feature3()
a2.feature4()
class A:
def feature1(self):
print('Feature 1 in process...')
def feature2(self):
print('Feature 2 in process...')
class B(A):
def feature3(self):
print('Feature 3 in process...')
def feature4(self):
print ('Feature 4 in process...')
a1 = A()
a1.feature1()
a1.feature2()
a2 = B()
a2.feature3()
a2.feature4()