<SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
 Numpy Overview
Scientific computing package for Python  
Arrays are the fundamental elements
Methods to manipulate and perform mathematical operations on arrays and matrices
Documentation
Step1:  Create Basic Arrays
Step2:  Array Indexing
Step3:  Array Attributes
Step4:  Array Methods
Step5:  Array Calcuations
Step6:  Array Arithmetic
numpy performs element-wise arithmetic
<ASSISTANT_TASK:>
Python Code:
import numpy as np
Explanation: Numpy Overview
Scientific computing package for Python  
Arrays are the fundamental elements
Methods to manipulate and perform mathematical operations on arrays and matrices
Documentation: https://docs.scipy.org/doc/
Import the Numpy Package
Must import numpy package before use
Import as 'np' and then call using np.<>
End of explanation
A = np.array([[1,2,3]]); print(A)
B = np.array([[1,2,3],[4,5,6],[7,8,9]]); print(B)
C = np.zeros((2,1)); print(C)
D = np.ones((1,3)); print(D)
E = np.random.randn(3,3); print(E)
Explanation: Create Basic Arrays
End of explanation
print(B)
B[0]  #first row
B[:,0] #first column
B[0,0]
B[2,2]
B[:,0]
Explanation: Array Indexing
End of explanation
print(B.dtype)
print(B.shape)
print(B.ndim)
print(B.size)
Explanation: Array Attributes
End of explanation
B.tolist()
B.T
B.reshape(1,9)
B.flatten()
A.nonzero()
Explanation: Array Methods
End of explanation
A
A.min()
A.max()
A.sum()
A.mean()
A.var()
A.std()
Explanation: Array Calcuations
End of explanation
A
A*A
A**A
A/A
A-A
A+A
A<B
A==B
Explanation: Array Arithmetic
numpy performs element-wise arithmetic
End of explanation
<END_TASK>