Numeric Python
list - collection of different type of elements
array - collection of similar type of elements
!pip install numpy
Requirement already satisfied: numpy in c:\\\\users\\\\himan\\\\anaconda3\\\\lib\\\\site-packages (1.21.5)
import numpy as np
# help(np.array)
np.array?
v = np.array([1,2,3,4])
v
array([1, 2, 3, 4])
print(v)
[1 2 3 4]
print(type(v))
<class 'numpy.ndarray'>
v = np.array([[1],[2],[3]])
v
array([[1],
[2],
[3]])
matrix = np.array([[1,2,3], [4,5,6],[7,8,9]])
matrix
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
print(matrix)
[[1 2 3]
[4 5 6]
[7 8 9]]
0th dimension ---> .
1st dimension ---> .______.
2nd dimension ---> .___|___.
3rd dimension ---> .___|___.
/
4th dimension ?
.
.
.
n dimension
# -5 -4 -3 -2 -1
v = np.array([11,12,13,14,15,16,17])
# 0 1 2 3 4 5 6
print(v[0])
11
v[:] # v[start : end]
array([11, 12, 13, 14, 15, 16, 17])
v[3:6]
array([14, 15, 16])
v[1:3]
array([12, 13])
v[-1]
17
# -5 -4 -3 -2 -1
v = np.array([11,12,13,14,15,16,17])
# 0 1 2 3 4 5 6
print(v[-4:-1])
[14 15 16]
matrix = np.array([[1,2,3], [4,5,6],[7,8,9]])
matrix
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
matrix[0,0] # matrix[rows , columns]
1
matrix[1,1]
5
matrix[2,1]
8
print(matrix)
[[1 2 3]
[4 5 6]
[7 8 9]]
matrix[:,1:2]
array([[2],
[5],
[8]])
matrix[:,2:3]
array([[3],
[6],
[9]])
print(matrix)
[[1 2 3]
[4 5 6]
[7 8 9]]
matrix[0:3, 0:3]
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
matrix[-3:-1, -3:-2]
array([[1],
[4]])
matrix = np.array([[1,2,3], [4,5,6],[7,8,9], [1,2,3]])
matrix
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9],
[1, 2, 3]])
matrix.shape
(4, 3)
matrix.size
12
matrix.ndim
2
matrix = np.array([[1,2,3], [4,5,6],[7,8,9]])
matrix
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
print(np.max(matrix))
9
print(np.min(matrix))
1
print(np.max(matrix, axis = 0)) # column
[7 8 9]
print(np.max(matrix, axis = 1)) # rows
[3 6 9]
np.max(matrix, axis = 1)[0]
3
matrix = np.array([[1,2,3], [4,5,6],[7,8,9]])
matrix
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
print(np.mean(matrix))
5.0
print(np.std(matrix))
2.581988897471611
print(np.var(matrix))
6.666666666666667
matrix = np.array([[1,2,3], [4,5,6],[7,8,9]])
matrix
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
print(matrix.reshape(9))
[1 2 3 4 5 6 7 8 9]
print(matrix.reshape(9,1))
[[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]]
print(matrix.reshape(9,2))
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
Input In [49], in <cell line: 1>()
----> 1 print(matrix.reshape(9,2))
ValueError: cannot reshape array of size 9 into shape (9,2)
print(matrix.reshape(1,-1)) # possible number of columns
[[1 2 3 4 5 6 7 8 9]]
print(matrix.flatten())
[1 2 3 4 5 6 7 8 9]
What is the real world example of linear algebra?
matrix = np.array([[1,2,3], [4,5,6],[7,8,9]])
matrix
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
print(matrix.T)
[[1 4 7]
[2 5 8]
[3 6 9]]