python array(nump) for 9021 quiz 6

import numpy
There are 3 ways to import numpy
1)import numpy
2)from numpy import *
3)import numpy as np
definition of an array

#Definition of an array
import numpy as np
grid = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16],[17,18,19,20]])
print(grid)
#output:
[[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]
 [13 14 15 16]
 [17 18 19 20]]

Find the elements
the first column

print(grid[:,0])
#output:
[ 1  5  9 13 17]

the first row

print(grid[0,:])
#output:
[1 2 3 4]

the second row and column

print(grid[1,:])
print(grid[:,1])
#output:
[5 6 7 8]
[ 2  6 10 14 18]

from a to b column
X[:, a:b+1]
zeros
numpy.zeros(shape, dtype = None, order = ‘C’) : Return a new array of given shape and type, with zeros.
shape : integer or sequence of integers dtype : [optional, float(byDeafult)] Data type of returned array. order : C_contiguous or F_contiguous C-contiguous order in memory(last index varies the fastest) C order means that operating row-rise on the array will be slightly quicker FORTRAN-contiguous order in memory (first index varies the fastest). F order means that column-wise operations will be faster.

array_zero = np.zeros([10, 9], dtype=np.float)
print(array_zero)
#output: 10 rows, 9 columns
[[0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0.]]