Robofied

## Simple without stride and slice
print(y[1,2])

#[Output]:
#9

## Using ":" will go from start to end

## Without stride
print("This is without stride-:")

Robofied

import numpy as np

x = np.arange(10)
print(x[2:5])
print(x[2:5:2])

#[Output]:
#[2 3 4]
#[2 4]

Robofied

import numpy as np

##Let's first create 1-D array
x = np.arange(10)
print(x)
print(x[0])

#[Output]:
#[0 1 2 3 4 5 6 7 8 9]
#0

Robofied

""""It is almost similar to the last function arange we have discussed with the parameters but the only difference is, 
it doest not exlude the end value."""
x = np.linspace(1., 4., 5)
print(x)

#[Output]:
#[1.   1.75 2.5  3.25 4.  ]

Robofied

x = np.arange(10)
print(x)

#[Output]:
#[0 1 2 3 4 5 6 7 8 9]

##It will create an array from 2 to 10(as last value is excluded)
y = np.arange(2, 11, dtype=np.float)
print(y)

Robofied

import numpy as np

x = np.zeros((3, 3))

print(x)

#[Output]:
#[[0. 0. 0.]
# [0. 0. 0.]
# [0. 0. 0.]]

Robofied

import numpy as np

## Creating array using list
x = np.array([2,3,1,0])

print(x)

#[Output]:
#[2 3 1 0]

Robofied

import numpy as np
a = np.array([[1,2,3],[4,5,6],[7,8,9],[10,11,12]])

print(a)

#[Output]:
#[[ 1  2  3]
# [ 4  5  6]
# [ 7  8  9]
# [10 11 12]]

Robofied

## Creating a int8 type of array.
z = np.int8([-12,2,3])

## Printing the array.
print(z)

#[Output]:
#array([-12,   2,   3], dtype=int8)

## Creating an array with datatype -> uint.

Robofied

## importing numpy for creating numpy array.
import numpy as np

## Creating a normal integer array.
x = np.int_([1,2,4])

## Printing the created array.
x

#[Output]: