What is the output of the following code?
import numpy as np a=np.array([1,2,3,5,8]) b=np.array([0,3,4,2,1]) c=a+b c=c*a print(c[2])
10
21
12
28
unlimited length
all private members must have leading and trailing underscores
Preferred Installer Program
None of the above
What will be output for the following code?
import numpy as npa = np.array([1,2,3,5,8])b = np.array([0,3,4,2,1])c = a + bc = c*aprint (c[2])
18
20
22
arr=np.float([1,2,3,4])
arr=np.array([1,2,3,4]).toFloat()
arr=np.array([1,2,3,4],dtype='float')
arr=np.farray([1,2,3,4])
numpy.array(list)
numpy.array(list, dtype=float)
Both a and b
What is a correct syntax to print the number 8 from the array below:
arr = np.array([[1,2,3,4,5], [6,7,8,9,10]])
print(arr[3,0])
print(arr[1,2])
print(arr[7,2])
None of The Above
What will be output for the following code ?
import numpy as np
ary=np.array([1,2,3,5,8])
ary=ary+1
print(ary[1])
0
1
2
3
What will be the output of the following ?
import numpy as npa = np.arange(5,1)print(a)
[ ]
[1 2 3 4 5]
[5 4 3 2 1]
[1 2 3 4]
make a matrix with first column 0
make a matrix with all elements 0
make a matrix with diagonal elements 0
All of the above
arr=np.array([1,2,3,4],dtype='f')
arr=np.array([1,2,3,4],dtype=float)
What will be the output of the following code?
import numpy as npa=np.array([1,2,3])print(a.ndim)
To make a Matrix with all diagonal element 0
To make a Matrix with first row 0
To make a Matrix with all elements 0
Numbering Python
Number In Python
Numerical Python
List
Array
Matrix
Set
import numpy as npa = np.array([[ 1,2,3,4], [5,6,7,8], [9,10,11,12]])print(a[2,2])
7
11
8
Mathematical and logical operations on arrays.
Fourier transforms and routines for shape manipulation.
Operations related to linear algebra.
ndarray
narray
nd_array
darray
import numpy as npa = np.array([[1, 2, 3],[0,1,4],[11,22,33]])print (a.size)
9
4
Number in Python
Number for Python
axes
degree
cordinate
points
Number of Rows and Column in array
Size of each items in array
Number of elements in array
Largest element of an array
What is the datatype of x ?
import numpy as npa=np.array([1,2,3,4])x=a.tolist()
int
array
tuple
list
import numpy as npa=np.array([2,4,1])b=a.copy()a[1]=3print(b)
[2 4 1]
[2 3 1]
[3 4 1]
[2 4 3]
89
[1,2,3,4]
[1,2,3],[3,4,5],[1,3,4]
[[2 3 5][ 4 5 6][4 5 6]]
What is the output of following code ?
a = np.array([[1,2,3],[4,5,6]])print(a.shape)
(2,3)
(3,2)
(1,1)
none of these
import numpy as npa=np.array([2,4,1])b=aa[1]=3print(b)
import numpy as npprint(np.maximum([2, 3, 4], [1, 5, 2]))
[1 5 2]
[1 5 4]
[2 3 4]
[2 5 4]
import numpy as nparr=np.array([1,2,3])print(arr.shape)
(3,)
(4,)
np.ndim(array_name)
array_name.ndim()
np.dim(array_name)
array_name.dim
Indexed
Sliced
Iterated
All of the mentioned above
np.array()
np.zeros()
np.empty()
import numpy as npa = np.array([1, 5, 4, 7, 8])a = a + 1print(a[1])
5
6
Which syntax would print the last 3 numbers from the array below:
arr = np.array([1,2,3,4,5,6,7])
print(arr[3:])
print(arr[3])
print(arr[:3])
print(arr[4:])
np.array([4,5,6])
np.create_array([4,5,6])
np.createArray([4,5,6])
np.numpyArray([4,5,6])
float
integer
string
boolean
What will be the output of the following Python code?
len(["hello",2, 4, 6])
Error
import numpy as npa=np.array([2,4,1])b=np.array([3,5])c=a+bprint(c)
[2 4 1 3 5 ]
[5 9 1]
15
ValueError
the shape is the number of rows
the shape is the number of columns
the shape is the number of element in each dimension
Total number of elements in array
import numpy as npa = np.array([1,2,3,5,8])b = np.array([0,1,5,4,2])c = a + bc = c*aprint (c[2])
24
None of these
import numpy as npa=np.array([[1,2,3],[0,1,4]])print (a.size)
Tuple
numpy.maximum()
numpy.arraymax()
numpy.amax()
numpy.big()
To make a Matrix with all element 0
Web development
Machine learning and scientific computing
Game development
Database management
It creates a new Python list.
It creates a NumPy array.
It performs element-wise addition.
It calculates the mean of an array.
NumPy arrays have contiguous memory location
They are more speedy to work with
They are more convenient to deal with
Indexing
Slicing
Reshaping
What is the output of the following code ?
import numpy as npy = np.array([[11, 12, 13, 14], [32, 33, 34, 35]])print(y.ndim)
import numpy as npa=np.array([2,3,4,5])print(a.dtype)
int32
Shape
both a) and b)
None of the above.