What will be the output of the following ?
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
import numpy as npa = np.array( [2, 3, 4, 5] )b = np.arange(4)print(a+b)
[2 3 4 5]
[3 4 5 6]
[1 2 3 4]
[2 4 6 8]
rank
dtype
shape
None of these
np.ndim(array_name)
array_name.ndim()
np.dim(array_name)
array_name.dim
What will be the output of the following Python code?
len(["hello",2, 4, 6])
Error
6
4
3
print(arr[1])
print(arr,0)
print(arr,1)
None of These
import numpy as npa=np.array([2,4])b=np.array([3,5])c=a*bprint(c)
[ 2 4 3 5]
[ 6 20]
[ 6 12 10 20]
26
ndarray
narray
nd_array
darray
import numpy as npprint(np.maximum([2, 3, 4], [1, 5, 2]))
[1 5 2]
[1 5 4]
[2 3 4]
[2 5 4]
What will be output for the following code ?
import numpy as npa = np.array([[1, 2, 3],[0,1,4],[11,22,33]])print (a.size)
1
9
change in shape of array
reshaping of array
get the shape of the array
All of above
What is a correct syntax to print the numbers [3, 4, 5] from the array below:
arr = np.array([1,2,3,4,5,6,7])
print(arr[2:4])
print(arr[2:5])
print(arr[2:6])
print(arr[3:6])
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
Numbering Python
Number in Python
Numerical Python
Number for Python
import numpy as npa = np.arange(5,1)print(a)
[ ]
[1 2 3 4 5]
[5 4 3 2 1]
what will be output for the following code?
import numpy as npa=np.array([1,2,3,5,8])print(a.ndim)
0
2
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)
Indexed
Sliced
Iterated
All of the mentioned above
np.array([4,5,6])
np.create_array([4,5,6])
np.createArray([4,5,6])
np.numpyArray([4,5,6])
NumPy arrays have contiguous memory location
They are more speedy to work with
They are more convenient to deal with
Indexing
Slicing
Reshaping
None of the above
numpy.maximum()
numpy.arraymax()
numpy.amax()
numpy.big()
What will be output for the following code?
import numpy as npary = np.array([1,2,3,5,8])ary = ary + 1print (ary[1])
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 is the output of the following code?
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
array_split()
split()
split_array()
hstack() and vstack()
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
21
22
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
shape, dtype, ndim
objects, type, list
objects, non vectorization
Unicode and shape
import numpy as np
ary=np.array([1,2,3,5,8])
ary=ary+1
print(ary[1])
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
12
28
Shape
Array
both a) and b)
None of the above.
What will be the output of the following code?
import numpy as npa=np.array([1,2,3])print(a.ndim)
numpy.array(list)
numpy.array(list, dtype=float)
Both a and b
Number of Rows and Column in array
Size of each items in array
Number of elements in array
Largest element of an array
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]
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
List
Matrix
Set
float
integer
string
boolean
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
arr=np.array([1,2,3,4],dtype='float')
arr=np.array([1,2,3,4],dtype='f')
arr=np.array([1,2,3,4],dtype=float)
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([[1,2,3],[0,1,4]])print (a.size)
5
import numpy as nparr=np.array([1,2,3])print(arr.shape)
(3,)
(4,)
arr=np.float([1,2,3,4])
arr=np.array([1,2,3,4]).toFloat()
arr=np.farray([1,2,3,4])
Guido van Rossum
Travis Oliphant
Wes McKinney
Jim Hugunin
import numpy as npa = np.arange(1,5,2)print(a)
[1 3 5]
[1 3]
[1,3]
[1,2,3,4,5]
import numpy as npa = np.array([1, 5, 4, 7, 8])a = a + 1print(a[1])
all_like
ones_like
one_alike
all of the mentioned