np.ndim(array_name)
array_name.ndim()
np.dim(array_name)
array_name.dim
What will be the output?
import numpy as npaa=np.array([1,2,3])print(a*2)
[2 4 6]
[1 2 3 1 2 3]
[3 4 5]
Error
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
Web development
Machine learning and scientific computing
Game development
Database management
import numpy as npa = np.array([[1,2],[3,4]])print(a.shape)
(4,)
(2,2)
(2,1)
4
rank
dtype
shape
None of these
np.array()
np.zeros()
np.empty()
All of the above
List
Array
Matrix
Set
Numbering Python
Number In Python
Numerical Python
None of the above
from numpy import *
import numpy
import numpy as my_numpy
All of above
Mathematical and logical operations on arrays.
Fourier transforms and routines for shape manipulation.
Operations related to linear algebra.
Number of Rows and Column in array
Size of each items in array
Number of elements in array
Largest element of an array
Number in Python
Number for Python
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 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
What will be the output of the following ?
import numpy as nparr=np.array([1,2,3])print(arr.shape)
(3,)
Indexed
Sliced
Iterated
All of the mentioned above
numpy.array(list)
numpy.array(list, dtype=float)
Both a and b
A machine learning library
A web development framework
A numerical computing library in Python
A data visualization tool
import numpy as npa = np.array([[ 1,2,3,4], [5,6,7,8], [9,10,11,12]])print(a[2,2])
7
11
10
8
What will be the output of following Python code?
import numpy as npa = np.array([(10,20,30)])print(a.itemsize)
9
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
np.concatenate()
np.join()
np.array_join()
np.join_array()
range()
space()
arange()
linspace()
What will be the output of the following Python code?
len(["hello",2, 4, 6])
6
It creates a new Python list.
It creates a NumPy array.
It performs element-wise addition.
It calculates the mean of an array.
import numpy as npa = np.array([[1, 2, 3],[0,1,4],[11,22,33]])print (a.size)
import numpy as npa = np.array([1,2,3])b = np.array([4,5,6])print(a+b)
[5 7 9]
[1 2 3 4 5 6]
21
array_split()
split()
split_array()
hstack() and vstack()
Shape
both a) and b)
None of the above.
We can find the dimension of the array
Size of array
Operational activities on Matrix
None of the mentioned above
What will be output for the following code?
import numpy as npa=np.array([[1,2,3],[0,1,4]])print (a.size)
5
89
[1,2,3,4]
[1,2,3],[3,4,5],[1,3,4]
[[2 3 5][ 4 5 6][4 5 6]]
create()
list()
tuple()
array()
full
empty
init
unlimited length
all private members must have leading and trailing underscores
Preferred Installer Program
To make a Matrix with all element 0
To make a Matrix with all diagonal element 0
To make a Matrix with first row 0
all_like
ones_like
one_alike
all of the mentioned
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.arange(1,5,2)print(a)
[1 3 5]
[1 3]
[1,3]
[1,2,3,4,5]
How many values are generated?
import numpy as npprint(np.linspace(0, 10, 6))
make a matrix with first column 0
make a matrix with all elements 0
make a matrix with diagonal elements 0
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.arange(5,1)print(a)
[ ]
[1 2 3 4 5]
[5 4 3 2 1]
[1 2 3 4]
arr=np.float([1,2,3,4])
arr=np.array([1,2,3,4]).toFloat()
arr=np.farray([1,2,3,4])
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
Tuple
ndarray
narray
nd_array
darray
import numpy as npa = np.array([1, 5, 4, 7, 8])a = a + 1print(a[1])