What will be the output of the following ?
import numpy as npa=np.array([2,4,1])b=aa[1]=3print(b)
[2 4 1]
[3 4 1]
[2 3 1]
[2 4 3]
import numpy as nparr=np.array([1,2,3])print(arr.shape)
(3,)
(4,)
1
3
Shape
Array
both a) and b)
None of the above.
List
Matrix
Set
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)
All of the above
np.ndim(array_name)
array_name.ndim()
np.dim(array_name)
array_name.dim
create()
list()
tuple()
array()
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)
9
4
Indexing
Slicing
Reshaping
None of the above
from numpy import *
import numpy
import numpy as my_numpy
All of above
What will be the output of the following code?
import numpy as npa=np.array([1,2,3])print(a.ndim)
2
0
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
range()
space()
arange()
linspace()
What will be output for the following code?
import numpy as npary = np.array([1,2,3,5,8])ary = ary + 1print (ary[1])
It creates a new Python list.
It creates a NumPy array.
It performs element-wise addition.
It calculates the mean of an array.
What is the output of the following code ?
import numpy as npa = np.array([[1,2,3]])print(a.shape)
(3,1)
(1,3)
None of These
We can find the dimension of the array
Size of array
Operational activities on Matrix
None of the mentioned above
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
import numpy as npa = np.arange(5,1)print(a)
[ ]
[1 2 3 4 5]
[5 4 3 2 1]
[1 2 3 4]
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([[1,2,3],[0,1,4]])print (a.size)
5
6
size
dtype
ndim
shape
import numpy as npprint(np.maximum([2, 3, 4], [1, 5, 2]))
[1 5 2]
[1 5 4]
[2 3 4]
[2 5 4]
A machine learning library
A web development framework
A numerical computing library in Python
A data visualization tool
Guido van Rossum
Travis Oliphant
Wes McKinney
Jim Hugunin
import numpy as npa=np.array([2,4,1])b=a.copy()a[1]=3print(b)
Numbering Python
Number in Python
Numerical Python
Number for Python
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
What is the datatype of x ?
import numpy as npa=np.array([1,2,3,4])x=a.tolist()
int
array
tuple
list
change in shape of array
reshaping of array
get the shape of the array
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
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
print(arr[1])
print(arr,0)
print(arr,1)
all_like
ones_like
one_alike
all of the mentioned
import numpy as npy = np.array([[11, 12, 13, 14], [32, 33, 34, 35]])print(y.ndim)
Number of Rows and Column in array
Size of each items in array
Number of elements in array
Largest element of an array
Size, shape
memory consumption
data type of array
All of these
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
Mathematical and logical operations on arrays.
Fourier transforms and routines for shape manipulation.
Operations related to linear algebra.
import numpy as npa = np.arange(1,5,2)print(a)
[1 3 5]
[1 3]
[1,3]
[1,2,3,4,5]
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:])
89
[1,2,3,4]
[1,2,3],[3,4,5],[1,3,4]
[[2 3 5][ 4 5 6][4 5 6]]
rank
None of these
np.concatenate()
np.join()
np.array_join()
np.join_array()
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
np.array([4,5,6])
np.create_array([4,5,6])
np.createArray([4,5,6])
np.numpyArray([4,5,6])
axes
degree
cordinate
points
Indexed
Sliced
Iterated
All of the mentioned above
What is a correct syntax to print the numbers [3, 4, 5] from the array below:
print(arr[2:4])
print(arr[2:5])
print(arr[2:6])
print(arr[3:6])