all_like
ones_like
one_alike
all of the mentioned
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
np.concatenate()
np.join()
np.array_join()
np.join_array()
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])
Web development
Machine learning and scientific computing
Game development
Database management
What will be output for the following code ?
import numpy as npa=np.array([2,3,4,5])print(a.dtype)
int32
int
float
none of these
Guido van Rossum
Travis Oliphant
Wes McKinney
Jim Hugunin
np.array()
np.zeros()
np.empty()
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
None of the above
To make a Matrix with all elements 0
Indexing
Slicing
Reshaping
Shape
Array
both a) and b)
None of the above.
Numbering Python
Number In Python
Numerical Python
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 the output of the following ?
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]
Size, shape
memory consumption
data type of array
All of these
from numpy import *
import numpy
import numpy as my_numpy
All of above
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)
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
Mathematical and logical operations on arrays.
Fourier transforms and routines for shape manipulation.
Operations related to linear algebra.
what will be output for the following code?
import numpy as npa=np.array([1,2,3,5,8])print(a.ndim)
0
1
2
3
axes
degree
cordinate
points
print(arr[1])
print(arr,0)
print(arr,1)
None of These
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
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 npa = np.arange(5,1)print(a)
[ ]
[1 2 3 4 5]
[5 4 3 2 1]
numpy.array(list)
numpy.array(list, dtype=float)
Both a and b
numpy.maximum()
numpy.arraymax()
numpy.amax()
numpy.big()
What is the output of the following code ?
import numpy as npa = np.array([[1,2,3]])print(a.shape)
(2,3)
(3,1)
(1,3)
create()
list()
tuple()
array()
import numpy as npa = np.array([[1, 2, 3],[0,1,4],[11,22,33]])print (a.size)
9
4
size
dtype
ndim
shape
What will be the output of following Python code?
import numpy as npa = np.array([(10,20,30)])print(a.itemsize)
All of the mentioned above
import numpy as npprint(np.maximum([2, 3, 4], [1, 5, 2]))
[1 5 2]
[1 5 4]
[2 3 4]
[2 5 4]
array_split()
split()
split_array()
hstack() and vstack()
89
[1,2,3,4]
[1,2,3],[3,4,5],[1,3,4]
[[2 3 5][ 4 5 6][4 5 6]]
unlimited length
all private members must have leading and trailing underscores
Preferred Installer Program
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])
6
24
None of these
List
Matrix
Set
Number of Rows and Column in array
Size of each items in array
Number of elements in array
Largest element of an array
NumPy arrays have contiguous memory location
They are more speedy to work with
They are more convenient to deal with
import numpy as np
ary=np.array([1,2,3,5,8])
ary=ary+1
print(ary[1])
import numpy as npa = np.array([1, 5, 4, 7, 8])a = a + 1print(a[1])
5
7
rank
full
empty
init
A machine learning library
A web development framework
A numerical computing library in Python
A data visualization tool
import numpy as npa = np.arange(1,5,2)print(a)
[1 3 5]
[1 3]
[1,3]
[1,2,3,4,5]
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
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