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
We can find the dimension of the array
Size of array
Operational activities on Matrix
None of the mentioned above
What is the datatype of x ?
import numpy as npa=np.array([1,2,3,4])x=a.tolist()
int
array
tuple
list
What will be the output?
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
Error
What will be output for the following code?
import numpy as npa=np.array([[1,2,3],[0,1,4]])print (a.size)
1
5
6
4
Indexed
Sliced
Iterated
All of the mentioned above
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)
2
3
0
Shape
Array
both a) and b)
None of the above.
List
Matrix
Tuple
What will be the output of the following ?
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]
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
NumPy arrays have contiguous memory location
They are more speedy to work with
They are more convenient to deal with
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
Indexing
Slicing
Reshaping
numpy.maximum()
numpy.arraymax()
numpy.amax()
numpy.big()
import numpy as np
ary=np.array([1,2,3,5,8])
ary=ary+1
print(ary[1])
size
dtype
ndim
shape
numpy.array(list)
numpy.array(list, dtype=float)
Both a and b
What will be the output of the following code?
import numpy as npa=np.array([1,2,3])print(a.ndim)
How many values are generated?
import numpy as npprint(np.linspace(0, 10, 6))
10
11
Which syntax would print the last 3 numbers from the array below:
print(arr[3:])
print(arr[3])
print(arr[:3])
print(arr[4:])
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
None of these
unlimited length
all private members must have leading and trailing underscores
Preferred Installer Program
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)
Number of Rows and Column in array
Size of each items in array
Number of elements in array
Largest element of an array
rank
import numpy as npa = np.array([[1,2,3]])print(a.shape)
(2,3)
(3,1)
(1,3)
None of These
import numpy as npa = np.array([[1,2],[3,4]])print(a.shape)
(4,)
(2,2)
(2,1)
np.ndim(array_name)
array_name.ndim()
np.dim(array_name)
array_name.dim
all_like
ones_like
one_alike
all of the mentioned
arr=np.float([1,2,3,4])
arr=np.array([1,2,3,4]).toFloat()
arr=np.farray([1,2,3,4])
Web development
Machine learning and scientific computing
Game development
Database management
ndarray
narray
nd_array
darray
Size, shape
memory consumption
data type of array
All of these
what will be output for the following code?
import numpy as npa=np.array([1,2,3,5,8])print(a.ndim)
shape, dtype, ndim
objects, type, list
objects, non vectorization
Unicode and shape
Mathematical and logical operations on arrays.
Fourier transforms and routines for shape manipulation.
Operations related to linear algebra.
axes
degree
cordinate
points
Numbering Python
Number In Python
Numerical Python
import numpy as npa=np.array([2,4,1])b=aa[1]=3print(b)
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
array_split()
split()
split_array()
hstack() and vstack()
What will be the output of the following Python code?
len(["hello",2, 4, 6])
from numpy import *
import numpy
import numpy as my_numpy
All of 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 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])
12
28
import numpy as npaa=np.array([1,2,3])print(a*2)
[2 4 6]
[1 2 3 1 2 3]
[3 4 5]