Page 187 - Robotics and AI class 10
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So if we compare NumPy-Arrays and Python-List then:
• Array is a collection of homogeneous values whereas List as studied in class 9 - is a collection of heterogeneous
values.
• In Arrays data of one type does not support data of another type whereas in List it works perfectly by using data
of one type by converting into another datatype.
• Arrays can be accessed only through package -NumPy and occupies less memory space whereas List occupies
more memory space and can be accessed directly in Python without any package support.
• In arrays the mathematical operators can be directly used whereas in list the mathematical operators cannot be
used directly on it instead need to be used separately on individual elements.
• Arrays are mainly used for mathematical operations where Lists are mainly used for data management.
• Syntax of creating array is: import numpy
marks=numpy.array([34,23,41,42])
Syntax of creating a list is: marks=[34,23,41,42]
Creating an Array using NumPy:
• Creating one dimensional array:
import numpy
rollno = numpy.array([1, 2, 3])
print(rollno)
Output:
[1 2 3]
• Create a sequential 1 D array with values as multiples of 10 from 10 to 100:
import numpy as np
a = np.arange(10,101,10)
print(a)
Output:
[ 10 20 30 40 50 60 70 80 90 100]
Another example :
>>>import numpy as np
>>> student = np.array([11,'Amita',92.5])
>>> student
• Creating 1 D array with 4 random values:
import numpy as np
a = np.random.random(4)
print(a)
Output:
[0.9290503 0.89991053 0.7563874 0.89570953]
• Creating a 3X4 array with random integer values less than 10:
import numpy as np
a = np.random.randint(10, size=(3,4))
print(a)
Introduction to Data and Programming with Python 185

