it's introduction to python

1. LAB 1- INTRODUCTION TO PYTHON
PROGRAMMING LANGUAGE
Eng. Ahmed S. Alsayadi
Winter-2020
Sana’a University
Faculty of Engineering
Mechatronics Engineering Department
Mechatronics System Design Practical Lab
Mechatronics System Design(2) MT503
5th Level

2. Working with numpy
1.Creating arrays
2.Reshaping arrays
3.Array manipulation
4.String operations

3. >> np.array([])
#create an array of given values
>> np.empty(Shape, data type)
#create an array of random values
>> np.zeros(Shape, data type)
#create an array of zero values
>> np.eye(row, column)
#create an array of ones-in-diagonal and zeros else where
Creating Arrays

4. >> np.arange(X).reshape(row, column)
#an array of 0 to X with a specific shape
>> np.arange(start, stop, increment)
#an array starts from – to – with an increment
>> np.flatten()
#convert an array into one row
Reshaping Arrays

5. Exercise
Create the array shown using
reshape
Reshaping Arrays

6. list1=[1,2,3,4]
list2=[1,2,3,4]
Print(list1*list2)
Arrays manipulation

7. list1=[1,2,3,4]
list2=[1,2,3,4]
lis1 = np.array(list1)
# Convert list1 into a NumPy array
lis2 = np.array(list2)
# Convert list2 into a NumPy array
print(lis1*lis2)
Arrays manipulation

8. import numpy as np
x = np.random.randint(0, 10, 40)
print("Original array:")
print(x)
print("Most frequent value in the above array:")
print(np.bincount(x).argmax())
Most frequent value in an array

9. x = np.random.randint(0,3,6)
y = np.random.randint(0,3,6)
array_equal = np.allclose(x, y)
Comparing arrays

10. Sorting arrays

11. Sorting arrays

12. Dealing with strings

13. Eng. Ahmed S. Alsayadi
777 278 525
For the next lab
• Review operations with numpay arrays
• Prepare for a simple understanding check ”quiz”
• Material related
• Numpy documentation