This document summarizes a lesson on the NumPy library in Python. It introduces NumPy, which is a library for scientific computing that allows managing n-dimensional arrays. NumPy can be used for mathematical functions like Fourier transforms and linear algebra. It is also the foundation for data science in Python. The lesson demonstrates how to import NumPy, create different types of arrays from 0 to 3 dimensions, access and slice array elements, and perform operations like addition on arrays. Exercises include matrix multiplication and generating Pascal's triangle using NumPy.

1. Data Wrangling
Week 7
Dr. Ferdin Joe John Joseph
Faculty of Information Technology
Thai – Nichi Institute of Technology, Bangkok

2. Today’s Lesson
• Introduction to Numpy
• Numpy - Theories
• Numpy usage in Python
• Demonstration
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3. Numpy
• Python library for scientific computing
• Install in command prompt
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4. Usage of Numpy
• Managing n dimensional arrays
• Mathematical functions like fourier transform, linear algebra and random
number generator
• Backbone of data science in python
• Pandas is built on top of this
• Created in 2005 by Travis Oliphant
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5. Import numpy
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6. np notation
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7. Numpy version
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8. Type of numpy array
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9. 0 Dimensional array
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10. 1 Dimensional array
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11. 2 Dimensional Array
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12. 3 Dimensional Array
• Otherwise known as Tensor
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13. 3 dimensional array
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14. Find dimension of array
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15. Dimension of array
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16. Get first element of array
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17. Get second element of array
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18. Add two elements in array
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19. Access elements in 2 dimensional array
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20. Access elements in 3 dimensional array
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21. Negative indexing
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22. Array Slicing
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23. Slicing from beginning
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24. Negative Slicing
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25. Jump two indices
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26. Slicing 2 dimensional arrays
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27. Activity
• Using numpy perform matrix multiplication of two dimensional arrays
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28. Activity
• Using numpy create pascal’s triangle
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29. Revision- Pre Mid Term
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30. Next Week
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https://github.com/ferdinjoe/DSA201
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