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Lesson 21 NumPy

Lesson 21 NumPy. Python Mini-Course University of Oklahoma Department of Psychology . Lesson objectives. Use the NumPy package. What is NumPy?. NumPy is the fundamental package needed for scientific computing with Python. It contains: a powerful N-dimensional array object

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Lesson 21 NumPy

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  1. Lesson 21NumPy Python Mini-Course University of Oklahoma Department of Psychology Python Mini-Course: Lesson 21

  2. Lesson objectives • Use the NumPy package Python Mini-Course: Lesson 21

  3. What is NumPy? • NumPy is the fundamental package needed for scientific computing with Python. It contains: • a powerful N-dimensional array object • basic linear algebra functions • basic Fourier transforms • sophisticated random number capabilities • tools for integrating Fortran code • tools for integrating C/C++ code Python Mini-Course: Lesson 21

  4. NumPy documentation • Official documentation • http://docs.scipy.org/doc/ • The NumPy book • http://www.tramy.us/numpybook.pdf • Example list • http://www.scipy.org/Numpy_Example_List_With_Doc Python Mini-Course: Lesson 21

  5. The ndarray data structure • NumPy adds a new data structure to Python – the ndarray • An N-dimensional array is a homogeneous collection of “items” indexed using N integers • Defined by: • the shape of the array, and • the kind of item the array is composed of Python Mini-Course: Lesson 21

  6. Array shape • ndarrays are rectangular • The shape of the array is a tuple of N integers (one for each dimension) Python Mini-Course: Lesson 21

  7. Array item types • Every ndarray is a homogeneous collection of exactly the same data-type • every item takes up the same size block of memory • each block of memory in the array is interpreted in exactly the same way Python Mini-Course: Lesson 21

  8. Python Mini-Course: Lesson 21

  9. Python Mini-Course: Lesson 21

  10. Example: creating an array import numpy a = array([[1,2,3], [4,5,6], [7,8,9]]) a.shape a.dtype Python Mini-Course: Lesson 21

  11. Indexing arrays • Use a tuple to index multi-dimensional arrays • Example: a[1,2] Python Mini-Course: Lesson 21

  12. Slicing arrays • Slicing arrays is almost the same as slicing lists, except you can specify multiple dimensions Python Mini-Course: Lesson 21

  13. Examples: Slicing arrays a[1] a[1,:] a[1,1:] a[:1,1:] Python Mini-Course: Lesson 21

  14. Some ndarray methods • ndarray. tolist () • The contents of self as a nested list • ndarray. copy () • Return a copy of the array • ndarray. fill (scalar) • Fill an array with the scalar value Python Mini-Course: Lesson 21

  15. Some NumPy functions abs() add() binomial() cumprod() cumsum() floor() histogram() min() max() multipy() polyfit() randint() shuffle() transpose() Python Mini-Course: Lesson 21

  16. Suggested exercise • Complete the desc_stat_calc.py program Python Mini-Course: Lesson 21

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