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NumPy
NumPy

NumPy

AI summary

NumPy is a powerful Python library for numerical computing, offering n-dimensional array processing and various mathematical functions. It enhances performance with optimized C code while maintaining Python's flexibility. The tutorial covers array creation, manipulation, matrix operations, linear algebra, and random data handling, making it accessible for programmers of all backgrounds.

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NumPy Tutorial – Python Library

NumPy is a general-purpose array-processing Python library which provides handy methods/functions for working n-dimensional arrays. NumPy is a short form for “Numerical Python“. It provides various computing tools such as comprehensive mathematical functions, and linear algebra routines.

  • NumPy provides both the flexibility of Python and the speed of well-optimized compiled C code.
  • Its easy-to-use syntax makes it highly accessible and productive for programmers from any background.

This NumPy tutorial helps you learn the fundamentals of NumPy from Basics to Advanced, like operations on NumPy array, creating and plotting random data sets, and working with NumPy functions.

Why Numpy ?

NumPy revolutionized the way we handle numerical data in Python. It is created to address the limitations of traditional Python lists when it comes to numerical computing. It is developed by Travis Olliphant in 2005.

Numpy Array in Python

  1. create a array object
  2. create numpy array from list
  3. create a numpy array from Tuple
  4. create a numpy using fromtier()
  5. create a numpy array using arange()
  6. create a numpy array using linespace
  7. Create a numpy array using nump.empty( )
  8. create a numpy array using nump.one( )
  9. create a numpy array using nump.zero( )
  10. Create a Numpy Array using nump.eye( )
  11. Create 1D NumPy Array using nump.random.rand()
  12. Create a Full NumPy Array using np.full()
  13. Create Numpy from numpy.core.fromrecords()

NumPy Array Manipulation

  1. new_array = np.copy(original_array)
  2. new_array = original_array.view()
  3. new_array.base

Matrix in NumPy

Matrix manipulation in Pythonnumpy matrix operations | empty() functionnumpy matrix operations | zeros() functionnumpy matrix operations | ones() functionnumpy matrix operations | eye() functionnumpy matrix operations | identity() functionAdding and Subtracting Matrices in PythonMatrix Multiplication in NumPyDot product of two arraysNumPy | Vector MultiplicationHow to calculate dot product of two vectors in Python?Multiplication of two Matrices in Single line using Numpy in PythonGet the eigen values of a matrixCalculate the determinant of a matrix using NumPyFind the transpose of the matrixFind the variance of a matrixCompute the inverse of a matrix using NumPy

Operations on NumPy Array

Numpy – Binary OperationsNumpy – Mathematical FunctionNumpy – String Operations

Reshaping NumPy Array

Reshape NumPy ArrayResize the shape of the given matrixReshape the shape of the given matrixGet the Shape of NumPy ArrayChange the dimension of a NumPy arrayChange shape and size of array in-placeFlatten a Matrix in Python using NumPyFlatten a matrix – matrix.ravel()Move axes of an array to new positionsInterchange two axes of an arraySwap the axes a matrixSplit an array into multiple sub-arrays verticallySplit an array into multiple sub-arrays horizontallyGive a new shape to the masked array without changing its dataSqueeze the size of a matrix

Indexing NumPy Array

Basic Slicing and Advanced Indexing in NumPy PythonGet selected slices of an array along mentioned axisAccessing Data Along Multiple Dimensions Arrays in Python NumpyHow to access different rows of a multidimensional NumPy array?Get the indices for the lower-triangle of an (n, m) array

Arithmetic operations on NumPy Array

Broadcasting with NumPy ArraysEstimation of VariablePython: Operations on Numpy ArraysHow to use the NumPy sum function?Divide the NumPy array element wiseComputes the inner product of two arraysAbsolute Deviation and Absolute Mean Deviation using NumPyFind the standard deviation a matrixCalculate the GCD of the NumPy array

Linear Algebra in NumPy Array

Numpy | Linear AlgebraGet the QR factorization of a given NumPy arrayHow to get the magnitude of a vector in NumPy?Compute the eigenvalues and right eigenvectors of a given square array using NumPy?

NumPy and Random Data

Random sampling in numpy | ranf() functionRandom sampling in numpy | random() functionRandom sampling in numpy | random_sample() functionRandom sampling in numpy | sample() functionRandom sampling in numpy | random_integers() functionRandom sampling in numpy | randint() functionGet random elements from NumPy – random.choice()How to choose elements from the list with different probability using NumPy?How to get weighted random choice in Python?How to get the random positioning of different integer values?Get Random Elements form geometric distributionGet Random samples of a sequence of permutation

Sorting and Searching in NumPy Array

Searching in a NumPy arrayHow to sort a Numpy ArrayNumpy – Sorting, Searching and CountingVariations in different Sorting techniques in PythonSort a complex arrayGet the minimum value of masked arraySort the values in a matrixSort the elements in the given matrix having one or more dimension

Universal Functions

Numpy ufunc | Universal functionsCreate your own universal function in NumPy

Working With Images

Create a white image using NumPy in PythonConvert a NumPy array to an imageHow to Convert images to NumPy array?Convert an image to NumPy array and save it to CSV file using Python?

Projects and Applications with NumPy

Print checkerboard pattern of nxn using numpyImplementation of neural network from scratch using NumPyAnalyzing selling price of used cars using Python

Python Numpy Exercises

Python NumPy – Practice Exercises, Questions, and SolutionsPython MCQ (Multiple Choice Questions) with AnswersNumpy Program Examples