What Is NumPy?

NumPy is a third-party Python library that provides support for large multidimensional arrays and matrices along with a collection of mathematical functions to operate on these elements.

The library relies on well-known packages implemented in another language (e.g. C or Fortran) to perform efficient computations, bringing the user both the expressiveness of Python and a performance similar to Matlab or Fortran.

NumPy Practical Examples: Useful Techniques

NumPy Practical Examples: Useful Techniques

Nov 20, 2024 intermediate numpy python

NumPy Practical Examples: Useful Techniques

NumPy Practical Examples: Useful Techniques

Nov 20, 2024 intermediate numpy python

How to Use Conditional Expressions With NumPy where()

How to Use Conditional Expressions With NumPy where()

Sep 11, 2024 intermediate data-science numpy

How to Use Conditional Expressions With NumPy where()

How to Use Conditional Expressions With NumPy where()

Sep 02, 2024 intermediate data-science numpy

Astrophysics With Pandas & Matplotlib Art

Exploring Astrophysics in Python With pandas and Matplotlib

Aug 20, 2024 intermediate data-science numpy

Split Your Dataset With scikit-learn's train_test_split()

Split Your Dataset With scikit-learn's train_test_split()

Jul 15, 2024 intermediate data-science machine-learning numpy

Split Your Dataset With scikit-learn's train_test_split()

Split Your Dataset With scikit-learn's train_test_split()

Jul 09, 2024 intermediate data-science machine-learning numpy

Using the NumPy Random Number Generator

Using the NumPy Random Number Generator

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How to Get Normally Distributed Random Numbers With NumPy

How to Get Normally Distributed Random Numbers With NumPy

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Using NumPy reshape() to Change the Shape of an Array

Using NumPy reshape() to Change the Shape of an Array

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Linear Algebra in Python: Matrix Inverses and Least Squares

Linear Algebra in Python: Matrix Inverses and Least Squares

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Working With Linear Systems in Python With scipy.linalg

Working With Linear Systems in Python With scipy.linalg

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NumPy's max() and maximum(): Find Extreme Values in Arrays

NumPy's max() and maximum(): Find Extreme Values in Arrays

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Pythonic Data Cleaning With Pandas and NumPy

Data Cleaning With pandas and NumPy

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Draw the Mandelbrot Set in Python

Draw the Mandelbrot Set in Python

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Split Your Dataset With scikit-learn's train_test_split()

Splitting Datasets With scikit-learn and train_test_split()

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Stochastic Gradient Descent Algorithm With Python and NumPy

Stochastic Gradient Descent Algorithm With Python and NumPy

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NumPy Tutorial: Your First Steps Into Data Science in Python

NumPy Tutorial: Your First Steps Into Data Science in Python

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np.linspace(): Create Evenly or Non-Evenly Spaced Arrays

np.linspace(): Create Evenly or Non-Evenly Spaced Arrays

intermediate data-science numpy

SettingWithCopyWarning in Pandas: Views vs Copies

SettingWithCopyWarning in pandas: Views vs Copies

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NumPy arange(): How to Use np.arange()

Using NumPy's np.arange() Effectively

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Scientific Python: Using SciPy for Optimization

Scientific Python: Using SciPy for Optimization

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NumPy, SciPy, and Pandas: Correlation With Python

NumPy, SciPy, and pandas: Correlation With Python

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Python Statistics Fundamentals: How to Describe Your Data

Python Statistics Fundamentals: How to Describe Your Data

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MATLAB vs Python: Why and How to Make the Switch

MATLAB vs Python: Why and How to Make the Switch

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Python Histogram Plots

Histogram Plotting in Python: NumPy, Matplotlib, Pandas & Seaborn

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NumPy arange(): How to Use np.arange()

NumPy arange(): How to Use np.arange()

intermediate data-science numpy

Python Histogram Plots

Python Histogram Plotting: NumPy, Matplotlib, pandas & Seaborn

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Pure Python vs NumPy vs TensorFlow performance comparison

Pure Python vs NumPy vs TensorFlow Performance Comparison

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Python Data Science Artwork

Look Ma, No for Loops: Array Programming With NumPy

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Pythonic Data Cleaning With Pandas and NumPy

Pythonic Data Cleaning With pandas and NumPy

intermediate data-science numpy