This full NumPy tutorial for beginners covers everything you need to know about this powerful Python library. With over 20 topics, this course will take you from a beginner to an expert in NumPy. From installing NumPy to advanced array manipulation techniques, this tutorial covers it all. Topics include: array indexing, negative indexing, data types, array reshaping, concatenating arrays, sorting arrays, filtering data, and much more. Learn how to use the popular NumPy functions like np.mean, np.median, and np.random.rand. We'll also show you how to use NumPy with Jupyter Notebook and Anaconda Python. By the end of this course, you'll be able to confidently use NumPy in your own projects. Content – Introduction + Installing numpy – The N-dimensional array (ndarray) – Array indexing – Negative indexing and ndim() method – Array Slicing – Data Types – NumPy Astype method – NumPy Array Copy vs View – NumPy Array Reshaping – How to Manipulate Arrays | NumPy Reshape Function (Part 1) – How to Manipulate Arrays | NumPy Reshape Function (Part 2) – NumPy Matrix transpose() – Transpose of an Array in Python – Flatten a Matrix in Python using NumPy – How To Concatenate Arrays in NumPy | numpy.concatenate() – NumPy Sorting Arrays | How to sort a Numpy Array in Python – Iterating Numpy Arrays – Iterate Down To Scalar in Numpy – Numpy nditer | Loop Through Numpy array – NumPy Searching Arrays | numpy.where – NumPy | searchsorted method with Examples – NumPy | Filtering Data in Python with Boolean Indexes – NumPy Direct Filtering – How to Filter a NumPy Array (Examples) – Numpy Mean, Median, Mode, Standard Deviation in Python – numpy.arange(), numpy.linspace() – ARRAYS OF ONES & ONES and IDENTITY MATRICES – Introduction to Random Numbers in NumPy – numpy.random.rand() | How to use NumPy Random Function – numpy.random.randn() in Python – Numpy Tutorial for beginners – How to Use NumPy random.randint() – How to Use Python NumPy Random Function (EXAMPLES) – Numpy Tutorial for beginners – Numpy Permutation() | The fundamental library needed for scientific computing with Python is called NumPy. NumPy is Open Source library that contains a powerful N-dimensional array object and advanced array slicing methods (to select array elements), convenient array reshaping methods. I will explain what is numpy. why do we use numpy, NumPy is suited to what applications. at last i am going to show How to install numpy on windows using pip install and how to add numpy to your pycharm IDE. A NumPy array is an N-dimensional homogeneous collection of “items” of the same “kind”. The kind can be any arbitrary structure and is specified using the data-type. 1 – Introduction + Installing numpy
2 – Python List Vs Numpy Array
3 – Basic properties and Methods in NumPy Array
4 – Creating specific arrays, Reshape and more