NumPy is the essential package for scientific computing in Python. Numpy arrays exhibits advanced mathematical and different types of operations on large numbers of data. Commonly, such operations are run more efficiently and by using Python’s built-in sequence it is possible with less code. NumPy is Python extension module but not another programming language. It offers quick and efficient operations on arrays of homogeneous data.
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Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
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The most important feature of NumPy is the homogeneous high-performance n-dimensional array object. Data manipulation in Python is nearly equivalent to the manipulation of NumPy arrays. NumPy array manipulation is basically related to accessing data and sub-arrays. It also includes array splitting, reshaping, and joining of arrays. Even the other external libraries in Python relate to NumPy arrays.
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Arrays in NumPy are synonymous with lists in Python with a homogenous nature. The homogeneity helps to perform smoother mathematical operations. These arrays are mutable. NumPy is useful to perform basic operations like finding the dimensions, the bite-size, and also the data types of elements of the array.
NumPy has a variety of built-in functions to create an array.
For 1-D arrays the most common function is np.arange(…), passing any value create an array from 0 to that number.
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16, 17, 18, 19])
We can check the dimensions by using array.shape.
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In this Python tutorial, you will start learning about one of the most important open-source packages in Python (NumPy). Numpy offers:
In this introductory video you will be presented to NumPy library, learn how to install it and learn how to create arrays and matrices. Finally, you will understand why NumPy arrays are more efficient than Python Lists when dealing with mathematical operations. We will perform a benchmark comparing NumPy arrays and Python Lists. Let’s get started!
Learn how to use Jupyter Notebooks: https://www.youtube.com/watch?v=gGYaFfAvYtg&t=343s
Playlist: NumPy Course | Video #1
Access the code here: https://github.com/rscorrea1/youtube.git
0:00 - What is Numpy
0:48 - Course will be presented using Jupyter Notebook
1:07 - Content of the video
1:32 - How to install
2:01 - What is a NumPy Array
2:50 - How to create NumPy Array
3:59 - Why use NumPy Array
5:39 - Speed test Benchmark
9:39 - Next NumPy video announcement
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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Python Programming language makes everything easier and straightforward. Effective use of its built-in libraries can save a lot of time and help with faster submissions while doing Competitive Programming. Below are few such useful tricks that every Pythonist should have at their fingertips:
Below is the implementation to convert a given number into a list of digits:
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