Vishal

Hi, I am Vishal Jaiswal, I have about a decade of experience of working in MNCs like Genpact, Savista, Ingenious. Currently i am working in EXL as a senior quality analyst. Using my writing skills i want to share the experience i have gained and help as many as i can.

NumPy Concatenation

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NumPy Concatenation

NumPy, the powerhouse of numerical computing in Python, empowers users with an array of functions for efficient data manipulation. Among its arsenal lies the versatile tool of concatenation, allowing for seamless merging of arrays along specified axes. In this article, we delve into NumPy concatenation, exploring its functionalities, applications, and best practices. Understanding NumPy Concatenation … Read more

Mastering hstack and vstack in NumPy

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In this article, we will dive deep to understand hstack and vstack, exploring their usage, advantages, and practical implementations. Understanding hstack and vstack hstack (Horizontal Stack): vstack (Vertical Stack): Usage and Syntax hstack: vstack: Benefits and Applications Data Integration: Matrix Operations: Practical Examples Horizontal Stack: [[1 2 5 6] [3 4 7 8]] Vertical Stack: … Read more

Demystifying NumPy Copy and NumPy View

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NumPy, the cornerstone of numerical computing in Python, introduces two key concepts: “numpy copy” and “numpy view.” Let’s unravel these concepts concisely, exploring their differences, applications, and impact on array operations. Copy vs. View: Unveiling the Contrast NumPy Copy: NumPy View: Creating Copies and Views Copy Creation: In this example: Slicing, reshaping, transposing, and certain … Read more

NumPy Array Indexing and Slicing

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Understanding how to efficiently manipulate data in Python is crucial, and NumPy‘s array indexing and slicing features are indispensable tools in this regard. Here’s a concise overview to help you master these essential NumPy techniques: Basic Techniques Basic Indexing: In these examples, we create both 1D and 2D arrays using NumPy. Then, we access individual … Read more

NumPy Reshaping | np.reshape|numpy.reshape |

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NumPy reshaping is a vital feature for manipulating array shapes without compromising data integrity. Here’s a concise overview: Understanding NumPy Reshaping NumPy reshaping allows seamless alteration of array shapes while preserving data integrity, essential for adapting arrays to various dimensions and formats. Key Reshaping Functions Let’s understand the reshaping and its function with example. reshape … Read more

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