NumPy Cheat Sheet Mouse Pad – Large Mouse Mat for Developers, with Essential Quick Guide for Coders, Essential Computer Accessories for Study, Work, and Reference Purposes NVA

Color:

NumPy

Beyond Maths

CSS 3 Shortcuts

Music Theory

NumPy

Piano Music Theory

PowerShell Shortcut

Regex

Vim Commands

Detalles del producto

Disponibilidad:
En stock

Peso con empaque:
0.38 kg

Devolución:
No

Condición
Nuevo

Producto de:
Amazon

Viaja desde
USA

Sobre este producto

Upgrade your workspace with this large mouse pad (31.5 x 11.8 inches, 3mm thick), offering ample space for your mouse, keyboard, and essentials. Its ultra-smooth surface ensures precise control, while the non-slip rubber base keeps it securely in place. Designed with invisible stitching for durability and a sleek look, it also features a waterproof coating for easy cleaning. This multi-functional desk mat protects your surface from scratches and stains - an ideal gift for gamers, professionals, and home offices.

U$S 65,96

55% OFF

U$S 29,98

U$S 65,96

55% OFF

U$S 29,98

Llega en 25 o más días hábiles

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Medios de pago

Conoce más detalles

Extra Large & Comfortable: Measuring 31.5 x 11.8 inches with a 3mm thickness, this XL mouse pad offers ample space for your mouse, keyboard, and more - ensuring comfort and reducing noise. Smooth & Precise Control: Enjoy effortless mouse movement with the ultra-smooth surface, perfect for both gaming and office work. Non-Slip Rubber Base: The anti-slip rubber base keeps the pad securely in place during intense gaming or work sessions. Durable & Stylish Design: Invisible stitching prevents edge wear while maintaining a sleek look, extending the pad’s lifespan. Waterproof & Easy to Clean: The water-resistant coating allows for quick cleaning—spills and stains wipe away easily. Perfect Gift for Coders – Ideal for Python developers, data scientists, and students; makes a practical and inspiring desk accessory for any workspace. Comprehensive NumPy Reference – Features an easy-to-read, high-contrast layout with essential NumPy functions, array operations, and examples for quick coding guidance. Stay in the Flow – Keep all essential Python array operations right under your hands so you can focus on coding, not searching.