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9 Python Libraries I Always Install First ⚡
Boost Your Productivity, Data Analysis, and Development Workflow with These Must-Have Tools
Tabish anwar
3 min read
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4 hours ago
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Introduction
Python’s ecosystem is vast, but a handful of libraries consistently prove indispensable. Whether you’re a data scientist, web developer, or automation enthusiast, these tools will save time and supercharge your projects. Here are the 9 libraries I install at the start of every Python journey.
1. 🚀 NumPy: The Foundation of Scientific Computing
What it does: NumPy provides support for large, multi-dimensional arrays and matrices, along with mathematical functions to operate on them.
Why I install it first: It’s the backbone of data manipulation in Python. Libraries like Pandas and TensorFlow rely on it.
Key features:
- Efficient array operations
- Broadcasting and vectorization
- Integration with C/C++ and Fortran
Use case:
import numpy as np
arr = np.array([1, 2, 3])
print(arr * 2) # Output: [2 4 6]
2. 🐼 Pandas: Data Wrangling Made Easy
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