NumPy, Pandas, Matplotlib, and Seaborn are essential libraries in the Python ecosystem for data science and analysis. NumPy is a foundational package providing support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. Pandas builds on NumPy by offering high-level data structures and methods designed for efficient manipulation of structured data, including DataFrames and Series. For data visualization, Matplotlib serves as a versatile library that allows users to create a wide range of static, animated, and interactive plots. Seaborn builds on Matplotlib by providing a high-level interface for drawing attractive and informative statistical graphics, making it easier to generate complex visualizations with fewer lines of code. Together, these libraries offer a comprehensive toolkit for handling and visualizing data in Python.
Introduction to Data Science
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Programming for Data Science
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Statistics and Probability
0/3
Data Wrangling and Cleaning
0/3
Data Visualization
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Exploratory Data Analysis (EDA)
0/3
Machine Learning
0/3
Big Data Technologies
0/3
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