Data Science Mit Python F R Dummies
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Python for Data Science For Dummies
Author: John Paul Mueller
language: en
Publisher: John Wiley & Sons
Release Date: 2015-06-23
Unleash the power of Python for your data analysis projects with For Dummies! Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization. Python for Data Science For Dummies shows you how to take advantage of Python programming to acquire, organize, process, and analyze large amounts of information and use basic statistics concepts to identify trends and patterns. You’ll get familiar with the Python development environment, manipulate data, design compelling visualizations, and solve scientific computing challenges as you work your way through this user-friendly guide. Covers the fundamentals of Python data analysis programming and statistics to help you build a solid foundation in data science concepts like probability, random distributions, hypothesis testing, and regression models Explains objects, functions, modules, and libraries and their role in data analysis Walks you through some of the most widely-used libraries, including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib Whether you’re new to data analysis or just new to Python, Python for Data Science For Dummies is your practical guide to getting a grip on data overload and doing interesting things with the oodles of information you uncover.
Data Science with Python: Guide for Beginners
Python's Reign in Data Science: Its intuitive syntax, robust libraries (pandas, NumPy, scikit-learn), and active community make Python the lingua franca of data analysis.
Hands on Data Science with Python for Beginners
Author: Bhawna
language: en
Publisher: Research Beacon Publication
Release Date: 2025-08-15
"Hands-On Data Science with Python for Beginners," authored by Ms. Bhawna and Mr. Sumit Kumar Sharma. Those who have a solid background in Python and data science have gained experience working on diverse projects ranging from data analysis and automation to web development, scripting, and research studies on ML algorithms. Over time, we have developed a strong command of Python’s core features, as well as its core libraries like pandas, NumPy, matplotlib, etc. This not only helped readers in improving problem-solving skills but also allowed them to write clean, efficient, and maintainable code. Whether it’s building tools, analyzing datasets, or automating tasks, Python is always a better choice for crafting reliable and effective solutions.