Ultimate Python Libraries for Data Analysis and Visualization: Leverage Pandas, NumPy, Matplotlib, Seaborn, Julius AI and No-Code Tools for Data ... and Statistical Analysis (English Edition)

Ultimate Python Libraries for Data Analysis and Visualization: Leverage Pandas, NumPy, Matplotlib, Seaborn, Julius AI and No-Code Tools for Data ... and Statistical Analysis (English Edition)
by: Abhinaba Banerjee (Author)
Publication Date: 4 April 2024
Language: English
Print Length: 265 pages
ISBN-10: 8197081913
ISBN-13: 9788197081910


Book Description
Test your Data Analysis skills to its fullest using Python and other no-code tools
Book DescriptionUltimate Data Analysis and Visualization with Python is your comprehensive guide to mastering the intricacies of data analysis and visualization using Python. This book serves as your roadmap to unlocking the full potential of Python for extracting insights from data using Pandas, NumPy, Matplotlib, Seaborn, and Julius AI. Starting with the fundamentals of data acquisition, you'll learn essential techniques for gathering and preparing data for analysis. From there, you’ll dive into exploratory data analysis, uncovering patterns and relationships hidden within your datasets.Through step-by-step tutorials, you'll gain proficiency in statistical analysis, time series forecasting, and signal processing, equipping you with the tools to extract actionable insights from any dataset. What sets this book apart is its emphasis on real-world applications. With a series of hands-on projects, you’ll apply your newfound skills to analyze diverse datasets spanning industries such as finance, healthcare, e-commerce, and more.By the end of the book, you'll have the confidence and expertise to tackle any data analysis challenge with Python. To aid your journey, the book includes a handy Python cheat sheet in the appendix, serving as a quick reference guide for common functions and syntax.
Table of contents1. Introduction to Data Analysis and Data Visualization using Python2. Data Acquisition3. Data Cleaning and Preparation4. Exploratory Data Analysis5. Statistical Analysis6. Time Series Analysis and Forecasting7. Signal Processing8. Analyzing Real-World Data Sets using Python APPENDIX A Python Cheat Sheet Index

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