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)

Banerjee, Abhinaba

ISBN 10: 8197081913 / ISBN 13: 9788197081910

Published by Orange Education Pvt Ltd, 2024

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Bibliographic Details

• Title: 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)
• Publisher: Orange Education Pvt Ltd
• Publication Date: 2024
• Language: English
• ISBN 10: 8197081913
• ISBN 13: 9788197081910
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Test your Data Analysis skills to its fullest using Python and other no-code tools

Book Description
Ultimate Python Libraries for Data Analysis and Visualization 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 Contents
1. Introduction to Data Analysis and Data Visualization using Python
2. Data Acquisition
3. Data Cleaning and Preparation
4. Exploratory Data Analysis
5. Statistical Analysis
6. Time Series Analysis and Forecasting
7. Signal Processing
8. Analyzing Real-World Data Sets using Python
APPENDIX A Python Cheat Sheet
Index