Pandas Apply Mean
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Thinking in Pandas
Understand and implement big data analysis solutions in pandas with an emphasis on performance. This book strengthens your intuition for working with pandas, the Python data analysis library, by exploring its underlying implementation and data structures. Thinking in Pandas introduces the topic of big data and demonstrates concepts by looking at exciting and impactful projects that pandas helped to solve. From there, you will learn to assess your own projects by size and type to see if pandas is the appropriate library for your needs. Author Hannah Stepanek explains how to load and normalize data in pandas efficiently, and reviews some of the most commonly used loaders and several of their most powerful options. You will then learn how to access and transform data efficiently, what methods to avoid, and when to employ more advanced performance techniques. You will also go over basic data access and munging in pandas and the intuitive dictionary syntax. Choosing the right DataFrame format, working with multi-level DataFrames, and how pandas might be improved upon in the future are also covered. By the end of the book, you will have a solid understanding of how the pandas library works under the hood. Get ready to make confident decisions in your own projects by utilizing pandas—the right way. What You Will Learn Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance Choose the right DataFrame so that the data analysis is simple and efficient. Improve performance of pandas operations with other Python libraries Who This Book Is ForSoftware engineers with basic programming skills in Python keen on using pandas for a big data analysis project. Python software developers interested in big data.
Comprehensive Guide to the Pandas Library: Unlocking Data Manipulation and Analysis in Python
Welcome to "Comprehensive Guide to the Pandas Library: Unlocking Data Manipulation and Analysis in Python," an all-encompassing resource crafted to elevate your data manipulation and analytical prowess using the robust Pandas library in Python. Pandas has transformed the landscape for data scientists and analysts by providing a versatile toolkit for working with structured data, making complex data handling tasks both intuitive and efficient. This guide delves into the core techniques of Pandas programming, with each chapter dedicated to exploring different dimensions of the library's extensive capabilities. Our goal is not just to convey information, but to cultivate a deep understanding and instinct for sophisticated data management. Rich in substance and clarity, each section serves as a building block towards mastering intricate operations through Pandas' advanced functionalities.
Ultimate Pandas for Data Manipulation and Visualization: Efficiently Process and Visualize Data with Python’s Most Popular Data Manipulation Library
Author: Tahera Firdose
language: en
Publisher: Orange Education Pvt Limited
Release Date: 2024-06-10
Unlock the power of Data Manipulation with Pandas. Key Features● Master Pandas from basics to advanced and its data manipulation techniques. ● Visualize data effectively with Matplotlib and explore data efficiently. ● Learn through hands-on examples and practical real-world use cases. Book DescriptionUnlock the power of Pandas, the essential Python library for data analysis and manipulation. This comprehensive guide takes you from the basics to advanced techniques, ensuring you master every aspect of pandas. You'll start with an introduction to pandas and data analysis, followed by in-depth explorations of pandas Series and DataFrame, the core data structures. Learn essential skills for data cleaning and filtering, and master grouping and aggregation techniques to summarize and analyze your data sets effectively. Discover how to reshape and pivot data, join and merge multiple datasets, and handle time series analysis. Enhance your data analysis with compelling visualizations using Matplotlib, and apply your knowledge in a real-world scenario by analyzing bank customer churn. Through hands-on examples and practical use cases, this book equips you with the tools to clean, filter, aggregate, reshape, merge, and visualize data effectively, transforming it into actionable insights. What you will learn ● Wrangle data efficiently using Pandas' cleaning, filtering, and transformation techniques. ● Unlock hidden patterns with advanced grouping, joining, and merging operations. ● Master time series analysis with Pandas to extract valuable insights from your data. ● Apply Pandas to real-world scenarios like customer churn analysis and financial modeling. ● Unleash the power of data visualization with Matplotlib and craft compelling charts and graphs. ● Enhance your workflow with essential Pandas optimizations and performance tips. Table of Contents1. Introduction to Pandas and Data Analysis 2. Pandas Series 3. Pandas DataFrame 4. Data Cleaning with Pandas 5. Data Filtering with Pandas 6. Grouping and Aggregating Data 7. Reshaping and Pivoting in Pandas 8. Joining and Merging Data in Pandas 9. Introduction to Time Series Analysis in Pandas 10. Visualization Using Matplotlib 11. Analyzing Bank Customer Churn Using Pandas Index