Do We Need Pandas

Download or read book Do We Need Pandas? written by Ken Thompson and published by Bloomsbury Publishing. This book was released on 2011-05-28 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: How much do we really know about the species that make up the natural world? All over the world, biodiversity is gravely threatened – by overfishing, habitat destruction, pollution and climate change. Yet life on Earth has previously experienced five episodes of mass extinction, and nature has repeatedly proved itself to be a resilient, regenerative force. In this fascinating book, ecologist Dr. Ken Thompson surveys the Earth's biodiversity, its origins and some of the threats it currently faces. Thought-provoking and deeply engaging, Do We Need Pandas? offers a non-technical overview of our ecosystems and expands on the causes and consequences of biodiversity loss. Importantly, it also examines what we should be doing to secure the survival not only of the species with which we share the planet, but of ourselves – and whether we need to be more concerned about ecosystems as a whole than about iconic species such as the orangutan and giant Panda.

Download or read book Do We Need Pandas? written by Ken Thompson and published by Bloomsbury Publishing. This book was released on 2011-04-28 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: How much do we really know about the species that make up the natural world? All over the world, biodiversity is gravely threatened – by overfishing, habitat destruction, pollution and climate change. Yet life on Earth has previously experienced five episodes of mass extinction, and nature has repeatedly proved itself to be a resilient, regenerative force. In this fascinating book, ecologist Dr. Ken Thompson surveys the Earth's biodiversity, its origins and some of the threats it currently faces. Thought-provoking and deeply engaging, Do We Need Pandas? offers a non-technical overview of our ecosystems and expands on the causes and consequences of biodiversity loss. Importantly, it also examines what we should be doing to secure the survival not only of the species with which we share the planet, but of ourselves – and whether we need to be more concerned about ecosystems as a whole than about iconic species such as the orangutan and giant Panda.

Download or read book Pandas for Everyone written by Daniel Y. Chen and published by Addison-Wesley Professional. This book was released on 2017-12-15 with total page 1093 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems. Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes. Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability, and introduces you to the wider Python data analysis ecosystem. Work with DataFrames and Series, and import or export data Create plots with matplotlib, seaborn, and pandas Combine datasets and handle missing data Reshape, tidy, and clean datasets so they’re easier to work with Convert data types and manipulate text strings Apply functions to scale data manipulations Aggregate, transform, and filter large datasets with groupby Leverage Pandas’ advanced date and time capabilities Fit linear models using statsmodels and scikit-learn libraries Use generalized linear modeling to fit models with different response variables Compare multiple models to select the “best” Regularize to overcome overfitting and improve performance Use clustering in unsupervised machine learning

Download or read book Thinking in Pandas written by Hannah Stepanek and published by Apress. This book was released on 2020-06-05 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 circumstancesDiscover how to use pandas to extract, transform, and load data correctly with an emphasis on performanceChoose 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.

Download or read book 100 Facts About Pandas written by David O'Doherty and published by Penguin. This book was released on 2010-09-28 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pandas are irresistible and people think they know a lot about them. But only the true panda expert knows: -The age of a panda can be determined by measuring the distance between its nipples -In Egyptian hieroglyphics, the panda symbol means "notwithstanding" -Prince's song "Purple Rain" was inspired by the mixed emotions he feels about pandas Smart, funny, and chock-full of panda pictures, 100 Facts About Pandas will astonish and entertain both animal lovers and everyone who laughed their way through The Book of Bunny Suicides and F U, Penguin.

Download or read book Hands-On Data Analysis with Pandas written by Stefanie Molin and published by Packt Publishing Ltd. This book was released on 2019-07-26 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different real-world domains using step-by-step demonstrationsGet accustomed to using pandas as an effective data exploration toolBook Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling in PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning (ML) algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsUse pandas to solve common data representation and analysis problemsBuild Python scripts, modules, and packages for reusable analysis codeWho this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial.

Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples