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Manny /ma·ne/ n A male nanny or babysitter, known to be handsome, fabulous, and a lover of eighties music. "Be interesting." That's what the manny tells Keats Dalinger the first time he packs Keats's school lunch, but for Keats that's not always the easiest thing to do. Even though he's the only boy at home, it always feels like no one ever remembers him. His sisters are everywhere! Lulu is the smart one, India is the creative one, and Belly...well, Belly is the naked one. And the baby. School isn't much better. There, he's the shortest kid in the entire class. But now the manny is the Dalinger's new babysitter, and things are starting to look up. It seems as though the manny always knows the right thing to do. Not everyone likes the manny as much as Keats does, however. Lulu finds the manny embarrassing, and she's started to make a list of all the crazy things that he does, such as serenading the kids with "La Cucaracha" from the front yard or wearing underwear on his head or meeting the school bus with Belly, dressed as limo drivers. Keats is worried. What if Lulu's "Manny Files" makes his parents fire the manny? Who will teach him how to be interesting then?
Cue the pretend drum-roll: Keats's parents have a big surprise. No, they're not having a new baby. It's—wait for it, wait for it—a family road trip! Okay, so this is not exactly the birthday present Keats had in mind (no iPod?!), but when Dad parks a rented RV in the Dalinger's driveway, Keats piles in with the rest of his family—and the manny, of course—bound for the open road. From the big skies of farm country to the bright lights of Las Vegas, this, in typical manny fabulousness, is an all-American adventure filled with more Glamour-dos than Glamour-don'ts. But a stopover at the manny's childhood home is making the manny feel not so fabulous. Why can't his parents ever accept him for who he is? And Keats, at first, sees their point. Why does the manny always have to be so interesting? Hit the road for more manny shenanigans, where it's all about Elton John, Diet Coke, and being brave enough to be yourself.
Now available in a deluxe keepsake edition! A Time Best YA Book of All Time (2021) Run away to the Metropolitan Museum of Art with E. L. Konigsburg’s beloved classic and Newbery Medal­–winning novel From the Mixed-Up Files of Mrs. Basil E. Frankweiler. When Claudia decided to run away, she planned very carefully. She would be gone just long enough to teach her parents a lesson in Claudia appreciation. And she would go in comfort-she would live at the Metropolitan Museum of Art. She saved her money, and she invited her brother Jamie to go, mostly because be was a miser and would have money. Claudia was a good organizer and Jamie bad some ideas, too; so the two took up residence at the museum right on schedule. But once the fun of settling in was over, Claudia had two unexpected problems: She felt just the same, and she wanted to feel different; and she found a statue at the Museum so beautiful she could not go home until she bad discovered its maker, a question that baffled the experts, too. The former owner of the statue was Mrs. Basil E. Frankweiler. Without her—well, without her, Claudia might never have found a way to go home.
As one of the only highly praised resources on this important topic, this thoughtfully compiled book examines and suggests picture books and chapter books presenting LGBTQ content to children under the age of 12. Highlighting titles for children from infancy to age 11, Rainbow Family Collections examines over 250 children's picture books, informational books, and chapter books with LGBTQ content from around the world. Each entry in Rainbow Family Collections supplies a synopsis of the title's content, lists awards it has received, cites professional reviews, and provides suggestions for librarians considering acquisition. The book also provides a brief historical overview of LGBTQ children's literature along with the major book awards for this genre, tips on planning welcoming spaces and offering effective library service to this population, and a list of criteria for selecting the best books with this content. Interviews with authors and key individuals in LGBTQ children's book publishing are also featured.
Research data management is becoming more complicated. Researchers are collecting more data, using more complex technologies, all the while increasing the visibility of our work with the push for data sharing and open science practices. Ad hoc data management practices may have worked for us in the past, but now others need to understand our processes as well, requiring researchers to be more thoughtful in planning their data management routines. This book is for anyone involved in a research study involving original data collection. While the book focuses on quantitative data, typically collected from human participants, many of the practices covered can apply to other types of data as well. The book contains foundational context, instructions, and practical examples to help researchers in the field of education begin to understand how to create data management workflows for large-scale, typically federally funded, research studies. The book starts by describing the research life cycle and how data management fits within this larger picture. The remaining chapters are then organized by each phase of the life cycle, with examples of best practices provided for each phase. Finally, considerations on whether the reader should implement, and how to integrate those practices into a workflow, are discussed. Key Features: Provides a holistic approach to the research life cycle, showing how project management and data management processes work in parallel and collaboratively Can be read in its entirety, or referenced as needed throughout the life cycle Includes relatable examples specific to education research Includes a discussion on how to organize and document data in preparation for data sharing requirements Contains links to example documents as well as templates to help readers implement practices
For those interested in finding a computer application well-suited for their own qualitative research or just learning more about the capabilities of the latest generation of computer software designed with text, Computer Programs for Qualitative Data Analysis by Eben A. Weitzman and Matthew B. Miles probably represents the single investment they can make. . . . In Computer Programs for Qualitative Data Analysis, Weitzman and Miles . . . provide a critical, in-depth look at 24 separate applications. The authors make an impressive team: Weitzman is a professor of social and organizational psychology with an extensive computer background, and Miles is a social psychologist who is well-known in the field of qualitative research for co-authoring a popular book on qualitative data analysis with A. Michael Huberman. Together, the two researchers have produced an informative, user-friendly sourcebook that can save readers a significant amount of time and money when shopping for a software program for qualitative data analysis. Weitzman and Miles clearly put a tremendous amount of work into Computer Programs for Qualitative Data Analysis; they write their reviews of each application in remarkably lucid and jargon-free language in a format reminiscent of Consumer Reports. The level of detail in the reviews reflects their careful and thoughtful field-testing of 24 software programs. Reviews average about 10 pages each and actually show you what each application can do, and every review includes a series of realistic visuals (complete with helpful captions) that display what the computer screen looks like when performing various functions with that specific computer program. In addition to describing the special features of each computer program, Weitzman and Miles discuss the strengths and weaknesses of every application and make explicit comparisons with other applications in the same ′family.′ "Sage Publications deserves special credit for their role in publishing Computer Programs for Qualitative Data Analysis. Instead of issuing this book in hardcover and attaching a hefty price tag, they released it as an oversized (81/2-by-11-inch) paperback and made this valuable information available at a modest cost. Computer Programs for Qualitative Data Analysis is the most comprehensive resource on its subject currently available, and is an excellent starting point for qualitative researchers interested in integrating computer technology more fully into their own data analysis strategies." --Harvard Educational Review "The book by Weitzman & Miles is one of many new books on computers and qualitative software and indeed a good one. . . . The book is truly a user′s book--one of the useful ones. . . . After this first feeling of self-confidence, I just kept on reading the book and found very thorough and illuminative reviews of no less that 24 computer programs for qualitative analysis. . . . Renata Tesch initiated the work of making it easier for us to survey the qualitative analysis methods--Weitzman & Miles carry on in the finest way." --Nyhedsbrer "Although the authors have a background in social and organizational psychology, their expertise on qualitative research methods is relevant to gerontologists. . . . The authors give a history of the use of computers in qualitative data analysis, describe the different types of programs, and suggest future directions, but the bulk of this book is reviews of the software out there. . . . Before you spend several hundred dollars on a software program, spend thirty and get this book." --T. L. Brink in Clinical Gerontologist "Eben A. Weitzman and Matthew B. Miles′s valuable sourcebook on computer programs is designed exclusively for those interested in qualitative data analysis. . . . For qualitative researchers who want to learn or update their knowledge of the use of computer software." --Choice "What program do I use to analyze my field notes? Eben A. Weitzman and Matthew B. Miles provide the information you need to make that decision intelligently: full descriptions, informed judgments, and helpful comparisons. Anyone who does fieldwork needs this book." --Howard Becker, Department of Sociology, University of Washington, Seattle "This will be the standard work of reference for several years to come. We owe the authors a considerable debt of gratitude for all the work they have put into reviewing such a comprehensive range of software. The result is incredibly lucid." --Paul Atkinson, University of Wales, Cardiff "The book is absolutely perfect for my situation. I don′t know how many readers will be in the position of purchasing software for respective labs, but those who are will be in for a real treat. The comprehensiveness of the reviews is more than adequate to determine whether a particular program meets the needs of an individual or group. . . . It is the most comprehensive book of its kind, for any kind of software, that I have ever seen." --Steven E. Wolfel, Research Publishing Consultant "Making decisions about choosing software for qualitative data analysis can be intimidating and I think this book will be an excellent resource for those of us who are involved in this type of research. I found this to be an extremely well-thought-out and informative resource book. The detail is wonderful." --Kathleen R. Gilbert, Indiana University, Bloomington Do you want to start, extend, or update your use of computer software for qualitative data analysis? If so, this clear and user-friendly guidebook is for you. Without assuming its reader has extensive computer experience, Computer Programs for Qualitative Data Analysis takes a critical yet practical look at the wide range of software currently available. It gives detailed reviews of 24 programs in five major categories (text retrievers, textbase managers, code-and-retrieve programs, code-based theory-builders, and conceptual network-builders) and gives ratings of more than 75 features per program. The authors also provide detailed guidance in operating each program. They help you to ask key questions about your computer use--the nature of your project, time line, analyses planned, and the worksheets required--to help you identify the programs best suited to your needs. Up-to-date and practical, Computer Programs for Qualitative Data Analysis is an absolute must-have book for any qualitative researcher who uses--or wants to use--computer programs in analyses.
File I/O can be faster in Python when using concurrency. * Discover how to write files 3x faster with processes * Discover how to read files 3x faster with processes and threads * Discover how to unzip files 4x faster with processes and threads File I/O stands for File Input/Output, referring to the process of reading data from and writing data to files on a storage device like a hard drive. Studying how to bring concurrency to file I/O is critical for Python developers. Adding concurrency into your file I/O tasks, you can unlock the full potential of modern computer hardware, making your applications more efficient and capable of handling large workloads. The problem is, there is no silver bullet. Each program and each task is different and unique. We cannot know which approach to Python concurrency will give good or even the best performance. Therefore in addition to learning how to perform file I/O operations concurrently, Python developers must learn how to benchmark a suite of different approaches to implementing file I/O operations concurrently. Introducing: "Concurrent File I/O in Python". A new book designed to teach you how to bring concurrency to your file I/O tasks in Python, super fast! You will get rapid-paced tutorials showing you how to bring concurrency to the most common file I/O tasks. Including: * How to perform file I/O operation in the background. * How to concurrently read files from disk and write files to disk. * How to concurrently delete files from disk. * How to concurrently copy, move, and rename files on disk. * How to efficiently append files on disk. * How to concurrently zip files and unzip files on disk. Don't worry if you are new to file I/O or concurrency, you will also get primers on the background required to get the most out of this book, including: * The importance of concurrency for high-performance file I/O. * How to perform common file I/O operations in Python. * How to use Python concurrency APIs including threading, multiprocessing, and asyncio. * How to perform file I/O with coroutines in asyncio using the aiofiles library. * How to use programming patterns for concurrent file I/O. Each tutorial is carefully designed to teach one critical aspect of how to bring concurrency to file I/O tasks. Stop copy-pasting code from StackOverflow answers. Learn Python concurrency correctly, step-by-step.
This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools--useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on text, CSV, HTML, XML, and JSON files Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow Create your own tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines Model data with dimensionality reduction, regression, and classification algorithms Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark