Inhaltsangabe
Summary
Dask is a native parallel analytics tool designed to integrate seamlessly with the libraries you're already using, including Pandas, NumPy, and Scikit-Learn. With Dask you can crunch and work with huge datasets, using the tools you already have. And Data Science with Python and Dask is your guide to using Dask for your data projects without changing the way you work!
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. You'll find registration instructions inside the print book.
About the Technology
An efficient data pipeline means everything for the success of a data science project. Dask is a flexible library for parallel computing in Python that makes it easy to build intuitive workflows for ingesting and analyzing large, distributed datasets. Dask provides dynamic task scheduling and parallel collections that extend the functionality of NumPy, Pandas, and Scikit-learn, enabling users to scale their code from a single laptop to a cluster of hundreds of machines with ease.
About the Book
Data Science with Python and Dask teaches you to build scalable projects that can handle massive datasets. After meeting the Dask framework, you'll analyze data in the NYC Parking Ticket database and use DataFrames to streamline your process. Then, you'll create machine learning models using Dask-ML, build interactive visualizations, and build clusters using AWS and Docker.
What's inside
- Working with large, structured and unstructured datasets
- Visualization with Seaborn and Datashader
- Implementing your own algorithms
- Building distributed apps with Dask Distributed
- Packaging and deploying Dask apps
About the Reader
For data scientists and developers with experience using Python and the PyData stack.
About the Author
Jesse Daniel is an experienced Python developer. He taught Python for Data Science at the University of Denver and leads a team of data scientists at a Denver-based media technology company.
Table of Contents
- Why scalable computing matters
- Introducing Dask
- Introducing Dask DataFrames
- Loading data into DataFrames
- Cleaning and transforming DataFrames
- Summarizing and analyzing DataFrames
- Visualizing DataFrames with Seaborn
- Visualizing location data with Datashader
- Working with Bags and Arrays
- Machine learning with Dask-ML
- Scaling and deploying Dask
PART 1 - The Building Blocks of scalable computing
PART 2 - Working with Structured Data using Dask DataFrames
PART 3 - Extending and deploying Dask
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Über die Autorin bzw. den Autor
Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Suchergebnisse für Data Science with Python and Dask
Beispielbild für diese ISBN
Data Science with Python and Dask
Anbieter: HPB-Red, Dallas, TX, USA
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Bestandsnummer des Verkäufers S_368122428
Beispielbild für diese ISBN
Data Science at Scale with Python and Dask
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Bestandsnummer des Verkäufers GOR014542245
Gebraucht kaufen
EUR 6,04
Versand:
EUR 6,39
Von Vereinigtes Königreich nach USA
Anzahl: 1 verfügbar
Beispielbild für diese ISBN
Data Science with Python and Dask Format: Paperback
Anbieter: INDOO, Avenel, NJ, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: As New. Unread copy in mint condition. Bestandsnummer des Verkäufers SS9781617295607
Gebraucht kaufen
EUR 40,09
Versand:
Gratis
Innerhalb der USA
Anzahl: Mehr als 20 verfügbar
Beispielbild für diese ISBN
Data Science with Python and Dask Format: Paperback
Anbieter: INDOO, Avenel, NJ, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: New. Brand New. Bestandsnummer des Verkäufers 9781617295607
Neu kaufen
EUR 40,18
Versand:
Gratis
Innerhalb der USA
Anzahl: Mehr als 20 verfügbar
Beispielbild für diese ISBN
Data Science with Python and Dask
Anbieter: Toscana Books, AUSTIN, TX, USA
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks. Bestandsnummer des Verkäufers Scanned1617295604
Beispielbild für diese ISBN
Data Science at Scale with Python and Dask
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Bestandsnummer des Verkäufers PB-9781617295607
Neu kaufen
EUR 41,50
Versand:
EUR 5,73
Von Vereinigtes Königreich nach USA
Anzahl: 15 verfügbar
Foto des Verkäufers
Data Science at Scale with Python and Dask
Anbieter: Rarewaves USA, OSWEGO, IL, USA
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: New. Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the reader's analysis. Key Features Working with large structured datasets Writing DataFrames Cleaningand visualizing DataFrames Machine learning with Dask-ML Working with Bags and Arrays Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required. About the technology Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets. Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course. Bestandsnummer des Verkäufers LU-9781617295607
Beispielbild für diese ISBN
Data Science at Scale with Python and Dask (Paperback)
Verlag:
Manning Publications, New York, 2019
ISBN 10: 1617295604
ISBN 13: 9781617295607
Neu
Paperback
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: new. Paperback. Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the readers analysis. Key Features Working with large structured datasets Writing DataFrames Cleaningand visualizing DataFrames Machine learning with Dask-ML Working with Bags and Arrays Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required. About the technology Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets. Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course. Large datasets tend to be distributed, non-uniform, and prone to change. Teaching readers how to build distributed data projects that can handle huge amounts of data, this edition introduces Dask DataFrames and teaches helpful code patterns to streamline the reader's analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781617295607
Beispielbild für diese ISBN
Data Science at Scale With Python and Dask
Anbieter: Books Puddle, New York, NY, USA
Verkäuferbewertung 4 von 5 Sternen
Zustand: New. pp. 400. Bestandsnummer des Verkäufers 26375758709
Beispielbild für diese ISBN
Data Science at Scale With Python and Dask
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Verkäuferbewertung 4 von 5 Sternen
Zustand: New. pp. 400. Bestandsnummer des Verkäufers 370286762
Neu kaufen
EUR 50,64
Versand:
EUR 7,42
Von Vereinigtes Königreich nach USA
Anzahl: 2 verfügbar