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  1. Python data visualization cookbook
    Erschienen: 2013
    Verlag:  Packt Publishing, Birmingham

    This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general.... mehr

    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
    uneingeschränkte Fernleihe, Kopie und Ausleihe

     

    This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic. Intro -- Python Data Visualization Cookbook -- Table of Contents -- Python Data Visualization Cookbook -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers and more -- Why Subscribe? -- Free Access for Packt account holders -- Preface -- What this book covers -- What you need for this book -- Who this book is for -- Conventions -- Reader feedback -- Customer support -- Downloading the example code -- Errata -- Piracy -- Questions -- 1. Preparing Your Working Environment -- Introduction -- Installing matplotlib, NumPy, and SciPy -- Getting ready -- How to do it... -- How it works... -- There's more... -- Installing virtualenv and virtualenvwrapper -- Getting ready -- How to do it... -- Installing matplotlib on Mac OS X -- Getting ready -- How to do it... -- Installing matplotlib on Windows -- Getting ready -- How to do it... -- There's more... -- Installing Python Imaging Library (PIL) for image processing -- How to do it... -- How it works... -- There's more... -- Installing a requests module -- How to do it... -- How it works... -- Customizing matplotlib's parameters in code -- Getting ready -- How to do it... -- How it works... -- Customizing matplotlib's parameters per project -- Getting ready -- How to do it... -- How it works... -- There's more... -- 2. Knowing Your Data -- Introduction -- Importing data from CSV -- Getting ready -- How to do it... -- How it works... -- There's more... -- Importing data from Microsoft Excel files -- Getting ready -- How to do it... -- How it works... -- There's more... -- Importing data from fixed-width datafiles -- Getting ready -- How to do it... -- How it works... -- Importing data from tab-delimited files -- Getting ready -- How to do it... -- How it works... -- There's more... -- Importing data from a JSON resource -- Getting ready.

     

    Export in Literaturverwaltung   RIS-Format
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9781782163374; 9781782163367
    RVK Klassifikation: ES 935 ; ST 250 ; ST 320
    Auflage/Ausgabe: Online-Ausg.
    Schlagworte: Python (Computer program language); Scripting languages (Computer science); Python (Computer program language); Scripting languages (Computer science); Electronic books
    Umfang: Online-Ressource (1 online resource (280 pages)), illustrations
    Bemerkung(en):

    Includes index. - Description based on online resource; title from PDF (ebrary, viewed December 30, 2013)

  2. Python data visualization cookbook
    Erschienen: 2013
    Verlag:  Packt Pub., Birmingham, UK

    This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general.... mehr

    Max-Planck-Institut für ethnologische Forschung, Bibliothek
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    Duale Hochschule Baden-Württemberg Mannheim, Bibliothek
    E-Book Safari
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    This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the co

     

    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9781782163367
    RVK Klassifikation: ES 935 ; ST 250 ; ST 320
    Schlagworte: Information visualization; Electronic books; Python (Computer program language); Scripting languages (Computer science); Information visualization; Python (Computer program language)
    Umfang: Online-Ressource (1 v. p.)
    Bemerkung(en):

    Author: Igor Milovanovi¿̐¿̒. Cf. "About the author" page. - Includes index

  3. Python data visualization cookbook
    Erschienen: 2013
    Verlag:  Packt Publishing, Birmingham

    This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general.... mehr

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    This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic. Intro -- Python Data Visualization Cookbook -- Table of Contents -- Python Data Visualization Cookbook -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers and more -- Why Subscribe? -- Free Access for Packt account holders -- Preface -- What this book covers -- What you need for this book -- Who this book is for -- Conventions -- Reader feedback -- Customer support -- Downloading the example code -- Errata -- Piracy -- Questions -- 1. Preparing Your Working Environment -- Introduction -- Installing matplotlib, NumPy, and SciPy -- Getting ready -- How to do it... -- How it works... -- There's more... -- Installing virtualenv and virtualenvwrapper -- Getting ready -- How to do it... -- Installing matplotlib on Mac OS X -- Getting ready -- How to do it... -- Installing matplotlib on Windows -- Getting ready -- How to do it... -- There's more... -- Installing Python Imaging Library (PIL) for image processing -- How to do it... -- How it works... -- There's more... -- Installing a requests module -- How to do it... -- How it works... -- Customizing matplotlib's parameters in code -- Getting ready -- How to do it... -- How it works... -- Customizing matplotlib's parameters per project -- Getting ready -- How to do it... -- How it works... -- There's more... -- 2. Knowing Your Data -- Introduction -- Importing data from CSV -- Getting ready -- How to do it... -- How it works... -- There's more... -- Importing data from Microsoft Excel files -- Getting ready -- How to do it... -- How it works... -- There's more... -- Importing data from fixed-width datafiles -- Getting ready -- How to do it... -- How it works... -- Importing data from tab-delimited files -- Getting ready -- How to do it... -- How it works... -- There's more... -- Importing data from a JSON resource -- Getting ready.

     

    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Hinweise zum Inhalt
    Volltext (Lizenzpflichtig)
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9781782163374; 9781782163367
    RVK Klassifikation: ES 935 ; ST 250 ; ST 320
    Auflage/Ausgabe: Online-Ausg.
    Schlagworte: Python (Computer program language); Scripting languages (Computer science); Python (Computer program language); Scripting languages (Computer science); Electronic books; Art and state ; Great Britain ; History ; 19th century..; Great Britain ; Civilization ; 18th century..; Great Britain ; Civilization ; 19th century; Art and state ; Great Britain ; History ; 18th century..
    Umfang: Online-Ressource (1 online resource (280 pages)), illustrations
    Bemerkung(en):

    Includes index. - Description based on online resource; title from PDF (ebrary, viewed December 30, 2013)

    Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Preparing Your Working Environment; Introduction; Installing matplotlib, NumPy, and SciPy; Installing virtualenv and virtualenvwrapper; Installing matplotlib on Mac OS X; Installing matplotlib on Windows; Installing Python Imaging Library (PIL) for image processing; Installing a requests module; Customizing matplotlib's parameters in code; Customizing matplotlib's parameters per project; Chapter 2: Knowing Your Data; Introduction; Importing data from CSV

    Importing data from Microsoft Excel filesImporting data from fixed-width data files; Importing data from tab-delimited files; Importing data from a JSON resource; Exporting data to JSON, CSV, and Excel; Importing data from a database; Cleaning up data from outliers; Reading files in chunks; Reading streaming data sources; Importing image data into NumPy arrays; Generating controlled random datasets; Smoothing the noise in real-world data; Chapter 3: Drawing Your First Plots and Customizing Them; Introduction; Defining plot types - bar, line, and stacked charts

    Drawing simple sine and cosine plotDefining axis lengths and limits; Defining plot line styles, properties, and format strings; Setting ticks, labels, and grids; Adding legend and annotations; Moving spines to the center; Making histograms; Making bar charts with error bars; Making pie charts count; Plotting with filled areas; Drawing scatter plots with colored markers; Chapter 4: More Plots and Customizations; Introduction; Setting the transparency and size of axis labels; Adding a shadow to the chart line; Adding a data table to the figure; Using subplots; Customizing grids

    Creating contour plotsFilling an under-plot area; Drawing polar plots; Visualizing the file system tree using a polar bar; Chapter 5: Making 3D Visualizations; Introduction; Creating 3D bars; Creating 3D histograms; Animating in matplotlib; Animating with OpenGL; Chapter 6: Plotting Charts with Images and Maps; Introduction; Processing images with PIL; Plotting with images; Displaying image with other plots in the figure; Plotting data on a map using Basemap; Plotting data on a map using Google Map API; Generating CAPTCHA images; Chapter 7: Using Right Plots to Understand Data; Introduction

    Understanding logarithmic plotsUnderstanding spectrograms; Creating a stem plot; Drawing streamlines of vector flow; Using colormaps; Using scatter plots and histograms; Plotting the cross-correlation between two variables; Importance of autocorrelation; Chapter 8: More on Matplotlib Gems; Introduction; Drawing barbs; Making a box and whisker plot; Making Gantt charts; Making errorbars; Making use of text and font properties; Rendering text with LaTeX; Understanding the difference between pyplot and OO API; Index