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Hands-On Data Visualization with Bokeh : Interactive Web Plotting for Python Using Bokeh.
Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both i...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing Ltd,
2018.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Jolly, Kevin. | |
| 245 | 1 | 0 | |a Hands-On Data Visualization with Bokeh : |b Interactive Web Plotting for Python Using Bokeh. |
| 260 | |a Birmingham : |b Packt Publishing Ltd, |c 2018. | ||
| 300 | |a 1 online resource (168 pages) | ||
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| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover; Title Page; Copyright and Credits; Dedication; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Bokeh Installation and Key Concepts; Technical requirements; The difference between static and interactive plotting; Installing the Bokeh library; Installing Bokeh using a Python distribution; Verifying your installation; When things go wrong; Key concepts and the building blocks of Bokeh; Plot outputs; Summary; Chapter 2: Plotting using Glyphs; Technical requirements; What are glyphs?; Plotting with glyphs; Creating line plots; Creating bar plots; Creating patch plots. | |
| 505 | 8 | |a Creating scatter plotsCustomizing glyphs; Summary; Chapter 3: Plotting with different Data Structures; Technical requirements; Creating plots using NumPy arrays ; Creating line plots using NumPy arrays; Creating scatter plots using NumPy arrays; Creating plots using pandas DataFrames; Creating a time series plot using a pandas DataFrame; Creating scatter plots using a pandas DataFrame; Creating plots with ColumnDataSource ; Creating a time series plot using the ColumnDataSource; Creating a scatter plot using the ColumnDataSource; Summary; Chapter 4: Using Layouts for Effective Presentation. | |
| 505 | 8 | |a Technical requirementsCreating multiple plots along the same row; Creating multiple plots in the same column; Creating multiple plots in a row and column; Creating multiple plots using a tabbed layout; Creating a robust grid layout; Linking multiple plots together; Summary; Chapter 5: Using Annotations, Widgets, and Visual Attributes for Visual Enhancement; Technical requirements; Creating annotations to convey supplemental information; Adding titles to plots; Adding legends to plots; Adding color maps to plots; Creating widgets to add interactivity to plots; Creating a button widget. | |
| 505 | 8 | |a Creating the checkbox widgetCreating a drop-down menu widget; Creating the radio button widget; Creating a slider widget; Creating a text input widget; Creating visual attributes to enhance style and interactivity; Attributes that add interactivity to the plot; Creating a hover tooltip; Creating selections; Attributes that enhance the visual style of the plot; Styling the title ; Styling the background; Styling the outline of the plot; Styling the labels; Summary; Chapter 6: Building and Hosting Applications Using the Bokeh Server; Technical requirements; Introduction to the Bokeh Server. | |
| 505 | 8 | |a Building a Bokeh applicationCreating a single slider application; Creating a multi-slider application; Combining the slider application with a scatter plot; Combining the slider application with a line plot; Creating an application with the select widget; Creating an application with the button widget; Creating an application to select different columns; Introduction to deploying the Bokeh application; Summary; Chapter 7: Advanced Plotting with Networks, Geo Data, WebGL, and Exporting Plots; Technical requirements; Using Bokeh to visualize networks; Visualizing networks with straight paths. | |
| 500 | |a Visualizing networks with explicit paths. | ||
| 520 | |a Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. | ||
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| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Information visualization. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Visualisation de l'information. | |
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| 758 | |i has work: |a HANDS DATA VISUALIZATION WITH BOKEH;INTERACTIVE WEB PLOTTING FOR PYTHON USING BOKEH (Text) |1 https://id.oclc.org/worldcat/entity/E39PCYqrbbTfGRrd37WMXVm7h3 |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Jolly, Kevin. |t Hands-On Data Visualization with Bokeh : Interactive Web Plotting for Python Using Bokeh. |d Birmingham : Packt Publishing Ltd, ©2018 |z 9781789135404 |
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