Coverart for item
The Resource Python data visualization cookbook : over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries, Igor Milovanović

Python data visualization cookbook : over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries, Igor Milovanović

Label
Python data visualization cookbook : over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries
Title
Python data visualization cookbook
Title remainder
over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries
Statement of responsibility
Igor Milovanović
Creator
Author
Subject
Language
eng
Summary
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
Member of
Cataloging source
IDEBK
http://library.link/vocab/creatorName
Milovanović, Igor
Dewey number
005.13/3
Index
no index present
LC call number
QA76.73.P98
LC item number
M55 2013eb
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/subjectName
  • Python (Computer program language)
  • COMPUTERS
  • Python (Computer program language)
Label
Python data visualization cookbook : over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries, Igor Milovanović
Instantiates
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 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
Control code
864381760
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9781782163374
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)864381760
Label
Python data visualization cookbook : over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries, Igor Milovanović
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 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
Control code
864381760
Dimensions
unknown
Extent
1 online resource
File format
unknown
Form of item
online
Isbn
9781782163374
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)864381760

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