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Mastering Python Data Visualization

You're reading from   Mastering Python Data Visualization Generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783988327
Length 372 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. A Conceptual Framework for Data Visualization 2. Data Analysis and Visualization FREE CHAPTER 3. Getting Started with the Python IDE 4. Numerical Computing and Interactive Plotting 5. Financial and Statistical Models 6. Statistical and Machine Learning 7. Bioinformatics, Genetics, and Network Models 8. Advanced Visualization A. Go Forth and Explore Visualization Index

Conventions

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "First we use norm() from SciPy to create normal distribution samples and later, use hstack() from NumPy to stack them horizontally and apply gaussian_kde() from SciPy."

A block of code is set as follows:

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
students = pd.read_csv("/Users/Macbook/python/data/ucdavis.csv")
g = sns.FacetGrid(students, palette="Set1", size=7)
g.map(plt.scatter, "momheight", "height", s=140, linewidth=.7, edgecolor="#ffad40", color="#ff8000")
g.set_axis_labels("Mothers Height", "Students Height")

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

import blockspring 
import json  

print blockspring.runParsed("stock-price-comparison", 
   { "tickers": "FB, LNKD, TWTR", 
   "start_date": "2014-01-01", "end_date": "2015-01-01" }).params

Any command-line input or output is written as follows:

conda install jsonschema

Fetching package metadata: ....
Solving package specifications: .
Package plan for installation in environment /Users/MacBook/anaconda:

The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    jsonschema-2.4.0           |           py27_0          51 KB

The following NEW packages will be INSTALLED:

    jsonschema: 2.4.0-py27_0

Proceed ([y]/n)?

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Further, you can select the Copy code option to copy the contents of the code block into Canopy's copy-and-paste buffer to be used in an editor."

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

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