Pythonfordataanalysis第二版英文html格式资源-CSDN文库

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Python for data analysis.rar （86个子文件）

Python for data analysis

10. Data Aggregation and Group Operations_files

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5. Getting Started with pandas.html 405KB

9. Plotting and Visualization.html 319KB

4. NumPy Basics Arrays and Vectorized Comput.html 490KB

3. Built-in Data Structures, Functions, and F.html 461KB

12. Advanced NumPy.html 60KB

10. Data Aggregation and Group Operations.html 56KB

9. Plotting and Visualization_files

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14. Appendix Advanced IPython and Jupyter.html 48KB

11. Time Series_files

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4. NumPy Basics Arrays and Vectorized Comput_files

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13. Examples Data Sets.html 82KB

7. Data Cleaning and Preparation.html 334KB

3. Built-in Data Structures, Functions, and F_files

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index.html 2KB

2. Python Language Basics, IPython, and Jupyt.html 74KB

2. Python Language Basics, IPython, and Jupyt_files

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6. Data Loading, Storage, and File Formats.html 276KB

8. Data Wrangling Join, Combine, and Reshape.html 47KB

11. Time Series.html 74KB

13. Examples Data Sets_files

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Preface.html 13KB

1. Preliminaries.html 33KB

12. Advanced NumPy_files

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<html> <head> <title>4. NumPy Basics: Arrays and Vectorized Computation</title> <basefont face="Tahoma" size="2" /> <meta http-equiv="Content-Type" content="text/html;charset=utf-8" /> <meta name="exporter-version" content="Evernote Windows/304720 (en-US, DDL); Windows/6.1.7601 Service Pack 1 (Win64);"/> <style> body, td { font-family: Tahoma; font-size: 12pt; } </style> </head> <body> <a name="339"/> <h1>4. NumPy Basics: Arrays and Vectorized Computation</h1> <div> <span><div style="-evernote-webclip:true"><br/><div style="font-size: 16px; display: inline-block;"><div style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;font-size:100%;text-size-adjust:100%;"><div style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;background-color:rgb(255, 255, 255);"><div style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;background-color:rgb(255, 255, 255);"><div style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;"><div style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;"><div style="font-size:118%;transform:none;box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;color:rgb(51, 51, 51);font-family:Georgia, "Droid Serif", Times, serif;font-style:normal;font-weight:400;"><div style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;font-family:serif, DejaVuSerif;outline:0px;font-size:100%;vertical-align:baseline;background:transparent;text-align:left;text-indent:0px;"><div style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;"><div style="box-sizing:border-box;-webkit-font-smoothing:antialiased;-webkit-tap-highlight-color:transparent;font-family:serif, DejaVuSerif;outline:0px;vertical-align:baseline;background:transparent;text-align:left;text-indent:0px;font-size:100%;"><h1 style="font-family:"source sans pro", sans-serif, AvenirNextCondensed-Medium, HelveticaNeue-CondensedBold, "Droid Sans", Helvetica, Arial, sans-serif;font-weight:bold;text-align:left;hyphens:none;background:transparent;box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;padding:0px;font-style:normal;word-wrap:break-word;vertical-align:baseline;word-break:break-word;border:0px;outline:0px;color:rgb(0, 0, 0);font-size:2em;margin-bottom:50px;padding-bottom:10px;border-bottom:1px solid rgb(0, 0, 0);margin:1.5em 0px 0.35em;break-after:avoid;"><span style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;margin:0px;padding:0px;border:0px;outline:0px;font-size:100%;vertical-align:baseline;background:transparent;">Chapter 4.</span> NumPy Basics: Arrays and <span style="box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;margin:0px;padding:0px;border:0px;outline:0px;font-size:100%;vertical-align:baseline;background:transparent;">Vectorized Computation</span></h1><p style="text-indent:0px;background:transparent;vertical-align:baseline;outline:0px;box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;border:0px;padding:0px;text-align:left;font-family:inherit;margin:0.75em 0px 1.25em;margin-left:0px;margin-right:0px;font-size:100%;">NumPy, short for Numerical Python, is one of the most important foundational packages for numerical computing in Python. Most computational packages providing scientific functionality use NumPy’s array objects as the <em style="border:0px;box-sizing:border-box;-webkit-font-smoothing:antialiased;-webkit-tap-highlight-color:transparent;margin:0px;padding:0px;font-style:italic;outline:0px;font-size:100%;vertical-align:baseline;background:transparent;font-family:inherit;">lingua franca</em> for data exchange.</p><p style="text-indent:0px;background:transparent;vertical-align:baseline;outline:0px;box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;border:0px;padding:0px;text-align:left;font-family:inherit;margin:0.75em 0px 1.25em;margin-left:0px;margin-right:0px;font-size:100%;">Here are some of the things you’ll find in NumPy:</p><ul style="margin-left:0px;padding:0px;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;margin:0px;list-style:none;list-style-type:square;background:transparent;vertical-align:baseline;outline:0px;box-sizing:border-box;border:0px;text-align:left;margin-top:8px;margin-bottom:8px;padding-left:20px;margin-right:0px;text-indent:0px;font-size:100%;"><li style="font-size:100%;margin-bottom:0.25em;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;background:transparent;padding:0px;vertical-align:baseline;box-sizing:border-box;list-style:disc;border:0px;outline:0px;text-align:left;margin:0.5em 0px 0.65em;"><p style="text-indent:0px;background:transparent;vertical-align:baseline;outline:0px;box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;border:0px;padding:0px;margin-bottom:0px;text-align:left;font-family:inherit;margin:0.75em 0px 1.25em;margin-left:0px;margin-right:0px;font-size:100%;"><code style="font-family:"Ubuntu Mono", monospace;box-sizing:border-box;-webkit-font-smoothing:antialiased;-webkit-tap-highlight-color:transparent;font-style:normal;font-weight:400;padding:0px;margin:0px;border:0px;outline:0px;vertical-align:baseline;background:transparent;hyphens:none;font-size:inherit;">ndarray</code>, an efficient multidimensional array providing fast array-oriented arithmetic operations and flexible <em style="border:0px;box-sizing:border-box;-webkit-font-smoothing:antialiased;-webkit-tap-highlight-color:transparent;margin:0px;padding:0px;font-style:italic;outline:0px;font-size:100%;vertical-align:baseline;background:transparent;font-family:inherit;">broadcasting</em> capabilities.</p></li><li style="font-size:100%;margin-bottom:0.25em;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;background:transparent;padding:0px;vertical-align:baseline;box-sizing:border-box;list-style:disc;border:0px;outline:0px;text-align:left;margin:0.5em 0px 0.65em;"><p style="text-indent:0px;background:transparent;vertical-align:baseline;outline:0px;box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;border:0px;padding:0px;margin-bottom:0px;text-align:left;font-family:inherit;margin:0.75em 0px 1.25em;margin-left:0px;margin-right:0px;font-size:100%;">Mathematical functions for fast operations on entire arrays of data without having to write loops.</p></li><li style="font-size:100%;margin-bottom:0.25em;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;background:transparent;padding:0px;vertical-align:baseline;box-sizing:border-box;list-style:disc;border:0px;outline:0px;text-align:left;margin:0.5em 0px 0.65em;"><p style="text-indent:0px;background:transparent;vertical-align:baseline;outline:0px;box-sizing:border-box;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;border:0px;padding:0px;margin-bottom:0px;text-align:left;font-family:inherit;margin:0.75em 0px 1.25em;margin-left:0px;margin-right:0px;font-size:100%;">Tools for reading / writing array data to disk and working with memory-mapped files.</p></li><li style="font-size:100%;margin-bottom:0.25em;-webkit-tap-highlight-color:transparent;-webkit-font-smoothing:antialiased;background:transparent;padding:0px;vertical-align:baseline;box-sizing:border-box;list-style:disc;border:0px;outline:0px;text-align:left;margin:0.5em 0px 0.65em;"><p style="text-indent:0px;background:transparent;vertical-align:baseline;ou

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