Data visualization with Python and JavaScript scrape, clean, explore & transform your data
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| Sprache: | English |
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| Ausgabe: | First edition |
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| 245 | 1 | 0 | |a Data visualization with Python and JavaScript |b scrape, clean, explore & transform your data |c Kyran Dale |
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Datensatz im Suchindex
| _version_ | 1819632069322473472 |
|---|---|
| adam_text | Titel: Data visualization with Python and JavaScript
Autor: Dale, Kyran
Jahr: 2016
Table of Contents
Preface....................................................... ix
Introduction.................................................. xv
1. Development Setup..........................................1
The Accompanying Code 1
Python 1
JavaScript 5
Databases 6
Integrated Development Environments 8
Summary 8
Parti. Basic Toolkit
2. A Language-Learning Bridge Between Python and JavaScript... 13
Similarities and Differences 14
Interacting with the Code 15
Basic Bridge Work 18
Differences in Practice 42
A Cheat Sheet 54
Summary 56
3. Reading and Writing Data with Python.......................59
Easy Does It 59
Passing Data Around 60
Working with System Files 61
CSV, TSV, and Row-Column Data Formats 62
JSON 65
SQL 69
MongoDB 79
Dealing with Dates, Times, and Complex Data 84
Summary 86
4. Webdev101.............................................. 87
The Big Picture 87
Single-Page Apps 88
Tooling Up 88
Building a Web Page 93
Chrome s Developer Tools 102
A Basic Page with Placeholders 105
Scalable Vector Graphics 109
Summary 125
Partii. Getting Your Data
5. Getting Data off the Web with Python.......................129
Getting Web Data with the requests Library 129
Getting Data Files with requests 130
Using Python to Consume Data from a Web API 134
Using Libraries to Access Web APIs 140
Scraping Data 146
Getting the Soup 149
Selecting Tags 149
Summary 159
6. Heavyweight Scraping with Scrapy......................... 161
Setting Up Scrapy 163
Establishing the Targets 164
Targeting HTML with Xpaths 165
A First Scrapy Spider 171
Scraping the Individual Biography Pages 177
Chaining Requests and Yielding Data 180
Scrapy Pipelines 185
Scraping Text and Images with a Pipeline 187
Summary 194
iv I Table of Contents
Part III. Cleaning and Exploring Data with Pandas
7. Introduction to NumPy....................................197
The NumPy Array 198
Creating Array Functions 204
Summary 206
8. Introduction to Pandas....................................207
Why Pandas Is Tailor-Made for Dataviz 207
Why Pandas Was Developed 207
Heterogeneous Data and Categorizing Measurements 208
TheDataFrame 210
Creating and Saving DataFrames 214
Series into DataFrames 223
Panels 225
Summary 226
9. Cleaning Data with Pandas................................ 229
Coming Clean About Dirty Data 229
Inspecting the Data 231
Indices and Pandas Data Selection 235
Cleaning the Data 239
The Full clean_data Function 256
Saving the Cleaned Dataset 257
Summary 259
10. Visualizing Data with Matplotlib........................... 261
Pyplot and Object-Oriented Matplotlib 261
Starting an Interactive Session 262
Interactive Plotting with Pyplot s Global State 264
Figures and Object-Oriented Matplotlib 269
Plot Types 274
Seaborn 282
Summary 291
11. Exploring Data with Pandas............................... 293
Starting to Explore 294
Plotting with Pandas 296
Gender Disparities 297
National Trends 304
Age and Life Expectancy of Winners 316
Table of Contents | v
The Nobel Diaspora
Summary
323
325
Part IV. Delivering the Data
12. Delivering the Data.......................................329
Serving the Data 330
Delivering Static Files 336
Dynamic Data with Flask 340
Using Static or Dynamic Delivery 344
Summary 344
13. RESTful Data with Flask................................... 347
A RESTful, MongoDB API with Eve 348
Delivering Data to the Nobel Prize Visualization 356
RESTful SQL with Flask-Restless 361
Summary 365
Part V. Visualizing Your Data with D3
14. Imagining a Nobel Visualization............................369
Who Is It For? 369
Choosing Visual Elements 370
Menu Bar 371
Prizes by Year 372
A Map Showing Selected Nobel Countries 373
A Bar Chart Showing Number of Winners by Country 375
A List of the Selected Winners 375
The Complete Visualization 377
Summary 378
15. Building a Visualization................................... 379
Preliminaries 380
The HTML Skeleton 382
CSS Styling 386
The JavaScript Engine 390
Running the Nobel Prize Visualization App 404
Summary 405
vi I Table of Contents
16. Introducing D3—The Story of a Bar Chart................... 407
Framing the Problem 408
Working with Selections 408
Adding DOM Elements 412
Leveraging D3 418
Measuring Up with D3 s Scales 418
Unleashing the Power of D3 with Data Binding 423
The enter Method 425
Accessing the Bound Data 429
The Update Pattern 430
Axes and Labels 436
Transitions 442
Summary 447
17. Visualizing Individual Prizes............................... 449
Building the Framework 449
Scales 450
Axes 451
Category Labels 452
Nesting the Data 454
Adding the Winners with a Nested Data-Join 456
A Little Transitional Sparkle 460
Summary 463
18. Mapping with D3.........................................465
Available Maps 466
D3 s Mapping Data Formats 467
D3 Geo, Projections, and Paths 471
Putting the Elements Together 477
Updating the Map 481
Adding Value Indicators 484
Our Completed Map 487
Building a Simple Tooltip 488
Summary 491
19. Visualizing Individual Winners............................. 493
Building the List 494
Building the Bio-Box 497
Summary 500
Table of Contents | vii
20. The Menu Bar............................................503
Creating HTML Elements with D3 504
Building the Menu Bar 504
Summary 514
21. Conclusion............................................................................................515
Recap 515
Future Progress 518
Final Thoughts 521
A. Moving from Development to Production..........................................523
Index..............................................................................................................545
viii I Table of Contents
|
| any_adam_object | 1 |
| author | Dale, Kyran |
| author_GND | (DE-588)1112956220 |
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| bvnumber | BV043737250 |
| classification_rvk | ST 250 ST 320 |
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| discipline | Informatik |
| edition | First edition |
| format | Book |
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| id | DE-604.BV043737250 |
| illustrated | Illustrated |
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| isbn | 9781491920510 |
| language | English |
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| spellingShingle | Dale, Kyran Data visualization with Python and JavaScript scrape, clean, explore & transform your data Information visualization Python (Computer program language) JavaScript (Computer program language) Information visualization fast JavaScript (Computer program language) fast Python (Computer program language) fast Python Programmiersprache (DE-588)4434275-5 gnd Information (DE-588)4026899-8 gnd Visualisierung (DE-588)4188417-6 gnd JavaScript (DE-588)4420180-1 gnd |
| subject_GND | (DE-588)4434275-5 (DE-588)4026899-8 (DE-588)4188417-6 (DE-588)4420180-1 |
| title | Data visualization with Python and JavaScript scrape, clean, explore & transform your data |
| title_auth | Data visualization with Python and JavaScript scrape, clean, explore & transform your data |
| title_exact_search | Data visualization with Python and JavaScript scrape, clean, explore & transform your data |
| title_full | Data visualization with Python and JavaScript scrape, clean, explore & transform your data Kyran Dale |
| title_fullStr | Data visualization with Python and JavaScript scrape, clean, explore & transform your data Kyran Dale |
| title_full_unstemmed | Data visualization with Python and JavaScript scrape, clean, explore & transform your data Kyran Dale |
| title_short | Data visualization with Python and JavaScript |
| title_sort | data visualization with python and javascript scrape clean explore transform your data |
| title_sub | scrape, clean, explore & transform your data |
| topic | Information visualization Python (Computer program language) JavaScript (Computer program language) Information visualization fast JavaScript (Computer program language) fast Python (Computer program language) fast Python Programmiersprache (DE-588)4434275-5 gnd Information (DE-588)4026899-8 gnd Visualisierung (DE-588)4188417-6 gnd JavaScript (DE-588)4420180-1 gnd |
| topic_facet | Information visualization Python (Computer program language) JavaScript (Computer program language) Python Programmiersprache Information Visualisierung JavaScript |
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