Data visualization with Python and JavaScript scrape, clean, explore, and transform your data
Chapter 2. A Language-Learning Bridge Between Python and JavaScript -- Similarities and Differences -- Interacting with the Code -- Python -- JavaScript -- Basic Bridge Work -- Style Guidelines, PEP 8, and use strict -- CamelCase Versus Underscore -- Importing Modules, Including Scripts -- JavaScrip...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
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| Ausgabe: | Second edition |
| Online-Zugang: | DE-1050 |
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| 245 | 1 | 0 | |a Data visualization with Python and JavaScript |b scrape, clean, explore, and transform your data |c Kryan Dale |
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| 264 | 1 | |a Beijing |b O'Reilly |c [2023] | |
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| 505 | 8 | |a Cover -- Copyright -- Table of Contents -- Preface -- The Second Edition -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Second Edition -- Introduction -- Who This Book Is For -- Minimal Requirements to Use This Book -- Why Python and JavaScript? -- Why Not Python in the Browser? -- Why Python for Data Processing -- Python's Getting Better All the Time -- What You'll Learn -- The Choice of Libraries -- Preliminaries -- The Dataviz Toolchain -- 1. Scraping Data with Scrapy -- 2. Cleaning Data with pandas | |
| 505 | 8 | |a 3. Exploring Data with pandas and Matplotlib -- 4. Delivering Your Data with Flask -- 5. Transforming Data into Interactive Visualizations with Plotly and D3 -- Smaller Libraries -- Using the Book -- A Little Bit of Context -- Summary -- Recommended Books -- Part I. Basic Toolkit -- Chapter 1. Development Setup -- The Accompanying Code -- Python -- Anaconda -- Installing Extra Libraries -- Virtual Environments -- JavaScript -- Content Delivery Networks -- Installing Libraries Locally -- Databases -- Getting MongoDB Up and Running -- Easy MongoDB with Docker -- Integrated Development Environments | |
| 505 | 8 | |a Data Containers: dicts, objects, lists, Arrays -- Functions -- Iterating: for Loops and Functional Alternatives -- Conditionals: if, else, elif, switch -- File Input and Output -- Classes and Prototypes -- Differences in Practice -- Method Chaining -- Enumerating a List -- Tuple Unpacking -- Collections -- Underscore -- Functional Array Methods and List Comprehensions -- Map, Reduce, and Filter with Python's Lambdas -- JavaScript Closures and the Module Pattern -- A Cheat Sheet -- Summary -- Chapter 3. Reading and Writing Data with Python -- Easy Does It -- Passing Data Around | |
| 505 | 8 | |a Working with System Files -- CSV, TSV, and Row-Column Data Formats -- JSON -- Dealing with Dates and Times -- SQL -- Creating the Database Engine -- Defining the Database Tables -- Adding Instances with a Session -- Querying the Database -- Easier SQL with Dataset -- MongoDB -- Dealing with Dates, Times, and Complex Data -- Summary -- Chapter 4. Webdev 101 -- The Big Picture -- Single-Page Apps -- Tooling Up -- The Myth of IDEs, Frameworks, and Tools -- A Text-Editing Workhorse -- Browser with Development Tools -- Terminal or Command Prompt -- Building a Web Page -- Serving Pages with HTTP | |
| 520 | |a Chapter 2. A Language-Learning Bridge Between Python and JavaScript -- Similarities and Differences -- Interacting with the Code -- Python -- JavaScript -- Basic Bridge Work -- Style Guidelines, PEP 8, and use strict -- CamelCase Versus Underscore -- Importing Modules, Including Scripts -- JavaScript Modules -- Keeping Your Namespaces Clean -- Outputting "Hello World!" -- Simple Data Processing -- String Construction -- Significant Whitespace Versus Curly Brackets -- Comments and Doc-Strings -- Declaring Variables Using let or var -- Strings and Numbers -- Booleans | ||
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| author | Dale, Kyran |
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| contents | Cover -- Copyright -- Table of Contents -- Preface -- The Second Edition -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Second Edition -- Introduction -- Who This Book Is For -- Minimal Requirements to Use This Book -- Why Python and JavaScript? -- Why Not Python in the Browser? -- Why Python for Data Processing -- Python's Getting Better All the Time -- What You'll Learn -- The Choice of Libraries -- Preliminaries -- The Dataviz Toolchain -- 1. Scraping Data with Scrapy -- 2. Cleaning Data with pandas 3. Exploring Data with pandas and Matplotlib -- 4. Delivering Your Data with Flask -- 5. Transforming Data into Interactive Visualizations with Plotly and D3 -- Smaller Libraries -- Using the Book -- A Little Bit of Context -- Summary -- Recommended Books -- Part I. Basic Toolkit -- Chapter 1. Development Setup -- The Accompanying Code -- Python -- Anaconda -- Installing Extra Libraries -- Virtual Environments -- JavaScript -- Content Delivery Networks -- Installing Libraries Locally -- Databases -- Getting MongoDB Up and Running -- Easy MongoDB with Docker -- Integrated Development Environments Data Containers: dicts, objects, lists, Arrays -- Functions -- Iterating: for Loops and Functional Alternatives -- Conditionals: if, else, elif, switch -- File Input and Output -- Classes and Prototypes -- Differences in Practice -- Method Chaining -- Enumerating a List -- Tuple Unpacking -- Collections -- Underscore -- Functional Array Methods and List Comprehensions -- Map, Reduce, and Filter with Python's Lambdas -- JavaScript Closures and the Module Pattern -- A Cheat Sheet -- Summary -- Chapter 3. Reading and Writing Data with Python -- Easy Does It -- Passing Data Around Working with System Files -- CSV, TSV, and Row-Column Data Formats -- JSON -- Dealing with Dates and Times -- SQL -- Creating the Database Engine -- Defining the Database Tables -- Adding Instances with a Session -- Querying the Database -- Easier SQL with Dataset -- MongoDB -- Dealing with Dates, Times, and Complex Data -- Summary -- Chapter 4. Webdev 101 -- The Big Picture -- Single-Page Apps -- Tooling Up -- The Myth of IDEs, Frameworks, and Tools -- A Text-Editing Workhorse -- Browser with Development Tools -- Terminal or Command Prompt -- Building a Web Page -- Serving Pages with HTTP |
| ctrlnum | (OCoLC)1371323763 (DE-599)BVBBV048833833 |
| edition | Second edition |
| format | Electronic eBook |
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| id | DE-604.BV048833833 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-24T09:42:06Z |
| institution | BVB |
| isbn | 9781098111823 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034099375 |
| oclc_num | 1371323763 |
| open_access_boolean | |
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| owner_facet | DE-1050 |
| physical | 1 Online-Ressource (xxxvi, 529 Seiten) |
| psigel | ZDB-30-PQE ZDB-30-PQE FHD01_PQE_Kauf |
| publishDate | 2023 |
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| publisher | O'Reilly |
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| spelling | Dale, Kyran Verfasser (DE-588)1112956220 aut Data visualization with Python and JavaScript scrape, clean, explore, and transform your data Kryan Dale Second edition Beijing O'Reilly [2023] 1 Online-Ressource (xxxvi, 529 Seiten) txt rdacontent c rdamedia cr rdacarrier Cover -- Copyright -- Table of Contents -- Preface -- The Second Edition -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Second Edition -- Introduction -- Who This Book Is For -- Minimal Requirements to Use This Book -- Why Python and JavaScript? -- Why Not Python in the Browser? -- Why Python for Data Processing -- Python's Getting Better All the Time -- What You'll Learn -- The Choice of Libraries -- Preliminaries -- The Dataviz Toolchain -- 1. Scraping Data with Scrapy -- 2. Cleaning Data with pandas 3. Exploring Data with pandas and Matplotlib -- 4. Delivering Your Data with Flask -- 5. Transforming Data into Interactive Visualizations with Plotly and D3 -- Smaller Libraries -- Using the Book -- A Little Bit of Context -- Summary -- Recommended Books -- Part I. Basic Toolkit -- Chapter 1. Development Setup -- The Accompanying Code -- Python -- Anaconda -- Installing Extra Libraries -- Virtual Environments -- JavaScript -- Content Delivery Networks -- Installing Libraries Locally -- Databases -- Getting MongoDB Up and Running -- Easy MongoDB with Docker -- Integrated Development Environments Data Containers: dicts, objects, lists, Arrays -- Functions -- Iterating: for Loops and Functional Alternatives -- Conditionals: if, else, elif, switch -- File Input and Output -- Classes and Prototypes -- Differences in Practice -- Method Chaining -- Enumerating a List -- Tuple Unpacking -- Collections -- Underscore -- Functional Array Methods and List Comprehensions -- Map, Reduce, and Filter with Python's Lambdas -- JavaScript Closures and the Module Pattern -- A Cheat Sheet -- Summary -- Chapter 3. Reading and Writing Data with Python -- Easy Does It -- Passing Data Around Working with System Files -- CSV, TSV, and Row-Column Data Formats -- JSON -- Dealing with Dates and Times -- SQL -- Creating the Database Engine -- Defining the Database Tables -- Adding Instances with a Session -- Querying the Database -- Easier SQL with Dataset -- MongoDB -- Dealing with Dates, Times, and Complex Data -- Summary -- Chapter 4. Webdev 101 -- The Big Picture -- Single-Page Apps -- Tooling Up -- The Myth of IDEs, Frameworks, and Tools -- A Text-Editing Workhorse -- Browser with Development Tools -- Terminal or Command Prompt -- Building a Web Page -- Serving Pages with HTTP Chapter 2. A Language-Learning Bridge Between Python and JavaScript -- Similarities and Differences -- Interacting with the Code -- Python -- JavaScript -- Basic Bridge Work -- Style Guidelines, PEP 8, and use strict -- CamelCase Versus Underscore -- Importing Modules, Including Scripts -- JavaScript Modules -- Keeping Your Namespaces Clean -- Outputting "Hello World!" -- Simple Data Processing -- String Construction -- Significant Whitespace Versus Curly Brackets -- Comments and Doc-Strings -- Declaring Variables Using let or var -- Strings and Numbers -- Booleans Erscheint auch als Druck-Ausgabe 978-1-098-11187-8 |
| spellingShingle | Dale, Kyran Data visualization with Python and JavaScript scrape, clean, explore, and transform your data Cover -- Copyright -- Table of Contents -- Preface -- The Second Edition -- Conventions Used in This Book -- Using Code Examples -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Second Edition -- Introduction -- Who This Book Is For -- Minimal Requirements to Use This Book -- Why Python and JavaScript? -- Why Not Python in the Browser? -- Why Python for Data Processing -- Python's Getting Better All the Time -- What You'll Learn -- The Choice of Libraries -- Preliminaries -- The Dataviz Toolchain -- 1. Scraping Data with Scrapy -- 2. Cleaning Data with pandas 3. Exploring Data with pandas and Matplotlib -- 4. Delivering Your Data with Flask -- 5. Transforming Data into Interactive Visualizations with Plotly and D3 -- Smaller Libraries -- Using the Book -- A Little Bit of Context -- Summary -- Recommended Books -- Part I. Basic Toolkit -- Chapter 1. Development Setup -- The Accompanying Code -- Python -- Anaconda -- Installing Extra Libraries -- Virtual Environments -- JavaScript -- Content Delivery Networks -- Installing Libraries Locally -- Databases -- Getting MongoDB Up and Running -- Easy MongoDB with Docker -- Integrated Development Environments Data Containers: dicts, objects, lists, Arrays -- Functions -- Iterating: for Loops and Functional Alternatives -- Conditionals: if, else, elif, switch -- File Input and Output -- Classes and Prototypes -- Differences in Practice -- Method Chaining -- Enumerating a List -- Tuple Unpacking -- Collections -- Underscore -- Functional Array Methods and List Comprehensions -- Map, Reduce, and Filter with Python's Lambdas -- JavaScript Closures and the Module Pattern -- A Cheat Sheet -- Summary -- Chapter 3. Reading and Writing Data with Python -- Easy Does It -- Passing Data Around Working with System Files -- CSV, TSV, and Row-Column Data Formats -- JSON -- Dealing with Dates and Times -- SQL -- Creating the Database Engine -- Defining the Database Tables -- Adding Instances with a Session -- Querying the Database -- Easier SQL with Dataset -- MongoDB -- Dealing with Dates, Times, and Complex Data -- Summary -- Chapter 4. Webdev 101 -- The Big Picture -- Single-Page Apps -- Tooling Up -- The Myth of IDEs, Frameworks, and Tools -- A Text-Editing Workhorse -- Browser with Development Tools -- Terminal or Command Prompt -- Building a Web Page -- Serving Pages with HTTP |
| title | Data visualization with Python and JavaScript scrape, clean, explore, and transform your data |
| title_auth | Data visualization with Python and JavaScript scrape, clean, explore, and transform your data |
| title_exact_search | Data visualization with Python and JavaScript scrape, clean, explore, and transform your data |
| title_full | Data visualization with Python and JavaScript scrape, clean, explore, and transform your data Kryan Dale |
| title_fullStr | Data visualization with Python and JavaScript scrape, clean, explore, and transform your data Kryan Dale |
| title_full_unstemmed | Data visualization with Python and JavaScript scrape, clean, explore, and transform your data Kryan Dale |
| title_short | Data visualization with Python and JavaScript |
| title_sort | data visualization with python and javascript scrape clean explore and transform your data |
| title_sub | scrape, clean, explore, and transform your data |
| work_keys_str_mv | AT dalekyran datavisualizationwithpythonandjavascriptscrapecleanexploreandtransformyourdata |