{"id":174703,"date":"2025-09-14T12:29:04","date_gmt":"2025-09-14T12:29:04","guid":{"rendered":"https:\/\/express24.ir\/d\/product\/%da%a9%d8%aa%d8%a7%d8%a8-%d8%aa%d8%ad%d9%84%db%8c%d9%84-%d8%af%d8%a7%d8%af%d9%87%d9%87%d8%a7-%d8%a8%d8%a7-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d9%88-%d9%be%d8%a7%db%8c%d8%a7%d8%b3\/"},"modified":"2025-09-14T12:29:08","modified_gmt":"2025-09-14T12:29:08","slug":"%da%a9%d8%aa%d8%a7%d8%a8-%d8%aa%d8%ad%d9%84%db%8c%d9%84-%d8%af%d8%a7%d8%af%d9%87%d9%87%d8%a7-%d8%a8%d8%a7-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d9%88-%d9%be%d8%a7%db%8c%d8%a7%d8%b3","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%da%a9%d8%aa%d8%a7%d8%a8-%d8%aa%d8%ad%d9%84%db%8c%d9%84-%d8%af%d8%a7%d8%af%d9%87%d9%87%d8%a7-%d8%a8%d8%a7-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d9%88-%d9%be%d8%a7%db%8c%d8%a7%d8%b3\/","title":{"rendered":"\u06a9\u062a\u0627\u0628 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647\u200c\u0647\u0627 \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0648 \u067e\u0627\u06cc\u200c\u0627\u0633\u067e\u0627\u0631\u06a9 (\u0646\u0633\u062e\u0647 \u0646\u0647\u0627\u06cc\u06cc)"},"content":{"rendered":"
\"\u062f\u0627\u0646\u0644\u0648\u062f<\/p>\n<\/div>\n\n\n\n\n\n\n\n\n\n\n
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\u0639\u0646\u0648\u0627\u0646 \u06a9\u062a\u0627\u0628 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/h3>\n<\/td>\n

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\u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0627 Python \u0648 Pyspark (\u0627\u0646\u062a\u0634\u0627\u0631 \u0646\u0647\u0627\u06cc\u06cc)<\/h3>\n<\/td>\n<\/tr>\n

\u0633\u0627\u0644 \u0627\u0646\u062a\u0634\u0627\u0631 \u06a9\u062a\u0627\u0628<\/td>\n2022<\/td>\n<\/tr>\n
\u0632\u0628\u0627\u0646<\/td>\n\u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n<\/tr>\n
\u0646\u0627\u0634\u0631<\/td>\nManning Publications<\/td>\n<\/tr>\n
\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n425<\/td>\n<\/tr>\n
ISBN10<\/td>\n1617297208<\/td>\n<\/tr>\n
ISBN13<\/td>\n9781617297205<\/td>\n<\/tr>\n
\u062d\u062c\u0645 \u0648 \u0641\u0631\u0645\u062a \u0641\u0627\u06cc\u0644<\/td>\nPDF | PDF, 14.58 MB<\/td>\n<\/tr>\n
\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646<\/td>\nJonathan Rioux<\/td>\n<\/tr>\n<\/table>\n

\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u06a9\u062a\u0627\u0628<\/h2>\n
Think big about your data! PySpark brings the powerful Spark big data processing engine to the Python ecosystem, letting you seamlessly scale up your data tasks and create lightning-fast pipelines.In Data Analysis with Python and PySpark you will learn how to:\u2022 Manage your data as it scales across multiple machines\u2022 Scale up your data programs with full confidence\u2022 Read and write data to and from a variety of sources and formats\u2022 Deal with messy data with PySpark\u2019s data manipulation functionality\u2022 Discover new data sets and perform exploratory data analysis\u2022 Build automated data pipelines that transform, summarize, and get insights from data\u2022 Troubleshoot common PySpark errors\u2022 Creating reliable long-running jobsData Analysis with Python and PySpark is your guide to delivering successful Python-driven data projects. Packed with relevant examples and essential techniques, this practical book teaches you to build pipelines for reporting, machine learning, and other data-centric tasks. Quick exercises in every chapter help you practice what you\u2019ve learned, and rapidly start implementing PySpark into your data systems. No previous knowledge of Spark is required.About the technologyThe Spark data processing engine is an amazing analytics factory: raw data comes in, insight comes out. PySpark wraps Spark\u2019s core engine with a Python-based API. It helps simplify Spark\u2019s steep learning curve and makes this powerful tool available to anyone working in the Python data ecosystem.About the bookData Analysis with Python and PySpark helps you solve the daily challenges of data science with PySpark. You\u2019ll learn how to scale your processing capabilities across multiple machines while ingesting data from any source\u2014whether that\u2019s Hadoop clusters, cloud data storage, or local data files. Once you\u2019ve covered the fundamentals, you\u2019ll explore the full versatility of PySpark by building machine learning pipelines, and blending Python, pandas, and PySpark code.What’s inside\u2022 Organizing your PySpark code\u2022 Managing your data, no matter the size\u2022 Scale up your data programs with full confidence\u2022 Troubleshooting common data pipeline problems\u2022 Creating reliable long-running jobsAbout the readerWritten for data scientists and data engineers comfortable with Python.About the authorAs a ML director for a data-driven software company, Jonathan Rioux uses PySpark daily. He teaches the software to data scientists, engineers, and data-savvy business analysts.<\/div>\n

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\r\n\t\t\t\u0634\u0645\u0627\u0631\u0647 \u062a\u0645\u0627\u0633: 09395106248 \r\n\r\n\t\t<\/td>\r\n\t<\/tr>\r\n\t\r\n<\/table>\r\n
\r\n\r\n<\/p>\n","protected":false},"excerpt":{"rendered":"

\u0639\u0646\u0648\u0627\u0646 \u06a9\u062a\u0627\u0628 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0627 Python \u0648 Pyspark (\u0627\u0646\u062a\u0634\u0627\u0631 \u0646\u0647\u0627\u06cc\u06cc) \u0633\u0627\u0644 \u0627\u0646\u062a\u0634\u0627\u0631 \u06a9\u062a\u0627\u0628 2022 \u0632\u0628\u0627\u0646 […]<\/p>\n","protected":false},"featured_media":174701,"comment_status":"open","ping_status":"closed","template":"","meta":{"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}}},"product_cat":[15],"product_tag":[],"class_list":{"0":"post-174703","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-15","7":"pmpro-has-access","8":"desktop-align-left","9":"tablet-align-left","10":"mobile-align-left","12":"first","13":"instock","14":"shipping-taxable","15":"purchasable","16":"product-type-variable"},"yoast_head":"\n\u06a9\u062a\u0627\u0628 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647\u200c\u0647\u0627 \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0648 \u067e\u0627\u06cc\u200c\u0627\u0633\u067e\u0627\u0631\u06a9 (\u0646\u0633\u062e\u0647 \u0646\u0647\u0627\u06cc\u06cc) - 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