Python in Excel for Data Pipelines: Turning Excel into a Live Data Hub with APIs, Automation, and Scheduled Refresh: 10 (Excel with Python) - Tapa blanda
Libro 9 de 9: Excel with Python
Sinopsis
Reactive Publishing
Python in Excel for Data Pipelines shows how to turn Excel from a static spreadsheet into a living, breathing data hub.
This book is for analysts, operators, and builders who already live in Excel but need real pipelines not copy-paste workflows. You’ll learn how to embed Python directly into Excel to pull data from APIs, automate transformations, schedule refreshes, and keep models continuously up to date without leaving the spreadsheet environment.
Rather than treating Excel as the final stop, this book reframes it as the control layer. Python becomes the engine underneath handling ingestion, validation, enrichment, and orchestration while Excel remains the interface decision-makers actually use.
Inside, you’ll learn how to:
Connect Excel to live data sources using REST APIs, webhooks, and authenticated endpoints
Build repeatable ingestion pipelines that clean, normalize, and version data automatically
Schedule refresh cycles so spreadsheets update themselves on defined intervals
Design resilient workflows that handle failures, stale data, and API limits
Combine Python logic with Excel formulas, tables, and Power Query for hybrid pipelines
Turn Excel into a lightweight data product for finance, ops, analytics, and reporting teams
The focus is practical and production-minded. No toy examples. No abstract data engineering theory. Every pattern is designed for real-world constraints where Excel is non-negotiable but manual work is unacceptable.
If you want Excel dashboards that stay current, models that refresh themselves, and spreadsheets that behave like systems instead of documents, this book gives you the architecture and tooling to make it happen.
"Sinopsis" puede pertenecer a otra edición de este libro.
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Python in Excel for Data Pipelines: Turning Excel into a Live Data Hub with APIs, Automation, and Scheduled Refresh (Excel with Python)
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Paperback. Condición: new. Paperback. Reactive PublishingPython in Excel for Data Pipelines shows how to turn Excel from a static spreadsheet into a living, breathing data hub.This book is for analysts, operators, and builders who already live in Excel but need real pipelines not copy-paste workflows. You'll learn how to embed Python directly into Excel to pull data from APIs, automate transformations, schedule refreshes, and keep models continuously up to date without leaving the spreadsheet environment.Rather than treating Excel as the final stop, this book reframes it as the control layer. Python becomes the engine underneath handling ingestion, validation, enrichment, and orchestration while Excel remains the interface decision-makers actually use.Inside, you'll learn how to: Connect Excel to live data sources using REST APIs, webhooks, and authenticated endpointsBuild repeatable ingestion pipelines that clean, normalize, and version data automaticallySchedule refresh cycles so spreadsheets update themselves on defined intervalsDesign resilient workflows that handle failures, stale data, and API limitsCombine Python logic with Excel formulas, tables, and Power Query for hybrid pipelinesTurn Excel into a lightweight data product for finance, ops, analytics, and reporting teamsThe focus is practical and production-minded. No toy examples. No abstract data engineering theory. Every pattern is designed for real-world constraints where Excel is non-negotiable but manual work is unacceptable.If you want Excel dashboards that stay current, models that refresh themselves, and spreadsheets that behave like systems instead of documents, this book gives you the architecture and tooling to make it happen. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798242347267
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Python in Excel for Data Pipelines (Paperback)
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Paperback. Condición: new. Paperback. Reactive PublishingPython in Excel for Data Pipelines shows how to turn Excel from a static spreadsheet into a living, breathing data hub.This book is for analysts, operators, and builders who already live in Excel but need real pipelines not copy-paste workflows. You'll learn how to embed Python directly into Excel to pull data from APIs, automate transformations, schedule refreshes, and keep models continuously up to date without leaving the spreadsheet environment.Rather than treating Excel as the final stop, this book reframes it as the control layer. Python becomes the engine underneath handling ingestion, validation, enrichment, and orchestration while Excel remains the interface decision-makers actually use.Inside, you'll learn how to: Connect Excel to live data sources using REST APIs, webhooks, and authenticated endpointsBuild repeatable ingestion pipelines that clean, normalize, and version data automaticallySchedule refresh cycles so spreadsheets update themselves on defined intervalsDesign resilient workflows that handle failures, stale data, and API limitsCombine Python logic with Excel formulas, tables, and Power Query for hybrid pipelinesTurn Excel into a lightweight data product for finance, ops, analytics, and reporting teamsThe focus is practical and production-minded. No toy examples. No abstract data engineering theory. Every pattern is designed for real-world constraints where Excel is non-negotiable but manual work is unacceptable.If you want Excel dashboards that stay current, models that refresh themselves, and spreadsheets that behave like systems instead of documents, this book gives you the architecture and tooling to make it happen. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798242347267
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Python in Excel for Data Pipelines : Turning Excel into a Live Data Hub with APIs, Automation, and Scheduled Refresh
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Taschenbuch. Condición: Neu. Neuware - Reactive PublishingPython in Excel for Data Pipelines shows how to turn Excel from a static spreadsheet into a living, breathing data hub.This book is for analysts, operators, and builders who already live in Excel but need real pipelines not copy-paste workflows. You'll learn how to embed Python directly into Excel to pull data from APIs, automate transformations, schedule refreshes, and keep models continuously up to date without leaving the spreadsheet environment.Rather than treating Excel as the final stop, this book reframes it as the control layer. Python becomes the engine underneath handling ingestion, validation, enrichment, and orchestration while Excel remains the interface decision-makers actually use.Inside, you'll learn how to: - Connect Excel to live data sources using REST APIs, webhooks, and authenticated endpoints- Build repeatable ingestion pipelines that clean, normalize, and version data automatically- Schedule refresh cycles so spreadsheets update themselves on defined intervals- Design resilient workflows that handle failures, stale data, and API limits- Combine Python logic with Excel formulas, tables, and Power Query for hybrid pipelines- Turn Excel into a lightweight data product for finance, ops, analytics, and reporting teamsThe focus is practical and production-minded. No toy examples. No abstract data engineering theory. Every pattern is designed for real-world constraints where Excel is non-negotiable but manual work is unacceptable.If you want Excel dashboards that stay current, models that refresh themselves, and spreadsheets that behave like systems instead of documents, this book gives you the architecture and tooling to make it happen. Nº de ref. del artículo: 9798242347267
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