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Python in Excel for Data Analytics: Unlock advanced analysis, visualization, and modeling inside Excel using Python
Not yet published
Expected 9 Feb 27Learn how to use Python directly in Excel to clean data, build models, and create advanced visualizations. A practical guide for analysts who want to extend Excel without leaving the spreadsheet environment.
Key FeaturesUse Python inside Excel for real analytical workflowsBuild visualizations, models, and simulations with easeCombine Excel structure with Python’s analytical powerBook DescriptionExcel is one of the most widely used tools for business analysis, but many analytical tasks quickly reach the limits of formulas and built-in features. Python in Excel changes that by allowing you to perform advanced analysis directly within the spreadsheet environment.
This book shows how to combine Excel’s structure and usability with Python’s analytical power. You will learn how to move data between Excel and Python DataFrames, clean and transform datasets efficiently, and explore data using modern visualization techniques.
As you progress, you will apply Python to real analytical problems including statistical testing, regression modeling, forecasting, and simulation. You will also learn how to integrate Python outputs into Excel dashboards and reports, creating workflows that are both powerful and practical.
Designed for Excel users with no prior programming experience, this book introduces Python concepts gradually and focuses on real-world applications rather than theory. By the end, you will be able to extend Excel in meaningful ways, helping you analyze data more effectively and support better decision-making.
What you will learnUse Python directly inside Excel cellsMove data between Excel and DataFramesClean and transform datasets efficientlyBuild advanced visualizations with PythonPerform statistical analysis and modelingForecast trends using time series methodsRun simulations to evaluate uncertaintyCombine Python results with Excel reportsWho this book is forThis book is for business, finance, and operations analysts who rely on Excel and want to go further with their analysis. It is ideal for professionals comfortable with formulas, tables, and PivotTables who want to explore Python without becoming programmers. Early-career data analysts, consultants, and Excel power users will benefit from learning how to extend Excel with more advanced analytical capabilities.
Table of ContentsGetting Started with Python in ExcelExploring and Analyzing Data with pandasVisualizing Data with SeabornPerforming Exploratory Data AnalysisRunning Statistical TestsBuilding Regression ModelsForecasting Time Series DataRunning Simulations and Scenario ModelsExtracting Insights from Text DataIntegrating Python with Native Excel FeaturesAccelerating Analysis with AI AssistanceContinuing Your Python in Excel Journey
Key FeaturesUse Python inside Excel for real analytical workflowsBuild visualizations, models, and simulations with easeCombine Excel structure with Python’s analytical powerBook DescriptionExcel is one of the most widely used tools for business analysis, but many analytical tasks quickly reach the limits of formulas and built-in features. Python in Excel changes that by allowing you to perform advanced analysis directly within the spreadsheet environment.
This book shows how to combine Excel’s structure and usability with Python’s analytical power. You will learn how to move data between Excel and Python DataFrames, clean and transform datasets efficiently, and explore data using modern visualization techniques.
As you progress, you will apply Python to real analytical problems including statistical testing, regression modeling, forecasting, and simulation. You will also learn how to integrate Python outputs into Excel dashboards and reports, creating workflows that are both powerful and practical.
Designed for Excel users with no prior programming experience, this book introduces Python concepts gradually and focuses on real-world applications rather than theory. By the end, you will be able to extend Excel in meaningful ways, helping you analyze data more effectively and support better decision-making.
What you will learnUse Python directly inside Excel cellsMove data between Excel and DataFramesClean and transform datasets efficientlyBuild advanced visualizations with PythonPerform statistical analysis and modelingForecast trends using time series methodsRun simulations to evaluate uncertaintyCombine Python results with Excel reportsWho this book is forThis book is for business, finance, and operations analysts who rely on Excel and want to go further with their analysis. It is ideal for professionals comfortable with formulas, tables, and PivotTables who want to explore Python without becoming programmers. Early-career data analysts, consultants, and Excel power users will benefit from learning how to extend Excel with more advanced analytical capabilities.
Table of ContentsGetting Started with Python in ExcelExploring and Analyzing Data with pandasVisualizing Data with SeabornPerforming Exploratory Data AnalysisRunning Statistical TestsBuilding Regression ModelsForecasting Time Series DataRunning Simulations and Scenario ModelsExtracting Insights from Text DataIntegrating Python with Native Excel FeaturesAccelerating Analysis with AI AssistanceContinuing Your Python in Excel Journey
242 pages, Paperback
Expected publication February 9, 2027
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