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Python in Excel for Data Analytics

Python in Excel for Data Analytics

By : George Mount
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Python in Excel for Data Analytics

Python in Excel for Data Analytics

By: George Mount

Overview of this book

Excel 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.
Table of Contents (7 chapters)
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Statistical inference is the point where analysis shifts from describing what happened to assessing how confident we can be in those results. In earlier chapters, you used exploratory data analysis (EDA) and visualization to spot patterns in the data. Those approaches help surface interesting questions, but they do not tell you how much weight to place on what you see. A bar chart might suggest one group outperforms another, but it cannot tell you whether that difference would persist in a new sample or if it is simply due to random variation.

In this chapter, you will use Python in Excel to run formal statistical tests that address these questions directly. Rather than relying on the Analysis ToolPak or manual formula construction, you will write Python code using libraries such as SciPy (specifically its scipy.stats module) and statsmodels, which are designed for statistical inference. These packages provide...

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Python in Excel for Data Analytics
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