From Excel to R

Your manager asked for a t-test. Your Excel Data Analysis Toolpak gave you a wall of numbers with no explanation. There is a better way to do statistics — and it produces charts good enough to publish.

R is the programming language built specifically for statistics, data visualisation, and reproducible analysis. It is the tool of choice in academic research, pharmaceutical trials, financial modelling, and any field where "trust me, the numbers are right" is not good enough — you need to show your work, and show it cleanly.

From Spreadsheets to R teaches you statistical computing from the ground up, translating every Excel habit you already have into the R way of thinking.

Vectors work like Excel columns, but faster and without dragging a formula down. Data frames work like a worksheet, but can hold millions of rows without flinching. dplyr replaces filters and pivot tables with code that reads almost like English. And ggplot2 — the most respected charting library in data science — turns "a chart for the report" into a chart someone would frame.

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WHAT YOU WILL LEARN

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✔ R fundamentals through Excel — vectors, data frames, and functions explained using the columns, rows, and formulas you have used for years

✔ Data manipulation with the tidyverse — filter, sort, group, and summarise data using dplyr — the modern replacement for manual filters and pivot tables

✔ Reshaping data with tidyr — convert wide data to long and back, the single most useful skill for preparing data that Excel makes painfully manual

✔ Joining data frames — combine multiple tables properly with inner, left, and full joins — what VLOOKUP always wanted to be

✔ Professional visualisation with ggplot2 — build bar charts, histograms, box plots, scatter plots, and publication-ready graphics using the Grammar of Graphics, the system behind the cleanest charts in data journalism and science

✔ Real statistical testing — run t-tests, chi-square tests, and ANOVA with output you can actually interpret, not just a list of numbers

✔ Regression and prediction — build linear models, understand what the coefficients mean, and predict outcomes from your data with confidence

✔ Three complete real-world projects — a Sales Forecasting Report built with R Markdown, an Employee Analytics Dashboard built with Shiny, and a full A/B Test Analysis with an executive summary ready to present

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WHY R INSTEAD OF EXCEL'S DATA ANALYSIS TOOLPAK

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Excel's statistical tools are limited, hard to interpret, and impossible to reproduce reliably across a team. Run the same t-test twice in Excel and you cannot easily prove you used the same settings. Run it in R, and the script is the proof — anyone can re-run it and get the identical result, instantly, forever.

R was built by statisticians, for statistics. Every test, every distribution, every modelling technique you will ever need already exists as a tested, peer-reviewed package. You are not reinventing statistical methods — you are applying decades of rigorous, validated tools to your own data, correctly, the first time.

And the charts are not a side benefit — they are the reason data journalists, research labs, and increasingly business intelligence teams have standardised on ggplot2. Clean, layered, customisable, and genuinely beautiful by default.

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HOW THIS BOOK IS STRUCTURED

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Every chapter title tells you exactly what Excel habit you are upgrading: "From Filters to dplyr," "From Pivot Tables to tidyr," "From VLOOKUP to Joins," "From Excel Charts to ggplot2." There is never a moment where you are learning a concept disconnected from something you already do at work.

You will work in RStudio — free, professional-grade, and used by data teams worldwide. By the end of the statistics chapters, you will run and correctly interpret a real hypothesis test. By the end of the book, you will have built an interactive Shiny dashboard and a polished R Markdown report — two of the most requested deliverables in data-driven organisations today.

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WHO THIS BOOK IS FOR

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→ Analysts and researchers asked to produce statistical results that need to be defensible, reproducible, and clearly explained

→ Finance professionals who need forecasting, regression, and scenario modelling beyond what Excel's Toolpak can deliver

→ HR and people analytics teams who want to move from static headcount reports to interactive dashboards

→ Marketing and product teams running A/B tests who need to know whether a result is genuinely significant, not just "the number went up"

→ Anyone in academia, healthcare, or research moving from Excel-based analysis to a tool built for proper statistical rigor

No prior programming or statistics background required. Every statistical concept is explained in plain English before a single line of code appears.

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ABOUT THE FROM SPREADSHEETS TO CODE SERIES

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From Spreadsheets to R is Book 4 of the From Spreadsheets to Code series by Waskey Press — six practical books that teach Python, SQL, JavaScript, VBA, and AI Tools to Excel professionals who want to extend their capabilities without a computer science degree. Each book starts from Excel, builds to professional-grade technical skills, and delivers results through real-world projects with zero academic filler.