marketing

the marketing dataset contains \(8\) features and \(40\) records as 40 days that report how much we spent, how many clicks, impressions and transactions we got, whether or not a display campaign was running, as well as our revenue, click-through-rate and conversion rate. the target feature is revenue and the remaining 7 variables are predictors.

 datasets

Provides a collection of helper functions and illustrative datasets to support learning and teaching of data science with R. The package is designed as a companion to the book <https://book-data-science-r.netlify.app>, making key data science techniques accessible to individuals with minimal coding experience. Functions include tools for data partitioning, performance evaluation, and data transformations (e.g., z-score and min-max scaling). The included datasets are curated to highlight practical applications in data exploration, modeling, and multivariate analysis. An early inspiration for the package came from an ancient Persian idiom about "eating the liveR," symbolizing deep and immersive engagement with knowledge.

Abdolreza Mohammadi

liver

Toolkit and Datasets for Data Science

Reza Mohammadi

Kevin Burke

marketing function

the <code>marketing</code> dataset, as a data frame, contains \(40\) rows and \(8\) columns (variables/features). the \(8\) variables are:<ul>
<li><code>spend</code>: daily send of money on PPC (apy-per-click).</li>
<li><code>clicks</code>: number of clicks on for that ad.</li>
<li><code>impressions</code>: amount of impressions per day.</li>
<li><code>display</code>: whether or not a display campaign was running.</li>
<li><code>transactions</code>: number of transactions per day.</li>
<li><code>click.rate</code>: click-through-rate.</li>
<li><code>conversion.rate</code>: conversion rate.</li>
<li><code>revenue</code>: daily revenue.</li>
</ul>

marketing: marketing data set

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