The choice of what to read is both influenced by and indicative of such factors as a person’s beliefs, culture, gender, and socioeconomic status. However, obtaining data including such personal attributes, as well as detailed reading habits and activities of individuals is difficult and would usually require either (i) data from e-readers, such as the Amazon Kindle, or from library checkouts, both of which are hard to obtain, or (ii) distributing questionnaires and conducting interviews, which can be expensive and suffers from recall bias. In this study, we present a dataset of over 40 million reading instances of 1,872,677 unique individuals collected from Goodreads. Goodreads is a book-cataloging social media platform with millions of users, where users share comments on the books they have read, while creating and maintaining social connections. We enrich the dataset with gender and location information. The dataset presented in this study can be used to perform cross-national and cross-gender analyses of reading behavior among book enthusiasts.