Although the applications of data science and machine learning in solar engineering have increased tremendously in the past decade, most of the solar datasets come from heterogeneous and autonomous sources. For that reason, identifying spatially collocated and temporally aligned datasets has always been time consuming, or even frustrating sometimes, in data-driven solar research. In this regard, I present a new R package-SolarData-for easy access of some publicly available solar datasets. In version 1.0, a total of 5 datasets are included: (1) NREL physical solar model version 3; (2) NREL Oahu solar measurement grid; (3) NOAA surface radiation network; (4) SoDa Linke turbidity factor; and (5) NASA shuttle radar topography mission. This paper provides an overview of each of dataset, and gives code segments that exemplify the usage of the package. Furthermore, in the appendices, a series of self-contained R scripts are used to provide perspectives on how these datasets can be used in solar research. To promote the widespread uptake of this R package, and to facilitate future contribution and collaboration, all contents herein described are made available on GitHub. This paper is the first Data Article, a new submission type offered by the Solar Energy journal.