Google Earth Engine (Gorelick et al., 2017) is a cloud computing platform designed for planetary-scale environmental data analysis. Its multi-petabyte data catalog and computation services are accessed via an Internet-accessible API. The API is exposed through JavaScript and Python client libraries. Google provides a browser-based IDE for the JavaScript API, and while convenient and useful for rapid data exploration and script development, it does not allow third-party package integration, relying solely on Google Maps and Google Charts for data visualization, and proprietary systems for metadata viewing and asset management. In contrast, the Python and Node.js distributions offer much flexibility for developers to integrate with third-party libraries. However, without the structure of a dedicated IDE, casual users can be left directionless and daunted. A significant gap exists between these two offerings (Google-supported JavaScript IDE and base client libraries) where convenience and flexibility meet. We propose to fill this gap with an R package that wraps the Earth Engine Python API to provide R users with a familiar interface, rapid development features, and flexibility to analyze data using open-source, third-party packages. rgee is an Earth Engine (EE) client library for R that allows users to leverage the strengths of the R spatial ecosystem and Google Earth Engine in the same workflow. All of the Earth Engine Python API classes, modules, and functions are made available through the reticulate package (JJ Allaire & Eddelbuettel, 2017), which embeds a Python session within an R session, enabling seamless interoperability. Additionally, rgee adds several new features such as (i) new I/O design, (ii) interactive map display, (iii) easy extraction of time series, (iv) asset management interface, and (v) metadata display. In addition, rgee also makes it possible to execute Earth Engine Python code from within R, making the translation of large Python projects unnecessary.