A large number of web data repositories are hidden behind restrictive web interfaces, making it an important challenge to enable data analytics over these hidden web databases. Most existing techniques assume a form-like web interface which consists solely of categorical attributes (or numeric ones that can be discretized). Nonetheless, many real-world web interfaces (of hidden databases) also feature checkbox interfaces—e.g., the specification of a set of desired features, such as A/C, navigation, etc., for a car-search website like Yahoo! Autos. We find that, for the purpose of data analytics, such checkbox-represented attributes differ fundamentally from the categorical/numerical ones that were traditionally studied. In this paper, we address the problem of data analytics over hidden databases with checkbox interfaces. Extensive experiments on both synthetic and real datasets demonstrate the accuracy and efficiency of our proposed algorithms.