The severe underrepresentation of women contributors in the open-source software (OSS) community has been a widely recognized problem. Past research has found that, in public code collaboration, a gender-diverse team can enhance productivity and lower community smell. However, these benefits will be hindered when a team lacks gender diversity. To obtain a clearer image of the gender representation problem in open source, we aim to understand gender representation across 20 open-source ecosystems. While inherently limited by the ability of automatic name-based gender inference to capture true gender identities at an individual level, our census still provides valuable population-level insights. In this study, we investigate how gender distribution in open source has evolved over time and which specific ecosystems have been most successful at attracting and retaining women contributors.