The GitHub platform allows repository maintainers and contributors to automate their activities through GitHub Actions work�ows or through the use of bots. The second category includes some built-in GitHub automation services (e.g., Dependabot), GitHub Apps, and automated bot accounts. Each of them interact with regular users in GitHub repositories. There has been little to no empirical research on the presence and use of such bots in large software ecosystems. We are also unaware of any study that has compared the use of bot accounts to the use of GitHub Apps in and across GitHub repositories. This paper aims to address this gap, through an empirical analysis of the presence and use of bot accounts and GitHub Apps in NumFocus, a large open source software ecosystem for data science. We analyse, during a three-month period, the activity sequences of 853 contributors within and across 59 GitHub organisations hosting 1,044 repositories. Using state-of-the-art bot identi�cation approaches we identi�ed activities of 802 humans, 34 bot accounts, 13 GitHub Apps and 4 built-in GitHub automation services. Based on this dataset we reveal behavioural differences in NumFocus between bots and humans on the one hand, and between different bot categories on the other hand.