  Keeping abreast of current trends, technologies, and best practices in
visualization and data analysis is becoming increasingly difficult, especially
for fledgling data scientists. In this paper, we propose Lodestar, an
interactive computational notebook that allows users to quickly explore and
construct new data science workflows by selecting from a list of automated
analysis recommendations. We derive our recommendations from directed graphs of
known analysis states, with two input sources: one manually curated from online
data science tutorials, and another extracted through semi-automatic analysis
of a corpus of over 6,000 Jupyter notebooks. We evaluate Lodestar in a
formative study guiding our next set of improvements to the tool. Our results
suggest that users find Lodestar useful for rapidly creating data science
workflows.
