API pain points off the top of my head:

- There are both `pivot` and `pivot_table` methods which behave slightly differently. I'd have to look up why `pivot` exists; I've learned simply to reach for `pivot_table` every time, since it aggregates more flexibly.

- The dreaded SettingWithCopyWarning is a huge pain for new pandas users, and simply should not exist in any mature data analysis software.

- Unlike in SQL, in pandas you can take a data table (a DataFrame) and group it by one or more columns without immediately specifying an aggregation function. The result of this `groupby` operation is a "groupby object", which contains all the information of the input DataFrame, but behaves completely differently from a DataFrame. By contrast, in R's tidyverse, my understanding is that when you group a tibble (the tidyverse's data table), the result is still a tibble, just grouped.

- It took a while to mentally sort out the similarities and differences of merge, join, append, and concatenate. In practice, I almost always reach for `merge` or `concat`.