It doesn't count `failure` — just the number of rows. But neither does the pandas version: `pd_df.groupby(['date'])['failure'].count()` and `pd_df.groupby(['dat

It doesn't count `failure` — just the number of rows. But neither does the pandas version: `pd_df.groupby(['date'])['failure'].count()` and `pd_df.groupby(['date']).count()` are the same except the former returns a single `pd.Series` with the count and the latter produces a `pd.DataFrame` where each column has the same count (not super useful). e.g. > iris.groupby('species').count() sepal_length sepal_width petal_length petal_width species setosa 50 50 50 50 versicolor 50 50 50 50 virginica 50 50 50 50 vs. > iris.groupby('species')['sepal_length'].count() species setosa 50 versicolor 50 virginica 50