It's time to wrap things up. Here's what we learned:

1. Some basic statistical functions you can use in pandas are:

   • describe() – shows multiple basic statistics,
   • count() – counts the number of non-empty values,
   • sum() – calculates the total sum,
   • min() / max() – finds the minimum/maximum value, respectively,
   • std() – calculates the standard deviation,
   • mean() – calculates the mean value,
   • quantile(...) – calculates specified quantiles:

     quantile([0.25,0.5,0.75])

     will calculate 1st, 2nd and 3rd quartiles
2. To group rows by a single column, use

   dataFrame.groupby('column')

3. To group rows by multiple columns, use

   dataFrame.groupby(['column1','column2'...])

4. The size() function shows the number of rows in each group.
5. You can access columns in grouped rows using square brackets: grouped['column'].
6. You can use statistical functions and sorting with grouped rows. For example:

   grouped['aces'].mean().sort_values(ascending=False)

Alright, how about a short quiz now?