Good. You probably noticed that the mean values of grouped rows were not sorted. Luckily, we can change that. We'll use the sort_values() function that you already know.
grouped['aces'].mean().sort_values(ascending=False)
We will get the following result:
| height | |
|---|---|
| 203 | 5837.000000 |
| 185 | 5060.000000 |
| 198 | 3658.666667 |
| 191 | 2366.500000 |
| 180 | 1689.000000 |
| Name: aces, dtype: float64 | |
Note that we can specify ascending/descending order inside sort_values(), but we don't specify any column names. The expression grouped['aces'].mean() creates a Series, so there is only one column (aces).
Group all movies by director (movies_by_director), show the average rating for each director, and sort the results from best to worst ratings.
Start by grouping the rows by directors:
movies.groupby('director')
Then, select the rating column, and use the mean() function, as in the instruction. Next, use the sort_values function.
