Coding Ref

To group by and then sort within groups in pandas, you can use the `sort_values`

method after the groupby method.

The `sort_values`

method allows you to specify the column to sort by, as well as the sorting order (ascending or descending).

Here is an example:

main.py

```
import pandas as pd
# create a sample dataframe
df = pd.DataFrame({'A': ['a', 'b', 'a', 'b'],
'B': [3, 2, 1, 4],
'C': [1, 2, 3, 4]})
# group by column A
grouped = df.groupby('A')
# sort the groups by column B in descending order
sorted_groups = grouped.apply(lambda x: x.sort_values('B', ascending=False))
# display the sorted groups
print(sorted_groups)
```

output

```
A B C
A
a 0 a 3 1
2 a 1 3
b 3 b 4 4
1 b 2 2
```

This will group the data by column `A`

and then sort each group by column `B`

in descending order.

The resulting dataframe will have the same structure as the original dataframe, but the rows within each group will be sorted by the values in column `B`

.

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