How to create nested serialization on a single model in Django Rest Framework?

Question

I am working in DRF and trying to output nested serialized data from a single model. I am already using annotate() and getting the correct values for the data but I would like to go a step further and nest data if it is possible.

I have a model looking like this:

class Paragraph(models.Model):
    uuid = models.UUIDField()
    date = models.DateTimeField(null=True)
    author = models.CharField(max_length=200, null=True)
    paragraph = models.TextField(null=False, blank=False)
    value = models.CharField(max_length=20, null=True)
    score = models.DecimalField(max_digits=8, decimal_places=4, null=True)
    final_score = models.DecimalField(max_digits=8, decimal_places=4, null=True)

and my serializer looks like this:

class ParagraphGroupByAuthorDateListGeneric(serializers.ModelSerializer):
    date = serializers.DateTimeField()
    total = serializers.DecimalField(max_digits=8, decimal_places=4)
    sum_positive = serializers.DecimalField(max_digits=8, decimal_places=4)
    count_positive = serializers.IntegerField(min_value=0)
    sum_negative = serializers.DecimalField(max_digits=8, decimal_places=4)
    count_negative = serializers.IntegerField(min_value=0)
    count_neutral = serializers.IntegerField(min_value=0)
    average = serializers.DecimalField(max_digits=8, decimal_places=4)
    count = serializers.IntegerField(min_value=0)

    class Meta:
        model = Paragraph
        fields = ['date', 'total', 'average', 'count', 'author',
                  'sum_positive', 'sum_negative',
                  'count_positive', 'count_negative', 'count_neutral'
                  ]

My view looks like this:

class ParagraphGroupByAuthorDateListGeneric(ListAPIView):
    queryset = Paragraph.objects.all()
    pagination_class = MyLimitOffsetPagination
    serializer_class = ParagraphGroupByAuthorDateListGeneric
    filter_backends = [DjangoFilterBackend, filters.OrderingFilter]
    filterset_fields = ['uuid', 'date', 'author']
    ordering_fields = ['total', 'average', 'sum_positive', 'sum_negative']

    def get_queryset(self):
        return Paragraph.objects.values('author', 'date').annotate(
            total=Sum('final_score'),
            average=Avg('final_score'),
            count=Count('final_score'),
            sum_positive=Sum('final_score', filter=Q(value='positive')),
            count_positive=Count('final_score', filter=Q(value='positive')),
            sum_negative=Sum('final_score', filter=Q(value='negative')),
            count_negative=Count('final_score', filter=Q(value='negative')),
            count_neutral=Count('final_score', filter=Q(value='negative'))
        ).order_by('author', 'date')

and I' am getting this result.

 "results": [
        {
            "date": "2022-09-29T00:00:00Z",
            "total": "0.9637",
            "average": "0.1377",
            "count": 7,
            "author": "Peter",
            "sum_positive": "0.9637",
            "sum_negative": null,
            "count_positive": 1,
            "count_negative": 0,
            "count_neutral": 0
        },
        {
            "date": "2022-10-03T00:00:00Z",
            "total": "0.9307",
            "average": "0.1034",
            "count": 9,
            "author": "Peter",
            "sum_positive": "1.9287",
            "sum_negative": "-0.9980",
            "count_positive": 2,
            "count_negative": 1,
            "count_neutral": 1
        },
        {
            "date": "2022-10-06T00:00:00Z",
            "total": "2.9870",
            "average": "0.3734",
            "count": 8,
            "author": "Ana",
            "sum_positive": "2.9870",
            "sum_negative": null,
            "count_positive": 3,
            "count_negative": 0,
            "count_neutral": 0
        },
        {
            "date": "2022-10-11T00:00:00Z",
            "total": "0.7079",
            "average": "0.0787",
            "count": 9,
            "author": "Ana",
            "sum_positive": "0.7079",
            "sum_negative": null,
            "count_positive": 1,
            "count_negative": 0,
            "count_neutral": 0
        },       

but I would like to somehow get this or similar to this, grouped by author:

"results": [
    "Peter": [
        {
            "date": "2022-09-29T00:00:00Z",
            "total": "0.9637",
            "average": "0.1377",
            "count": 7,
            "sum_positive": "0.9637",
            "sum_negative": null,
            "count_positive": 1,
            "count_negative": 0,
            "count_neutral": 0
        },
        {
            "date": "2022-10-03T00:00:00Z",
            "total": "0.9307",
            "average": "0.1034",
            "count": 9,
            "sum_positive": "1.9287",
            "sum_negative": "-0.9980",
            "count_positive": 2,
            "count_negative": 1,
            "count_neutral": 1
        },
    ],
    "Ana": [
        {
            "date": "2022-10-06T00:00:00Z",
            "total": "2.9870",
            "average": "0.3734",
            "count": 8,
            "sum_positive": "2.9870",
            "sum_negative": null,
            "count_positive": 3,
            "count_negative": 0,
            "count_neutral": 0
        },
        {
            "date": "2022-10-11T00:00:00Z",
            "total": "0.7079",
            "average": "0.0787",
            "count": 9,
            "sum_positive": "0.7079",
            "sum_negative": null,
            "count_positive": 1,
            "count_negative": 0,
            "count_neutral": 0
        }
    ]
]

What would be the best way to approach the problem?