class MeasureValue(models.Model):
    org = models.ForeignKey(Org, null=True, blank=True)
    month = models.DateField()
    calc_value = models.FloatField(null=True, blank=True)
    percentile = models.FloatField(null=True, blank=True)

records = MeasureValue.objects.filter(month=month).values()
df = pd.DataFrame.from_records(records)
// use calc_value to set percentile on each row, using scipy's rankdata

for i, row in df.iterrows():
    mv = MeasureValue.objects.get(org=row.org, month=month)
    if (row.percentile is None) or np.isnan(row.percentile):
        row.percentile = None
    mv.percentile = row.percentile
    mv.save()

from django.db import transaction

with transaction.atomic():
    for i, row in df.iterrows():
        mv = MeasureValue.objects.get(org=row.org, month=month)

        if (row.percentile is None) or np.isnan(row.percentile):
            # if it's already None, why set it to None?
            row.percentile = None

        mv.percentile = row.percentile
        mv.save()

>>> objs = [
...    Entry.objects.create(headline='Entry 1'),
...    Entry.objects.create(headline='Entry 2'),
... ]
>>> objs[0].headline = 'This is entry 1'
>>> objs[1].headline = 'This is entry 2'
>>> Entry.objects.bulk_update(objs, ['headline'])