django annotate count is giving wrong output - django

Suppose
class Comment(models.Model):
...
likes = models.ManyToManyField(User,...)
class Post
...
content = models.CharField(...)
likes = models.ManyToManyFiled(User,...)
comment = models.ManyToManyField(Comment,...)
Now if I run
Statement1
Post.objects.annotate(likecount=Count('likes')).values('content','likecount')
Output:
<QuerySet [{'content': 'delta', 'likecount': 3}, {'content': 'gamma', 'likecount': 6}, {'content': 'beta', 'likecount': 7}, {'content': 'alpha', 'likecount': 3}]>
Statement2
Post.objects.annotate(commentlikecount=Count('comment__likes')).values('content','commentlikecount')
Output:
<QuerySet [{'content': 'delta', 'commentlikecount': 6}, {'content': 'gamma', 'commentlikecount': 0}, {'content': 'beta', 'commentlikecount': 3}, {'content': 'alpha', 'commentlikecount': 0}]>
Statement3
Post.objects.annotate(likecount=Count('likes'),commentlikecount=Count('comment__likes')).values('content','likecount','commentlikecount')
Output:
<QuerySet [{'content': 'delta', 'likecount': 18, 'commentlikecount': 18}, {'content': 'gamma', 'likecount': 6, 'commentlikecount': 0}, {'content': 'beta', 'likecount': 21, 'commentlikecount': 21}, {'content': 'alpha', 'likecount': 3, 'commentlikecount': 0}]>
Why the output of third statement is this instead of
<QuerySet [{'content': 'delta', 'likecount': 3, 'commentlikecount': 6}, {'content': 'gamma', 'likecount': 6, 'commentlikecount': 0}, {'content': 'beta', 'likecount': 7, 'commentlikecount': 3}, {'content': 'alpha', 'likecount': 3, 'commentlikecount': 0}]>
How can i have this as output?

Related

How add 0 when TruncWeek's week no result in Django Query?

I want query the issue's count of group by weekly.
query1 = MyModel.object.filter(issue_creator__in=group.user_set.all()).\
annotate(week=TruncWeek('issue_creat_date')).values('week').annotate(count=Count('id')).order_by('week'))
the query result is OK. the queryset result:
[
{'week': datetime.datetime(2022, 1, 3, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 9},
{'week': datetime.datetime(2022, 1, 10, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 12},
{'week': datetime.datetime(2022, 1, 17, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 10},
{'week': datetime.datetime(2022, 2, 7, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1},
{'week': datetime.datetime(2022, 2, 14, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 6},
{'week': datetime.datetime(2022, 2, 21, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 11},
{'week': datetime.datetime(2022, 2, 28, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1}
]
but 20220101-20220301 has 9 weeks:
[
datetime.datetime(2022, 1, 3, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 10, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 17, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 24, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 1, 31, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 7, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 14, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 21, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>),
datetime.datetime(2022, 2, 28, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>)
]
I want add zero when that week no result as this result:
[
{'week': datetime.datetime(2022, 1, 3, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 9},
{'week': datetime.datetime(2022, 1, 10, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 12},
{'week': datetime.datetime(2022, 1, 17, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 10},
{'week': datetime.datetime(2022, 1, 24, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 0},
{'week': datetime.datetime(2022, 1, 31, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 0},
{'week': datetime.datetime(2022, 2, 7, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1},
{'week': datetime.datetime(2022, 2, 14, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 6},
{'week': datetime.datetime(2022, 2, 21, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 11},
{'week': datetime.datetime(2022, 2, 28, 0, 0, tzinfo=<DstTzInfo 'Europe/Stockholm' CEST+2:00:00 DST>), 'count': 1}
]
how to write the right queryset?
Thanks.

Django method for None value Coalesce.
from django.db.models.functions import Coalesce
query1 = MyModel.object.filter(issue_creator__in=group.user_set.all()).\
annotate(week=TruncWeek('issue_creat_date')).values('week').annotate(count=Count('id')).order_by('week'))

Looking for applications of BDDs to problems involving x,y concept

I am looking at the applications of BDD to figure out if it's possible to implement the x,y concept there.
Let me explain.
Let's say I have z of something to distribute in an x,y coordinate plane. The constraints are:
All the z items have to be placed in the x,y coordinate plane.
Some of the z items have to be a certain distance away from each other.
I think integer linear programming can sort this out. For example, with a set of equations, I can represent the constraints above and do linear programming to solve for the exact locations.
But what I am asking is if BDD can help with this?
In other words, can Binary Decision Diagram represent x,y coordinates and can I represent the above constraints with Boolean functions (equivalent to the set of equations above) and BDDs be manipulated to sort out the above constraints for exact locations just like linear programming?
I do not have any concrete examples to show but I think representing x,y coordinates equivalent in Binary is a place to start?

Yes, it is possible to encode the given integer-valued problem of placement over a plane using binary decision diagrams, and thus compute answers (as satisfying assignments). For example, using the Python package omega (which uses the Python package dd for BDD computations):
from omega.symbolic import fol
fol = _fol.Context()
# Register integer-valued variables, with ranges of representation using BDDs
fol.declare(x1=(0, 11), y1=(0, 11), x2=(0, 11), y2=(0, 11))
# Encode the problem:
#
# Two points on a Euclidean plane are represented by their Cartesian coordinates
# `x1, y1` and `x2, y2`.
# Each point is in the square mesh `x \in 1..10 /\ y \in 1..10`.
#
# Note that the variables are declared with larger domains,
# in order to ensure that this boundary constraint is representable with the
# resulting BDDs.
#
# The distance between the two points should be the square root of 10.
expr = r'''
(x1 >= 1) /\ (x1 <= 10)
/\ (x2 >= 1) /\ (x2 <= 10)
/\ (y1 >= 1) /\ (y1 <= 10)
/\ (y2 >= 1) /\ (y1 <= 10)
/\ (x1 - x2) * (x1 - x2) + (y1 - y2) * (y1 - y2) = 10
'''
# Solve the problem, by adding creating a BDD for it
u = fol.add_expr(expr)
# Enumerate all solutions (i.e., all satisfying assignments)
# These are all the pairs of points within the box mesh x \in 1..10 /\ y \in 1..10
# that have a distance equal to the square root of 10.
assignments = list(fol.pick_iter(u))
print(assignments)
Using BDDs with distance constraints as above can lead to BDDs that are exponential in size in the number of variables. The reason is that representing multiplication can lead to exponentially-sized BDDs, as proved in https://doi.org/10.1109/12.73590 .
If the constraints are not distance between points, but distance along each axis (i.e., an inequality or equality constraint on the absolute value of x1 - x2 or y1 - y2, or on both), then exponential complexity is avoided.
The above solves the placement problem over a mesh. This is a discrete placement problem. The continuous placement problem cannot be solved with binary decision diagrams, because it requires floating-point arithmetic.
The program above prints:
[{'x1': 4, 'y1': 5, 'x2': 1, 'y2': 4},
{'x1': 4, 'y1': 9, 'x2': 1, 'y2': 8},
{'x1': 4, 'y1': 3, 'x2': 1, 'y2': 4},
{'x1': 4, 'y1': 7, 'x2': 1, 'y2': 8},
{'x1': 4, 'y1': 1, 'x2': 1, 'y2': 2},
{'x1': 4, 'y1': 5, 'x2': 1, 'y2': 6},
{'x1': 4, 'y1': 9, 'x2': 1, 'y2': 10},
{'x1': 4, 'y1': 3, 'x2': 1, 'y2': 2},
{'x1': 4, 'y1': 7, 'x2': 1, 'y2': 6},
{'x1': 4, 'y1': 4, 'x2': 1, 'y2': 5},
{'x1': 4, 'y1': 8, 'x2': 1, 'y2': 9},
{'x1': 4, 'y1': 2, 'x2': 1, 'y2': 1},
{'x1': 4, 'y1': 6, 'x2': 1, 'y2': 5},
{'x1': 4, 'y1': 10, 'x2': 1, 'y2': 9},
{'x1': 4, 'y1': 4, 'x2': 1, 'y2': 3},
{'x1': 4, 'y1': 8, 'x2': 1, 'y2': 7},
{'x1': 4, 'y1': 2, 'x2': 1, 'y2': 3},
{'x1': 4, 'y1': 6, 'x2': 1, 'y2': 7},
{'x1': 4, 'y1': 10, 'x2': 1, 'y2': 11},
{'x1': 4, 'y1': 1, 'x2': 5, 'y2': 4},
{'x1': 4, 'y1': 5, 'x2': 5, 'y2': 8},
{'x1': 4, 'y1': 9, 'x2': 5, 'y2': 12},
{'x1': 4, 'y1': 7, 'x2': 5, 'y2': 4},
{'x1': 4, 'y1': 5, 'x2': 5, 'y2': 2},
{'x1': 4, 'y1': 9, 'x2': 5, 'y2': 6},
{'x1': 4, 'y1': 3, 'x2': 5, 'y2': 6},
{'x1': 4, 'y1': 7, 'x2': 5, 'y2': 10},
{'x1': 4, 'y1': 4, 'x2': 5, 'y2': 1},
{'x1': 4, 'y1': 8, 'x2': 5, 'y2': 5},
{'x1': 4, 'y1': 2, 'x2': 5, 'y2': 5},
{'x1': 4, 'y1': 6, 'x2': 5, 'y2': 9},
{'x1': 4, 'y1': 10, 'x2': 5, 'y2': 13},
{'x1': 4, 'y1': 4, 'x2': 5, 'y2': 7},
{'x1': 4, 'y1': 8, 'x2': 5, 'y2': 11},
{'x1': 4, 'y1': 6, 'x2': 5, 'y2': 3},
{'x1': 4, 'y1': 10, 'x2': 5, 'y2': 7},
{'x1': 2, 'y1': 1, 'x2': 1, 'y2': 4},
{'x1': 2, 'y1': 5, 'x2': 1, 'y2': 8},
{'x1': 2, 'y1': 9, 'x2': 1, 'y2': 12},
{'x1': 2, 'y1': 7, 'x2': 1, 'y2': 4},
{'x1': 2, 'y1': 5, 'x2': 1, 'y2': 2},
{'x1': 2, 'y1': 9, 'x2': 1, 'y2': 6},
{'x1': 2, 'y1': 3, 'x2': 1, 'y2': 6},
{'x1': 2, 'y1': 7, 'x2': 1, 'y2': 10},
{'x1': 2, 'y1': 4, 'x2': 1, 'y2': 1},
{'x1': 2, 'y1': 8, 'x2': 1, 'y2': 5},
{'x1': 2, 'y1': 2, 'x2': 1, 'y2': 5},
{'x1': 2, 'y1': 6, 'x2': 1, 'y2': 9},
{'x1': 2, 'y1': 10, 'x2': 1, 'y2': 13},
{'x1': 2, 'y1': 4, 'x2': 1, 'y2': 7},
{'x1': 2, 'y1': 8, 'x2': 1, 'y2': 11},
{'x1': 2, 'y1': 6, 'x2': 1, 'y2': 3},
{'x1': 2, 'y1': 10, 'x2': 1, 'y2': 7},
{'x1': 2, 'y1': 5, 'x2': 5, 'y2': 4},
{'x1': 2, 'y1': 9, 'x2': 5, 'y2': 8},
{'x1': 2, 'y1': 3, 'x2': 5, 'y2': 4},
{'x1': 2, 'y1': 7, 'x2': 5, 'y2': 8},
{'x1': 2, 'y1': 1, 'x2': 5, 'y2': 2},
{'x1': 2, 'y1': 5, 'x2': 5, 'y2': 6},
{'x1': 2, 'y1': 9, 'x2': 5, 'y2': 10},
{'x1': 2, 'y1': 3, 'x2': 5, 'y2': 2},
{'x1': 2, 'y1': 7, 'x2': 5, 'y2': 6},
{'x1': 2, 'y1': 4, 'x2': 5, 'y2': 5},
{'x1': 2, 'y1': 8, 'x2': 5, 'y2': 9},
{'x1': 2, 'y1': 2, 'x2': 5, 'y2': 1},
{'x1': 2, 'y1': 6, 'x2': 5, 'y2': 5},
{'x1': 2, 'y1': 10, 'x2': 5, 'y2': 9},
{'x1': 2, 'y1': 4, 'x2': 5, 'y2': 3},
{'x1': 2, 'y1': 8, 'x2': 5, 'y2': 7},
{'x1': 2, 'y1': 2, 'x2': 5, 'y2': 3},
{'x1': 2, 'y1': 6, 'x2': 5, 'y2': 7},
{'x1': 2, 'y1': 10, 'x2': 5, 'y2': 11},
{'x1': 6, 'y1': 1, 'x2': 5, 'y2': 4},
{'x1': 6, 'y1': 5, 'x2': 5, 'y2': 8},
{'x1': 6, 'y1': 9, 'x2': 5, 'y2': 12},
{'x1': 6, 'y1': 7, 'x2': 5, 'y2': 4},
{'x1': 6, 'y1': 5, 'x2': 5, 'y2': 2},
{'x1': 6, 'y1': 9, 'x2': 5, 'y2': 6},
{'x1': 6, 'y1': 3, 'x2': 5, 'y2': 6},
{'x1': 6, 'y1': 7, 'x2': 5, 'y2': 10},
{'x1': 6, 'y1': 4, 'x2': 5, 'y2': 1},
{'x1': 6, 'y1': 8, 'x2': 5, 'y2': 5},
{'x1': 6, 'y1': 2, 'x2': 5, 'y2': 5},
{'x1': 6, 'y1': 6, 'x2': 5, 'y2': 9},
{'x1': 6, 'y1': 10, 'x2': 5, 'y2': 13},
{'x1': 6, 'y1': 4, 'x2': 5, 'y2': 7},
{'x1': 6, 'y1': 8, 'x2': 5, 'y2': 11},
{'x1': 6, 'y1': 6, 'x2': 5, 'y2': 3},
{'x1': 6, 'y1': 10, 'x2': 5, 'y2': 7},
{'x1': 4, 'y1': 1, 'x2': 3, 'y2': 4},
{'x1': 4, 'y1': 5, 'x2': 3, 'y2': 8},
{'x1': 4, 'y1': 9, 'x2': 3, 'y2': 12},
{'x1': 4, 'y1': 7, 'x2': 3, 'y2': 4},
{'x1': 4, 'y1': 5, 'x2': 3, 'y2': 2},
{'x1': 4, 'y1': 9, 'x2': 3, 'y2': 6},
{'x1': 4, 'y1': 3, 'x2': 3, 'y2': 6},
{'x1': 4, 'y1': 7, 'x2': 3, 'y2': 10},
{'x1': 4, 'y1': 4, 'x2': 3, 'y2': 1},
{'x1': 4, 'y1': 8, 'x2': 3, 'y2': 5},
{'x1': 4, 'y1': 2, 'x2': 3, 'y2': 5},
{'x1': 4, 'y1': 6, 'x2': 3, 'y2': 9},
{'x1': 4, 'y1': 10, 'x2': 3, 'y2': 13},
{'x1': 4, 'y1': 4, 'x2': 3, 'y2': 7},
{'x1': 4, 'y1': 8, 'x2': 3, 'y2': 11},
{'x1': 4, 'y1': 6, 'x2': 3, 'y2': 3},
{'x1': 4, 'y1': 10, 'x2': 3, 'y2': 7},
{'x1': 4, 'y1': 5, 'x2': 7, 'y2': 4},
{'x1': 4, 'y1': 9, 'x2': 7, 'y2': 8},
{'x1': 4, 'y1': 3, 'x2': 7, 'y2': 4},
{'x1': 4, 'y1': 7, 'x2': 7, 'y2': 8},
{'x1': 4, 'y1': 1, 'x2': 7, 'y2': 2},
{'x1': 4, 'y1': 5, 'x2': 7, 'y2': 6},
{'x1': 4, 'y1': 9, 'x2': 7, 'y2': 10},
{'x1': 4, 'y1': 3, 'x2': 7, 'y2': 2},
{'x1': 4, 'y1': 7, 'x2': 7, 'y2': 6},
{'x1': 4, 'y1': 4, 'x2': 7, 'y2': 5},
{'x1': 4, 'y1': 8, 'x2': 7, 'y2': 9},
{'x1': 4, 'y1': 2, 'x2': 7, 'y2': 1},
{'x1': 4, 'y1': 6, 'x2': 7, 'y2': 5},
{'x1': 4, 'y1': 10, 'x2': 7, 'y2': 9},
{'x1': 4, 'y1': 4, 'x2': 7, 'y2': 3},
{'x1': 4, 'y1': 8, 'x2': 7, 'y2': 7},
{'x1': 4, 'y1': 2, 'x2': 7, 'y2': 3},
{'x1': 4, 'y1': 6, 'x2': 7, 'y2': 7},
{'x1': 4, 'y1': 10, 'x2': 7, 'y2': 11},
{'x1': 2, 'y1': 1, 'x2': 3, 'y2': 4},
{'x1': 2, 'y1': 5, 'x2': 3, 'y2': 8},
{'x1': 2, 'y1': 9, 'x2': 3, 'y2': 12},
{'x1': 2, 'y1': 7, 'x2': 3, 'y2': 4},
{'x1': 2, 'y1': 5, 'x2': 3, 'y2': 2},
{'x1': 2, 'y1': 9, 'x2': 3, 'y2': 6},
{'x1': 2, 'y1': 3, 'x2': 3, 'y2': 6},
{'x1': 2, 'y1': 7, 'x2': 3, 'y2': 10},
{'x1': 2, 'y1': 4, 'x2': 3, 'y2': 1},
{'x1': 2, 'y1': 8, 'x2': 3, 'y2': 5},
{'x1': 2, 'y1': 2, 'x2': 3, 'y2': 5},
{'x1': 2, 'y1': 6, 'x2': 3, 'y2': 9},
{'x1': 2, 'y1': 10, 'x2': 3, 'y2': 13},
{'x1': 2, 'y1': 4, 'x2': 3, 'y2': 7},
{'x1': 2, 'y1': 8, 'x2': 3, 'y2': 11},
{'x1': 2, 'y1': 6, 'x2': 3, 'y2': 3},
{'x1': 2, 'y1': 10, 'x2': 3, 'y2': 7},
{'x1': 6, 'y1': 5, 'x2': 3, 'y2': 4},
{'x1': 6, 'y1': 9, 'x2': 3, 'y2': 8},
{'x1': 6, 'y1': 3, 'x2': 3, 'y2': 4},
{'x1': 6, 'y1': 7, 'x2': 3, 'y2': 8},
{'x1': 6, 'y1': 1, 'x2': 3, 'y2': 2},
{'x1': 6, 'y1': 5, 'x2': 3, 'y2': 6},
{'x1': 6, 'y1': 9, 'x2': 3, 'y2': 10},
{'x1': 6, 'y1': 3, 'x2': 3, 'y2': 2},
{'x1': 6, 'y1': 7, 'x2': 3, 'y2': 6},
{'x1': 6, 'y1': 4, 'x2': 3, 'y2': 5},
{'x1': 6, 'y1': 8, 'x2': 3, 'y2': 9},
{'x1': 6, 'y1': 2, 'x2': 3, 'y2': 1},
{'x1': 6, 'y1': 6, 'x2': 3, 'y2': 5},
{'x1': 6, 'y1': 10, 'x2': 3, 'y2': 9},
{'x1': 6, 'y1': 4, 'x2': 3, 'y2': 3},
{'x1': 6, 'y1': 8, 'x2': 3, 'y2': 7},
{'x1': 6, 'y1': 2, 'x2': 3, 'y2': 3},
{'x1': 6, 'y1': 6, 'x2': 3, 'y2': 7},
{'x1': 6, 'y1': 10, 'x2': 3, 'y2': 11},
{'x1': 6, 'y1': 1, 'x2': 7, 'y2': 4},
{'x1': 6, 'y1': 5, 'x2': 7, 'y2': 8},
{'x1': 6, 'y1': 9, 'x2': 7, 'y2': 12},
{'x1': 6, 'y1': 7, 'x2': 7, 'y2': 4},
{'x1': 6, 'y1': 5, 'x2': 7, 'y2': 2},
{'x1': 6, 'y1': 9, 'x2': 7, 'y2': 6},
{'x1': 6, 'y1': 3, 'x2': 7, 'y2': 6},
{'x1': 6, 'y1': 7, 'x2': 7, 'y2': 10},
{'x1': 6, 'y1': 4, 'x2': 7, 'y2': 1},
{'x1': 6, 'y1': 8, 'x2': 7, 'y2': 5},
{'x1': 6, 'y1': 2, 'x2': 7, 'y2': 5},
{'x1': 6, 'y1': 6, 'x2': 7, 'y2': 9},
{'x1': 6, 'y1': 10, 'x2': 7, 'y2': 13},
{'x1': 6, 'y1': 4, 'x2': 7, 'y2': 7},
{'x1': 6, 'y1': 8, 'x2': 7, 'y2': 11},
{'x1': 6, 'y1': 6, 'x2': 7, 'y2': 3},
{'x1': 6, 'y1': 10, 'x2': 7, 'y2': 7},
{'x1': 8, 'y1': 5, 'x2': 5, 'y2': 4},
{'x1': 8, 'y1': 9, 'x2': 5, 'y2': 8},
{'x1': 8, 'y1': 3, 'x2': 5, 'y2': 4},
{'x1': 8, 'y1': 7, 'x2': 5, 'y2': 8},
{'x1': 8, 'y1': 1, 'x2': 5, 'y2': 2},
{'x1': 8, 'y1': 5, 'x2': 5, 'y2': 6},
{'x1': 8, 'y1': 9, 'x2': 5, 'y2': 10},
{'x1': 8, 'y1': 3, 'x2': 5, 'y2': 2},
{'x1': 8, 'y1': 7, 'x2': 5, 'y2': 6},
{'x1': 8, 'y1': 4, 'x2': 5, 'y2': 5},
{'x1': 8, 'y1': 8, 'x2': 5, 'y2': 9},
{'x1': 8, 'y1': 2, 'x2': 5, 'y2': 1},
{'x1': 8, 'y1': 6, 'x2': 5, 'y2': 5},
{'x1': 8, 'y1': 10, 'x2': 5, 'y2': 9},
{'x1': 8, 'y1': 4, 'x2': 5, 'y2': 3},
{'x1': 8, 'y1': 8, 'x2': 5, 'y2': 7},
{'x1': 8, 'y1': 2, 'x2': 5, 'y2': 3},
{'x1': 8, 'y1': 6, 'x2': 5, 'y2': 7},
{'x1': 8, 'y1': 10, 'x2': 5, 'y2': 11},
{'x1': 8, 'y1': 1, 'x2': 7, 'y2': 4},
{'x1': 8, 'y1': 5, 'x2': 7, 'y2': 8},
{'x1': 8, 'y1': 9, 'x2': 7, 'y2': 12},
{'x1': 8, 'y1': 7, 'x2': 7, 'y2': 4},
{'x1': 8, 'y1': 5, 'x2': 7, 'y2': 2},
{'x1': 8, 'y1': 9, 'x2': 7, 'y2': 6},
{'x1': 8, 'y1': 3, 'x2': 7, 'y2': 6},
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{'x1': 7, 'y1': 4, 'x2': 8, 'y2': 7},
{'x1': 7, 'y1': 8, 'x2': 8, 'y2': 11},
{'x1': 7, 'y1': 6, 'x2': 8, 'y2': 3},
{'x1': 7, 'y1': 10, 'x2': 8, 'y2': 7},
{'x1': 7, 'y1': 5, 'x2': 10, 'y2': 4},
{'x1': 7, 'y1': 9, 'x2': 10, 'y2': 8},
{'x1': 7, 'y1': 3, 'x2': 10, 'y2': 4},
{'x1': 7, 'y1': 7, 'x2': 10, 'y2': 8},
{'x1': 7, 'y1': 1, 'x2': 10, 'y2': 2},
{'x1': 7, 'y1': 5, 'x2': 10, 'y2': 6},
{'x1': 7, 'y1': 9, 'x2': 10, 'y2': 10},
{'x1': 7, 'y1': 3, 'x2': 10, 'y2': 2},
{'x1': 7, 'y1': 7, 'x2': 10, 'y2': 6},
{'x1': 7, 'y1': 4, 'x2': 10, 'y2': 5},
{'x1': 7, 'y1': 8, 'x2': 10, 'y2': 9},
{'x1': 7, 'y1': 2, 'x2': 10, 'y2': 1},
{'x1': 7, 'y1': 6, 'x2': 10, 'y2': 5},
{'x1': 7, 'y1': 10, 'x2': 10, 'y2': 9},
{'x1': 7, 'y1': 4, 'x2': 10, 'y2': 3},
{'x1': 7, 'y1': 8, 'x2': 10, 'y2': 7},
{'x1': 7, 'y1': 2, 'x2': 10, 'y2': 3},
{'x1': 7, 'y1': 6, 'x2': 10, 'y2': 7},
{'x1': 7, 'y1': 10, 'x2': 10, 'y2': 11},
{'x1': 9, 'y1': 1, 'x2': 8, 'y2': 4},
{'x1': 9, 'y1': 1, 'x2': 10, 'y2': 4},
{'x1': 9, 'y1': 5, 'x2': 8, 'y2': 8},
{'x1': 9, 'y1': 5, 'x2': 10, 'y2': 8},
{'x1': 9, 'y1': 9, 'x2': 8, 'y2': 12},
{'x1': 9, 'y1': 9, 'x2': 10, 'y2': 12},
{'x1': 9, 'y1': 7, 'x2': 8, 'y2': 4},
{'x1': 9, 'y1': 7, 'x2': 10, 'y2': 4},
{'x1': 9, 'y1': 5, 'x2': 8, 'y2': 2},
{'x1': 9, 'y1': 5, 'x2': 10, 'y2': 2},
{'x1': 9, 'y1': 9, 'x2': 8, 'y2': 6},
{'x1': 9, 'y1': 9, 'x2': 10, 'y2': 6},
{'x1': 9, 'y1': 3, 'x2': 8, 'y2': 6},
{'x1': 9, 'y1': 3, 'x2': 10, 'y2': 6},
{'x1': 9, 'y1': 7, 'x2': 8, 'y2': 10},
{'x1': 9, 'y1': 7, 'x2': 10, 'y2': 10},
{'x1': 9, 'y1': 4, 'x2': 8, 'y2': 1},
{'x1': 9, 'y1': 4, 'x2': 10, 'y2': 1},
{'x1': 9, 'y1': 8, 'x2': 8, 'y2': 5},
{'x1': 9, 'y1': 8, 'x2': 10, 'y2': 5},
{'x1': 9, 'y1': 2, 'x2': 8, 'y2': 5},
{'x1': 9, 'y1': 2, 'x2': 10, 'y2': 5},
{'x1': 9, 'y1': 6, 'x2': 8, 'y2': 9},
{'x1': 9, 'y1': 6, 'x2': 10, 'y2': 9},
{'x1': 9, 'y1': 10, 'x2': 8, 'y2': 13},
{'x1': 9, 'y1': 10, 'x2': 10, 'y2': 13},
{'x1': 9, 'y1': 4, 'x2': 8, 'y2': 7},
{'x1': 9, 'y1': 4, 'x2': 10, 'y2': 7},
{'x1': 9, 'y1': 8, 'x2': 8, 'y2': 11},
{'x1': 9, 'y1': 8, 'x2': 10, 'y2': 11},
{'x1': 9, 'y1': 6, 'x2': 8, 'y2': 3},
{'x1': 9, 'y1': 6, 'x2': 10, 'y2': 3},
{'x1': 9, 'y1': 10, 'x2': 8, 'y2': 7},
{'x1': 9, 'y1': 10, 'x2': 10, 'y2': 7}]

How to exclude items with identical field if the datefield is bigger than in others duplicates?

So I have a Comments model and by querying
comments = Comments.objects.values('students_id', 'created_at')
I get this output
<QuerySet [
{'students_id': 4, 'created_at': datetime.date(2019, 6, 19)}, {'students_id': 2, 'created_at': datetime.date(2019, 6, 3)}, {'students_id': 1, 'created_at': datetime.date(2019, 6, 24)}, {'students_id': 6, 'created_at': datetime.date(2019, 6, 4)}, {'students_id': 6, 'created_at': datetime.date(2019, 6, 19)}, {'students_id': 5, 'created_at': datetime.date(2019, 6, 5)}, {'students_id': 4, 'created_at': datetime.date(2019, 7, 28)}, {'students_id': 6, 'created_at': datetime.date(2019, 6, 11)}]>
It's three comments by student with id=6 and two comments by student with id=4.
What I need to get is only one latest comment from every student. In this example it'll look like this:
<QuerySet [
{'students_id': 2, 'created_at': datetime.date(2019, 6, 3)}, {'students_id': 1, 'created_at': datetime.date(2019, 6, 24)}, {'students_id': 6, 'created_at': datetime.date(2019, 6, 19)}, {'students_id': 5, 'created_at': datetime.date(2019, 6, 5)}, {'students_id': 4, 'created_at': datetime.date(2019, 7, 28)},]>
Thanks in advance for the answer!

You can use annotate and max to get desired result like this Comments.objects.values('students_id').annotate(Max('created_at'))
and the output will be like this <QuerySet [
{'students_id': 2, 'created_at__max': datetime.date(2019, 6, 3)}, {'students_id': 1, 'created_at__max': datetime.date(2019, 6, 24)},]> which will have students_id and latest created_at. To use this you have to import Max from django.db.models like this from django.db.models import Max

use this code :
queryset=Comments.objects.values('students_id', 'created_at').group_by('students_id').annotate(Latest_created_at=Max('created_at'))
queryset.delete()

In raw SQL it would be ... WHERE NOT EXISTS(SELECT * FROM Comments cc WHERE cc.student_id = c.student_id AND cc.created_at > c.created_at)
later_comments = Comments.objects.filter(student_id=OuterRef('student_id'),
created_at__gt=OuterRef('created_at'), ).values('created_at', )
latest_comments = Comments.objects.\
annotate(has_later_comments=Exists(later_comments), ).\
filter(has_later_comments=False, )
If your created_at is a Date column (no time), then you need to use => instead of > because perhaps more than one comment can be created during a day. So the query would contain additional predicate with extra column for ordering comments (like id): WHERE cc.created_at > c.created_at OR cc.created_at = c.created_at AND cc.id > c.id
https://docs.djangoproject.com/en/2.2/ref/models/expressions/#exists-subqueries

Access Pandas MultiIndex column by name

I have a spreadsheet imported with pandas like this:
df = pd.read_excel('my_spreadsheet.xlsx',header = [0,1],index_col=0,sheetname='Sheet1')
The output of df.columns is:
MultiIndex(levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],
labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],
names=[None, u'De-Identified MRN'])
I have been trying to access the values of column named 'De-Identified MRN', but can't seem to find the way to do this.
What I have tried (based on similar posts):
[in] df.index.get_level_values('De-Identified MRN')
[out] KeyError: 'Level De-Identified MRN must be same as name (None)'
and
[in] df.index.unique(level='De-Identified MRN')
[out] KeyError: 'Level De-Identified MRN must be same as name (None)'
UPDATE:
The following did the trick for some reason. I really do not understand the format of the MultiIndex Pandas Dataframe:
pd.Series(df.index)

By using your data
s="MultiIndex(levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],names=[None, u'De-Identified MRN'])"
idx=eval(s, {}, {'MultiIndex': pd.MultiIndex})
df=pd.DataFrame(index=idx)
df.index.get_level_values(level=1) # df.index.get_level_values('De-Identified MRN')
Out[336]:
Index(['ExamDesc', 'completedDTTM', 'BIRADS', 'ExamDesc', 'completedDTTM',
'BIRADS', 'ExamDesc', 'completedDTTM', 'BIRADS', 'ExamDesc',...
Also if all above still does not work , try
df.reset_index()['De-Identified MRN']

Try the following:
midx = pd.MultiIndex(
levels=[[u'MR 1', u'MR 10', u'MR 11', u'MR 12', u'MR 13', u'MR 14', u'MR 15', u'MR 16', u'MR 17', u'MR 18', u'MR 19', u'MR 2', u'MR 20', u'MR 21', u'MR 22', u'MR 3', u'MR 4', u'MR 5', u'MR 6', u'MR 7', u'MR 8', u'MR 9'], [u'BIRADS', u'ExamDesc', u'completedDTTM']],
labels=[[0, 0, 0, 11, 11, 11, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 12, 12, 12, 13, 13, 13, 14, 14, 14], [1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0, 1, 2, 0]],
names=[None, u'De-Identified MRN']
)
midx.levels[1] # returns the following
Index(['BIRADS', 'ExamDesc', 'completedDTTM'], dtype='object', name='De-Identified MRN')
midx.levels[1].values # returns the following
array(['BIRADS', 'ExamDesc', 'completedDTTM'], dtype=object)

Django count number of records per day

I'm using Django 2.0
I am preparing data to show on a graph in template. I want to fetch number of records per day.
This is what I'm doing
qs = self.get_queryset().\
extra({'date_created': "date(created)"}).\
values('date_created').\
annotate(item_count=Count('id'))
but, the output given is
[
{'date_created': datetime.date(2018, 5, 24), 'item_count': 1},
{'date_created': datetime.date(2018, 5, 24), 'item_count': 1},
{'date_created': datetime.date(2018, 5, 24), 'item_count': 1},
{'date_created': datetime.date(2018, 5, 24), 'item_count': 1},
{'date_created': datetime.date(2018, 5, 24), 'item_count': 1},
{'date_created': datetime.date(2018, 5, 24), 'item_count': 1},
{'date_created': datetime.date(2018, 5, 24), 'item_count': 1}
]
Here data is not grouped and same date is returning repeatedly with count as 1

Try using TruncDate function.
See that answer