I want to check if chron_id is present and get rows without duplicates.
If chron_id is null then get all rows.
toponymies_one = Toponymy.objects.filter(chron_id__isnull=False).distinct('chron_id')
toponymies_two = Toponymy.objects.filter(chron_id__isnull=True)
Should I merge these two query sets? Is there a better way to do it?
| id | somevalue | somevalue | chron_id |
|----|-----------|-----------|----------|
| 1 | foo | foo | | # I want this row
| 2 | bar | foo | 2 |
| 3 | foo | bar | | # I want this row
| 4 | foo | foo | | # I want this row
| 5 | bar | foo | 5 |
| 6 | foo | bar | | # I want this row
| 7 | foo | foo | | # I want this row
| 8 | bar | foo | 5 | # I want this row
| 9 | foo | bar | 2 | # I want this row
Thanks...
What about using OR statment in filter via Q vide: https://docs.djangoproject.com/en/dev/topics/db/queries/#complex-lookups-with-q-objects
Related
i have a data for group no and its set value. When the set value is same for all the batches i dont want those batches to be counted. but if there are more than 1 set values in each batch then the dax query should count it as 1.
My current data is like this
| group_no | values |
| ---------- | ---------------------- |
| H110201208 | 600 |
| H110201208 | 600 |
| H110201208 | 680 |
| H101201215 | 665 |
| H109201210 | 640 |
| H123201205 | 600 |
| H125201208 | 610 |
| H111201212 | 610 |
| H111201212 | 630 |
I want my output like this
| Group no | Grand Total |
| ---------- | ----------- |
| H101201215 | 1 |
| H109201210 | 1 |
| H110201208 | 3 |
| H111201212 | 2 |
| H123201205 | 1 |
| H125201208 | 1 |
i want to create another table like the one above using dax so that i can plot graphs n percentages based on its output
i want to do this in powerbi using DAX language.
TABLE =
GROUPBY (
Groups, //SourceTable
Groups[ group_no ],
"GrandTotal", COUNTX ( CURRENTGROUP (), DISTINCTCOUNTNOBLANK ( Groups[ values ] ) )
)
I have simplified my problem to solve. Lets suppose I have three tables. One containing data and specific codes that identify objects lets say Apples.
+-------------+------------+-----------+
| Data picked | Color code | Size code |
+-------------+------------+-----------+
| 1-8-2018 | 1 | 1 |
| 1-8-2018 | 1 | 3 |
| 1-8-2018 | 2 | 2 |
| 1-8-2018 | 2 | 3 |
| 1-8-2018 | 2 | 2 |
| 1-8-2018 | 3 | 3 |
| 1-8-2018 | 4 | 1 |
| 1-8-2018 | 4 | 1 |
| 1-8-2018 | 5 | 3 |
| 1-8-2018 | 6 | 1 |
| 1-8-2018 | 6 | 2 |
| 1-8-2018 | 6 | 2 |
+-------------+------------+-----------+
And i have two related helping tables to help understand the codes (their relationships are inactive in the model due to ambiguity with other tables in the real case).
+-----------+--------+
| Size code | Size |
+-----------+--------+
| 1 | Small |
| 2 | Medium |
| 3 | Large |
+-----------+--------+
and
+------------+----------------+-------+
| Color code | Color specific | Color |
+------------+----------------+-------+
| 1 | Light green | Green |
| 2 | Green | Green |
| 3 | Semi green | Green |
| 4 | Red | Red |
| 5 | Dark | Red |
| 6 | Pink | Red |
+------------+----------------+-------+
Lets say that I want to create an extra column in the original table to determine which apples are class A and class B given that medium green Apples are class A and large Red apples are class B, the other remain blank as the example below.
+-------------+------------+-----------+-------+
| Data picked | Color code | Size code | Class |
+-------------+------------+-----------+-------+
| 1-8-2018 | 1 | 1 | |
| 1-8-2018 | 1 | 3 | |
| 1-8-2018 | 2 | 2 | A |
| 1-8-2018 | 2 | 3 | |
| 1-8-2018 | 2 | 2 | A |
| 1-8-2018 | 3 | 3 | |
| 1-8-2018 | 4 | 1 | |
| 1-8-2018 | 4 | 1 | |
| 1-8-2018 | 5 | 3 | B |
| 1-8-2018 | 6 | 1 | |
| 1-8-2018 | 6 | 2 | |
| 1-8-2018 | 6 | 2 | |
+-------------+------------+-----------+-------+
What's the proper DAX to use given the relationships are initially inactive. Preferably solvable without creating any further additional columns in any table. I already tried codes like:
CALCULATE (
"A" ;
FILTER ( 'Size Table' ; 'Size Table'[Size] = "Medium");
FILTER ( 'Color Table' ; 'Color Table'[Color] = "Green")
)
And many variations on the same principle
Given that the relationships are inactive, I'd suggest using LOOKUPVALUE to match ID values on the other tables. You should be able to create a calculated column as follows:
Class =
VAR Size = LOOKUPVALUE('Size Table'[Size],
'Size Table'[Size code], 'Data Table'[Size code])
VAR Color = LOOKUPVALUE('Color Table'[Color],
'Color Table'[Color code], 'Data Table'[Color code])
RETURN SWITCH(TRUE(),
(Size = "Medium") && (Color = "Green"), "A",
(Size = "Large") && (Color = "Red"), "B", BLANK())
If your relationships are active, then you don't need the lookups:
Class = SWITCH(TRUE(),
(RELATED('Size Table'[Size]) = "Medium") &&
(RELATED('Color Table'[Color]) = "Green"),
"A",
(RELATED('Size Table'[Size]) = "Large") &&
(RELATED('Color Table'[Color]) = "Red"),
"B",
BLANK())
Or a bit more elegantly written (especially for more classes):
Class =
VAR SizeColor = RELATED('Size Table'[Size]) & " " & RELATED('Color Table'[Color])
RETURN SWITCH(TRUE(),
SizeColor = "Medium Green", "A",
SizeColor = "Large Red", "B",
BLANK())
i have database scheme like this.
# periode
+------+--------------+--------------+
| id | from | to |
+------+--------------+--------------+
| 1 | 2018-04-12 | 2018-05-11 |
| 2 | 2018-05-12 | 2018-06-11 |
+------+--------------+--------------+
# foo
+------+---------+
| id | name |
+------+---------+
| 1 | John |
| 2 | Doe |
| 3 | Trodi |
| 4 | son |
| 5 | Alex |
+------+---------+
#bar
+------+---------------+--------------+
| id | employee_id | periode_id |
+------+---------------+--------------+
| 1 | 1 |1 |
| 2 | 2 |1 |
| 3 | 1 |2 |
| 4 | 3 |1 |
+------+---------------+--------------+
I need to show employee that not in salary.
for now I do like this
queryset=Bar.objects.all().filter(periode_id=1)
result=Foo.objects.exclude(id=queryset)
but its fail, how do filter employee list not in salary?...
Well here you basically want the foos such that there is no period_id=1 in the Bar table.
We can let this work with:
ex = Bar.objects.all().filter(periode_id=1).values_list('employee_id', flat=True)
result=Foo.objects.exclude(id__in=ex)
I have a Django model with three fields: product, condition and quantity with data such as:
| Product | Condition | Quantity |
+---------+-----------+----------+
| A | new | 2 |
| A | new | 3 |
| A | new | 4 |
| A | old | 1 |
| A | old | 2 |
| B | new | 2 |
| B | new | 3 |
| B | new | 1 |
| B | old | 4 |
| B | old | 2 |
I'd like to sum the quantities of the entries where product and condition are equal:
| Product | Condition | Quantity |
+---------+-----------+----------+
| A | new | 9 |
| A | old | 3 |
| B | new | 6 |
| B | old | 6 |
This answer helps to count entries with the same field value, but I need to count two fields.
How could I implement this?
from django.db.models import Sum
Model.objects.values('product', 'condition').order_by().annotate(Sum('quantity'))
I have 2 tables in 2 databases:
table call in history.db:
ROWID | ADDRESS | DATE
1 | +98765 | 1396771532
2 | +98765 | 1396771533
3 | +98765 | 1396771534
4 | +98765 | 1396771535
5 | +98765 | 1396771536
6 | +98765 | 1396771537
7 | +98765 | 1396771538
8 | +98765 | 1396771539
9 | +98765 | 1396771510
table info in voices.db:
ID | CALLID | PATH | CODE
1 | 2 | voice1.m4a | 12234
2 | 5 | voice2.m4a | 12234
3 | 1 | voice4.m4a | 89765
First, I did an attach:
conn = sqlite3.connect("history.db")
conn.row_factory = sqlite3.Row
cursor = conn.cursor()
cursor.execute("attach ? as voice", ("voices.db",))
conn.commit()
Then, I joined 2 tables:
cursor.execute("SELECT * FROM call c JOIN (SELECT PATH, CALLID, CODE FROM voice.info WHERE CODE = ?) f ON c.ROWID = f.CALLID ORDER BY c.DATE", ("12234",))
So, I got the following result:
ROWID | ADDRESS | DATE | PATH | CALLID | CODE
2 | +98765 | 1396771533 | voice1.m4a | 2 | 12234
5 | +98765 | 1396771536 | voice2.m4a | 5 | 12234
But, I need a full outer join to get something like:
ROWID | ADDRESS | DATE | PATH | CALLID | CODE
1 | +98765 | 1396771532 | NULL | NULL | NULL
2 | +98765 | 1396771533 | voice1.m4a | 2 | 12234
3 | +98765 | 1396771534 | NULL | NULL | NULL
4 | +98765 | 1396771535 | NULL | NULL | NULL
5 | +98765 | 1396771536 | voice2.m4a | 5 | 12234
6 | +98765 | 1396771537 | NULL | NULL | NULL
7 | +98765 | 1396771538 | NULL | NULL | NULL
8 | +98765 | 1396771539 | NULL | NULL | NULL
9 | +98765 | 1396771510 | NULL | NULL | NULL
I tried this, but I got an error of ... UNION do not have same number result columns ....
How could I have a full outer Join?
I am using Python 2.7, so
Right and FULL OUTER JOINs are not currently supported
Your original query is badly written. Write it like this:
SELECT c.*, i.* FROM CALL c
JOIN voice.info i ON i.CODE = ? AND c.ROWID = i.CALLID
ORDER BY c.DATE;
Now transforming it into the full outer join as in the answer you linked is trivial:
SELECT c.*, i.* FROM CALL c
LEFT JOIN voice.info i ON c.ROWID = i.CALLID AND i.CODE = ?
UNION
SELECT c.*, i.* FROM voice.info i
LEFT JOIN CALL c ON c.ROWID = i.CALLID
WHERE i.CODE = ?;
In the answer you linked they use UNION ALL, which keeps duplicates in the result set. I don't think you want that, so therefore I prefer to use UNION, which removes duplicates (rows where all the columns are equal).
Also: it's actually even better to write out all columns instead of using *, but I didn't do that here for brevity.