I would like to create an increment function from a dataframe.
Me dataframe look like this:
___________ ___________
| Action_ID | Unique_ID |
| 4 | |
| 3 | |
| 2 | |
| 1 | |
| 4 | |
___________ ___________
Would like to set Unique_ID egals i+1 when Action_ID egals 4. So:
___________ ___________
| Action_Id | Unique_Id |
| 4 | 1 |
| 3 | |
| 2 | |
| 1 | |
| 4 | 2 |
___________ ___________
I've try this code:
def order_code(grp):
i=0
if(grp.loc[grp.first_valid_index(),'Action_Id']==4):
i = i+1
grp['Unique_Id']=i
return(grp)
c=(c.groupby('Action_Id')).apply(order_code)
But it displays me:
___________ ___________
| Action_Id | Unique_Id |
| 4 | 1 |
| 3 | |
| 2 | |
| 1 | |
| 4 | 1 |
___________ ___________
Someone can help me please?
Your problem is that i is in the scope of the function which you're working in. If you were to do for example:
inc = 0
def order_code(grp):
global inc
if(grp.loc[grp.first_valid_index(),'Action_Id']==4):
inc += 1
grp['Unique_Id']=inc
return(grp)
c=(c.groupby('Action_Id')).apply(order_code)
it would work.
Related
I would like to apply the total count('case_id'), while grouping by the Item.
This was my previous ask DAX Measure to calculate aggregate data, but group by Case ID. This gave me the total count('case_id') by sub_item.
Measure =
VAR datesSelection =
DATE(
YEAR(SELECTEDVALUE('Date Selection'[DateWoTime]))
,MONTH(SELECTEDVALUE('Date Selection'[DateWoTime]))
,DAY(SELECTEDVALUE('Date Selection'[DateWoTime]))
)
VAR devicesTotal =
CALCULATETABLE (
VALUES ( Outages[Sub_Item] ),
ALLSELECTED ( Outages ),
Outages[DATE] >= datesSelection,
VALUES ( Outages[Sub_Item] )
)
var counts =
CALCULATE (
COUNT( Outages[CASE_ID] ),
ALLSELECTED( Outages ),
Outages[Sub_Item] IN devicesTotal
)
return
counts
I'm getting this.
| Item | Sub_Item | TYPE | Case ID | Date | Measure |
|-------|----------|------|------------|------------------|---------|
| 701ML | abc | TFUS | 1312937981 | 7/16/19 7:18:00 | 1 |
| 702ML | abc | TFUS | 1312958225 | 7/16/19 11:13:00 | 1 |
| 702ML | abc1 | TFUS | 1312957505 | 7/16/19 11:03:00 | 1 |
| 702ML | abc2 | TFUS | 1312954287 | 7/16/19 10:24:00 | 1 |
| 702ML | abc3 | TFUS | 1312938599 | 7/16/19 7:28:00 | 1 |
| 702ML | abc4 | TFUS | 1290599620 | 5/25/18 15:43:00 | 2 |
| 702ML | abc4 | TFUS | 1312950297 | 7/16/19 9:43:00 | 2 |
| 708BI | abc | TFUS | 1312947288 | 7/16/19 9:13:00 | 1 |
| 712BI | abc | TFUS | 1312944078 | 7/16/19 8:30:00 | 1 |
| 785DL | abc | TFUS | 1312937536 | 7/16/19 7:12:00 | 1 |
| 786DL | abc | TFUS | 1312992583 | 7/16/19 14:59:00 | 1 |
| 791DI | abc | LFUS | 1289094627 | 4/28/18 20:07:00 | 2 |
| 791DI | abc | LFUS | 1312958972 | 7/16/19 11:17:00 | 2 |
| 791DI | abc1 | LFUS | 1313005237 | 7/16/19 14:00:00 | 2 |
| 791DI | abc2 | RCLR | 1290324328 | 5/22/18 15:36:00 | 2 |
| 841JU | abc | TFUS | 1312955016 | 7/16/19 10:32:00 | 1 |
| 841JU | abc1 | SBKR | 1288688911 | 4/15/18 10:09:56 | 2 |
| 841JU | abc1 | SBKR | 1312961007 | 7/16/19 11:46:24 | 2 |
| 871NI | abc2 | TFUS | 1304308511 | 3/24/19 19:13:00 | 2 |
| 871NI | abc | TFUS | 1313015455 | 7/16/19 18:39:00 | 2 |
| 917CN | abc | TFUS | 1312945831 | 7/16/19 8:58:00 | 1 |
| 918CN | abc | LFUS | 1292611263 | 6/30/18 9:41:00 | 2 |
| 918CN | abc | LFUS | 1313006283 | 7/16/19 17:03:00 | 2 |
| 922DU | abc | TFUS | 1312987081 | 7/16/19 14:20:00 | 1 |
| 922DU | abc1 | TFUS | 1313005803 | 7/16/19 17:04:00 | 1 |
| 922DU | abc2 | TFUS | 1313003541 | 7/16/19 16:42:00 | 1 |
| 931LF | abc | TFUS | 1312972165 | 7/16/19 12:46:00 | 1 |
When I would like to get this.
| Item | Sub_Item | TYPE | Case ID | Date | Measure |
|-------|----------|------|------------|-----------------|---------|
| 701ML | abc | TFUS | 1312937981 | 7/16/2019 7:18 | 1 |
| 702ML | abc | TFUS | 1312958225 | 7/16/2019 11:13 | 6 |
| 702ML | abc1 | TFUS | 1312957505 | 7/16/2019 11:03 | 6 |
| 702ML | abc2 | TFUS | 1312954287 | 7/16/2019 10:24 | 6 |
| 702ML | abc3 | TFUS | 1312938599 | 7/16/2019 7:28 | 6 |
| 702ML | abc4 | TFUS | 1290599620 | 5/25/2018 15:43 | 6 |
| 702ML | abc4 | TFUS | 1312950297 | 7/16/2019 9:43 | 6 |
| 708BI | abc | TFUS | 1312947288 | 7/16/2019 9:13 | 1 |
| 712BI | abc | TFUS | 1312944078 | 7/16/2019 8:30 | 1 |
| 785DL | abc | TFUS | 1312937536 | 7/16/2019 7:12 | 1 |
| 786DL | abc | TFUS | 1312992583 | 7/16/2019 14:59 | 1 |
| 791DI | abc | LFUS | 1289094627 | 4/28/2018 20:07 | 4 |
| 791DI | abc | LFUS | 1312958972 | 7/16/2019 11:17 | 4 |
| 791DI | abc1 | LFUS | 1313005237 | 7/16/2019 14:00 | 4 |
| 791DI | abc2 | RCLR | 1290324328 | 5/22/2018 15:36 | 4 |
| 841JU | abc | TFUS | 1312955016 | 7/16/2019 10:32 | 3 |
| 841JU | abc1 | SBKR | 1288688911 | 4/15/2018 10:09 | 3 |
| 841JU | abc1 | SBKR | 1312961007 | 7/16/2019 11:46 | 3 |
| 871NI | abc2 | TFUS | 1304308511 | 3/24/2019 19:13 | 2 |
| 871NI | abc | TFUS | 1313015455 | 7/16/2019 18:39 | 2 |
| 917CN | abc | TFUS | 1312945831 | 7/16/2019 8:58 | 1 |
| 918CN | abc | LFUS | 1292611263 | 6/30/2018 9:41 | 2 |
| 918CN | abc | LFUS | 1313006283 | 7/16/2019 17:03 | 2 |
| 922DU | abc | TFUS | 1312987081 | 7/16/2019 14:20 | 3 |
| 922DU | abc1 | TFUS | 1313005803 | 7/16/2019 17:04 | 3 |
| 922DU | abc2 | TFUS | 1313003541 | 7/16/2019 16:42 | 3 |
| 931LF | abc | TFUS | 1312972165 | 7/16/2019 12:46 | 1 |
You need to specify what level you are aggregating at in your measure. Currently, you are aggregating at the Sub_Item level.
To aggregate at the Item level, simply replace Sub_Item with Item in your measure.
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'))
First time post so hopefully someone can kindly assist on this problem I'm facing within SAS EG (still learning SAS coding so please be kind!)
If you see a snippet of the dataset below what I'm trying to do is tally up the scores (pts) by Ref based on consecutive occurrences that flag has showed for that Ref.
For Example:
If you take Ref 505 for A_Flag there is 2 different sets of consecutive occurrences of that flag then scoring will be as follows:
1st ID > 1st instance = 25 points
2nd ID > 2nd instance but 1st consecutive instance = double to 50 points
3rd ID > 0 instance = 0 points
4th ID > 1st instance = 25 points
5th ID > 2nd instance but 1st consecutive instance = double to 50 points
6th ID > 0 instance = 0 points
Therefore for this Ref A_Pts will be 150 points.
Another example:
If you take Ref 527 for B_Flag there is 4 consecutive occurrences of that flag so coring per ID:
1st ID > 0 instance = 0 points
2nd ID > 1st instance = 10 points
3rd ID > 2nd instance but 1st consecutive instance = double to 20 points
4th ID > 3rd instance but 2nd consecutive instance = double to 40 points
5th ID > 4th instance but 3rd consecutive instance = double to 80 points
Therefore for this Ref B_Pts will be 150 points
I have to say the data is in the necessary order for what I'm trying to achieve.
I'd tried using LAG function but that will only work based on the 1st consecutive instance.
I also tried calculate a count - an enumeration variable based on cats(Ref,A_Flag) - but it then orders the data incorrectly and doesnt count up accordingly
Hopefully this makes sense to someone out there!
The dataset in question:
+-----------+-----+--------+--------+--------+-------+-------+
| date | Ref | FormID | A_Flag | B_Flag | A_Pts | B_Pts |
+-----------+-----+--------+--------+--------+-------+-------+
| 01-Feb-17 | 505 | 74549 | A | | 25 | 0 |
| 01-Feb-17 | 505 | 74550 | A | | 25 | 0 |
| 10-Jan-17 | 505 | 82900 | | B | 0 | 10 |
| 13-Jan-17 | 505 | 82906 | A | | 25 | 0 |
| 09-Jan-17 | 505 | 82907 | A | | 25 | 0 |
| 11-Jan-17 | 505 | 82909 | | B | 0 | 10 |
| 03-Jan-17 | 527 | 62549 | A | | 25 | 0 |
| 04-Jan-17 | 527 | 62550 | | B | 0 | 10 |
| 04-Jan-17 | 527 | 76151 | | B | 0 | 10 |
| 04-Jan-17 | 527 | 76152 | A | B | 25 | 10 |
| 04-Jan-17 | 527 | 76153 | A | B | 25 | 10 |
+-----------+-----+--------+--------+--------+-------+-------+
Desired output (unless there is a better suggestion):
+-----------+-----+--------+--------+--------+-----------+-----------+
| date | Ref | FormID | A_Flag | B_Flag | A_Pts_Agg | B_Pts_Agg |
+-----------+-----+--------+--------+--------+-----------+-----------+
| 01-Feb-17 | 505 | 74549 | A | | 25 | 0 |
| 01-Feb-17 | 505 | 74550 | A | | 50 | 0 |
| 10-Jan-17 | 505 | 82900 | | B | 0 | 10 |
| 13-Jan-17 | 505 | 82906 | A | | 25 | 0 |
| 09-Jan-17 | 505 | 82907 | A | | 50 | 0 |
| 11-Jan-17 | 505 | 82909 | | B | 0 | 10 |
| 03-Jan-17 | 527 | 62549 | A | | 25 | 0 |
| 04-Jan-17 | 527 | 62550 | | B | 0 | 10 |
| 04-Jan-17 | 527 | 76151 | | B | 0 | 20 |
| 04-Jan-17 | 527 | 76152 | A | B | 25 | 40 |
| 04-Jan-17 | 527 | 76153 | A | B | 50 | 80 |
+-----------+-----+--------+--------+--------+-----------+-----------+
So when totalled up it'll be
+-----+-----------+-----------+
| Ref | A_Pts_Agg | B_Pts_Agg |
+-----+-----------+-----------+
| 505 | 150 | 20 |
| 527 | 100 | 150 |
+-----+-----------+-----------+
Try this:
data have;
infile cards dlm='|';
input date :date7. Ref :8. FormID :8. A_Flag :$1. B_Flag :$1. A_Pts :8. B_Pts :8.;
format date date7.;
cards;
| 01-Feb-17 | 505 | 74549 | A | | 25 | 0 |
| 01-Feb-17 | 505 | 74550 | A | | 25 | 0 |
| 10-Jan-17 | 505 | 82900 | | B | 0 | 10 |
| 13-Jan-17 | 505 | 82906 | A | | 25 | 0 |
| 09-Jan-17 | 505 | 82907 | A | | 25 | 0 |
| 11-Jan-17 | 505 | 82909 | | B | 0 | 10 |
| 03-Jan-17 | 527 | 62549 | A | | 25 | 0 |
| 04-Jan-17 | 527 | 62550 | | B | 0 | 10 |
| 04-Jan-17 | 527 | 76151 | | B | 0 | 10 |
| 04-Jan-17 | 527 | 76152 | A | B | 25 | 10 |
| 04-Jan-17 | 527 | 76153 | A | B | 25 | 10 |
;
run;
data want;
set have;
by Ref;
retain A_pts_agg B_pts_agg;
if first.Ref then do;
A_pts_agg = A_pts;
B_pts_agg = B_pts;
end;
if lag(A_flag) ne (A_flag) then A_pts_agg = A_pts;
else if A_flag = 'A' then A_pts_agg = A_pts_agg * 2;
if lag(B_flag) ne (B_flag) then B_pts_agg = B_pts;
else if B_flag = 'B' then B_pts_agg = B_pts_agg * 2;
run;