Suppose I have the following records:
code sequence_no group_no
4 1 1
2 2 1
3 3 1
4 4 1
1 1 2
3 1 3
4 2 3
the output should be: within the same group(by group_no) the code column is updated with the first(by sequence_no) code that is not 4.
so the output should look like this:
code sequence_no group_no
2 1 1
2 2 1
2 3 1
2 4 1
1 1 2
3 1 3
3 2 3
Here's my code, and my logic is that if the input.code == 4, then assign the next code to the temp variable. This doesn't work if the first record code == 4 for some reason. And I don't think this logic covers the last record of the group if it == 4.
type temporary_type=
record
decimal("\x01") l_code;
end;
temp :: scan(temp, in) =
begin
temp.l_code::
if (temp.l_code == 4) in.code
else temp.l_code;
end;
temp :: initialize(in) =
begin
temp.code :: in.code;
end;
out :: finalize(temp, in) =
begin
out.* :: in.*;
out.code :: temp.l_code;
end;
Related
My Doubt in a Table/Dataframe viewI have a dataframe containing 2 columns: ID and Code.
ID Code Flag
1 A 0
1 C 1
1 B 1
2 A 0
2 B 1
3 A 0
4 C 0
Within each ID, if Code 'A' exists with 'B' or 'C', then it should flag 1.
I tried Groupby('ID') with filter(). but it is not showing the perfect result. Could anyone please help ?
You can do the following:
First use pd.groupby('ID') and concatenate the codes using 'sum' to create a new column. Then assing the value 1 if a row contains A or B as Code and when the new column contains an A:
df['s'] = df.groupby('ID').Code.transform('sum')
df['Flag'] = 0
df.loc[((df.Code == 'B') | (df.Code == 'C')) & df.s.str.contains('A'), 'Flag'] = 1
df = df.drop(columns = 's')
Output:
ID Code Flag
0 1 A 0
1 1 C 1
2 1 B 1
3 2 A 0
4 2 B 1
5 3 A 0
6 4 C 0
You can use boolean masks, direct for B/C, per group for A, then combine them and convert to integer:
# is the Code a B or C?
m1 = df['Code'].isin(['B', 'C'])
# is there also a A in the same group?
m2 = df['Code'].eq('A').groupby(df['ID']).transform('any')
# if both are True, flag 1
df['Flag'] = (m1&m2).astype(int)
Output:
ID Code Flag
0 1 A 0
1 1 C 1
2 1 B 1
3 2 A 0
4 2 B 1
5 3 A 0
6 4 C 0
I have the Following Output:
Sno
Value Stream
Duration
Inspection
1
Test1
3
1
2
ON
14
0
3
Start
5
0
4
Test1
5
1
5
OFF
0
1
6
Start
0
1
7
Test2
0
1
8
ON
3
1
9
START
0
1
10
Test2
2
2
I want to merge the same value after that before START values charge to after ON. For example S.no 4 will merge to s.no4.
1 | Test1 | 8 | 2 |
If the combination is not equal then don't allow it to merge. For Example, we have to consider only On/Start. If the condition is OFF/Start then don't allow to merge. E.g. S.no 5 and 6 OFF/Start then don't allow to merge s.no 4 & 7.
I think you are talking about summarization not merging:
select [Value Stream],
min(Sno) as First_Sno,
sum(Duration) as total_Duration,
sum(Inspection) as Inspection
from yourtable
group by [Value Stream]
Will give you the result
I've below table with some results for both Morning and Afternoon session (for different periods).
I would like to updated the results based on the simple condition:
Check if in 2 following morning sessions there was a change - if not add 5 to the score:
Example: ID=1, Mor2=C, Mor3=C so Score_M3 = 5+5= 10 (new value). All updated values are marked in the 'Wanted' table.
How can I write this in SQL? I will have a lot of columns and IDs.
My dataset:
ID Mor1 Aft1 Mor2 Aft2 Mor3 Aft3 Score_M1 Score_A1 Score_M2 Score_A2 Score_M3 Score_A3
1 A A C B C B 1 1 1 1 5 6
2 C C C B C B 1 1 1 1 4 5
3 A A A A A A 1 1 1 1 4 1
Wanted :
ID Mor1 Aft1 Mor2 Aft2 Mor3 Aft3 Score_M1 Score_A1 Score_M2 Score_A2 Score_M3 Score_A3
1 A A C B C B 1 1 1 1 *10 6
2 C C C B C B 1 1 *6 1 *9 5
3 A A A A A A 1 1 *6 1 *9 1
Here is the SQL to get you started. You can add many more columns as you see fit.
Can we restate as SAME, rather than Change?
If Mor1 = Mor2 then add +5 to Score2
If Mor2 = Mor3 then add +5 to Score3
UPDATE [StackOver].[dbo].[UpdateMultiCols]
SET
[Score_M1] = Score_M1
,[Score_M2] = Score_M2 +
Case When Mor1 = Mor2 Then 5 else 0 End
,[Score_M3] = Score_M3 +
Case When Mor2 = Mor3 Then 5 else 0 End
GO
I have a view with Columns:
WeekNo, MerchantId, Transactions
With a Select Query let's say that we have the following results:
TrnWeek AgencyId WeeklyTrn
1 110008 1
2 110008 2
3 110008 2
1 110045 4
3 110065 4
3 110124 1
1 110153 1
1 110155 3
2 110163 1
2 110165 1
making a pivot (stored procedure which creates dynamically the columns) i get the TrnWeek as Columns and as a result the following:
[1] [2] [3]
1 1 1
1 0 0
1 0 0
1 0 0
0 1 1
0 1 0
0 0 1
what I want to get is a "matrix" as follows:
TrnWeek 1 2 3
1 4 1 1
2 0 2 1
3 0 0 1
ih which i calculate how many merchants performed a transaction in the first week (position: 1,1), how many of them performed a transaction in the second one (position: 1,2), how many performed their first transaction in 2nd week (position: 2,2) etc.
I am trying to figure how I could do this where I have a table as follows:
ID FKeyID Complete
1 6 1
2 6 0
3 6 0
4 7 0
5 8 0
6 8 0
I want to create a function to return 1 or true if any FKeyID for example 6 has a value of 1 in complete column and 0 if it does not.
This is a function that takes fKey value and should return 1 or 0 based on that.
So in above basically if my FKeyID is 6 return 1 because complete column is 1 in one of the rows, and 0 for FKeyID 8 because none of values in column complete is 1.
CREATE function [dbo].f_x
(
#FKeyID int
)
RETURNS bit
as
begin
return case when exists
(select 1 from test where Complete = 1 and FKeyID = #FKeyID)
then 1 else 0 end
end