I have a postgres table that looks like this:
A B
5 4
10 10
13 15
100 250
20 Null
Using SQL, I would like to check whether the value in column A is larger than the value in column B and if so, then add a 1 to the column True. If the value in column A is smaller or equal to the value in column B or if column B contains a [NULL] value, I would like to add a 1 to the column False, like so:
A B True False
5 4 1 0
10 10 0 1
13 15 0 1
100 25 1 0
20 [NULL] 0 1
What is the best way to achieve this?
You can use case logic:
select t.*,
(case when A > B then 1 else 0 end) as true_col,
(case when A > B then 0 else 1 end) as false_col
from t;
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 need to create 2 cumulative sums based on the value type, for example:
I have values of incoming stock units from 2 types: A and B. and I also have records of outgoing stock units.
If we have enough stock of type "A" it should taken out of type A, if not- it should be taken out of type B. so basically I need to crate the columns "A stock" and "B stock" below, representing the current balance of each type.
I tried using cumulative sum but I'm having trouble with the condition... is there a way to write this query without using a loop ? ( Vertica DB)
In table below A_stock and B_stock are the final result I need to create
ID Type In OUT A stock B stock Order_id
1 A 100 0 100 0 1
1 B 50 0 100 50 2
1 A 100 0 200 50 3
1 - 0 -200 0 50 4
1 - 0 -10 0 40 5
1 B 50 0 0 90 6
1 A 40 0 40 90 7
1 - 0 -20 20 90 8
2 A 30 0 30 0 1
2 B 20 0 30 20 2
2 A 10 0 40 20 3
2 - 0 -20 20 20 4
You can use window functions - but you need a column that defines the ordering of the rows, I assumed ordering_id:
select t.*,
sum(case when type = 'A' then in + out else 0 end) over(partition by id order by ordering_id) a_stock,
sum(case when type = 'B' then in + out else 0 end) over(partition by id order by ordering_id) b_stock
from mytable t
This assumes that you want the stock on a per-id basis; if that's not the case, just remove the partition clause from the over() clause.
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 weird situation where i need to order 0 first and then descends a column.
Let's say i have column that looks like this
Status
------
3
4
0
5
1
2
4
0
2
And Now i need to order it by
Status
------
0
0
5
4
4
3
2
2
1
Is this possible for SQL? I've been trying to test for 2 days now but i am stuck.
Use a case expression to first sort 0's and then the rest. After that sort by status desc:
order by case when Status = 0 then 0 else 1 end, status desc
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