I am trying to generate a list using M Query, but instead of generating a list starting from a specific, number, I want the number to start at 1 and then add 1 for every row on another table.
So for example, if I have:
Tbl1
Col1
A
B
C
D
D
I want to generate
Tbl2
Col1
1
2
3
4
5
I want the number to start at 1 and then add 1 for every row on another table.
if I understand your correctly, here it is:
={1..Table.RowCount(Tab1)}
Related
I have table where source has 1 column, like below. for example, column name is A and I have set of records in the source.
A
1
1
1
2
2
3
I want to populate two columns in target, Say columns are A and B.
Column A in the Target has same values as in source and column B has count
A B
1 1
1 2
1 3
2 1
2 2
3 1
Can someone please explain how can i achieve this.
Thanks in advance
If source is a dbms like oracle, you can use source qualifier overwrite sql like below. Use row number and partition by to generate sequence for every A.
Select
A, row_number() over(partition by A order by A) as B
From mytable
If you're looking for infomatica only solution then this is how you can do it.
Sort the data by column A
Use ex transformation, create one in/out two var, and one out port.
We are going to compare first val with prev val, if they r same, add 1to the sequence else start from 1 again.
A in/out
v_B = iif (A=prev_A, v_B +1, 1)
prev_A=A
o_B =v_B
Link A and o_B to the target.
Hi I am trying to merge two tables the FormA scores table that I made that is now CalculatingScores with the domain number found in DomainsFormA. I need to merge them by QuestionNum. Here is my code.
proc sql;
create table combined as
select *
from CalculatingScores inner join DomainsFormA
on CalculatingScores.Scores=DomainsFormA.QuestionNum;
quit;
proc print data=combined (obs=15);
run;
This table is what I am trying to get my merged tables to look like but for 15 observations.
Form
Student
QuestionNum
Scores
DomainNum
A
1
1
0
5
A
1
2
1
4
A
1
3
0
5
But My tables look more like this
Form
Student
QuestionNum
Scores
DomainNum
A
1
2
1
5
A
1
4
1
5
A
1
5
1
5
My entire Scores column for these 15 observations have a value of 1. Also my DomainNum column only has values of 5. My Student and Form columns are correct but I need to have varied scores and varied domain numbers. Any ideas for how to solve my problem? Maybe I need a order by statement?
You appear to be joining on the incorrect columns
You coded
on CalculatingScores.Scores=DomainsFormA.QuestionNum
which is joining a score to a question number
perhaps you should be coding
on CalculatingScores.QuestionNum=DomainsFormA.QuestionNum
^^^^^^^^^^^ ^^^^^^^^^^^
I've 2 cols lets say id and values. I want to concatenate values grouped by id col.
for eg.
I've
ID Values
1 a
1 b
2 a
2 b
I need the output as
ID Values
1 a,b
2 a,b
You can use an array_agg followed by an array_join
select id, array_join(array_agg(values),',') from table group by 1
The array_agg will give you an array of all values with the same id, and the array_join will concatenate them into a string. See the docs.
I have a pandas data frame and I have a list of values. I want to keep all the rows from my original DF that have a certain column value belonging to my list of values. However my list that I want to choose my rows from have repeated values. Each time I encounter the same values again I want to add the rows with that column values again to my new data frame.
lets say my frames name is: with_prot_choice_df and my list is: with_prot_choices
if I issue the following command:
with_prot_choice_df = with_df[with_df[0].isin(with_prot_choices)]
then this will only keep the rows once (as if for only unique values in the list).
I don't want to do this with for loops since I will repeat the process many times and it will be extremely time consuming.
Any advice will be appreciated. Thanks.
I'm adding an example here:
let's say my data frame is:
col1 col2
a 1
a 6
b 2
c 3
d 4
and my list is:
lst = [a,b,a,a]
I want my new data frame, new_df to be:
new_df
col1 col2
a 1
a 6
b 2
a 1
a 6
a 1
a 6
Seems like you need reindex
df.set_index('col1').reindex(lst).reset_index()
Out[224]:
col1 col2
0 a 1
1 b 2
2 a 1
3 a 1
Updated
df.merge(pd.DataFrame({'col1':lst}).reset_index()).sort_values('index').drop('index',1)
Out[236]:
col1 col2
0 a 1
3 a 6
6 b 2
1 a 1
4 a 6
2 a 1
5 a 6
I have a view with two columns: a person's ID (a number) and the sector that they below to (given as numbers 1-5).
I want to create a view to show whether people belong to the same sector. I think this would have three columns: ID1, ID2, and SameSector. The first column would list IDs, and for each ID in column 1 the second column would list ALL of the IDs. The third column would be an if statement, 1 if the sector was the same for both IDs, 0 if it wasn't. This is made slightly more complicated because a person can belong to more than one sector.
For example:
I have:
ID Sector
1 1
2 1
2 5
3 1
I want:
ID1 ID2 SameSector
1 1 1
1 2 1
1 2 0
1 3 0
2 1 1
2 1 0
etc.
I'm guessing this involves some sort of self join and if statement but I can't figure out how to get all of the ID fields to be listed in ID1 column and matched to all of the ID fields in ID2 any ideas?
This should be what you want:
SELECT a.ID AS ID1, b.ID AS ID2, IF(a.Sector=b.Sector,1,0) AS SameSector
FROM theTable AS a, theTable AS b
http://sqlfiddle.com/#!2/f2cbc/4
I initially had a much more complicated query, but then realized you wanted a complete cross-join, including the same ID comparing to itself.