I need to swap 1 set of number with another set of numbers.
y z pk x
------ ------ ------ -----
1 2 1 5
1 3 2 5
1 4 3 5
5 6 4 5
5 7 5 5
5 8 6 5
1 2 7 9
1 3 8 9
5 6 9 9
1 4 10 9
5 7 11 9
5 8 12 9
I need all 1's to be 5's and all 5's to be 1's in column y where x = 9.
y and z fields have FK constraints that cannot be dropped.
UPDATE table
SET y = 6 - y
WHERE x = 9
note:
if there are other values in column y for x = 9 that don't need to be touched, don't forget to also add something like
AND y IN (1,5)
EDIT:
General formula for swapping any two numbers a and b would be:
UPDATE tbl
SET col= (a+b) - col
WHERE col IN (a,b)
Assuming you know the primary keys and they are contiguous:
UPDATE table SET y = 5 WHERE pk BETWEEN 7 AND 9;
UPDATE table SET y = 1 WHERE pk BETWEEN 10 AND 12;
Otherwise, I would select the concerned rows primary keys into a temporary tables:
SELECT pk INTO TEMPORARY TABLE temp1 FROM table WHERE x = 9 AND y = 1;
SELECT pk INTO TEMPORARY TABLE temp2 FROM table WHERE x = 9 AND y = 5;
UPDATE table AS t FROM temp1 SET y = 5 WHERE t.pk = temp1.pk
UPDATE table AS t FROM temp2 SET y = 1 WHERE t.pk = temp2.pk
Related
I have a dataframe with 3240 rows and 3 columns. Column Block represents the block in which values in column A and B appeared. Unique number of blocks is 6 but they are repeating in sequence throughout whole dataframe from 1-6. Values in column A are repeating themselves in the sequences of exact order from 1-10 throughout the whole dataframe (blocks). Values in column B exist from a-j (n = 10), but they repeating themselves in random order in sequences from a-j, so they are never duplicated within the Block.
So in each of 6 Blocks, values in column A (1-10) repeat themselves in exact order from 1-10, while In column B, values (a-j) repeat themselves in random order.
Df looks like this:
Block A B ID
1 1 a XY
1 2 b XY
1 3 c XY
1 4 d XY
1 5 e XY
1 6 f XY
1 7 g XY
1 8 h XY
1 9 i XY
1 10 j XY
....
6 1 d XY
...
6 6 j XY
....
1 1 g XX
1 2 a XX
Throughout dataframe i would like to replace all values in column B based on corresponding value in column A for each separate Block. Logic would be to replace values in column B based on values in column A by this pattern 1=6, 2=7, 3=8, 4=9, 5=10.
Result would look like this:
Block A B ID
1 1 f XY
1 2 g XY
1 3 h XY
1 4 i XY
1 5 j XY
1 6 a XY
1 7 b XY
1 8 c XY
1 9 d XY
1 10 e XY
....
6 1 j XY
...
6 6 d XY
....
1 1 g XX
1 2 a XX
What would be an efficient to do this?
You want to identify the block of 5 within each block of 10 and swap them. This is my solution:
df['B'] = (df.assign(blk_5 = (np.arange(len(df))//5+1) % 2,
blk_10 = np.arange(len(df)) // 10
)
.sort_values(['Block','blk_10','blk_5'])
['B'].values
)
This post follow this one: SAS sum observations not in a group, by group
Where my minimal example was a bit too minimal sadly,I wasn't able to use it on my data.
Here is a complete case example, what I have is :
data have;
input group1 group2 group3 $ value;
datalines;
1 A X 2
1 A X 4
1 A Y 1
1 A Y 3
1 B Z 2
1 B Z 1
1 C Y 1
1 C Y 6
1 C Z 7
2 A Z 3
2 A Z 9
2 A Y 2
2 B X 8
2 B X 5
2 B X 5
2 B Z 7
2 C Y 2
2 C X 1
;
run;
For each group, I want a new variable "sum" with the sum of all values in the column for the same sub groups (group1 and group2), exept for the group (group3) the observation is in.
data want;
input group1 group2 group3 $ value $ sum;
datalines;
1 A X 2 8
1 A X 4 6
1 A Y 1 9
1 A Y 3 7
1 B Z 2 1
1 B Z 1 2
1 C Y 1 13
1 C Y 6 8
1 C Z 7 7
2 A Z 3 11
2 A Z 9 5
2 A Y 2 12
2 B X 8 17
2 B X 5 20
2 B X 5 20
2 B Z 7 18
2 C Y 2 1
2 C X 1 2
;
run;
My goal is to use either datasteps or proc sql (doing it on around 30 millions observations and proc means and such in SAS seems slower than those on previous similar computations).
My issue with solutions provided in the linked post is that is uses the total value of the column and I don't know how to change this by using the total in the sub group.
Any idea please?
A SQL solution will join all data to an aggregating select:
proc sql;
create table want as
select have.group1, have.group2, have.group3, have.value
, aggregate.sum - value as sum
from
have
join
(select group1, group2, sum(value) as sum
from have
group by group1, group2
) aggregate
on
aggregate.group1 = have.group1
& aggregate.group2 = have.group2
;
SQL can be slower than hash solution, but SQL code is understood by more people than those that understand SAS DATA Step involving hashes ( which can be faster the SQL. )
data want2;
if 0 then set have; * prep pdv;
declare hash sums (suminc:'value');
sums.defineKey('group1', 'group2');
sums.defineDone();
do while (not hash_loaded);
set have end=hash_loaded;
sums.ref(); * adds value to internal sum of hash data record;
end;
do while (not last_have);
set have end=last_have;
sums.sum(sum:sum); * retrieve group sum.;
sum = sum - value; * subtract from group sum;
output;
end;
stop;
run;
SAS documentation touches on SUMINC and has some examples
The question does not address this concept:
For each row compute the tier 2 sum that excludes the tier 3 this row is in
A hash based solution would require tracking each two level and three level sums:
data want2;
if 0 then set have; * prep pdv;
declare hash T2 (suminc:'value'); * hash for two (T)iers;
T2.defineKey('group1', 'group2'); * one hash record per combination of group1, group2;
T2.defineDone();
declare hash T3 (suminc:'value'); * hash for three (T)iers;
T3.defineKey('group1', 'group2', 'group3'); * one hash record per combination of group1, group2, group3;
T3.defineDone();
do while (not hash_loaded);
set have end=hash_loaded;
T2.ref(); * adds value to internal sum of hash data record;
T3.ref();
end;
T2_cardinality = T2.num_items;
T3_cardinality = T3.num_items;
put 'NOTE: |T2| = ' T2_cardinality;
put 'NOTE: |T3| = ' T3_cardinality;
do while (not last_have);
set have end=last_have;
T2.sum(sum:t2_sum);
T3.sum(sum:t3_sum);
sum = t2_sum - t3_sum;
output;
end;
stop;
drop t2_: t3:;
run;
From a given table I want to be able to sum values having the same number (should be easy, right?)
Problem: A given value can be assigned from 2 to n consecutive numbers.
For some reasons this information is stored in a single row describing the value, the starting number and the ending number as below.
TABLE A
id | starting_number | ending_number | value
----+-----------------+---------------+-------
1 2 5 8
2 0 3 5
3 4 6 6
4 7 8 10
For instance the first row means:
value '8' is assigned to numbers: 2, 3 and 4 (5 is excluded)
So, I would like the following intermediairy result table
TABLE B
id | number | value
----+--------+-------
1 2 8
1 3 8
1 4 8
2 0 5
2 1 5
2 2 5
3 4 6
3 5 6
4 7 10
So I can sum 'value' for elements having identical 'number'
SELECT number, sum(value)
FROM B
GROUP BY number
TABLE C
number | sum(value)
--------+------------
2 13
3 8
4 14
0 5
1 5
5 6
7 10
I don't know how to do this and didn't find any answer on the web (maybe not looking with appropriate key words...)
Any idea?
You can do what you want with generate_series(). So, TableB is basically:
select id, generate_series(starting_number, ending_number - 1, 1) as n, value
from tableA;
Your aggregation is then:
select n, sum(value)
from (select id, generate_series(starting_number, ending_number - 1, 1) as n, value
from tableA
) a
group by n;
I've got a bit of a complicated query that I'm struggling with. You will notice that the schema isn't the easiest thing to work with but it's what I've been given and there isn't time to re-design (common story!).
I have rows like the ones below. Note: The 3 digit value numbers are just random numbers I made up.
id field_id value
1 5 999
1 6 888
1 7 777
1 8 foo <--- foo so we want the 3 values above
1 9 don't care
2 5 123
2 6 456
2 7 789
2 8 bar <--- bar so we DON'T want the 3 values above
2 9 don't care
3 5 623
3 6 971
3 7 481
3 8 foo <--- foo so we want the 3 values above
3 9 don't care
...
...
n 5 987
n 6 654
n 7 321
n 8 foo <--- foo so we want the 3 values above
n 9 don't care
I want this result:
id result
1 999*888*777
3 623*971*481
...
n 987*654*321
Is this clear? So we have a table with n*5 rows. For each of the sets of 5 rows: 3 of them have values we might want to multiply together, 1 of them tells us if we want to multiply and 1 of them we don't care about so we don't want the row in the query result.
Can we do this in Oracle? Preferably one query.. I guess you need to use a multiplication operator (somehow), and a grouping.
Any help would be great. Thank you.
something like this:
select m.id, exp(sum(ln(m.value)))
from mytab m
where m.field_id in (5, 6, 7)
and m.id in (select m2.id
from mytab m2
where m2.field_id = 8
and m2.value = 'foo')
group by m.id;
eg:
SQL> select * from mytab;
ID FIELD_ID VAL
---------- ---------- ---
1 5 999
1 6 888
1 7 777
1 8 foo
1 9 x
2 5 123
2 6 456
2 7 789
2 8 bar
2 9 x
3 5 623
3 6 971
3 7 481
3 8 foo
3 9 x
15 rows selected.
SQL> select m.id, exp(sum(ln(m.value))) result
2 from mytab m
3 where m.field_id in (5, 6, 7)
4 and m.id in (select m2.id
5 from mytab m2
6 where m2.field_id = 8
7 and m2.value = 'foo')
8 group by m.id;
ID RESULT
---------- ----------
1 689286024
3 290972773
Same logic; just removed the hard-coded values. posting this answer thinking might be helpful to some others.
SELECT a.id,
exp(sum(ln(a.val)))
FROM mytab a,
(SELECT DISTINCT id,
field_id
FROM mytab
WHERE val = 'foo') b
WHERE a.id = b.id
AND a.field_id < b.field_id
GROUP BY a.id;
It's quiet hard to describe this problem but it's easy to see it graphically:
x y
1 1
2 1
3 1
* 4 1 *
5 2
* 6 2 *
7 3
8 3
9 3
* 10 3 *
I have sorted a table by x, then sub-sorted by y. I need to return the x value of the last item in the sub-sorted table (the stared rows).
I'm aware of the LAST command, but I don't know how to apply this recursively i.e. to each sub-sorted section.
Best,
Dan
SELECT y, Max(x) FROM [table] group by Y