SQL Custom unique Ordering with repeated sequence - sql

I have a datetime column (data type of timestamp without time zone) named time. I can best explain my issue with a example:
Example I've the following data in this column (pretifying timestamp for this example)
ID TIME
1 1 Mar 2022 - 1PM
2 1 Mar 2022 - 2PM
3 1 Mar 2022 - 1PM
4 1 Mar 2022 - 3PM
5 1 Mar 2022 - 2PM
6 2 Mar 2022 - 2PM
7 2 Mar 2022 - 1PM
8 2 Mar 2022 - 3PM
9 2 Mar 2022 - 1PM
10 1 Mar 2022 - 3PM
11 2 Mar 2022 - 2PM
12 2 Mar 2022 - 3PM
13 3 Mar 2022 - 4PM
14 3 Mar 2022 - 3PM
15 3 Mar 2022 - 3PM
16 3 Mar 2022 - 4PM
If i do ORDER BY time, i get the following result:
ID TIME
1 1 Mar 2022 - 1PM
3 1 Mar 2022 - 1PM
2 1 Mar 2022 - 2PM
5 1 Mar 2022 - 2PM
4 1 Mar 2022 - 3PM
10 1 Mar 2022 - 3PM
7 2 Mar 2022 - 1PM
9 2 Mar 2022 - 1PM
6 2 Mar 2022 - 2PM
11 2 Mar 2022 - 2PM
8 2 Mar 2022 - 3PM
12 2 Mar 2022 - 3PM
14 3 Mar 2022 - 3PM
15 3 Mar 2022 - 3PM
13 3 Mar 2022 - 4PM
16 3 Mar 2022 - 4PM
But i want the result in this way:
ID TIME
1 1 Mar 2022 - 1PM
2 1 Mar 2022 - 2PM
4 1 Mar 2022 - 3PM
13 3 Mar 2022 - 4PM
3 1 Mar 2022 - 1PM
5 1 Mar 2022 - 2PM
10 1 Mar 2022 - 3PM
16 3 Mar 2022 - 4PM
7 2 Mar 2022 - 1PM
6 2 Mar 2022 - 2PM
8 2 Mar 2022 - 3PM
9 2 Mar 2022 - 1PM
11 2 Mar 2022 - 2PM
12 2 Mar 2022 - 3PM
14 3 Mar 2022 - 3PM
13 3 Mar 2022 - 4PM
As you can see first 4 rows have unique timestamp and the sequence should repeat based on Time (1PM, 2PM, 3PM).
How can we do this in SQL? I'm using postresql as my DB. I'm using Rails for my Backend.
EDIT:
Have added more context to example to explain my scenario.

One way you can try to use ROW_NUMBER window function with REPLACE function
SELECT time
FROM (
SELECT *,REPLACE(time,'PM','') val,
ROW_NUMBER() OVER(PARTITION BY REPLACE(time,'PM','')) rn
FROM T
) t1
ORDER BY rn,val

For example, sequence of the col a
with tbl(a, othercol) as
(
SELECT 1,1 UNION ALL
SELECT 1,2 UNION ALL
SELECT 1,3 UNION ALL
SELECT 2,4 UNION ALL
SELECT 2,5 UNION ALL
SELECT 2,6 UNION ALL
SELECT 3,7 UNION ALL
SELECT 3,8 UNION ALL
SELECT 3,9
),
cte as (
SELECT *, row_number() over(partition by a order by a) rn
from tbl
)
select a, othercol
from cte
order by rn, a

The problem you have at hand is a direct result of not choosing the correct data type for the values you store.
To get the sorting correct, you need to convert the string to a proper time value. There is no to_time() function in Postgres, but you can convert it to a timestamp then cast it to a time:
order by to_timestamp("time", 'hham')::time
You should fix your database design and convert that column to a proper time type. Which will also prevent storing invalid values ('3 in the afternoon' or '128foo') in that column

Related

Pandas Sort Two Columns with Day of Year Wrap-Around to New Year

I have data that may at certain times of the year around the first of each year, that a day_of_year sequence involves changing the "year" column to the new year when day_of_year ==1. It is a trick that I have not been able to figure out and in some ways not sure how to start so any help here is much appreciated. My data looks like this:
Here is my df1 =
day_of_year year var_1
364 2017 17.71666667
364 2018 5.166666667
364 2019 2
364 2020 1.595833333
364 2021 3.75
364 2022 6.8875
365 2017 14.83333333
365 2018 2.758333333
365 2019 4.108333333
365 2020 5.766666667
365 2021 5.291666667
365 2022 10.58636364
1 2017 2.0125
1 2018 14.0125
1 2019 -0.504166667
1 2020 7.666666667
1 2021 5.520833333
1 2022 1.229166667
2 2017 1.7625
2 2018 15.10416667
2 2019 -0.391666667
2 2020 9.5
2 2021 7.645833333
2 2022 0.9125
And, after the re-formatting, I need it to look like the below sorted df with "n/a" for any missing or expected data in a year that might be missing data. thank you again,
final df:
day_of_year year var_1
364 2017 17.71666667
365 2017 14.83333333
1 2018 14.0125
2 2018 15.10416667
364 2018 5.166666667
365 2018 2.758333333
1 2019 -0.504166667
2 2019 -0.391666667
364 2019 2
365 2019 4.108333333
1 2020 7.666666667
2 2020 9.5
364 2020 1.595833333
365 2020 5.766666667
1 2021 5.520833333
2 2021 7.645833333
364 2021 3.75
365 2021 5.291666667
1 2022 1.229166667
2 2022 0.9125
364 2022 6.8875
365 2022 10.58636364
n/a n/a n/a
n/a n/a n/a
Why would you change the year based on the day? Just sort by the two columns:
df.sort_values(by=['year', 'day_of_year'])
Output:
day_of_year year var_1
12 1 2017 2.012500
18 2 2017 1.762500
0 364 2017 17.716667
6 365 2017 14.833333
13 1 2018 14.012500
19 2 2018 15.104167
1 364 2018 5.166667
7 365 2018 2.758333
14 1 2019 -0.504167
20 2 2019 -0.391667
2 364 2019 2.000000
8 365 2019 4.108333
15 1 2020 7.666667
21 2 2020 9.500000
3 364 2020 1.595833
9 365 2020 5.766667
16 1 2021 5.520833
22 2 2021 7.645833
4 364 2021 3.750000
10 365 2021 5.291667
17 1 2022 1.229167
23 2 2022 0.912500
5 364 2022 6.887500
11 365 2022 10.586364
If for some reason you really need to fix the year, use a conditional with mask:
(df.assign(year=df['year'].mask(df['day_of_year'].le(2), df['year'].add(1)))
.sort_values(by=['year', 'day_of_year'])
)
Or, if you want to update the years after a change from 365 to a lower day:
(df.assign(year=df['year'].add(df['day_of_year'].diff().lt(0).cumsum()))
.sort_values(by=['year', 'day_of_year'])
)
Output:
day_of_year year var_1
0 364 2017 17.716667
6 365 2017 14.833333
12 1 2018 2.012500
18 2 2018 1.762500
1 364 2018 5.166667
7 365 2018 2.758333
13 1 2019 14.012500
19 2 2019 15.104167
2 364 2019 2.000000
8 365 2019 4.108333
14 1 2020 -0.504167
20 2 2020 -0.391667
3 364 2020 1.595833
9 365 2020 5.766667
15 1 2021 7.666667
21 2 2021 9.500000
4 364 2021 3.750000
10 365 2021 5.291667
16 1 2022 5.520833
22 2 2022 7.645833
5 364 2022 6.887500
11 365 2022 10.586364
17 1 2023 1.229167
23 2 2023 0.912500
I would convert everything to date time first. Just run:
pd.to_datetime(df['day_of_year'].astype(str) + '-' + df['year'].astype(str),
format='%j-%Y')
I assign it to column ymd and sort, yielding the following:
>>> df.sort_values('ymd')
day_of_year year var_1 ymd
12 1 2017 2.012500 2017-01-01
18 2 2017 1.762500 2017-01-02
0 364 2017 17.716667 2017-12-30
6 365 2017 14.833333 2017-12-31
13 1 2018 14.012500 2018-01-01
19 2 2018 15.104167 2018-01-02
1 364 2018 5.166667 2018-12-30
7 365 2018 2.758333 2018-12-31
14 1 2019 -0.504167 2019-01-01
20 2 2019 -0.391667 2019-01-02
2 364 2019 2.000000 2019-12-30
8 365 2019 4.108333 2019-12-31
15 1 2020 7.666667 2020-01-01
21 2 2020 9.500000 2020-01-02
3 364 2020 1.595833 2020-12-29
9 365 2020 5.766667 2020-12-30
16 1 2021 5.520833 2021-01-01
22 2 2021 7.645833 2021-01-02
4 364 2021 3.750000 2021-12-30
10 365 2021 5.291667 2021-12-31
17 1 2022 1.229167 2022-01-01
23 2 2022 0.912500 2022-01-02
5 364 2022 6.887500 2022-12-30
11 365 2022 10.586364 2022-12-31

Get the last 4 weeks prior to current week of and the same 4 weeks of last year

I have a list of date, fiscal week, and fiscal year:
DATE_VALUE FISCAL_WEEK FISCAL_YEAR_VALUE
14-Dec-20 51 2020
15-Dec-20 51 2020
16-Dec-20 51 2020
17-Dec-20 51 2020
18-Dec-20 51 2020
19-Dec-20 51 2020
20-Dec-20 51 2020
21-Dec-20 52 2020
22-Dec-20 52 2020
23-Dec-20 52 2020
24-Dec-20 52 2020
25-Dec-20 52 2020
26-Dec-20 52 2020
27-Dec-20 52 2020
28-Dec-20 1 2021
29-Dec-20 1 2021
30-Dec-20 1 2021
31-Dec-20 1 2021
1-Jan-21 1 2021
2-Jan-21 1 2021
3-Jan-21 1 2021
4-Jan-21 2 2021
5-Jan-21 2 2021
6-Jan-21 2 2021
7-Jan-21 2 2021
8-Jan-21 2 2021
9-Jan-21 2 2021
10-Jan-21 2 2021
11-Jan-21 3 2021
12-Jan-21 3 2021
13-Jan-21 3 2021
14-Jan-21 3 2021
15-Jan-21 3 2021
16-Jan-21 3 2021
17-Jan-21 3 2021
18-Jan-21 4 2021
19-Jan-21 4 2021
20-Jan-21 4 2021
21-Jan-21 4 2021
22-Jan-21 4 2021
23-Jan-21 4 2021
24-Jan-21 4 2021
20-Dec-21 52 2021
21-Dec-21 52 2021
22-Dec-21 52 2021
23-Dec-21 52 2021
24-Dec-21 52 2021
25-Dec-21 52 2021
26-Dec-21 52 2021
27-Dec-21 53 2021
28-Dec-21 53 2021
29-Dec-21 53 2021
30-Dec-21 53 2021
31-Dec-21 53 2021
1-Jan-22 53 2021
2-Jan-22 53 2021
3-Jan-22 1 2022
4-Jan-22 1 2022
5-Jan-22 1 2022
6-Jan-22 1 2022
7-Jan-22 1 2022
8-Jan-22 1 2022
9-Jan-22 1 2022
10-Jan-22 2 2022
11-Jan-22 2 2022
12-Jan-22 2 2022
13-Jan-22 2 2022
14-Jan-22 2 2022
15-Jan-22 2 2022
16-Jan-22 2 2022
17-Jan-22 3 2022
18-Jan-22 3 2022
19-Jan-22 3 2022
20-Jan-22 3 2022
21-Jan-22 3 2022
22-Jan-22 3 2022
23-Jan-22 3 2022
24-Jan-22 4 2022
25-Jan-22 4 2022
26-Jan-22 4 2022
27-Jan-22 4 2022
28-Jan-22 4 2022
29-Jan-22 4 2022
30-Jan-22 4 2022
I want to pull the last 4 weeks prior to the current week AND the same 4 weeks of the year before. Please see example 1. This works fine when all 4 weeks are within the same year. But when it comes to the beginning of a year when 1 or more weeks are in the current year but the other are in the previous year, I am not able to get the desired output below:
FISCAL_YEAR_VALUE FISCAL_WEEK
2020 51
2020 52
2021 2
2021 1
2021 52
2021 53
2022 1
2022 2
The code I have is below. I am using the date of 21-JAN-22 as an example:
SELECT
FISCAL_YEAR_VALUE,
FISCAL_WEEK
FROM TABLE_NAME
WHERE FISCAL_YEAR_VALUE IN (SELECT *
FROM (WITH T AS (
SELECT DISTINCT FISCAL_YEAR_VALUE
FROM TABLE_NAME
WHERE TRUNC(DATE_VALUE) <= TRUNC(TO_DATE('21-JAN-22'))--TEST DATE
ORDER BY FISCAL_YEAR_VALUE DESC
FETCH NEXT 2 ROWS ONLY
)
SELECT FISCAL_YEAR_VALUE
FROM T ORDER BY FISCAL_YEAR_VALUE
)
)
AND FISCAL_WEEK IN (SELECT *
FROM (WITH T AS (
SELECT DISTINCT FISCAL_WEEK, FISCAL_YEAR_VALUE
FROM TABLE_NAME
WHERE TRUNC(DATE_VALUE) <= TRUNC(TO_DATE('21-JAN-22'))--TEST DATE
ORDER BY FISCAL_YEAR_VALUE DESC, FISCAL_WEEK DESC
OFFSET 1 ROWS
FETCH NEXT 4 ROWS ONLY
)
SELECT FISCAL_WEEK
FROM T ORDER BY FISCAL_YEAR_VALUE, FISCAL_WEEK
)
)
GROUP BY FISCAL_YEAR_VALUE, FISCAL_WEEK
ORDER BY FISCAL_YEAR_VALUE, FISCAL_WEEK
Output of the code is:
FISCAL_YEAR_VALUE FISCAL_WEEK
2021 2
2021 1
2021 52
2021 53
2022 1
2022 2
As you can see, the last 2 weeks of year 2020 are not included. Please see example 2. How can I also include this exception in the code to make it dynamic? Any help would be greatly appreciated!
To find the values this year, you can use:
SELECT DISTINCT fiscal_year_value, fiscal_week
FROM table_name
WHERE date_value < TRUNC(SYSDATE, 'IW')
AND date_value >= TRUNC(SYSDATE, 'IW') - INTERVAL '28' DAY
To find the values from the previous year, you can find the maximum fiscal week from this year and subtract 1 from the year and then use that to find the upper bound of the date_value for last fiscal year and, given that can use a similar range for last year:
WITH this_year (fiscal_year_value, fiscal_week) AS (
SELECT fiscal_year_value, fiscal_week
FROM table_name
WHERE date_value < TRUNC(SYSDATE, 'IW')
AND date_value >= TRUNC(SYSDATE, 'IW') - INTERVAL '28' DAY
),
max_last_year (max_date_value) AS (
SELECT MAX(date_value) + INTERVAL '1' DAY
FROM table_name
WHERE (fiscal_year_value, fiscal_week) IN (
SELECT fiscal_year_value - 1, fiscal_week
FROM this_year
ORDER BY fiscal_year_value DESC, fiscal_week DESC
FETCH FIRST ROW ONLY
)
)
SELECT fiscal_year_value, fiscal_week
FROM this_year
UNION
SELECT t.fiscal_year_value, t.fiscal_week
FROM table_name t
INNER JOIN max_last_year m
ON ( t.date_value < m.max_date_value
AND t.date_value >= m.max_date_value - INTERVAL '28' DAY);
Which, for the sample data:
Create Table table_name(DATE_VALUE DATE, FISCAL_WEEK INT, FISCAL_YEAR_VALUE INT);
INSERT INTO table_name (date_value, fiscal_week, fiscal_year_value)
SELECT DATE '2019-12-30' + LEVEL - 1, CEIL(LEVEL/7), 2020
FROM DUAL
CONNECT BY LEVEL <= 7 * 52
UNION ALL
SELECT DATE '2020-12-28' + LEVEL - 1, CEIL(LEVEL/7), 2021
FROM DUAL
CONNECT BY LEVEL <= 7 * 53
UNION ALL
SELECT DATE '2022-01-03' + LEVEL - 1, CEIL(LEVEL/7), 2022
FROM DUAL
CONNECT BY LEVEL <= 7 * 52;
Outputs:
FISCAL_YEAR_VALUE
FISCAL_WEEK
2022
38
2022
39
2022
40
2022
41
2021
38
2021
39
2021
40
2021
41
And if today's date was 2022-01-01, would output:
FISCAL_YEAR_VALUE
FISCAL_WEEK
2021
52
2021
53
2022
1
2022
2
2020
51
2020
52
2021
1
2021
2
There may be a simpler method but without any knowledge of how you calculate a fiscal year that is not immediately possible.
fiddle

Merge Time Series-Data with different time delta

I am trying to merge two dataframes with different time delta. One represents the returns of an asset (df2) on a daily basis and the other one is the inflation rate (df1) which is published once a month but not in a regular inverval. I am trying to merge those two.
df1 =
First Release
Original Release Date
30 Jun 2010 10:01 1.4%
30 Jul 2010 10:00 1.7%
31 Aug 2010 10:00 1.6%
30 Sep 2010 10:00 1.8%
29 Oct 2010 10:02 1.9%
... ...
17 Mar 2022 11:00 5.9%
21 Apr 2022 10:00 7.4%
18 May 2022 10:00 7.4%
17 Jun 2022 10:00 8.1%
19 Jul 2022 10:00 8.6%
[145 rows x 1 columns]
df2 =
Date
2010-08-11 -0.001654
2010-08-12 -0.028538
2010-08-13 0.001072
2010-08-16 -0.007665
2010-08-17 0.002667
...
2022-01-25 0.029663
2022-01-26 0.026082
2022-01-27 -0.000115
2022-01-28 0.002425
2022-01-31 0.007184
Obviously inflation rate should be placed in the new column from the day after it is released until there is a new release. For example 30. June is the first anouncement and 30 Jul the second. So from 1. July to the 30. July should be 1.4 %. The result is published on the 30. but to avoid look-ahead-bias it is more appropriate to have it . Does someone have an idea or maybe encountered some similar problem ?

SQL group by 7am to 7am

How do I simply group by a 24 hour interval from 7am to 7am in a manner similar to:
select format(t_stamp,'yyyy-MMM')
from mytable
group by format(t_stamp,'yyyy-MMM')
if input is like
3,Wed Mar 23 20:40:40 EDT 2022
3,Wed Mar 23 20:40:39 EDT 2022
4,Wed Mar 23 03:36:10 EDT 2022
3,Wed Mar 22 15:46:44 EST 2022
3,Tue Mar 22 04:16:52 EST 2022
4,Sat Mar 22 03:13:08 EDT 2022
3,Sat Mar 22 03:13:05 EDT 2022
4,Sat Mar 21 04:10:36 EDT 2022
output should be like
6, Mar 23
7, Mar 22
10, Mar 21
4, Mar 20

Databricks: replicate columns

Suppose I am having the following Dataframe :
YEAR MONTH Value
2019 JAN 100
2019 JAN 200
2019 MAR 400
2019 MAR 100
And I do the pivot group by YEAR. ( df.groupBy().pivot()....)
YEAR JAN MAR
2019 300 500
But I also wanted to replicate the column of the Months through out the year even there are no data in that month ...
which means I would like to have
YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
2019 300 0 500 0 0 0 0 0 0 0 0 0
Thanks