I've got a table with purchase orders stored in it. Each row has a timestamp indicating when the order was placed. I'd like to be able to create a report indicating the number of purchases each day, month, or year. I figured I would do a simple SELECT COUNT(xxx) FROM tbl_orders GROUP BY tbl_orders.purchase_time and get the value, but it turns out I can't GROUP BY a timestamp column.
Is there another way to accomplish this? I'd ideally like a flexible solution so I could use whatever timeframe I needed (hourly, monthly, weekly, etc.) Thanks for any suggestions you can give!
This does the trick without the date_trunc function (easier to read).
// 2014
select created_on::DATE from users group by created_on::DATE
// updated September 2018 (thanks to #wegry)
select created_on::DATE as co from users group by co
What we're doing here is casting the original value into a DATE rendering the time data in this value inconsequential.
Grouping by a timestamp column works fine for me here, keeping in mind that even a 1-microsecond difference will prevent two rows from being grouped together.
To group by larger time periods, group by an expression on the timestamp column that returns an appropriately truncated value. date_trunc can be useful here, as can to_char.
Related
I'm looking to only select one data point from each date in my report. I want to ensure each day is accounted for and has at least one row of information, as we had to do a few different things to move a large data file into our data warehouse (import one large Google Sheet for some data, use Python for daily pulls of some of the other data - want to make sure no date was left out), and this data goes from now through last summer. I could do a COUNT DISTINCT clause to just make sure the number of days between the first data point and yesterday (the latest data point), but I want to verify each day is accounted for. Should mention I am in BigQuery. Also, an example of the created_at style is: 2021-02-09 17:05:44.583 UTC
This is what I have so far:
SELECT FIRST(created_at)
FROM 'large_table'
ORDER BY created_at
**I know FIRST is probably not the best clause for this case, and it's currently acting to grab the very first data point in created_at, but just as a jumping-off point.
You can use aggregation:
select any_value(lt).*
from large_table lt
group by created_at
order by min(created_at);
Note: This assumes that created_at is a date -- or at least only has one value per date. You might need to convert it to a date:
select any_value(lt).*
from large_table lt
group by date(created_at)
order by min(created_at);
BigQuery equivalent of the query in your question
SELECT created_at
FROM 'large_table'
ORDER BY created_at
LIMIT 1
To put a long story short, I am working on a database using PostgreSQL that is managing yelp checkins. The checkintable has the attributes business_id(string), date(string in form yyyy-mm-dd), and time(string in form 00:00:00).
What I simply need to do is, given a business_id, I need to return a list of the total number of checkins based on just the mm (month) value.
So for instance, I need to retrieve the total checkins that were in Jan, Feb, March, April, etc, not based upon the year.
Any help is greatly appreciated. I've already considered group by clauses but I didn't know how to factor in '%mm%'.
Reiterating Gordon, class or not, storing dates and times as strings makes things harder, slower, and more likely to break. It's harder to take advantage of Postgres's powerful date math functions. Storing dates and times separately makes things even harder; you have to concatenate them together to get the full timestamp which means it will not be indexed. Determining the time between two events becomes unnecessarily difficult.
It should be a single timestamp column. Hopefully your class will introduce that shortly.
What I simply need to do is, given a business_id, I need to return a list of the total number of checkins based on just the mm (month) value.
This is deceptively straightforward. Cast your strings to dates, fortunately they're in ISO 8601 format so no reformatting is required. Then use extract to extract just the month part.
select
extract('month' from checkin_date::date) as month,
count(*)
from yelp_checkins
where business_id = ?
group by month
order by month
But there's a catch. What if there are no checkins for a business on a given month? We'll get no entry for that month. This is a pretty common problem.
If we want a row for every month, we need to generate a table with our desired months with generate_series, then left join with our checkin table. A left join ensures all the months (the "left" table) will be there even if there is no corresponding month in the join table (the "right" table).
select
months.month,
count(business_id)
from generate_series(1,12) as months(month)
left join yelp_checkins
on months.month = extract('month' from checkin_date::date)
and business_id = ?
group by months.month
order by months.month
Now that we have a table of months, we can group by that. We can't use a where business_id = ? clause or that will filter out empty months after the left join has happened. Instead we must put that as part of the left join.
Try it.
Why would you store the date as a string? That is a broken data model. You should fix the data.
That said, I recommend converting a date and truncating to the first day of the month:
select date_trunc('day', datestr::date) as yyyymm, count(*)
from t
group by yyyymm
order by yyyymm;
If you don't want these based on the year, then use extract():
select extract(month from datestr::date) as mm, count(*)
from t
group by mm
order by mm;
I have a table named Sales and a column within it named Date. I'm simply trying to find how many sales were made on a specific date. My intuition was to use something like this:
SELECT COUNT(Date) FROM Sales WHERE Date='2015-04-04'
this should count all sales that were made on that date, but that returns 0. What am I doing wrong?
While it is difficult to be precise without table definitions or an indication of what RDBMS you are using, it is likely that Date is a time/date stamp, and that the result you want would be obtained either by looking for a range from the beginning of the day to the end of the day in your WHERE clause, or by truncating Date down to a date without the time before comparing it to a date.
Try the below once.
select count(*) from <t.n> where date like '2015-04-04%';
When you want to find the count of rows based on a field (Date) You need to Group By over it like this:
SELECT Date, COUNT(*)
FROM Sales
GROUP BY Date
Now you have all count of rows for each Date.
Type and Value of Date is important in the result of the above query.
For example in SQL Server your best try is to convert a DateTime field to varchar and then check it as the result of CONVERT like this:
SELECT COUNT(*)
FROM Sales
WHERE CONVERT(VARCHAR, Date, 111) = '2015/04/04'
Long title, easy meaning:
How is it possible to extract from a date like "2014-04-04 10:47:30.000", which is stored in one column, it's components like year, month and day?
I'm not interested in the time.
For example, I have a table called "Incidents". Inside the table we got a column called "IncidentID" and a column called "ReportingDate", in which dates like the above-mentionend are stored. Let's say we have about 50k Incidents, therefore we have also 50k dates.
A year has 365 days. I want to query for the count of the Incidents, which were reported on different dates - for instance on the 5th of October 2013.
So: How can I get the components of the date and put them into another table while having own columns for the components and how can I query for the Incidents as well?
I guess at first I have to change the datatype of the date from DATETIME to DATE, but I'm not quite sure how to go further. May anyone help me while giving me a code and explains me what it does for a sql-noob? :-)
To achieve this
I want to query for the count of the Incidents, which were reported on
different dates - for instance on the 5th of October 2013.
you haven't do this:
I guess at first I have to change the datatype of the date from
DATETIME to DATE, but I'm not quite sure how to go further.
Just query
SELECT
IncidentID
FROM incidents
WHERE ReportingDate >= '20131005'
AND ReportingDate < '20131006'
I have an SQLite database with the following fields for example:
date (yyyymmdd fomrat)
total (0.00 format)
There is typically 2 months of records in the database. Does anyone know a SQL query to find a weekly average?
I could easily just execute:
SELECT COUNT(1) as total_records, SUM(total) as total FROM stats_adsense
Then just divide total by 7 but unless there is exactly x days that are divisible by 7 in the db I don't think it will be very accurate, especially if there is less than 7 days of records.
To get a daily summary it's obviously just total / total_records.
Can anyone help me out with this?
You could try something like this:
SELECT strftime('%W', thedate) theweek, avg(total) theaverage
FROM table GROUP BY strftime('%W', thedate)
I'm not sure how the syntax would work in SQLite, but one way would be to parse out the date parts of each [date] field, and then specifying which WEEK and DAY boundaries in your WHERE clause and then GROUP by the week. This will give you a true average regardless of whether there are rows or not.
Something like this (using T-SQL):
SELECT DATEPART(w, theDate), Avg(theAmount) as Average
FROM Table
GROUP BY DATEPART(w, theDate)
This will return a row for every week. You could filter it in your WHERE clause to restrict it to a given date range.
Hope this helps.
Your weekly average is
daily * 7
Obviously this doesn't take in to account specific weeks, but you can get that by narrowing the result set in a date range.
You'll have to omit those records in the addition which don't belong to a full week. So, prior to summing up, you'll have to find the min and max of the dates, manipulate them such that they form "whole" weeks, and then run your original query with a WHERE that limits the date values according to the new range. Maybe you can even put all this into one query. I'll leave that up to you. ;-)
Those values which are "truncated" are not used then, obviously. If there's not enough values for a week at all, there's no result at all. But there's no solution to that, apparently.