I wanted to take just the year and month from '2021-07-31 13:53:26' and group them based on count values.
i tried the date, datetime, strftime functions.
Date and Datetime resulting null. strftime result something, but i cant group the Year and Month i get with the count i want, resulting null again
Here is the preview of the data.
expected result example is like '2021-07' with the count of how many times this year and month occurs
This is the syntax i tried with strftime:
select strftime('%Y%m', started_at) year_month, count(year_month) from bike_trip
group by year_month
Thank You
Sqlite doesn't have a date data type so you will need to do string comparison to achieve this.
with d as (
select '2021-07-31 13:53:26' as d, 'A' val union all
select '2021-08-30 13:53:26' as d, 'B' val
)
select substr(d,1,4) as yyyy, substr(d,6,2) as mm, count(*)
from d
group by substr(d,1,4), substr(d,6,2)
in your query:
select substr(started_at,1,4) as yyyy, substr(started_at,6,2) as mm, count(*)
from bike_trip
group by substr(started_at,1,4), substr(started_at,6,2)
Use a CTE to get your answer.
with
-- uncomment to test
/*bike_trip(started_at) as (
values
('2021-07-31 13:53:26'),
('2021-07-17 19:06:01'),
('2021-08-30 13:53:26')
),*/
bike_months(year_month) as (
select strftime('%Y-%m', started_at) year_month from bike_trip
)
select year_month, count(year_month) count_year_month from bike_months
group by year_month;
Output:
year_month|count_year_month
2021-07|2
2021-08|1
Related
I am attempting to produce Table2 below - which essentially counts the rows that have the same day and adds up the "amount" column for the rows that are on the same day.
I found a solution online that can count entries from the same day, which works:
SELECT
DATE_TRUNC('day', datetime) AS date,
COUNT(datetime) AS date1
FROM Table1
GROUP BY DATE_TRUNC('day', datetime);
It is partially what I am looking for, but I am having difficulty trying to display all the column names.
In my attempt, I have all the columns I want but the Accumulated Count is not accurate since it counts the rows with unique IDs (because I put "id" in GROUP BY):
SELECT *, count(id) OVER(ORDER BY DateTime) as accumulated_count,
SUM(Amount) OVER(ORDER BY DateTime) AS Accumulated_Amount
FROM Table1
GROUP BY date(datetime), id
I've been working on this for days and seemingly have come across every possible outcome that is not what I am looking for. Does anyone have an idea as to what I'm missing here?
Cumulative sum and count should be calculated for each day
with Table1 (id,datetime,client,product,amount) as(values
(1 ,to_timestamp('2020-07-08 07:30:10','YYYY-MM-DD HH24:MI:SS'),'Tom','Bill Payment',24),
(2 ,to_timestamp('2020-07-08 07:50:30','YYYY-MM-DD HH24:MI:SS'),'Tom','Bill Payment',27),
(3 ,to_timestamp('2020-07-09 08:20:10','YYYY-MM-DD HH24:MI:SS'),'Tom','Bill Payment',37)
)
SELECT
Table1.*,
count(*) over (partition by DATE_TRUNC('day', datetime)
order by datetime asc ) accumulated_count,
sum(amount) over (partition by DATE_TRUNC('day', datetime) order by datetime asc) accumulated_sum
FROM Table1;
Not to familiar with postgresql but this does what you ask fror.
with data (id,date_time,client,product,amount) as(
select 1 ,to_timestamp('Jul 08 2020, 07:30:10','Mon DD YYYY, HH24:MI:SS'),'Tom','Bill',24 Union all
select 2 ,to_timestamp('Jul 08 2020, 07:50:30','Mon DD YYYY, HH24:MI:SS'),'Tom','Bill',27 Union all
select 3 ,to_timestamp('Jul 09 2020, 08:20:10','Mon DD YYYY, HH24:MI:SS'),'Tom','Bill',37
)
select d.id,d.date_time,d.client,d.product,d.amount,
(select count(*) from data d1
where d1.date_time <= d.date_time and date(d1.date_time) = date(d.date_time) ) acc_count,
(select sum(amount) from data d1
where d1.date_time <= d.date_time and date(d1.date_time) = date(d.date_time) ) acc_amount
from data d
I have a table like this, I hope to count the number of ids by month. I used the following code but it does not work.
id date_time
1390880502018723840,2021-05-08
1390881127930372100,2021-05-08
1390881498270736386,2021-05-08
SELECT twitter.tweets.id
WHERE Month(twitter.tweets.date_time)=01 AND Year(twitter.tweets.date_time)=2021 ;
you have to use count() function and to_char to get year month part of date in one column:
SELECT count(witter.tweets.id)
WHERE to_char(twitter.tweets.date_time,'YYYY-MM')= '2021-01';
you can generalize it for all the month/year by using group by :
SELECT to_char(twitter.tweets.date_time,'YYYY-MM') , count(witter.tweets.id)
group by to_char(twitter.tweets.date_time,'YYYY-MM');
To get counts for all months since Jan 2021:
SELECT date_trunc('month', date_time), count(*)
FROM twitter.tweets
WHERE date_time >= '2021-01-01'
GROUP BY 1;
If id can be NULL (which should be disallowed for an id column), use the slightly more expensive count(id) instead.
Count of distinct IDs:
SELECT date_trunc('month', date_time), count(DISTINCT id)
FROM twitter.tweets
WHERE date_time >= '2021-01-01'
GROUP BY 1;
For only Jan 2021:
SELECT count(DISTINCT id)
FROM twitter.tweets
WHERE date_time >= '2021-01-01'
WHERE date_time < '2021-02-01';
I am using the following to transfrom the date variable to YYYY and Mon
select
to_char(date, 'Mon') as month,
extract(year from date) as year,
v1,
count(v2) as count
from data
group by 1,2,3
order by 2,1;
However, when I do an order by, it does not order my data properly. So I think I have to convert Mon either to a number or back to a date to be able to sort it properly. Thoughts?
Of course not. It is ordering by the month name.
Instead, just order by the date:
order by date
If this were an aggregation query, then you would use an aggregation function:
order by min(date)
I would use a derived table where the grouping is done on a proper date value and convert it only for display purposes:
select to_char(month_date, 'Mon' as month,
extract(year from month_date) as year,
v1,
count
from (
select date_trunc('month', "date") as month_date
v1,
count(v2) as count
from data
group by 1,2
)
order by month_date
customer Date location
1 25Jan2018 texas
2 15Jan2018 texas
3 12Feb2018 Boston
4 19Mar2017 Boston.
I am trying to find out count of customers group by yearmon of Date column.Date column is of text data type
eg: In jan2018 ,the count is 2
I would do something like the following:
SELECT
date_part('year', formattedDate) as Year
,date_part('month', formattedDate) as Month
,count(*) as CustomerCountByYearMonth
FROM
(SELECT to_date(Date,'DDMonYYYY') as formattedDate from <table>) as tbl1
GROUP BY
date_part('year', formattedDate)
,date_part('month', formattedDate)
Any additional formatting for dates could be done on the inner query that will allow for adjustments in case some single digit days need to be padded or a month has four letters instead of three etc.
By converting to date type, you can properly order by date type and not alphabetical etc.
Optionally:
SELECT
Year
,Month
,count(*) as CustomerCountByYearMonth
FROM
(SELECT
date_part('year', to_date(Date,'DDMonYYYY')) as Year
,date_part('month', to_date(Date,'DDMonYYYY')) as Month
FROM <table>) as tbl1
GROUP BY
Year
,Month
You shouldn't store dates in a text column...
select substring(Date, length(Date)-6), count(*)
from tablename
group by substring(Date, length(Date)-6)
I thought #Jarlh asked a good question -- what about dates like January 1? Is it 01Jan2019 or 1Jan2019? If it can be either, perhaps a regex would work.
select
substring (date from '\d+(\D{3}\d{4})') as month,
count (distinct customer)
from t
group by month
The 'distinct customer' also presupposes you may have the same customer listed in the same month, but you only want to count it once. If that's not the case, just remove 'distinct.'
And, if you wanted the output in date format:
select
to_date (substring (date from '\d+(\D{3}\d{4})'), 'monyyyy') as month,
count (distinct customer)
from t
group by month
If it is a date column, you can truncate the date:
select date_trunc('month', date) as yyyymm, count(*)
from t
group by yyyymm
order by yyyymm;
I really read that the type was date. For a string, just use string functions:
select substr(date, 3, 7) as mmmyyyy, count(*)
from t
group by mmmyyyy;
Unfortunately, ordering doesn't work in this case. You should really be storing dates using the proper type.
I would like to query Athena with JSON files. I matched creation_date with id because I would like to get a heatmap where on Y axis I have month, on X axis there day and I count the id's inside. I created a table with 2 columns:
creation_date date, id int. Next I am query with the below code:
SELECT CAST(creation_date as DATE) as ad_creation,
COUNT(id) as Total_ads
FROM default.test
GROUP BY CAST(creation_at_first as DATE)
unfortunately I am getting this error:
DatabaseError: Execution failed on sql: SELECT CAST(creation_date as DATE) as ad_creation, COUNT(id) as Total_ads FROM default.testing_fresh_1 GROUP BY CAST(creation_date as DATE)
When I query Select * from...
I get results formatted like this:
creation_date
2018-07-01 02:02:09
2018-06-05 01:39:30
2018-05-16 21:28:48
2017-04-23 17:03:53
Any idea what I am doing wrong?
From your select * result set, I guess there isn't ID column in your table.
You can try to use COUNT(*) instead of COUNT(id)
SELECT CAST(creation_date as DATE) as ad_creation,
COUNT(*) as Total_ads
FROM default.test
GROUP BY CAST(creation_date as DATE)
Try below Code.
SELECT CAST(creation_date as DATE) as ad_creation,
COUNT(id) as Total_ads
FROM default.testing_fresh_1
GROUP BY ad_creation