Count all rows for each DISTINCT
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up vote
1
down vote
favorite
How can count all rows of WHERE statement:
SELECT DISTINCT column1 FROM table COUNT WHERE date::text LIKE '%2014%';
My output:
column1
=======
info1
info2
info3
Desired OUTPUT:
column1|number_of_rows
=====================
info1 | 2000
info2 | 1500
info3 | 1000
Can you support me How can improve it?
Thanks in advance.
postgresql query count distinct
add a comment |
up vote
1
down vote
favorite
How can count all rows of WHERE statement:
SELECT DISTINCT column1 FROM table COUNT WHERE date::text LIKE '%2014%';
My output:
column1
=======
info1
info2
info3
Desired OUTPUT:
column1|number_of_rows
=====================
info1 | 2000
info2 | 1500
info3 | 1000
Can you support me How can improve it?
Thanks in advance.
postgresql query count distinct
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
How can count all rows of WHERE statement:
SELECT DISTINCT column1 FROM table COUNT WHERE date::text LIKE '%2014%';
My output:
column1
=======
info1
info2
info3
Desired OUTPUT:
column1|number_of_rows
=====================
info1 | 2000
info2 | 1500
info3 | 1000
Can you support me How can improve it?
Thanks in advance.
postgresql query count distinct
How can count all rows of WHERE statement:
SELECT DISTINCT column1 FROM table COUNT WHERE date::text LIKE '%2014%';
My output:
column1
=======
info1
info2
info3
Desired OUTPUT:
column1|number_of_rows
=====================
info1 | 2000
info2 | 1500
info3 | 1000
Can you support me How can improve it?
Thanks in advance.
postgresql query count distinct
postgresql query count distinct
edited Nov 16 at 18:31
MDCCL
6,61531743
6,61531743
asked Nov 16 at 17:56
Mareyes
174
174
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add a comment |
1 Answer
1
active
oldest
votes
up vote
5
down vote
accepted
In this case you can use GROUP BY to get distinct column1 values, and instead of convert the date to text you can use EXTRACT function for this purpose.
select
colum1,
count(*) as number_of_rows
from
your_table
where
extract(year from date) = 2014
group by
column1;
Thank you! is working.
– Mareyes
Nov 16 at 19:56
I'm glad to help
– McNets
Nov 16 at 20:04
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
5
down vote
accepted
In this case you can use GROUP BY to get distinct column1 values, and instead of convert the date to text you can use EXTRACT function for this purpose.
select
colum1,
count(*) as number_of_rows
from
your_table
where
extract(year from date) = 2014
group by
column1;
Thank you! is working.
– Mareyes
Nov 16 at 19:56
I'm glad to help
– McNets
Nov 16 at 20:04
add a comment |
up vote
5
down vote
accepted
In this case you can use GROUP BY to get distinct column1 values, and instead of convert the date to text you can use EXTRACT function for this purpose.
select
colum1,
count(*) as number_of_rows
from
your_table
where
extract(year from date) = 2014
group by
column1;
Thank you! is working.
– Mareyes
Nov 16 at 19:56
I'm glad to help
– McNets
Nov 16 at 20:04
add a comment |
up vote
5
down vote
accepted
up vote
5
down vote
accepted
In this case you can use GROUP BY to get distinct column1 values, and instead of convert the date to text you can use EXTRACT function for this purpose.
select
colum1,
count(*) as number_of_rows
from
your_table
where
extract(year from date) = 2014
group by
column1;
In this case you can use GROUP BY to get distinct column1 values, and instead of convert the date to text you can use EXTRACT function for this purpose.
select
colum1,
count(*) as number_of_rows
from
your_table
where
extract(year from date) = 2014
group by
column1;
edited Nov 16 at 19:01
answered Nov 16 at 18:49
McNets
13.5k41753
13.5k41753
Thank you! is working.
– Mareyes
Nov 16 at 19:56
I'm glad to help
– McNets
Nov 16 at 20:04
add a comment |
Thank you! is working.
– Mareyes
Nov 16 at 19:56
I'm glad to help
– McNets
Nov 16 at 20:04
Thank you! is working.
– Mareyes
Nov 16 at 19:56
Thank you! is working.
– Mareyes
Nov 16 at 19:56
I'm glad to help
– McNets
Nov 16 at 20:04
I'm glad to help
– McNets
Nov 16 at 20:04
add a comment |
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