Javier de la Torre jatorre

## url.txt
SELECT *, 'http://maps.googleapis.com/maps/api/streetview?size=300x190&location='||urlencode (address)||'&sensor=false&fov=110' as image_with_address
FROM example_addresses

## gist:1377437b4b80e0ab11f8
<iframe width='100%' height='520' frameborder='0' src='http://osm2.cartodb.com/viz/9f8764fa-8eaf-11e4-ae69-0e9d821ea90d/embed_map' allowfullscreen webkitallowfullscreen mozallowfullscreen oallowfullscreen msallowfullscreen></iframe>

## index.html
<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="utf-8">
    <!--Edit the title of the page-->
    <title>CartoDB Point Clustering</title>
    <meta name="description" content="">
    <meta name="author" content="">
    <meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1">
    <link rel="stylesheet" href="http://libs.cartocdn.com/cartodb.js/v3/themes/css/cartodb.css" />

## gist:ff39d8e195fb286992ef
http://osmbuildings.cartodb.com/api/v2/sql?format=geojson&dp=6&q=SELECT%20cartodb_id%2CST_Intersection(CASE%20WHEN%20ST_Dimension(ST_Snap(ST_CollectionExtract(ST_SnapToGrid(ST_CollectionExtract(ST_Simplify(%22the_geom%22%2C%200.03055572509765625)%2C%20ST_Dimension(%22the_geom%22)%20%2B%201)%2C%200.0611114501953125)%2C%20ST_Dimension(%22the_geom%22)%20%2B%201)%2C%20ST_SnapToGrid(ST_Expand(ST_MakeEnvelope(-35.947265625%2C19.89072302399691%2C-20.302734375%2C33.797408767572485%2C%204326)%2C%207.3333740234375)%2C0.0611114501953125)%2C%200.0611114501953125))%20%3D%200%20OR%20GeometryType(ST_Snap(ST_CollectionExtract(ST_SnapToGrid(ST_CollectionExtract(ST_Simplify(%22the_geom%22%2C%200.03055572509765625)%2C%20ST_Dimension(%22the_geom%22)%20%2B%201)%2C%200.0611114501953125)%2C%20ST_Dimension(%22the_geom%22)%20%2B%201)%2C%20ST_SnapToGrid(ST_Expand(ST_MakeEnvelope(-35.947265625%2C19.89072302399691%2C-20.302734375%2C33.797408767572485%2C%204326)%2C%207.3333740234375)%2C0.0611114501953125)%2C%200.0611114501953125))%20%3D%

## gist:f2d5801a7365dc4ab364
https://stagingfonmaps.cartodb.com/api/v2/sql?q=SELECT%20external_id,%20ST_Y(the_geom)%20AS%20lat,%20ST_X(the_geom)%20AS%20lon,%20network_id,%20category_NAME,%20status,%20hotspots,%20metadata%20FROM%20pois%20WHERE%20the_geom%20%26%26%20ST_MakeEnvelope(0,%200,%20180,%2090,%204326)

## gist:11371647
SELECT *,
'http://maps.googleapis.com/maps/api/streetview?size=300x190&location='||
ST_Y((the_geom))||','||ST_X((the_geom))
||'&sensor=false&fov=110' as image
FROM table_2012_entire_tree_down_complaints_sandy

## gist:9368356
CartoDB 2 Sales/Account manager position

Who we are:
We are building the easiest and most powerful data mapping engine ever.
We have more than 40.000 loving users (growing rapidly) and customers
from all around the world. We have received awesome reviews from all the
key tech and startup media like Mashable today. And we have offices in
downtown Madrid and New York.

Our team of engineers and designers are changing the way maps are made.

## gist:9352791
Who we are:
We are building the easiest and most powerful data mapping engine ever. We have more than 40.000
loving users (growing rapidly) and customers from all around the world. We have received awesome
reviews from all the key tech and startup media like Mashable today. And we have offices in
downtown Madrid and New York.

Our team of engineers and designers are changing the way maps are made. This is a big task, we
need to scale! Because of that we need to complement our strong technical arm with your
organizational expertise and results driven attitude.

## gist:7401056
-- Return an array of table names scanned by a given query
--
-- Requires PostgreSQL 9.x+
--
CREATE OR REPLACE FUNCTION CDB_QueryTables(query text)
RETURNS name[]
AS $$
DECLARE
  exp JSON;
  tables NAME[];

## gist:7336704
WITH summary_groups as(
WITH summary as (
 select   (row_number() over (order by time asc nulls last)+1)/2 as rownum,time
  from     sensor_log_2013_10_27_12_01
  order by time asc)

SELECT
max(time) OVER(PARTITION BY rownum) -
min(time) OVER(PARTITION BY rownum) diff
FROM summary)
	SELECT *, 'http://maps.googleapis.com/maps/api/streetview?size=300x190&location='\|\|urlencode (address)\|\|'&sensor=false&fov=110' as image_with_address
	FROM example_addresses
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="utf-8">
	<!--Edit the title of the page-->
	<title>CartoDB Point Clustering</title>
	<meta name="description" content="">
	<meta name="author" content="">
	<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1">
	<link rel="stylesheet" href="http://libs.cartocdn.com/cartodb.js/v3/themes/css/cartodb.css" />
	SELECT *,
	'http://maps.googleapis.com/maps/api/streetview?size=300x190&location='\|\|
	ST_Y((the_geom))\|\|','\|\|ST_X((the_geom))
	\|\|'&sensor=false&fov=110' as image
	FROM table_2012_entire_tree_down_complaints_sandy
	CartoDB 2 Sales/Account manager position

	Who we are:
	We are building the easiest and most powerful data mapping engine ever.
	We have more than 40.000 loving users (growing rapidly) and customers
	from all around the world. We have received awesome reviews from all the
	key tech and startup media like Mashable today. And we have offices in
	downtown Madrid and New York.

	Our team of engineers and designers are changing the way maps are made.
	Who we are:
	We are building the easiest and most powerful data mapping engine ever. We have more than 40.000
	loving users (growing rapidly) and customers from all around the world. We have received awesome
	reviews from all the key tech and startup media like Mashable today. And we have offices in
	downtown Madrid and New York.

	Our team of engineers and designers are changing the way maps are made. This is a big task, we
	need to scale! Because of that we need to complement our strong technical arm with your
	organizational expertise and results driven attitude.
	-- Return an array of table names scanned by a given query
	--
	-- Requires PostgreSQL 9.x+
	--
	CREATE OR REPLACE FUNCTION CDB_QueryTables(query text)
	RETURNS name[]
	AS $$
	DECLARE
	exp JSON;
	tables NAME[];
	WITH summary_groups as(
	WITH summary as (
	select (row_number() over (order by time asc nulls last)+1)/2 as rownum,time
	from sensor_log_2013_10_27_12_01
	order by time asc)

	SELECT
	max(time) OVER(PARTITION BY rownum) -
	min(time) OVER(PARTITION BY rownum) diff
	FROM summary)