SELECT 'Hello World'; -- REPLACE THIS WITH YOUR QUERY
client
SELECT 'Hello World'; -- REPLACE THIS WITH YOUR QUERY
client
SELECT trip_id AS id, vendor_id AS vendor FROM trips;
client
SELECT DISTINCT cab_type FROM trips;
client
SELECT 'Hello World'; -- REPLACE THIS WITH YOUR QUERY
client
SELECT dish_name, price FROM menu_item_denorm ORDER BY price DESC, dish_name ASC
client
SELECT 'Hello World'; -- REPLACE THIS WITH YOUR QUERY
client
SELECT * FROM trips LIMIT 5
client
SELECT * FROM trips LIMIT 5 OFFSET 3
client
SELECT 'Hello World'; -- REPLACE THIS WITH YOUR QUERY
client
SELECT
dish_name,
price
FROM menu_item_denorm
ORDER BY price DESC
LIMIT 5
UNION ALL
SELECT
dish_name,
price
FROM menu_item_denorm
ORDER BY price ASC
LIMIT 5
client
DESCRIBE TABLE recipes
client
SHOW TABLES
client
SHOW DATABASES
client
SELECT
rand(0) AS a,
rand(1) AS b,
a + b AS added,
a - b AS subtracted,
a * b AS multiplied,
a / b AS divided,
a % b AS moded,
abs(subtracted)
FROM numbers(10);
client
SELECT
rand(0) AS a,
rand(1) AS b,
a > b AS gt,
a < b AS lt,
a = b AS eq,
a != b AS ne
FROM numbers(10);
client
SELECT 'Hello World'; -- REPLACE THIS WITH YOUR QUERY
client
SELECT
title,
source,
length(title),
concat(source, '-', trim(title)),
lower(title) LIKE '%chocolate%'
FROM recipes
client
SELECT 'Hello World'; -- REPLACE THIS WITH YOUR QUERY
client
SELECT
now(),
today(),
dateDiff('hour', yesterday(), today()) AS hrs_btn_td_ytd,
today() + INTERVAL 1 day AS tomorrow,
today() - INTERVAL 1 year AS yester_year,
formatDateTime(now(), '%D at %I:%M:%S %p', 'EST')
client
SELECT
CAST(1234 AS String) AS my_string,
CAST('1970-01-01' AS Date) AS my_date,
CAST('1899-01-01' AS Date) AS my_wrong_date,
CAST(0 AS BOOLEAN) AS my_false,
CAST(1 AS BOOLEAN) AS my_true
client
SELECT number FROM numbers(10)
client
SELECT
title,
length(ingredients) > 3 ? 'four or more ingredients' : 'three or less ingredients' AS category,
CASE source
WHEN 'Gathered' THEN true
ELSE false
END AS was_gathered
FROM recipes;
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.