library(DBI)
library(RPostgreSQL)
library(RPostgres)Visualización Científica
Ejercicio 2
Conexión a la base de datos de Python
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "localhost",
port = 5432,
user = "undatascience-user",
password = "undatascience-password")Conexión a la base de datos de Neon
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")Creación de Tablas:
El conjunto de datos para estos ejercicios es para un club campestre recién creado, con un conjunto de socios, instalaciones como canchas de tenis y un historial de reservas para esas instalaciones. Entre otras cosas, el club desea entender cómo pueden utilizar su información para analizar el uso/demanda de las instalaciones.
Members
Cada socio tiene un ID (no necesariamente secuencial), información básica de dirección, una referencia al socio que los recomendó (si la hay) y una marca de tiempo de cuando se unieron.
crear <- "
CREATE TABLE public.members
(
memid integer NOT NULL,
surname character varying(200) NOT NULL,
firstname character varying(200) NOT NULL,
address character varying(300) NOT NULL,
zipcode integer NOT NULL,
telephone character varying(20) NOT NULL,
recommendedby integer,
joindate timestamp NOT NULL,
CONSTRAINT members_pk PRIMARY KEY (memid),
CONSTRAINT fk_members_recommendedby FOREIGN KEY (recommendedby)
REFERENCES public.members(memid) ON DELETE SET NULL
);
"
insert <- "
INSERT INTO members (memid, surname, firstname, address, zipcode, telephone, recommendedby, joindate) VALUES
(0, 'GUEST', 'GUEST', 'GUEST', 0, '(000) 000-0000', NULL, '2012-07-01 00:00:00'),
(1, 'Smith', 'Darren', '8 Bloomsbury Close, Boston', 4321, '555-555-5555', NULL, '2012-07-02 12:02:05'),
(2, 'Smith', 'Tracy', '8 Bloomsbury Close, New York', 4321, '555-555-5555', NULL, '2012-07-02 12:08:23'),
(3, 'Rownam', 'Tim', '23 Highway Way, Boston', 23423, '(844) 693-0723', NULL, '2012-07-03 09:32:15'),
(4, 'Joplette', 'Janice', '20 Crossing Road, New York', 234, '(833) 942-4710', 1, '2012-07-03 10:25:05'),
(5, 'Butters', 'Gerald', '1065 Huntingdon Avenue, Boston', 56754, '(844) 078-4130', 1, '2012-07-09 10:44:09'),
(6, 'Tracy', 'Burton', '3 Tunisia Drive, Boston', 45678, '(822) 354-9973', NULL, '2012-07-15 08:52:55'),
(7, 'Dare', 'Nancy', '6 Hunting Lodge Way, Boston', 10383, '(833) 776-4001', 4, '2012-07-25 08:59:12'),
(8, 'Boothe', 'Tim', '3 Bloomsbury Close, Reading, 00234', 234, '(811) 433-2547', 3, '2012-07-25 16:02:35'),
(9, 'Stibbons', 'Ponder', '5 Dragons Way, Winchester', 87630, '(833) 160-3900', 6, '2012-07-25 17:09:05'),
(10, 'Owen', 'Charles', '52 Cheshire Grove, Winchester, 28563', 28563, '(855) 542-5251', 1, '2012-08-03 19:42:37'),
(11, 'Jones', 'David', '976 Gnats Close, Reading', 33862, '(844) 536-8036', 4, '2012-08-06 16:32:55'),
(12, 'Baker', 'Anne', '55 Powdery Street, Boston', 80743, '844-076-5141', 9, '2012-08-10 14:23:22'),
(13, 'Farrell', 'Jemima', '103 Firth Avenue, North Reading', 57392, '(855) 016-0163', NULL, '2012-08-10 14:28:01'),
(14, 'Smith', 'Jack', '252 Binkington Way, Boston', 69302, '(822) 163-3254', 1, '2012-08-10 16:22:05'),
(15, 'Bader', 'Florence', '264 Ursula Drive, Westford', 84923, '(833) 499-3527', 9, '2012-08-10 17:52:03'),
(16, 'Baker', 'Timothy', '329 James Street, Reading', 58393, '833-941-0824', 13, '2012-08-15 10:34:25'),
(17, 'Pinker', 'David', '5 Impreza Road, Boston', 65332, '811 409-6734', 13, '2012-08-16 11:32:47'),
(20, 'Genting', 'Matthew', '4 Nunnington Place, Wingfield, Boston', 52365, '(811) 972-1377', 5, '2012-08-19 14:55:55'),
(21, 'Mackenzie', 'Anna', '64 Perkington Lane, Reading', 64577, '(822) 661-2898', 1, '2012-08-26 09:32:05'),
(22, 'Coplin', 'Joan', '85 Bard Street, Bloomington, Boston', 43533, '(822) 499-2232', 16, '2012-08-29 08:32:41'),
(24, 'Sarwin', 'Ramnaresh', '12 Bullington Lane, Boston', 65464, '(822) 413-1470', 15, '2012-09-01 08:44:42'),
(26, 'Jones', 'Douglas', '976 Gnats Close, Reading', 11986, '844 536-8036', 11, '2012-09-02 18:43:05'),
(27, 'Rumney', 'Henrietta', '3 Burkington Plaza, Boston', 78533, '(822) 989-8876', 20, '2012-09-05 08:42:35'),
(28, 'Farrell', 'David', '437 Granite Farm Road, Westford', 43532, '(855) 755-9876', NULL, '2012-09-15 08:22:05'),
(29, 'Worthington-Smyth', 'Henry', '55 Jagbi Way, North Reading', 97676, '(855) 894-3758', 2, '2012-09-17 12:27:15'),
(30, 'Purview', 'Millicent', '641 Drudgery Close, Burnington, Boston', 34232, '(855) 941-9786', 2, '2012-09-18 19:04:01'),
(33, 'Tupperware', 'Hyacinth', '33 Cheerful Plaza, Drake Road, Westford', 68666, '(822) 665-5327', NULL, '2012-09-18 19:32:05'),
(35, 'Hunt', 'John', '5 Bullington Lane, Boston', 54333, '(899) 720-6978', 30, '2012-09-19 11:32:45'),
(36, 'Crumpet', 'Erica', 'Crimson Road, North Reading', 75655, '(811) 732-4816', 2, '2012-09-22 08:36:38'),
(37, 'Smith', 'Darren', '3 Funktown, Denzington, Boston', 66796, '(822) 577-3541', NULL, '2012-09-26 18:08:45');
"
# Crear la tabla
dbExecute(con, crear)[1] 0# Insertas datos en la tabla
dbExecute(con, insert)[1] 31
Facilities
La tabla de instalaciones enumera todas las instalaciones reservables que posee el club campestre. El club almacena información de id/nombre, el costo para reservar tanto para socios como para invitados, el costo inicial de construcción de la instalación y los costos estimados de mantenimiento mensual. Esperan utilizar esta información para rastrear qué tan rentable es financieramente cada instalación.
crear2 <- "
CREATE TABLE public.facilities
(
facid integer NOT NULL,
name character varying(100) NOT NULL,
membercost numeric NOT NULL,
guestcost numeric NOT NULL,
initialoutlay numeric NOT NULL,
monthlymaintenance numeric NOT NULL,
CONSTRAINT facilities_pk PRIMARY KEY (facid)
);
"
insert2 <- "
INSERT INTO facilities (facid, name, membercost, guestcost, initialoutlay, monthlymaintenance) VALUES
(0, 'Tennis Court 1', 5, 25, 10000, 200),
(1, 'Tennis Court 2', 5, 25, 8000, 200),
(2, 'Badminton Court', 0, 15.5, 4000, 50),
(3, 'Table Tennis', 0, 5, 320, 10),
(4, 'Massage Room 1', 35, 80, 4000, 3000),
(5, 'Massage Room 2', 35, 80, 4000, 3000),
(6, 'Squash Court', 3.5, 17.5, 5000, 80),
(7, 'Snooker Table', 0, 5, 450, 15),
(8, 'Pool Table', 0, 5, 400, 15);
"
# Crear la tabla
dbExecute(con, crear2)[1] 0# Insertas datos en la tabla
dbExecute(con, insert2)[1] 9
Bookings
Finalmente, hay una tabla que registra las reservas de instalaciones. Esta almacena el ID de la instalación, el socio que hizo la reserva, el inicio de la reserva y cuántos espacios de media hora se reservaron.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
crear3 <- "
CREATE TABLE public.bookings
(
bookid integer NOT NULL,
facid integer NOT NULL,
memid integer NOT NULL,
starttime timestamp NOT NULL,
slots integer NOT NULL,
CONSTRAINT bookings_pk PRIMARY KEY (bookid),
CONSTRAINT fk_bookings_facid FOREIGN KEY (facid) REFERENCES public.facilities(facid),
CONSTRAINT fk_bookings_memid FOREIGN KEY (memid) REFERENCES public.members(memid)
);
"
insert3 <- "
INSERT INTO bookings (bookid, facid, memid, starttime, slots) VALUES
(0, 3, 1, '2012-07-03 11:00:00', 2),
(1, 4, 1, '2012-07-03 08:00:00', 2),
(2, 6, 0, '2012-07-03 18:00:00', 2),
(3, 7, 1, '2012-07-03 19:00:00', 2),
(4, 8, 1, '2012-07-03 10:00:00', 1),
(5, 8, 1, '2012-07-03 15:00:00', 1),
(6, 0, 2, '2012-07-04 09:00:00', 3),
(7, 0, 2, '2012-07-04 15:00:00', 3),
(8, 4, 3, '2012-07-04 13:30:00', 2),
(9, 4, 0, '2012-07-04 15:00:00', 2),
(10, 4, 0, '2012-07-04 17:30:00', 2),
(11, 6, 0, '2012-07-04 12:30:00', 2),
(12, 6, 0, '2012-07-04 14:00:00', 2),
(13, 6, 1, '2012-07-04 15:30:00', 2),
(14, 7, 2, '2012-07-04 14:00:00', 2),
(15, 8, 2, '2012-07-04 12:00:00', 1),
(16, 8, 3, '2012-07-04 18:00:00', 1),
(17, 1, 0, '2012-07-05 17:30:00', 3),
(18, 2, 1, '2012-07-05 09:30:00', 3),
(19, 3, 3, '2012-07-05 09:00:00', 2),
(20, 3, 1, '2012-07-05 19:00:00', 2),
(21, 4, 3, '2012-07-05 18:30:00', 2),
(22, 6, 0, '2012-07-05 13:00:00', 2),
(23, 6, 1, '2012-07-05 14:30:00', 2),
(24, 7, 2, '2012-07-05 18:30:00', 2),
(25, 8, 3, '2012-07-05 12:30:00', 1),
(26, 0, 0, '2012-07-06 08:00:00', 3),
(27, 0, 0, '2012-07-06 14:00:00', 3),
(28, 0, 2, '2012-07-06 15:30:00', 3),
(29, 2, 1, '2012-07-06 17:00:00', 3),
(30, 3, 1, '2012-07-06 11:00:00', 2),
(31, 4, 3, '2012-07-06 12:00:00', 2),
(32, 6, 1, '2012-07-06 14:00:00', 2),
(33, 7, 2, '2012-07-06 08:30:00', 2),
(34, 7, 2, '2012-07-06 13:30:00', 2),
(35, 8, 3, '2012-07-06 15:30:00', 1),
(36, 0, 2, '2012-07-07 08:30:00', 3),
(37, 0, 0, '2012-07-07 12:30:00', 3),
(38, 0, 2, '2012-07-07 14:30:00', 3),
(39, 1, 3, '2012-07-07 08:30:00', 3),
(40, 2, 1, '2012-07-07 09:00:00', 3),
(41, 2, 1, '2012-07-07 11:30:00', 3),
(42, 2, 1, '2012-07-07 16:00:00', 3),
(43, 3, 2, '2012-07-07 12:30:00', 2),
(44, 4, 3, '2012-07-07 11:30:00', 2),
(45, 4, 3, '2012-07-07 14:00:00', 2),
(46, 4, 0, '2012-07-07 17:30:00', 2),
(47, 6, 0, '2012-07-07 08:30:00', 2),
(48, 6, 1, '2012-07-07 10:30:00', 2),
(49, 6, 1, '2012-07-07 14:30:00', 2),
(50, 6, 0, '2012-07-07 16:00:00', 2),
(51, 7, 2, '2012-07-07 11:30:00', 2),
(52, 8, 3, '2012-07-07 16:00:00', 1),
(53, 8, 3, '2012-07-07 17:30:00', 2),
(54, 0, 3, '2012-07-08 13:00:00', 3),
(55, 0, 2, '2012-07-08 17:30:00', 3),
(56, 1, 1, '2012-07-08 15:00:00', 3),
(57, 1, 1, '2012-07-08 17:30:00', 3),
(58, 3, 1, '2012-07-08 11:30:00', 2),
(59, 3, 3, '2012-07-08 18:30:00', 2),
(60, 3, 1, '2012-07-08 19:30:00', 2),
(61, 4, 0, '2012-07-08 11:00:00', 2),
(62, 4, 2, '2012-07-08 16:30:00', 2),
(63, 4, 0, '2012-07-08 18:00:00', 2),
(64, 4, 0, '2012-07-08 19:30:00', 2),
(65, 6, 0, '2012-07-08 14:00:00', 2),
(66, 6, 0, '2012-07-08 18:30:00', 2),
(67, 7, 2, '2012-07-08 11:00:00', 2),
(68, 7, 1, '2012-07-08 16:30:00', 2),
(69, 8, 3, '2012-07-08 10:00:00', 1),
(70, 8, 3, '2012-07-08 16:30:00', 1),
(71, 0, 2, '2012-07-09 12:30:00', 3),
(72, 0, 2, '2012-07-09 15:30:00', 3),
(73, 0, 2, '2012-07-09 19:00:00', 3),
(74, 1, 0, '2012-07-09 13:00:00', 3),
(75, 1, 1, '2012-07-09 19:00:00', 3),
(76, 2, 1, '2012-07-09 09:00:00', 6),
(77, 2, 0, '2012-07-09 19:00:00', 3),
(78, 3, 3, '2012-07-09 17:00:00', 2),
(79, 3, 3, '2012-07-09 18:30:00', 2),
(80, 4, 2, '2012-07-09 11:00:00', 2),
(81, 4, 3, '2012-07-09 14:30:00', 2),
(82, 6, 0, '2012-07-09 14:30:00', 2),
(83, 7, 1, '2012-07-09 15:30:00', 2),
(84, 7, 0, '2012-07-09 18:30:00', 4),
(85, 8, 3, '2012-07-09 09:30:00', 1),
(86, 8, 3, '2012-07-09 16:30:00', 1),
(87, 8, 3, '2012-07-09 20:00:00', 1),
(88, 0, 0, '2012-07-10 11:30:00', 3),
(89, 0, 0, '2012-07-10 16:00:00', 3),
(90, 3, 2, '2012-07-10 08:00:00', 2),
(91, 3, 1, '2012-07-10 11:00:00', 2),
(92, 3, 3, '2012-07-10 15:30:00', 2),
(93, 3, 2, '2012-07-10 16:30:00', 2),
(94, 3, 1, '2012-07-10 18:00:00', 2),
(95, 4, 0, '2012-07-10 10:00:00', 2),
(96, 4, 4, '2012-07-10 11:30:00', 2),
(97, 4, 0, '2012-07-10 15:00:00', 2),
(98, 4, 3, '2012-07-10 17:00:00', 4),
(99, 5, 0, '2012-07-10 08:30:00', 2),
(100, 6, 0, '2012-07-10 14:30:00', 2),
(101, 6, 0, '2012-07-10 19:00:00', 2),
(102, 7, 4, '2012-07-10 08:30:00', 2),
(103, 7, 2, '2012-07-10 17:30:00', 2),
(104, 8, 0, '2012-07-10 11:30:00', 1),
(105, 8, 3, '2012-07-10 12:00:00', 1),
(106, 8, 3, '2012-07-10 19:30:00', 1),
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(108, 0, 2, '2012-07-11 10:00:00', 3),
(109, 0, 0, '2012-07-11 12:00:00', 3),
(110, 0, 0, '2012-07-11 14:00:00', 3),
(111, 0, 2, '2012-07-11 15:30:00', 3),
(112, 0, 2, '2012-07-11 18:30:00', 3),
(113, 1, 0, '2012-07-11 12:30:00', 3),
(114, 1, 0, '2012-07-11 16:00:00', 3),
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(116, 4, 0, '2012-07-11 09:00:00', 2),
(117, 4, 3, '2012-07-11 11:00:00', 2),
(118, 4, 0, '2012-07-11 15:00:00', 2),
(119, 5, 4, '2012-07-11 17:00:00', 2),
(120, 6, 0, '2012-07-11 14:00:00', 2),
(121, 6, 0, '2012-07-11 19:30:00', 2),
(122, 7, 0, '2012-07-11 08:00:00', 2),
(123, 7, 0, '2012-07-11 14:00:00', 2),
(124, 7, 0, '2012-07-11 16:30:00', 2),
(125, 8, 4, '2012-07-11 11:00:00', 1),
(126, 8, 3, '2012-07-11 13:00:00', 1),
(127, 0, 0, '2012-07-12 13:30:00', 3),
(128, 0, 2, '2012-07-12 16:30:00', 3),
(129, 1, 1, '2012-07-12 11:30:00', 3),
(130, 2, 1, '2012-07-12 09:00:00', 3),
(131, 2, 1, '2012-07-12 18:30:00', 3),
(132, 3, 3, '2012-07-12 18:00:00', 2),
(133, 4, 1, '2012-07-12 16:00:00', 2),
(134, 6, 0, '2012-07-12 12:00:00', 4),
(135, 7, 2, '2012-07-12 08:00:00', 2),
(136, 7, 4, '2012-07-12 13:30:00', 2),
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(139, 0, 2, '2012-07-13 10:30:00', 3),
(140, 0, 4, '2012-07-13 14:00:00', 3),
(141, 0, 3, '2012-07-13 17:00:00', 3),
(142, 1, 1, '2012-07-13 15:00:00', 3),
(143, 2, 1, '2012-07-13 09:00:00', 3),
(144, 2, 0, '2012-07-13 15:00:00', 3),
(145, 2, 1, '2012-07-13 16:30:00', 3),
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(147, 4, 0, '2012-07-13 13:30:00', 2),
(148, 4, 0, '2012-07-13 15:00:00', 2),
(149, 4, 3, '2012-07-13 16:00:00', 2),
(150, 4, 4, '2012-07-13 17:30:00', 2),
(151, 6, 0, '2012-07-13 09:30:00', 2),
(152, 7, 0, '2012-07-13 08:00:00', 2),
(153, 7, 1, '2012-07-13 11:00:00', 2),
(154, 7, 4, '2012-07-13 12:30:00', 2),
(155, 8, 0, '2012-07-13 15:30:00', 1),
(156, 8, 2, '2012-07-13 18:30:00', 1),
(157, 0, 2, '2012-07-14 08:30:00', 3),
(158, 0, 4, '2012-07-14 11:30:00', 3),
(159, 0, 3, '2012-07-14 15:00:00', 3),
(160, 1, 3, '2012-07-14 10:30:00', 3),
(161, 1, 3, '2012-07-14 12:30:00', 3),
(162, 1, 0, '2012-07-14 14:30:00', 3),
(163, 2, 1, '2012-07-14 08:30:00', 3),
(164, 3, 2, '2012-07-14 16:00:00', 2),
(165, 4, 3, '2012-07-14 08:00:00', 2),
(166, 4, 1, '2012-07-14 14:30:00', 2),
(167, 6, 0, '2012-07-14 09:30:00', 2),
(168, 6, 1, '2012-07-14 12:30:00', 2),
(169, 6, 0, '2012-07-14 15:00:00', 2),
(170, 7, 2, '2012-07-14 12:30:00', 2),
(171, 7, 2, '2012-07-14 15:00:00', 2),
(172, 7, 4, '2012-07-14 16:30:00', 2),
(173, 7, 1, '2012-07-14 19:00:00', 2),
(174, 8, 3, '2012-07-14 09:00:00', 1),
(175, 8, 1, '2012-07-14 17:00:00', 1),
(176, 0, 2, '2012-07-15 08:00:00', 3),
(177, 0, 0, '2012-07-15 16:00:00', 3),
(178, 0, 2, '2012-07-15 19:00:00', 3),
(179, 1, 0, '2012-07-15 10:00:00', 3),
(180, 1, 0, '2012-07-15 12:00:00', 3),
(181, 1, 3, '2012-07-15 15:30:00', 3),
(182, 2, 1, '2012-07-15 13:00:00', 3),
(183, 3, 1, '2012-07-15 17:30:00', 2),
(184, 4, 3, '2012-07-15 11:30:00', 2),
(185, 4, 0, '2012-07-15 15:00:00', 2),
(186, 4, 3, '2012-07-15 17:30:00', 2),
(187, 7, 4, '2012-07-15 14:30:00', 2),
(188, 7, 4, '2012-07-15 17:00:00', 2),
(189, 8, 4, '2012-07-15 10:00:00', 1),
(190, 8, 2, '2012-07-15 12:00:00', 1),
(191, 8, 3, '2012-07-15 12:30:00', 1),
(192, 8, 3, '2012-07-15 13:30:00', 1),
(193, 0, 5, '2012-07-16 11:00:00', 3),
(194, 0, 5, '2012-07-16 19:00:00', 3),
(195, 1, 1, '2012-07-16 08:00:00', 3),
(196, 1, 0, '2012-07-16 12:30:00', 3),
(197, 2, 1, '2012-07-16 16:30:00', 3),
(198, 4, 3, '2012-07-16 09:00:00', 2),
(199, 4, 1, '2012-07-16 11:00:00', 2),
(200, 4, 3, '2012-07-16 12:00:00', 2),
(201, 4, 3, '2012-07-16 17:30:00', 2),
(202, 6, 0, '2012-07-16 18:30:00', 2),
(203, 7, 4, '2012-07-16 08:00:00', 2),
(204, 7, 2, '2012-07-16 11:30:00', 2),
(205, 7, 4, '2012-07-16 12:30:00', 2),
(206, 7, 5, '2012-07-16 14:00:00', 2),
(207, 8, 4, '2012-07-16 12:00:00', 1),
(208, 8, 1, '2012-07-16 15:00:00', 1),
(209, 8, 4, '2012-07-16 18:00:00', 1),
(210, 8, 3, '2012-07-16 19:30:00', 1),
(211, 0, 5, '2012-07-17 12:30:00', 3),
(212, 0, 5, '2012-07-17 18:00:00', 3),
(213, 1, 1, '2012-07-17 10:00:00', 3),
(214, 1, 4, '2012-07-17 14:30:00', 3),
(215, 2, 5, '2012-07-17 10:30:00', 3),
(216, 2, 1, '2012-07-17 12:30:00', 3),
(217, 2, 1, '2012-07-17 15:30:00', 3),
(218, 2, 2, '2012-07-17 19:00:00', 3),
(219, 3, 1, '2012-07-17 14:00:00', 2),
(220, 3, 2, '2012-07-17 15:00:00', 2),
(221, 4, 0, '2012-07-17 09:00:00', 2),
(222, 4, 3, '2012-07-17 10:30:00', 2),
(223, 4, 3, '2012-07-17 12:00:00', 2),
(224, 4, 5, '2012-07-17 16:00:00', 2),
(225, 4, 3, '2012-07-17 18:30:00', 2),
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(3988, 2, 29, '2012-09-30 11:00:00', 3),
(3989, 2, 35, '2012-09-30 12:30:00', 3),
(3990, 2, 1, '2012-09-30 14:00:00', 6),
(3991, 2, 5, '2012-09-30 17:00:00', 3),
(3992, 2, 35, '2012-09-30 18:30:00', 3),
(3993, 3, 24, '2012-09-30 08:00:00', 2),
(3994, 3, 3, '2012-09-30 09:30:00', 2),
(3995, 3, 36, '2012-09-30 10:30:00', 2),
(3996, 3, 36, '2012-09-30 12:00:00', 2),
(3997, 3, 0, '2012-09-30 14:30:00', 2),
(3998, 3, 1, '2012-09-30 18:30:00', 2),
(3999, 4, 13, '2012-09-30 08:00:00', 2),
(4000, 4, 16, '2012-09-30 09:00:00', 2),
(4001, 4, 0, '2012-09-30 10:00:00', 2),
(4002, 4, 20, '2012-09-30 11:00:00', 2),
(4003, 4, 4, '2012-09-30 12:30:00', 2),
(4004, 4, 3, '2012-09-30 13:30:00', 2),
(4005, 4, 20, '2012-09-30 15:00:00', 2),
(4006, 4, 0, '2012-09-30 16:00:00', 2),
(4007, 4, 3, '2012-09-30 17:00:00', 2),
(4008, 4, 0, '2012-09-30 18:00:00', 2),
(4009, 5, 0, '2012-09-30 11:30:00', 2),
(4010, 5, 0, '2012-09-30 19:30:00', 2),
(4011, 6, 0, '2012-09-30 08:00:00', 2),
(4012, 6, 27, '2012-09-30 09:30:00', 2),
(4013, 6, 0, '2012-09-30 11:00:00', 2),
(4014, 6, 0, '2012-09-30 12:30:00', 2),
(4015, 6, 12, '2012-09-30 14:00:00', 2),
(4016, 6, 0, '2012-09-30 15:30:00', 2),
(4017, 6, 35, '2012-09-30 16:30:00', 2),
(4018, 6, 0, '2012-09-30 17:30:00', 2),
(4019, 6, 0, '2012-09-30 19:00:00', 2),
(4020, 7, 27, '2012-09-30 08:30:00', 2),
(4021, 7, 33, '2012-09-30 09:30:00', 2),
(4022, 7, 33, '2012-09-30 11:00:00', 2),
(4023, 7, 5, '2012-09-30 14:30:00', 2),
(4024, 7, 15, '2012-09-30 16:30:00', 2),
(4025, 7, 24, '2012-09-30 17:30:00', 2),
(4026, 7, 5, '2012-09-30 19:00:00', 2),
(4027, 8, 16, '2012-09-30 08:00:00', 1),
(4028, 8, 21, '2012-09-30 08:30:00', 2),
(4029, 8, 3, '2012-09-30 10:30:00', 1),
(4030, 8, 16, '2012-09-30 11:00:00', 1),
(4031, 8, 3, '2012-09-30 11:30:00', 1),
(4032, 8, 17, '2012-09-30 12:00:00', 1),
(4033, 8, 21, '2012-09-30 12:30:00', 1),
(4034, 8, 3, '2012-09-30 13:00:00', 1),
(4035, 8, 29, '2012-09-30 13:30:00', 1),
(4036, 8, 28, '2012-09-30 14:30:00', 1),
(4037, 8, 29, '2012-09-30 15:30:00', 1),
(4038, 8, 29, '2012-09-30 16:30:00', 2),
(4039, 8, 29, '2012-09-30 18:00:00', 1),
(4040, 8, 21, '2012-09-30 18:30:00', 1),
(4041, 8, 16, '2012-09-30 19:00:00', 1),
(4042, 8, 29, '2012-09-30 19:30:00', 1),
(4043, 8, 5, '2013-01-01 15:30:00', 1);
"
# Crear la tabla
dbExecute(con, crear3)[1] 0# Insertas datos en la tabla
dbExecute(con, insert3)[1] 4044
Ejercicios PostgreSQL Exercises
Simple SQL Queries
1. How can you retrieve all the information from the cd.facilities table?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex1<- dbGetQuery(con, "SELECT * FROM public.facilities")
ex1 facid name membercost guestcost initialoutlay monthlymaintenance
1 0 Tennis Court 1 5.0 25.0 10000 200
2 1 Tennis Court 2 5.0 25.0 8000 200
3 2 Badminton Court 0.0 15.5 4000 50
4 3 Table Tennis 0.0 5.0 320 10
5 4 Massage Room 1 35.0 80.0 4000 3000
6 5 Massage Room 2 35.0 80.0 4000 3000
7 6 Squash Court 3.5 17.5 5000 80
8 7 Snooker Table 0.0 5.0 450 15
9 8 Pool Table 0.0 5.0 400 152. You want to print out a list of all of the facilities and their cost to members. How would you retrieve a list of only facility names and costs?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex2<- dbGetQuery(con, "SELECT name, membercost FROM public.facilities")
ex2 name membercost
1 Tennis Court 1 5.0
2 Tennis Court 2 5.0
3 Badminton Court 0.0
4 Table Tennis 0.0
5 Massage Room 1 35.0
6 Massage Room 2 35.0
7 Squash Court 3.5
8 Snooker Table 0.0
9 Pool Table 0.03. How can you produce a list of facilities that charge a fee to members?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex3<- dbGetQuery(con, "SELECT * FROM public.facilities WHERE membercost > 0;")
ex3 facid name membercost guestcost initialoutlay monthlymaintenance
1 0 Tennis Court 1 5.0 25.0 10000 200
2 1 Tennis Court 2 5.0 25.0 8000 200
3 4 Massage Room 1 35.0 80.0 4000 3000
4 5 Massage Room 2 35.0 80.0 4000 3000
5 6 Squash Court 3.5 17.5 5000 804. How can you produce a list of facilities that charge a fee tro memebers, and that fee is less than 1/50th of the monthly maintenance cost?
Return the facid, facility name, member cost, and monthly maintenance of the facilities in question.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex4<- dbGetQuery(con, "SELECT facid, name, membercost, monthlymaintenance
FROM public.facilities
WHERE
membercost > 0 and
(membercost < monthlymaintenance/50.0);")
ex4 facid name membercost monthlymaintenance
1 4 Massage Room 1 35 3000
2 5 Massage Room 2 35 30005. How can you produce a list of all facilities with the word ‘Tennis’ in their name?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex5<- dbGetQuery(con, "SELECT *
FROM public.facilities
WHERE
name LIKE '%Tennis%';")
ex5 facid name membercost guestcost initialoutlay monthlymaintenance
1 0 Tennis Court 1 5 25 10000 200
2 1 Tennis Court 2 5 25 8000 200
3 3 Table Tennis 0 5 320 106. How can you retrieve the details of facilities with ID 1 and 5? Try to do it without using OR operator.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex6<- dbGetQuery(con, "SELECT *
FROM public.facilities
WHERE
facid IN (1,5);")
ex6 facid name membercost guestcost initialoutlay monthlymaintenance
1 1 Tennis Court 2 5 25 8000 200
2 5 Massage Room 2 35 80 4000 30007. How can you produce a list of facilities, with each labelled as ‘cheap’ or ‘expensive’ depending on if their monthly maintenance cost is more than $100? Return the name and monthly maintenance of the facilities in question.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex7<- dbGetQuery(con, "SELECT name,
CASE WHEN (monthlymaintenance > 100) then
'expensive'
ELSE
'cheap'
END AS cost
FROM public.facilities; ")
ex7 name cost
1 Tennis Court 1 expensive
2 Tennis Court 2 expensive
3 Badminton Court cheap
4 Table Tennis cheap
5 Massage Room 1 expensive
6 Massage Room 2 expensive
7 Squash Court cheap
8 Snooker Table cheap
9 Pool Table cheap8. How can you produce a list of members who joined after the start of September 2012? Return the memid, surname, firstname, and joindate of the members in question.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex8<- dbGetQuery(con, "SELECT memid, surname, firstname, joindate
FROM public.members
WHERE joindate >= '2012-09-01'; ")
ex8 memid surname firstname joindate
1 24 Sarwin Ramnaresh 2012-09-01 08:44:42
2 26 Jones Douglas 2012-09-02 18:43:05
3 27 Rumney Henrietta 2012-09-05 08:42:35
4 28 Farrell David 2012-09-15 08:22:05
5 29 Worthington-Smyth Henry 2012-09-17 12:27:15
6 30 Purview Millicent 2012-09-18 19:04:01
7 33 Tupperware Hyacinth 2012-09-18 19:32:05
8 35 Hunt John 2012-09-19 11:32:45
9 36 Crumpet Erica 2012-09-22 08:36:38
10 37 Smith Darren 2012-09-26 18:08:459. How can you produce an ordered list of the first 10 surnames in the members table? The list must not contain duplicates.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex9<- dbGetQuery(con, "SELECT DISTINCT surname
FROM public.members
ORDER BY surname
limit 10; ")
ex9 surname
1 Bader
2 Baker
3 Boothe
4 Butters
5 Coplin
6 Crumpet
7 Dare
8 Farrell
9 GUEST
10 Genting10. You, for some reason, want a combined list of all surnames and all facility names. Yes, this is a contrived example :-). Produce that list!
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex10<- dbGetQuery(con, "SELECT surname
FROM public.members
UNION
SELECT name
FROM public.facilities; ")
ex10 surname
1 Table Tennis
2 Tupperware
3 Massage Room 2
4 Jones
5 Boothe
6 Massage Room 1
7 Smith
8 Owen
9 Purview
10 Snooker Table
11 Joplette
12 Hunt
13 GUEST
14 Badminton Court
15 Butters
16 Coplin
17 Genting
18 Bader
19 Worthington-Smyth
20 Pinker
21 Farrell
22 Dare
23 Squash Court
24 Tennis Court 1
25 Sarwin
26 Baker
27 Tennis Court 2
28 Rownam
29 Pool Table
30 Stibbons
31 Rumney
32 Tracy
33 Crumpet
34 Mackenzie11. You’d like to get the signup date of your last member. How can you retrieve this information?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex11<- dbGetQuery(con, "SELECT max(joindate) as latest
FROM public.members;")
ex11 latest
1 2012-09-26 18:08:4512. You’d like to get the first and last name of the last member(s) who signed up - not just the date. How can you do that?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ex12<- dbGetQuery(con, "SELECT firstname, surname, joindate
FROM public.members
WHERE joindate =
(select max(joindate)
from public.members);")
ex12 firstname surname joindate
1 Darren Smith 2012-09-26 18:08:45Joins and Subqueries
1. How can you produce a list of the start times for bookings by members named ‘David Farrell’?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez1<- dbGetQuery(con, "SELECT bks.starttime
FROM
public.bookings bks
INNER JOIN public.members mems
ON mems.memid = bks.memid
WHERE
mems.firstname='David'
AND mems.surname='Farrell';")
ez1 starttime
1 2012-09-18 09:00:00
2 2012-09-18 17:30:00
3 2012-09-18 13:30:00
4 2012-09-18 20:00:00
5 2012-09-19 09:30:00
6 2012-09-19 15:00:00
7 2012-09-19 12:00:00
8 2012-09-20 15:30:00
9 2012-09-20 11:30:00
10 2012-09-20 14:00:00
11 2012-09-21 10:30:00
12 2012-09-21 14:00:00
13 2012-09-22 08:30:00
14 2012-09-22 17:00:00
15 2012-09-23 08:30:00
16 2012-09-23 17:30:00
17 2012-09-23 19:00:00
18 2012-09-24 08:00:00
19 2012-09-24 16:30:00
20 2012-09-24 12:30:00
21 2012-09-25 15:30:00
22 2012-09-25 17:00:00
23 2012-09-26 13:00:00
24 2012-09-26 17:00:00
25 2012-09-27 08:00:00
26 2012-09-28 11:30:00
27 2012-09-28 09:30:00
28 2012-09-28 13:00:00
29 2012-09-29 16:00:00
30 2012-09-29 10:30:00
31 2012-09-29 13:30:00
32 2012-09-29 14:30:00
33 2012-09-29 17:30:00
34 2012-09-30 14:30:002. How can you produce a list of the start times for bookings for tennis courts, for the date ‘2012-09-21’? Return a list of start time and facility name pairings, ordered by the time.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez2<- dbGetQuery(con, "SELECT bks.starttime AS START, facs.name AS name
FROM
public.facilities facs
INNER JOIN public.bookings bks
ON facs.facid = bks.facid
WHERE
facs.name IN ('Tennis Court 2','Tennis Court 1') AND
bks.starttime >= '2012-09-21' AND
bks.starttime < '2012-09-22'
ORDER BY bks.starttime;")
ez2 start name
1 2012-09-21 08:00:00 Tennis Court 1
2 2012-09-21 08:00:00 Tennis Court 2
3 2012-09-21 09:30:00 Tennis Court 1
4 2012-09-21 10:00:00 Tennis Court 2
5 2012-09-21 11:30:00 Tennis Court 2
6 2012-09-21 12:00:00 Tennis Court 1
7 2012-09-21 13:30:00 Tennis Court 1
8 2012-09-21 14:00:00 Tennis Court 2
9 2012-09-21 15:30:00 Tennis Court 1
10 2012-09-21 16:00:00 Tennis Court 2
11 2012-09-21 17:00:00 Tennis Court 1
12 2012-09-21 18:00:00 Tennis Court 23. How can you output a list of all members who have recommended another member? Ensure that there are no duplicates in the list, and that results are ordered by (surname, firstname).
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez3<- dbGetQuery(con, "SELECT distinct recs.firstname AS firstname, recs.surname AS surname
FROM
public.members mems
INNER JOIN public.members recs
ON recs.memid = mems.recommendedby
ORDER BY surname, firstname;")
ez3 firstname surname
1 Florence Bader
2 Timothy Baker
3 Gerald Butters
4 Jemima Farrell
5 Matthew Genting
6 David Jones
7 Janice Joplette
8 Millicent Purview
9 Tim Rownam
10 Darren Smith
11 Tracy Smith
12 Ponder Stibbons
13 Burton Tracy4. How can you output a list of all members, including the individual who recommended them (if any)? Ensure that results are ordered by (surname, firstname).
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez4<- dbGetQuery(con, "SELECT mems.firstname AS memfname, mems.surname AS memsname, recs.firstname AS recfname, recs.surname AS recsname
FROM
public.members mems
LEFT OUTER JOIN public.members recs
ON recs.memid = mems.recommendedby
ORDER BY memsname, memfname; ")
ez4 memfname memsname recfname recsname
1 Florence Bader Ponder Stibbons
2 Anne Baker Ponder Stibbons
3 Timothy Baker Jemima Farrell
4 Tim Boothe Tim Rownam
5 Gerald Butters Darren Smith
6 Joan Coplin Timothy Baker
7 Erica Crumpet Tracy Smith
8 Nancy Dare Janice Joplette
9 David Farrell <NA> <NA>
10 Jemima Farrell <NA> <NA>
11 GUEST GUEST <NA> <NA>
12 Matthew Genting Gerald Butters
13 John Hunt Millicent Purview
14 David Jones Janice Joplette
15 Douglas Jones David Jones
16 Janice Joplette Darren Smith
17 Anna Mackenzie Darren Smith
18 Charles Owen Darren Smith
19 David Pinker Jemima Farrell
20 Millicent Purview Tracy Smith
21 Tim Rownam <NA> <NA>
22 Henrietta Rumney Matthew Genting
23 Ramnaresh Sarwin Florence Bader
24 Darren Smith <NA> <NA>
25 Darren Smith <NA> <NA>
26 Jack Smith Darren Smith
27 Tracy Smith <NA> <NA>
28 Ponder Stibbons Burton Tracy
29 Burton Tracy <NA> <NA>
30 Hyacinth Tupperware <NA> <NA>
31 Henry Worthington-Smyth Tracy Smith5. How can you produce a list of all members who have used a tennis court? Include in your output the name of the court, and the name of the member formatted as a single column. Ensure no duplicate data, and order by the member name followed by the facility name.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez5<- dbGetQuery(con, "SELECT DISTINCT mems.firstname || ' ' || mems.surname AS member, facs.name AS facility
FROM
public.members mems
INNER JOIN public.bookings bks
ON mems.memid = bks.memid
INNER JOIN public.facilities facs
ON bks.facid = facs.facid
WHERE
facs.name in ('Tennis Court 2','Tennis Court 1')
ORDER BY member, facility")
ez5 member facility
1 Anne Baker Tennis Court 1
2 Anne Baker Tennis Court 2
3 Burton Tracy Tennis Court 1
4 Burton Tracy Tennis Court 2
5 Charles Owen Tennis Court 1
6 Charles Owen Tennis Court 2
7 Darren Smith Tennis Court 2
8 David Farrell Tennis Court 1
9 David Farrell Tennis Court 2
10 David Jones Tennis Court 1
11 David Jones Tennis Court 2
12 David Pinker Tennis Court 1
13 Douglas Jones Tennis Court 1
14 Erica Crumpet Tennis Court 1
15 Florence Bader Tennis Court 1
16 Florence Bader Tennis Court 2
17 GUEST GUEST Tennis Court 1
18 GUEST GUEST Tennis Court 2
19 Gerald Butters Tennis Court 1
20 Gerald Butters Tennis Court 2
21 Henrietta Rumney Tennis Court 2
22 Jack Smith Tennis Court 1
23 Jack Smith Tennis Court 2
24 Janice Joplette Tennis Court 1
25 Janice Joplette Tennis Court 2
26 Jemima Farrell Tennis Court 1
27 Jemima Farrell Tennis Court 2
28 Joan Coplin Tennis Court 1
29 John Hunt Tennis Court 1
30 John Hunt Tennis Court 2
31 Matthew Genting Tennis Court 1
32 Millicent Purview Tennis Court 2
33 Nancy Dare Tennis Court 1
34 Nancy Dare Tennis Court 2
35 Ponder Stibbons Tennis Court 1
36 Ponder Stibbons Tennis Court 2
37 Ramnaresh Sarwin Tennis Court 1
38 Ramnaresh Sarwin Tennis Court 2
39 Tim Boothe Tennis Court 1
40 Tim Boothe Tennis Court 2
41 Tim Rownam Tennis Court 1
42 Tim Rownam Tennis Court 2
43 Timothy Baker Tennis Court 1
44 Timothy Baker Tennis Court 2
45 Tracy Smith Tennis Court 1
46 Tracy Smith Tennis Court 26. How can you produce a list of bookings on the day of 2012-09-14 which will cost the member (or guest) more than $30? Remember that guests have different costs to members (the listed costs are per half-hour ‘slot’), and the guest user is always ID 0. Include in your output the name of the facility, the name of the member formatted as a single column, and the cost. Order by descending cost, and do not use any subqueries.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez6<- dbGetQuery(con, "SELECT mems.firstname || ' ' || mems.surname AS member,
facs.name as facility,
CASE
WHEN mems.memid = 0 then
bks.slots*facs.guestcost
ELSE
bks.slots*facs.membercost
END AS cost
FROM
public.members mems
INNER JOIN public.bookings bks
ON mems.memid = bks.memid
INNER JOIN public.facilities facs
ON bks.facid = facs.facid
WHERE
bks.starttime >= '2012-09-14' AND
bks.starttime < '2012-09-15' AND (
(mems.memid = 0 AND bks.slots*facs.guestcost > 30) OR
(mems.memid != 0 AND bks.slots*facs.membercost > 30)
)
ORDER BY cost DESC; ")
ez6 member facility cost
1 GUEST GUEST Massage Room 2 320
2 GUEST GUEST Massage Room 1 160
3 GUEST GUEST Massage Room 1 160
4 GUEST GUEST Massage Room 1 160
5 GUEST GUEST Tennis Court 2 150
6 Jemima Farrell Massage Room 1 140
7 GUEST GUEST Tennis Court 1 75
8 GUEST GUEST Tennis Court 1 75
9 GUEST GUEST Tennis Court 2 75
10 Ponder Stibbons Massage Room 1 70
11 Jemima Farrell Massage Room 1 70
12 Burton Tracy Massage Room 1 70
13 Matthew Genting Massage Room 1 70
14 Florence Bader Massage Room 2 70
15 Jack Smith Massage Room 1 70
16 GUEST GUEST Squash Court 70
17 GUEST GUEST Squash Court 35
18 GUEST GUEST Squash Court 357. How can you output a list of all members, including the individual who recommended them (if any), without using any joins? Ensure that there are no duplicates in the list, and that each firstname + surname pairing is formatted as a column and ordered.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez7<- dbGetQuery(con, "SELECT DISTINCT mems.firstname || ' ' || mems.surname as member,
(SELECT recs.firstname || ' ' || recs.surname as recommender
FROM public.members recs
WHERE recs.memid = mems.recommendedby
)
FROM
public.members mems
ORDER BY member; ")
ez7 member recommender
1 Anna Mackenzie Darren Smith
2 Anne Baker Ponder Stibbons
3 Burton Tracy <NA>
4 Charles Owen Darren Smith
5 Darren Smith <NA>
6 David Farrell <NA>
7 David Jones Janice Joplette
8 David Pinker Jemima Farrell
9 Douglas Jones David Jones
10 Erica Crumpet Tracy Smith
11 Florence Bader Ponder Stibbons
12 GUEST GUEST <NA>
13 Gerald Butters Darren Smith
14 Henrietta Rumney Matthew Genting
15 Henry Worthington-Smyth Tracy Smith
16 Hyacinth Tupperware <NA>
17 Jack Smith Darren Smith
18 Janice Joplette Darren Smith
19 Jemima Farrell <NA>
20 Joan Coplin Timothy Baker
21 John Hunt Millicent Purview
22 Matthew Genting Gerald Butters
23 Millicent Purview Tracy Smith
24 Nancy Dare Janice Joplette
25 Ponder Stibbons Burton Tracy
26 Ramnaresh Sarwin Florence Bader
27 Tim Boothe Tim Rownam
28 Tim Rownam <NA>
29 Timothy Baker Jemima Farrell
30 Tracy Smith <NA>8. The Produce a list of costly bookings exercise contained some messy logic: we had to calculate the booking cost in both the WHERE clause and the CASE statement. Try to simplify this calculation using subqueries. For reference, the question was:
How can you produce a list of bookings on the day of 2012-09-14 which will cost the member (or guest) more than $30? Remember that guests have different costs to members (the listed costs are per half-hour ‘slot’), and the guest user is always ID 0. Include in your output the name of the facility, the name of the member formatted as a single column, and the cost. Order by descending cost.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ez8<- dbGetQuery(con, "SELECT member, facility, cost FROM (
SELECT
mems.firstname || ' ' || mems.surname AS member,
facs.name AS facility,
CASE
WHEN mems.memid = 0 THEN
bks.slots*facs.guestcost
ELSE
bks.slots*facs.membercost
END AS cost
FROM
public.members mems
INNER JOIN public.bookings bks
on mems.memid = bks.memid
INNER JOIN public.facilities facs
on bks.facid = facs.facid
WHERE
bks.starttime >= '2012-09-14' AND
bks.starttime < '2012-09-15'
) AS bookings
WHERE cost > 30
ORDER BY cost DESC; ")
ez8 member facility cost
1 GUEST GUEST Massage Room 2 320
2 GUEST GUEST Massage Room 1 160
3 GUEST GUEST Massage Room 1 160
4 GUEST GUEST Massage Room 1 160
5 GUEST GUEST Tennis Court 2 150
6 Jemima Farrell Massage Room 1 140
7 GUEST GUEST Tennis Court 1 75
8 GUEST GUEST Tennis Court 1 75
9 GUEST GUEST Tennis Court 2 75
10 Ponder Stibbons Massage Room 1 70
11 Jemima Farrell Massage Room 1 70
12 Burton Tracy Massage Room 1 70
13 Matthew Genting Massage Room 1 70
14 Florence Bader Massage Room 2 70
15 Jack Smith Massage Room 1 70
16 GUEST GUEST Squash Court 70
17 GUEST GUEST Squash Court 35
18 GUEST GUEST Squash Court 35Modifying data
1. The club is adding a new facility - a spa. We need to add it into the facilities table. Use the following values:
- facid: 9, Name: ‘Spa’, membercost: 20, guestcost: 30, initialoutlay: 100000, monthlymaintenance: 800.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
dbExecute(con, "INSERT INTO public.facilities
(facid, name, membercost, guestcost, initialoutlay, monthlymaintenance)
VALUES (9, 'Spa', 20, 30, 100000, 800); ")[1] 1
2. In the previous exercise, you learned how to add a facility. Now you’re going to add multiple facilities in one command. Use the following values:
facid: 9, Name: ‘Spa’, membercost: 20, guestcost: 30, initialoutlay: 100000, monthlymaintenance: 800.
facid: 10, Name: ‘Squash Court 2’, membercost: 3.5, guestcost: 17.5, initialoutlay: 5000, monthlymaintenance: 80.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
dbExecute(con, "DELETE FROM public.facilities WHERE facid = 9;")[1] 1dbExecute(con, "INSERT INTO public.facilities
(facid, name, membercost, guestcost, initialoutlay, monthlymaintenance)
values
(9, 'Spa', 20, 30, 100000, 800),
(10, 'Squash Court 2', 3.5, 17.5, 5000, 80);")[1] 2
3. Let’s try adding the spa to the facilities table again. This time, though, we want to automatically generate the value for the next facid, rather than specifying it as a constant. Use the following values for everything else:
- Name: ‘Spa’, membercost: 20, guestcost: 30, initialoutlay: 100000, monthlymaintenance: 800.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
dbExecute(con, "DELETE FROM public.facilities WHERE facid IN (9, 10, 11);")[1] 2dbExecute(con, "INSERT INTO public.facilities
(facid, name, membercost, guestcost, initialoutlay, monthlymaintenance)
SELECT (SELECT max(facid) FROM public.facilities)+1, 'Spa', 20, 30, 100000, 800; ")[1] 1
4. We made a mistake when entering the data for the second tennis court. The initial outlay was 10000 rather than 8000: you need to alter the data to fix the error.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
dbExecute(con, "UPDATE public.facilities
SET initialoutlay = 10000
WHERE facid = 1; ")[1] 1
5. We want to increase the price of the tennis courts for both members and guests. Update the costs to be 6 for members, and 30 for guests.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
dbExecute(con, "UPDATE public.facilities
SET
membercost = 6,
guestcost = 30
WHERE facid in (0,1); ")[1] 2
6. We want to alter the price of the second tennis court so that it costs 10% more than the first one. Try to do this without using constant values for the prices, so that we can reuse the statement if we want to.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
dbExecute(con, "UPDATE public.facilities facs
SET
membercost = (SELECT membercost * 1.1 FROM public.facilities where facid = 0),
guestcost = (SELECT guestcost * 1.1 FROM public.facilities WHERE facid = 0)
WHERE facs.facid = 1; ")[1] 1
7. As part of a clearout of our database, we want to delete all bookings from the public.bookings table. How can we accomplish this?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
# Duplicamos la tabla que vamos a eliminar por si es necesaria en un futuro
dbSendQuery(con, "CREATE TABLE public.bookings2 AS SELECT * FROM public.bookings")<PqResult>
SQL CREATE TABLE public.bookings2 AS SELECT * FROM public.bookings
ROWS Fetched: 0 [complete]
Changed: 4044# Eliminar registros
dbSendQuery(con, "DELETE FROM public.bookings2;")Warning: Closing open result set, cancelling previous query<PqResult>
SQL DELETE FROM public.bookings2;
ROWS Fetched: 0 [complete]
Changed: 4044
8. We want to remove member 37, who has never made a booking, from our database. How can we achieve that?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
# Duplicamos la tabla
dbSendQuery(con, "CREATE TABLE public.members2 AS SELECT * FROM public.members")<PqResult>
SQL CREATE TABLE public.members2 AS SELECT * FROM public.members
ROWS Fetched: 0 [complete]
Changed: 31#Eliminar registro requerido
dbExecute(con, "DELETE FROM public.members2 WHERE memid = 37; ")Warning: Closing open result set, cancelling previous query[1] 1
9. In our previous exercises, we deleted a specific member who had never made a booking. How can we make that more general, to delete all members who have never made a booking?
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
dbExecute(con, "DELETE FROM public.members2 WHERE memid NOT IN (SELECT memid FROM public.bookings);")[1] 0
Aggregation
1. For our first foray into aggregates, we’re going to stick to something simple. We want to know how many facilities exist - simply produce a total count.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey1<- dbGetQuery(con, "SELECT count(*) FROM public.facilities;")
ey1 count
1 102. Produce a count of the number of facilities that have a cost to guests of 10 or more.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey2<- dbGetQuery(con, "SELECT count(*) FROM public.facilities WHERE guestcost >= 10;")
ey2 count
1 73. Produce a count of the number of recommendations each member has made. Order by member ID.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey3<- dbGetQuery(con, "SELECT recommendedby, count(*)
FROM public.members
WHERE recommendedby is not null
GROUP BY recommendedby
ORDER BY recommendedby;")
ey3 recommendedby count
1 1 5
2 2 3
3 3 1
4 4 2
5 5 1
6 6 1
7 9 2
8 11 1
9 13 2
10 15 1
11 16 1
12 20 1
13 30 14. Produce a list of the total number of slots booked per facility. For now, just produce an output table consisting of facility id and slots, sorted by facility id.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey4 <- dbGetQuery(con, "SELECT facid, sum(slots) AS \"Total Slots\"
FROM public.bookings
GROUP BY facid
ORDER BY facid;")
ey4 facid Total Slots
1 0 1320
2 1 1278
3 2 1209
4 3 830
5 4 1404
6 5 228
7 6 1104
8 7 908
9 8 9115. Produce a list of the total number of slots booked per facility in the month of September 2012. Produce an output table consisting of facility id and slots, sorted by the number of slots.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey5 <- dbGetQuery(con, "SELECT facid, sum(slots) AS \"Total Slots\"
FROM public.bookings
WHERE starttime >= '2012-09-01' AND starttime < '2012-10-01'
GROUP BY facid
ORDER BY sum(slots);")
ey5 facid Total Slots
1 5 122
2 3 422
3 7 426
4 8 471
5 6 540
6 2 570
7 1 588
8 0 591
9 4 6486. Produce a list of the total number of slots booked per facility per month in the year of 2012. Produce an output table consisting of facility id and slots, sorted by the id and month.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey6 <- dbGetQuery(con, "select facid, extract(month FROM starttime) AS month, sum(slots) AS \"Total Slots\"
FROM public.bookings
WHERE extract(year FROM starttime) = 2012
GROUP BY facid, month
ORDER BY facid, month; ")
ey6 facid month Total Slots
1 0 7 270
2 0 8 459
3 0 9 591
4 1 7 207
5 1 8 483
6 1 9 588
7 2 7 180
8 2 8 459
9 2 9 570
10 3 7 104
11 3 8 304
12 3 9 422
13 4 7 264
14 4 8 492
15 4 9 648
16 5 7 24
17 5 8 82
18 5 9 122
19 6 7 164
20 6 8 400
21 6 9 540
22 7 7 156
23 7 8 326
24 7 9 426
25 8 7 117
26 8 8 322
27 8 9 4717. Find the total number of members (including guests) who have made at least one booking.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey7 <- dbGetQuery(con, "SELECT count(DISTINCT memid) FROM public.bookings ")
ey7 count
1 308. Produce a list of facilities with more than 1000 slots booked. Produce an output table consisting of facility id and slots, sorted by facility id.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey8 <- dbGetQuery(con, "SELECT facid, sum(slots) AS \"Total Slots\"
FROM public.bookings
GROUP BY facid
HAVING sum(slots) > 1000
ORDER BY facid ")
ey8 facid Total Slots
1 0 1320
2 1 1278
3 2 1209
4 4 1404
5 6 11049. Produce a list of facilities along with their total revenue. The output table should consist of facility name and revenue, sorted by revenue. Remember that there’s a different cost for guests and members!
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey9 <- dbGetQuery(con, "SELECT facs.name, sum(slots * CASE
WHEN memid = 0 THEN facs.guestcost
ELSE facs.membercost
END) AS revenue
FROM public.bookings bks
INNER JOIN public.facilities facs
on bks.facid = facs.facid
GROUP BY facs.name
ORDER BY revenue;")
ey9 name revenue
1 Table Tennis 180.0
2 Snooker Table 240.0
3 Pool Table 270.0
4 Badminton Court 1906.5
5 Squash Court 13468.0
6 Massage Room 2 15810.0
7 Tennis Court 1 16632.0
8 Tennis Court 2 18889.2
9 Massage Room 1 72540.010. Produce a list of facilities with a total revenue less than 1000. Produce an output table consisting of facility name and revenue, sorted by revenue. Remember that there’s a different cost for guests and members!
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey10 <- dbGetQuery(con, "SELECT name, revenue FROM (
SELECT facs.name, sum(CASE
WHEN memid = 0 THEN slots * facs.guestcost
ELSE slots * membercost
END) AS revenue
FROM public.bookings bks
INNER JOIN public.facilities facs
ON bks.facid = facs.facid
GROUP BY facs.name
) AS agg WHERE revenue < 1000
ORDER BY revenue;;")
ey10 name revenue
1 Table Tennis 180
2 Snooker Table 240
3 Pool Table 27011. Output the facility id that has the highest number of slots booked. For bonus points, try a version without a LIMIT clause. This version will probably look messy!
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey11 <- dbGetQuery(con, "SELECT facid, sum(slots) AS \"Total Slots\"
FROM public.bookings
GROUP BY facid
ORDER BY sum(slots) DESC
LIMIT 1;")
ey11 facid Total Slots
1 4 140412. Produce a list of the total number of slots booked per facility per month in the year of 2012. In this version, include output rows containing totals for all months per facility, and a total for all months for all facilities. The output table should consist of facility id, month and slots, sorted by the id and month. When calculating the aggregated values for all months and all facids, return null values in the month and facid columns.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey12 <- dbGetQuery(con, "SELECT facid, extract(month from starttime) AS month, sum(slots) AS slots
FROM public.bookings
WHERE
starttime >= '2012-01-01'
AND starttime < '2013-01-01'
GROUP BY rollup(facid, month)
ORDER BY facid, month;")
ey12 facid month slots
1 0 7 270
2 0 8 459
3 0 9 591
4 0 NA 1320
5 1 7 207
6 1 8 483
7 1 9 588
8 1 NA 1278
9 2 7 180
10 2 8 459
11 2 9 570
12 2 NA 1209
13 3 7 104
14 3 8 304
15 3 9 422
16 3 NA 830
17 4 7 264
18 4 8 492
19 4 9 648
20 4 NA 1404
21 5 7 24
22 5 8 82
23 5 9 122
24 5 NA 228
25 6 7 164
26 6 8 400
27 6 9 540
28 6 NA 1104
29 7 7 156
30 7 8 326
31 7 9 426
32 7 NA 908
33 8 7 117
34 8 8 322
35 8 9 471
36 8 NA 910
37 NA NA 919113. Produce a list of the total number of hours booked per facility, remembering that a slot lasts half an hour. The output table should consist of the facility id, name, and hours booked, sorted by facility id. Try formatting the hours to two decimal places.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey13 <- dbGetQuery(con, "SELECT facs.facid, facs.name,
trim(to_char(sum(bks.slots)/2.0, '9999999999999999D99')) AS \"Total Hours\"
FROM public.bookings bks
INNER JOIN public.facilities facs
ON facs.facid = bks.facid
GROUP BY facs.facid, facs.name
ORDER BY facs.facid;")
ey13 facid name Total Hours
1 0 Tennis Court 1 660.00
2 1 Tennis Court 2 639.00
3 2 Badminton Court 604.50
4 3 Table Tennis 415.00
5 4 Massage Room 1 702.00
6 5 Massage Room 2 114.00
7 6 Squash Court 552.00
8 7 Snooker Table 454.00
9 8 Pool Table 455.5014. Produce a list of each member name, id, and their first booking after September 1st 2012. Order by member ID.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey14 <- dbGetQuery(con, "SELECT mems.surname, mems.firstname, mems.memid, min(bks.starttime) AS starttime
FROM public.bookings bks
INNER JOIN public.members mems ON
mems.memid = bks.memid
WHERE starttime >= '2012-09-01'
GROUP BY mems.surname, mems.firstname, mems.memid
ORDER BY mems.memid;")
ey14 surname firstname memid starttime
1 GUEST GUEST 0 2012-09-01 08:00:00
2 Smith Darren 1 2012-09-01 09:00:00
3 Smith Tracy 2 2012-09-01 11:30:00
4 Rownam Tim 3 2012-09-01 16:00:00
5 Joplette Janice 4 2012-09-01 15:00:00
6 Butters Gerald 5 2012-09-02 12:30:00
7 Tracy Burton 6 2012-09-01 15:00:00
8 Dare Nancy 7 2012-09-01 12:30:00
9 Boothe Tim 8 2012-09-01 08:30:00
10 Stibbons Ponder 9 2012-09-01 11:00:00
11 Owen Charles 10 2012-09-01 11:00:00
12 Jones David 11 2012-09-01 09:30:00
13 Baker Anne 12 2012-09-01 14:30:00
14 Farrell Jemima 13 2012-09-01 09:30:00
15 Smith Jack 14 2012-09-01 11:00:00
16 Bader Florence 15 2012-09-01 10:30:00
17 Baker Timothy 16 2012-09-01 15:00:00
18 Pinker David 17 2012-09-01 08:30:00
19 Genting Matthew 20 2012-09-01 18:00:00
20 Mackenzie Anna 21 2012-09-01 08:30:00
21 Coplin Joan 22 2012-09-02 11:30:00
22 Sarwin Ramnaresh 24 2012-09-04 11:00:00
23 Jones Douglas 26 2012-09-08 13:00:00
24 Rumney Henrietta 27 2012-09-16 13:30:00
25 Farrell David 28 2012-09-18 09:00:00
26 Worthington-Smyth Henry 29 2012-09-19 09:30:00
27 Purview Millicent 30 2012-09-19 11:30:00
28 Tupperware Hyacinth 33 2012-09-20 08:00:00
29 Hunt John 35 2012-09-23 14:00:00
30 Crumpet Erica 36 2012-09-27 11:30:0015. Produce a list of member names, with each row containing the total member count. Order by join date, and include guest members.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey15 <- dbGetQuery(con, "SELECT count(*) OVER(), firstname, surname
FROM public.members
ORDER BY joindate ")
ey15 count firstname surname
1 31 GUEST GUEST
2 31 Darren Smith
3 31 Tracy Smith
4 31 Tim Rownam
5 31 Janice Joplette
6 31 Gerald Butters
7 31 Burton Tracy
8 31 Nancy Dare
9 31 Tim Boothe
10 31 Ponder Stibbons
11 31 Charles Owen
12 31 David Jones
13 31 Anne Baker
14 31 Jemima Farrell
15 31 Jack Smith
16 31 Florence Bader
17 31 Timothy Baker
18 31 David Pinker
19 31 Matthew Genting
20 31 Anna Mackenzie
21 31 Joan Coplin
22 31 Ramnaresh Sarwin
23 31 Douglas Jones
24 31 Henrietta Rumney
25 31 David Farrell
26 31 Henry Worthington-Smyth
27 31 Millicent Purview
28 31 Hyacinth Tupperware
29 31 John Hunt
30 31 Erica Crumpet
31 31 Darren Smith16. Produce a monotonically increasing numbered list of members (including guests), ordered by their date of joining. Remember that member IDs are not guaranteed to be sequential.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey16 <- dbGetQuery(con, "SELECT row_number() OVER(ORDER BY joindate), firstname, surname
FROM public.members
ORDER BY joindate")
ey16 row_number firstname surname
1 1 GUEST GUEST
2 2 Darren Smith
3 3 Tracy Smith
4 4 Tim Rownam
5 5 Janice Joplette
6 6 Gerald Butters
7 7 Burton Tracy
8 8 Nancy Dare
9 9 Tim Boothe
10 10 Ponder Stibbons
11 11 Charles Owen
12 12 David Jones
13 13 Anne Baker
14 14 Jemima Farrell
15 15 Jack Smith
16 16 Florence Bader
17 17 Timothy Baker
18 18 David Pinker
19 19 Matthew Genting
20 20 Anna Mackenzie
21 21 Joan Coplin
22 22 Ramnaresh Sarwin
23 23 Douglas Jones
24 24 Henrietta Rumney
25 25 David Farrell
26 26 Henry Worthington-Smyth
27 27 Millicent Purview
28 28 Hyacinth Tupperware
29 29 John Hunt
30 30 Erica Crumpet
31 31 Darren Smith17. Output the facility id that has the highest number of slots booked. Ensure that in the event of a tie, all tieing results get output.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey17 <- dbGetQuery(con, "SELECT facid, total FROM (
SELECT facid, sum(slots) total, rank() OVER (ORDER BY sum(slots) DESC) rank
FROM public.bookings
GROUP BY facid
) AS ranked
WHERE rank = 1")
ey17 facid total
1 4 140418. Produce a list of members (including guests), along with the number of hours they’ve booked in facilities, rounded to the nearest ten hours. Rank them by this rounded figure, producing output of first name, surname, rounded hours, rank. Sort by rank, surname, and first name.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey18 <- dbGetQuery(con, "SELECT firstname, surname,
((sum(bks.slots)+10)/20)*10 AS hours,
rank() OVER (ORDER BY ((sum(bks.slots)+10)/20)*10 DESC) AS rank
FROM public.bookings bks
INNER JOIN public.members mems
ON bks.memid = mems.memid
GROUP BY mems.memid
ORDER BY rank, surname, firstname; ")
ey18 firstname surname hours rank
1 GUEST GUEST 1200 1
2 Darren Smith 340 2
3 Tim Rownam 330 3
4 Tim Boothe 220 4
5 Tracy Smith 220 4
6 Gerald Butters 210 6
7 Burton Tracy 180 7
8 Charles Owen 170 8
9 Janice Joplette 160 9
10 Anne Baker 150 10
11 Timothy Baker 150 10
12 David Jones 150 10
13 Nancy Dare 130 13
14 Florence Bader 120 14
15 Anna Mackenzie 120 14
16 Ponder Stibbons 120 14
17 Jack Smith 110 17
18 Jemima Farrell 90 18
19 David Pinker 80 19
20 Ramnaresh Sarwin 80 19
21 Matthew Genting 70 21
22 Joan Coplin 50 22
23 David Farrell 30 23
24 Henry Worthington-Smyth 30 23
25 John Hunt 20 25
26 Douglas Jones 20 25
27 Millicent Purview 20 25
28 Henrietta Rumney 20 25
29 Erica Crumpet 10 29
30 Hyacinth Tupperware 10 2919. Produce a list of the top three revenue generating facilities (including ties). Output facility name and rank, sorted by rank and facility name.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey19 <- dbGetQuery(con, "SELECT name, rank from (
SELECT facs.name AS name, rank() over (ORDER BY sum(CASE
WHEN memid = 0 THEN slots * facs.guestcost
ELSE slots * membercost
END) DESC) AS rank
FROM public.bookings bks
INNER JOIN public.facilities facs
ON bks.facid = facs.facid
GROUP BY facs.name
) AS subq
WHERE rank <= 3
ORDER BY rank; ")
ey19 name rank
1 Massage Room 1 1
2 Tennis Court 2 2
3 Tennis Court 1 320. Classify facilities into equally sized groups of high, average, and low based on their revenue. Order by classification and facility name.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey20 <- dbGetQuery(con, "SELECT name, CASE WHEN class=1 THEN 'high'
WHEN class=2 THEN 'average'
ELSE 'low'
END revenue
FROM (
SELECT facs.name AS name, ntile(3) OVER (ORDER BY sum(CASE
WHEN memid = 0 THEN slots * facs.guestcost
ELSE slots * membercost
END) DESC) AS class
FROM public.bookings bks
INNER JOIN public.facilities facs
on bks.facid = facs.facid
GROUP BY facs.name
) as subq
ORDER BY class, name; ")
ey20 name revenue
1 Massage Room 1 high
2 Tennis Court 1 high
3 Tennis Court 2 high
4 Badminton Court average
5 Massage Room 2 average
6 Squash Court average
7 Pool Table low
8 Snooker Table low
9 Table Tennis low21. Based on the 3 complete months of data so far, calculate the amount of time each facility will take to repay its cost of ownership. Remember to take into account ongoing monthly maintenance. Output facility name and payback time in months, order by facility name. Don’t worry about differences in month lengths, we’re only looking for a rough value here!
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey21 <- dbGetQuery(con, "SELECT facs.name AS name,
facs.initialoutlay/((sum(CASE
WHEN memid = 0 then slots * facs.guestcost
ELSE slots * membercost
END)/3) - facs.monthlymaintenance) as months
FROM public.bookings bks
INNER JOIN public.facilities facs
on bks.facid = facs.facid
GROUP BY facs.facid
ORDER BY name; ")
ey21 name months
1 Badminton Court 6.8317677
2 Massage Room 1 0.1888574
3 Massage Room 2 1.7621145
4 Pool Table 5.3333333
5 Snooker Table 6.9230769
6 Squash Court 1.1339583
7 Table Tennis 6.4000000
8 Tennis Court 1 1.8712575
9 Tennis Court 2 1.640312322. For each day in August 2012, calculate a rolling average of total revenue over the previous 15 days. Output should contain date and revenue columns, sorted by the date. Remember to account for the possibility of a day having zero revenue. This one’s a bit tough, so don’t be afraid to check out the hint!
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ey22 <- dbGetQuery(con, "SELECT dategen.date,
(
-- correlated subquery that, for each day fed into it,
-- finds the average revenue for the last 15 days
SELECT sum(CASE
WHEN memid = 0 THEN slots * facs.guestcost
ELSE slots * membercost
END) AS rev
FROM public.bookings bks
INNER JOIN public.facilities facs
ON bks.facid = facs.facid
WHERE bks.starttime > dategen.date - interval '14 days'
AND bks.starttime < dategen.date + interval '1 day'
)/15 AS revenue
FROM
(
-- generates a list of days in august
SELECT cast(generate_series(timestamp '2012-08-01',
'2012-08-31','1 day') AS date) AS date
) AS dategen
ORDER BY dategen.date")
ey22 date revenue
1 2012-08-01 1191.793
2 2012-08-02 1219.320
3 2012-08-03 1229.460
4 2012-08-04 1245.207
5 2012-08-05 1228.933
6 2012-08-06 1254.360
7 2012-08-07 1249.187
8 2012-08-08 1238.640
9 2012-08-09 1218.507
10 2012-08-10 1240.673
11 2012-08-11 1245.593
12 2012-08-12 1266.427
13 2012-08-13 1290.640
14 2012-08-14 1324.867
15 2012-08-15 1352.180
16 2012-08-16 1364.113
17 2012-08-17 1409.947
18 2012-08-18 1458.933
19 2012-08-19 1490.587
20 2012-08-20 1512.627
21 2012-08-21 1534.013
22 2012-08-22 1629.380
23 2012-08-23 1656.540
24 2012-08-24 1683.333
25 2012-08-25 1710.393
26 2012-08-26 1723.480
27 2012-08-27 1751.673
28 2012-08-28 1775.800
29 2012-08-29 1771.993
30 2012-08-30 1746.053
31 2012-08-31 1791.840Working with TimeStamps
1. Produce a timestamp for 1 a.m. on the 31st of August 2012.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew1 <- dbGetQuery(con, "SELECT timestamp '2012-08-31 01:00:00';")
ew1 timestamp
1 2012-08-31 01:00:002. Find the result of subtracting the timestamp ‘2012-07-30 01:00:00’ from the timestamp ‘2012-08-31 01:00:00’
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew2 <- dbGetQuery(con, "SELECT timestamp '2012-08-31 01:00:00' - timestamp '2012-07-30 01:00:00' AS interval;")
ew2 interval
1 32 days3. Produce a list of all the dates in October 2012. They can be output as a timestamp (with time set to midnight) or a date.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew3 <- dbGetQuery(con, "SELECT generate_series(timestamp '2012-10-01', timestamp '2012-10-31', interval '1 day') AS ts;")
ew3 ts
1 2012-10-01
2 2012-10-02
3 2012-10-03
4 2012-10-04
5 2012-10-05
6 2012-10-06
7 2012-10-07
8 2012-10-08
9 2012-10-09
10 2012-10-10
11 2012-10-11
12 2012-10-12
13 2012-10-13
14 2012-10-14
15 2012-10-15
16 2012-10-16
17 2012-10-17
18 2012-10-18
19 2012-10-19
20 2012-10-20
21 2012-10-21
22 2012-10-22
23 2012-10-23
24 2012-10-24
25 2012-10-25
26 2012-10-26
27 2012-10-27
28 2012-10-28
29 2012-10-29
30 2012-10-30
31 2012-10-314. Get the day of the month from the timestamp ‘2012-08-31’ as an integer.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew4 <- dbGetQuery(con, "SELECT extract(day FROM timestamp '2012-08-31');")
ew4 extract
1 315. Work out the number of seconds between the timestamps ‘2012-08-31 01:00:00’ and ‘2012-09-02 00:00:00’
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew5 <- dbGetQuery(con, "SELECT extract(epoch FROM (timestamp '2012-09-02 00:00:00' - '2012-08-31 01:00:00'));")
ew5 extract
1 1692006. For each month of the year in 2012, output the number of days in that month. Format the output as an integer column containing the month of the year, and a second column containing an interval data type.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew6 <- dbGetQuery(con, "SELECT extract(month FROM cal.month) AS month,
(cal.month + interval '1 month') - cal.month AS length
FROM (
SELECT generate_series(timestamp '2012-01-01', timestamp '2012-12-01', interval '1 month') AS month
) cal
ORDER BY month;")
ew6 month length
1 1 31 days
2 2 29 days
3 3 31 days
4 4 30 days
5 5 31 days
6 6 30 days
7 7 31 days
8 8 31 days
9 9 30 days
10 10 31 days
11 11 30 days
12 12 31 days7. For any given timestamp, work out the number of days remaining in the month. The current day should count as a whole day, regardless of the time. Use ‘2012-02-11 01:00:00’ as an example timestamp for the purposes of making the answer. Format the output as a single interval value.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew7 <- dbGetQuery(con, "SELECT (date_trunc('month',ts.testts) + interval '1 month')
- date_trunc('day', ts.testts) AS remaining
FROM (SELECT timestamp '2012-02-11 01:00:00' as testts) ts ")
ew7 remaining
1 19 days8. Return a list of the start and end time of the last 10 bookings (ordered by the time at which they end, followed by the time at which they start) in the system.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew8 <- dbGetQuery(con, "select starttime, starttime + slots*(interval '30 minutes') endtime
from public.bookings
order by endtime desc, starttime desc
limit 10")
ew8 starttime endtime
1 2013-01-01 15:30:00 2013-01-01 16:00:00
2 2012-09-30 19:30:00 2012-09-30 20:30:00
3 2012-09-30 19:00:00 2012-09-30 20:30:00
4 2012-09-30 19:30:00 2012-09-30 20:00:00
5 2012-09-30 19:00:00 2012-09-30 20:00:00
6 2012-09-30 19:00:00 2012-09-30 20:00:00
7 2012-09-30 18:30:00 2012-09-30 20:00:00
8 2012-09-30 18:30:00 2012-09-30 20:00:00
9 2012-09-30 19:00:00 2012-09-30 19:30:00
10 2012-09-30 18:30:00 2012-09-30 19:30:009. Return a count of bookings for each month, sorted by month.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew9 <- dbGetQuery(con, "select date_trunc('month', starttime) as month, count(*)
from public.bookings
group by month
order by month")
ew9 month count
1 2012-07-01 658
2 2012-08-01 1472
3 2012-09-01 1913
4 2013-01-01 110. Work out the utilisation percentage for each facility by month, sorted by name and month, rounded to 1 decimal place. Opening time is 8am, closing time is 8.30pm. You can treat every month as a full month, regardless of if there were some dates the club was not open.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
ew10 <- dbGetQuery(con, "select name, month,
round((100*slots)/
cast(
25*(cast((month + interval '1 month') as date)
- cast (month as date)) as numeric),1) as utilisation
from (
select facs.name as name, date_trunc('month', starttime) as month, sum(slots) as slots
from public.bookings bks
inner join public.facilities facs
on bks.facid = facs.facid
group by facs.facid, month
) as inn
order by name, month")
ew10 name month utilisation
1 Badminton Court 2012-07-01 23.2
2 Badminton Court 2012-08-01 59.2
3 Badminton Court 2012-09-01 76.0
4 Massage Room 1 2012-07-01 34.1
5 Massage Room 1 2012-08-01 63.5
6 Massage Room 1 2012-09-01 86.4
7 Massage Room 2 2012-07-01 3.1
8 Massage Room 2 2012-08-01 10.6
9 Massage Room 2 2012-09-01 16.3
10 Pool Table 2012-07-01 15.1
11 Pool Table 2012-08-01 41.5
12 Pool Table 2012-09-01 62.8
13 Pool Table 2013-01-01 0.1
14 Snooker Table 2012-07-01 20.1
15 Snooker Table 2012-08-01 42.1
16 Snooker Table 2012-09-01 56.8
17 Squash Court 2012-07-01 21.2
18 Squash Court 2012-08-01 51.6
19 Squash Court 2012-09-01 72.0
20 Table Tennis 2012-07-01 13.4
21 Table Tennis 2012-08-01 39.2
22 Table Tennis 2012-09-01 56.3
23 Tennis Court 1 2012-07-01 34.8
24 Tennis Court 1 2012-08-01 59.2
25 Tennis Court 1 2012-09-01 78.8
26 Tennis Court 2 2012-07-01 26.7
27 Tennis Court 2 2012-08-01 62.3
28 Tennis Court 2 2012-09-01 78.4String Operations
1. Output the names of all members, formatted as ‘Surname, Firstname’
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es1 <- dbGetQuery(con, "SELECT surname || ', ' || firstname AS name FROM public.members ")
es1 name
1 GUEST, GUEST
2 Smith, Darren
3 Smith, Tracy
4 Rownam, Tim
5 Joplette, Janice
6 Butters, Gerald
7 Tracy, Burton
8 Dare, Nancy
9 Boothe, Tim
10 Stibbons, Ponder
11 Owen, Charles
12 Jones, David
13 Baker, Anne
14 Farrell, Jemima
15 Smith, Jack
16 Bader, Florence
17 Baker, Timothy
18 Pinker, David
19 Genting, Matthew
20 Mackenzie, Anna
21 Coplin, Joan
22 Sarwin, Ramnaresh
23 Jones, Douglas
24 Rumney, Henrietta
25 Farrell, David
26 Worthington-Smyth, Henry
27 Purview, Millicent
28 Tupperware, Hyacinth
29 Hunt, John
30 Crumpet, Erica
31 Smith, Darren2. Find all facilities whose name begins with ‘Tennis’. Retrieve all columns.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es2 <- dbGetQuery(con, "SELECT * FROM public.facilities WHERE name LIKE 'Tennis%'; ")
es2 facid name membercost guestcost initialoutlay monthlymaintenance
1 0 Tennis Court 1 6.0 30 10000 200
2 1 Tennis Court 2 6.6 33 10000 200Perform a case-insensitive search to find all facilities whose name begins with ‘tennis’. Retrieve all columns.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es3 <- dbGetQuery(con, "SELECT * from public.facilities WHERE upper(name) LIKE 'TENNIS%'; ")
es3 facid name membercost guestcost initialoutlay monthlymaintenance
1 0 Tennis Court 1 6.0 30 10000 200
2 1 Tennis Court 2 6.6 33 10000 2004. You’ve noticed that the club’s member table has telephone numbers with very inconsistent formatting. You’d like to find all the telephone numbers that contain parentheses, returning the member ID and telephone number sorted by member ID.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es4 <- dbGetQuery(con, "SELECT memid, telephone FROM public.members WHERE telephone ~ '[()]'; ")
es4 memid telephone
1 0 (000) 000-0000
2 3 (844) 693-0723
3 4 (833) 942-4710
4 5 (844) 078-4130
5 6 (822) 354-9973
6 7 (833) 776-4001
7 8 (811) 433-2547
8 9 (833) 160-3900
9 10 (855) 542-5251
10 11 (844) 536-8036
11 13 (855) 016-0163
12 14 (822) 163-3254
13 15 (833) 499-3527
14 20 (811) 972-1377
15 21 (822) 661-2898
16 22 (822) 499-2232
17 24 (822) 413-1470
18 27 (822) 989-8876
19 28 (855) 755-9876
20 29 (855) 894-3758
21 30 (855) 941-9786
22 33 (822) 665-5327
23 35 (899) 720-6978
24 36 (811) 732-4816
25 37 (822) 577-35415. The zip codes in our example dataset have had leading zeroes removed from them by virtue of being stored as a numeric type. Retrieve all zip codes from the members table, padding any zip codes less than 5 characters long with leading zeroes. Order by the new zip code.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es5 <- dbGetQuery(con, "SELECT lpad(cast(zipcode AS char(5)),5,'0') zip FROM public.members ORDER BY zip ")
es5 zip
1 00000
2 00234
3 00234
4 04321
5 04321
6 10383
7 11986
8 23423
9 28563
10 33862
11 34232
12 43532
13 43533
14 45678
15 52365
16 54333
17 56754
18 57392
19 58393
20 64577
21 65332
22 65464
23 66796
24 68666
25 69302
26 75655
27 78533
28 80743
29 84923
30 87630
31 976766. You’d like to produce a count of how many members you have whose surname starts with each letter of the alphabet. Sort by the letter, and don’t worry about printing out a letter if the count is 0.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es6 <- dbGetQuery(con, "SELECT substr (mems.surname,1,1) AS letter, count(*) AS count
FROM public.members mems
GROUP BY letter
ORDER BY letter ")
es6 letter count
1 B 5
2 C 2
3 D 1
4 F 2
5 G 2
6 H 1
7 J 3
8 M 1
9 O 1
10 P 2
11 R 2
12 S 6
13 T 2
14 W 17. You’d like to produce a count of how many members you have whose surname starts with each letter of the alphabet. Sort by the letter, and don’t worry about printing out a letter if the count is 0.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es7 <- dbGetQuery(con, "SELECT substr (mems.surname,1,1) AS letter, count(*) AS count
FROM public.members mems
GROUP BY letter
ORDER BY letter ")
es7 letter count
1 B 5
2 C 2
3 D 1
4 F 2
5 G 2
6 H 1
7 J 3
8 M 1
9 O 1
10 P 2
11 R 2
12 S 6
13 T 2
14 W 18. The telephone numbers in the database are very inconsistently formatted. You’d like to print a list of member ids and numbers that have had ‘-’,‘(’,‘)’, and ’ ’ characters removed. Order by member id.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
es8 <- dbGetQuery(con, "SELECT memid, translate(telephone, '-() ', '') AS telephone
FROM public.members
ORDER BY memid;")
es8 memid telephone
1 0 0000000000
2 1 5555555555
3 2 5555555555
4 3 8446930723
5 4 8339424710
6 5 8440784130
7 6 8223549973
8 7 8337764001
9 8 8114332547
10 9 8331603900
11 10 8555425251
12 11 8445368036
13 12 8440765141
14 13 8550160163
15 14 8221633254
16 15 8334993527
17 16 8339410824
18 17 8114096734
19 20 8119721377
20 21 8226612898
21 22 8224992232
22 24 8224131470
23 26 8445368036
24 27 8229898876
25 28 8557559876
26 29 8558943758
27 30 8559419786
28 33 8226655327
29 35 8997206978
30 36 8117324816
31 37 8225773541Recursive Queries
1. Find the upward recommendation chain for member ID 27: that is, the member who recommended them, and the member who recommended that member, and so on. Return member ID, first name, and surname. Order by descending member id.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
et1 <- dbGetQuery(con, "with recursive recommenders(recommender) as (
select recommendedby from public.members where memid = 27
union all
select mems.recommendedby
from recommenders recs
inner join public.members mems
on mems.memid = recs.recommender
)
select recs.recommender, mems.firstname, mems.surname
from recommenders recs
inner join public.members mems
on recs.recommender = mems.memid
order by memid desc")
et1 recommender firstname surname
1 20 Matthew Genting
2 5 Gerald Butters
3 1 Darren Smith2. Find the downward recommendation chain for member ID 1: that is, the members they recommended, the members those members recommended, and so on. Return member ID and name, and order by ascending member id.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
et2 <- dbGetQuery(con, "with recursive recommendeds(memid) as (
select memid from public.members where recommendedby = 1
union all
select mems.memid
from recommendeds recs
inner join public.members mems
on mems.recommendedby = recs.memid
)
select recs.memid, mems.firstname, mems.surname
from recommendeds recs
inner join public.members mems
on recs.memid = mems.memid
order by memid")
et2 memid firstname surname
1 4 Janice Joplette
2 5 Gerald Butters
3 7 Nancy Dare
4 10 Charles Owen
5 11 David Jones
6 14 Jack Smith
7 20 Matthew Genting
8 21 Anna Mackenzie
9 26 Douglas Jones
10 27 Henrietta Rumney3. Produce a CTE that can return the upward recommendation chain for any member. You should be able to select recommender from recommenders where member=x. Demonstrate it by getting the chains for members 12 and 22. Results table should have member and recommender, ordered by member ascending, recommender descending.
con <- dbConnect(RPostgres::Postgres(),
dbname = "undatascience-db",
host = "ep-cool-shape-a5kx7769.us-east-2.aws.neon.tech",
port = 5432,
user = "undatascience-db_owner",
password = "LCQzDZV1r4Ed")
et3 <- dbGetQuery(con, "WITH recursive recommenders(recommender, member) AS (
SELECT recommendedby, memid
FROM public.members
UNION ALL
SELECT mems.recommendedby, recs.member
FROM recommenders recs
INNER JOIN public.members mems
ON mems.memid = recs.recommender
)
SELECT recs.member member, recs.recommender, mems.firstname, mems.surname
FROM recommenders recs
INNER JOIN public.members mems
ON recs.recommender = mems.memid
WHERE recs.member = 22 OR recs.member = 12
ORDER BY recs.member ASC, recs.recommender DESC")
et3 member recommender firstname surname
1 12 9 Ponder Stibbons
2 12 6 Burton Tracy
3 22 16 Timothy Baker
4 22 13 Jemima Farrell