📊 Day 20 Data Download

Hotel Booking & Occupancy Trends Dataset

INNER JOIN DATEDIFF Data Cleaning Aggregations

Table 1: bookings (25 rows)

booking_id guest_id room_id check_in_date check_out_date
B001 G101R2012024-01-052024-01-08
b002G102 r305 06/01/20242024-01-09
B003 g103 R2012024/01/1012-01-2024
B004G104R1022024-01-07NULL
b005G105R40508-01-20242024-01-10
B006G106 R305 2024-01-122024-01-15
b007 g107 r20115/01/20242024-01-17
B008G108R1022024/01/1618-01-2024
B009G109R2032024-01-182024-01-20
b010G110 r405 20-01-2024NULL
B011 g101R3052024-01-222024-01-25
B012G111R20123/01/20242024-01-26
b013 G112 r1022024/01/2527-01-2024
B014G113R4052024-01-262024-01-29
B015g114 R203 28-01-20242024-01-30
b016G115R3052024-01-2902-02-2024
B017G102r20101/02/20242024-02-03
B018G116R1022024/02/03NULL
b019 g117 R4052024-02-052024-02-08
B020G118 R203 06-02-20242024-02-09
B021g119r30508/02/20242024-02-11
b022G120R2012024-02-1012-02-2024
B023G121R1022024/02/122024-02-14
B024 G103 r4052024-02-14NULL
b025G122R20315-02-20242024-02-18

Table 2: rooms (20 rows)

room_id room_type price_per_night floor_number
R201Deluxe150.002
r305SUITE250.003
R102standard100.001
R405Suite250.004
R203 Deluxe150.002
R101STANDARD100.001
r202deluxe150.002
R103Standard100.001
R301Suite250.003
r302 SUITE250.003
R303suite250.003
R304Suite250.003
R401SUITE250.004
r402Suite250.004
R403suite250.004
R404Suite250.004
R204 Deluxe150.002
R104standard100.001
r105Standard100.001
R205DELUXE150.002

Table 3: guests (25 rows)

guest_id guest_name email phone country
G101john smithjohn.smith@email.com555-0101USA
g102 MARIA GARCIAmaria.g@email.com555-0102spain
G103David Chend.chen@email.comNULLChina
G104 sarah johnson sarah.j@email.com555-0104CANADA
g105Mohammed Alim.ali@email.com555-0105UAE
G106Emma BROWNemma.b@email.comNULLuk
G107 raj patel raj.p@email.com555-0107India
g108LISA WANGlisa.w@email.com555-0108china
G109James Wilsonjames.w@email.com555-0109USA
G110anna MUELLERanna.m@email.comNULLGermany
g111 Carlos Rodriguezcarlos.r@email.com555-0111SPAIN
G112yuki tanakayuki.t@email.com555-0112Japan
G113Sophie MARTINsophie.m@email.com555-0113france
g114 MICHAEL LEE michael.l@email.comNULLCanada
G115Priya Sharmapriya.s@email.com555-0115INDIA
G116robert BROWNrobert.b@email.com555-0116usa
G117ELENA POPOVelena.p@email.com555-0117Russia
g118ahmed hassanahmed.h@email.comNULLEgypt
G119 Kim Park kim.p@email.com555-0119SOUTH KOREA
G120Isabella ROSSIisabella.r@email.com555-0120italy
G121THOMAS SCHMIDTthomas.s@email.com555-0121Germany
g122lucia silvalucia.s@email.comNULLBrazil

📖 How to Import Data

MySQL:

-- Create database CREATE DATABASE hotel_db; USE hotel_db; -- Create tables CREATE TABLE bookings ( booking_id VARCHAR(50), guest_id VARCHAR(50), room_id VARCHAR(50), check_in_date VARCHAR(50), check_out_date VARCHAR(50) ); -- Load data LOAD DATA INFILE 'day_20_bookings.csv' INTO TABLE bookings FIELDS TERMINATED BY ',' IGNORE 1 ROWS;

PostgreSQL:

-- Create tables CREATE TABLE bookings ( booking_id VARCHAR(50), guest_id VARCHAR(50), room_id VARCHAR(50), check_in_date VARCHAR(50), check_out_date VARCHAR(50) ); -- Load data COPY bookings FROM '/path/to/day_20_bookings.csv' DELIMITER ',' CSV HEADER;

Note: All columns are VARCHAR to preserve messy data formats. You'll clean them in your queries!

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Rahul Kanche — exploring data, decoding clarity!