Flight Price Predict (competition Format)

filght price regression problem

@kaggle.kukuroo3_flight_price_predict_competition_format

Table List

4 tables(194.66 KB)

X Test

X Train

Y Test

Y Train

X Test

@kaggle.kukuroo3_flight_price_predict_competition_format.x_test

46.31 KB
3347 rows
10 columns

filghtid FilghtId	airline Airline	flight Flight	source_city Source City	departure_time Departure Time	stops Stops	arrival_time Arrival Time	destination_city Destination City	duration Duration	days_left Days Left
278519	Air_India	AI-559	Hyderabad	Early_Morning	one	Night	Mumbai	14.75	22
264230	Vistara	UK-720	Kolkata	Early_Morning	one	Evening	Mumbai	9.33	6
260097	Vistara	UK-852	Bangalore	Morning	one	Evening	Chennai	10.42	27
218935	Vistara	UK-747	Delhi	Early_Morning	zero	Morning	Kolkata	2.08	47
211085	Air_India	AI-762	Delhi	Night	one	Night	Mumbai	23.83	41
251748	Air_India	AI-505	Bangalore	Morning	one	Night	Mumbai	11.17	37
292760	Air_India	AI-430	Chennai	Morning	one	Night	Mumbai	11.33	39
292966	Air_India	AI-440	Chennai	Early_Morning	one	Night	Mumbai	15.08	42
245610	Air_India	AI-565	Bangalore	Afternoon	one	Morning	Delhi	18.75	12
261821	Air_India	AI-773	Kolkata	Evening	one	Afternoon	Delhi	19	11


CREATE TABLE x_test (
  "filghtid" BIGINT,
  "airline" VARCHAR,
  "flight" VARCHAR,
  "source_city" VARCHAR,
  "departure_time" VARCHAR,
  "stops" VARCHAR,
  "arrival_time" VARCHAR,
  "destination_city" VARCHAR,
  "duration" DOUBLE,
  "days_left" BIGINT
);