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mor40
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cars-bg

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train · 23.1k rows

id stringlengths 24 24	brand stringlengths 2 13	model stringlengths 1 15	year int64 1.97k 2.02k	fuel stringclasses 6 values	kms float64 1 1,628B ⌀	transmission float64 0 1 ⌀	2door float64 0 1 ⌀	color stringclasses 20 values	type stringclasses 8 values	displacement float64 -2 1.23M ⌀	hp float64 1 173k ⌀	euro float64 1 6 ⌀	price float64 550 538k
5fe6139519a6c14a8f142552	Subaru	Impreza	2,009	p	195,200	0	0	gray	hatchback	null	null	null	7,700
6396206d1b2a258c300b44b3	Toyota	Land	2,007	d	162,500	0	0	black	jeep	3,000	173	4	47,500
63d6939e92363d5d130bb5f2	Mitsubishi	Pajero	2,003	d	294,000	0	0	black	jeep	3,200	164	null	9,500
6408ea82171cd6399a056183	Mercedes-Benz	C	2,007	d	296,000	1	0	gray	sedan	null	170	4	18,599
63ff91dd0d027c74b00b17c2	Mitsubishi	Pajero	2,003	d	226,618	0	1	gray	jeep	2,500	115	3	9,300
633c86a9aadf554908005983	Kia	Sportage	2,008	d	186,000	0	0	black	jeep	2,000	140	null	7,898
6409edad2c5d1546f00d49c4	Ford	Fiesta	2,007	p	158,000	0	0	red	hatchback	null	null	4	6,255
6408d26665c65366f30f81c3	Skoda	Octavia	2,007	d	212,000	1	0	silver	combi	1,900	105	4	7,990
63eb63038349be0e3b062972	Nissan	Bluebird	1,988	p	195,100	0	0	beige	hatchback	2,000	105	null	3,500
63f65798d9f46bafd30098c5	Mercedes-Benz	CLK	2,004	p	144,200	1	1	gray	coupe	null	218	null	11,300
6311c64be7a188d0740ddb32	Peugeot	207	2,008	p	111,500	0	0	silver	combi	1,400	null	4	5,560
63d6a4c3c966730fde09baf2	Audi	A6	2,008	d	212,000	1	0	black	combi	3,000	233	4	9,500
624dc92a30db2be25b036252	Ford	C-Max	2,007	d	138,000	0	0	black	hatchback	null	90	4	5,900
639486b5a2968c3b190d4283	Audi	A6	2,006	d	243,000	1	0	gray	combi	2,700	180	4	8,600
63b32f67058e1259a902dc25	Audi	A8	2,008	d	250,000	1	0	silver	sedan	3,000	233	4	18,500
63f3666e928c34053c020e06	LandRover	Freelander	2,006	d	240,000	0	1	black	jeep	2,000	112	4	5,280
639339b6681cc3907304b455	Daewoo	Nubira	2,004	p	128,956	0	0	blue	combi	1,600	109	null	3,600
63aca08d18269e4ca2091982	Suzuki	SX4	2,010	g	170,000	0	0	gray	jeep	1,600	110	4	10,800
6406139a4b3af49089093012	Hyundai	i30	2,008	d	235,000	0	0	black	hatchback	1,600	90	4	7,500
63bbc9173d0109e1910dc263	Hyundai	Kona	2,018	p	93,100	1	0	gray	jeep	1,599	177	null	38,999
63eb51ba998e124d8c096753	AlfaRomeo	156	2,005	d	230,000	0	0	silver	sedan	null	115	3	3,600
61cac47473c55823d024abb2	Chevrolet	Matiz	2,008	g	175,000	0	0	blue	hatchback	800	52	null	3,400
63a441f5d55aa25c47097693	Dacia	Logan	2,014	d	169,000	0	0	gray	combi	null	75	5	12,850
63fcebf10e1ec13ab401c043	Fiat	Panda	2,006	p	109,000	0	0	blue	hatchback	1,200	55	4	4,200
5fbb995781fbce744b471cb2	Nissan	Skyline	2,001	p	230,000	1	0	gray	sedan	2,500	200	3	16,500
636e7a61ae810e3b3f02c692	Mercedes-Benz	E	2,003	d	200,000	1	0	blue	sedan	2,200	150	4	4,500
63cfb7a615a3c3f449051682	VW	Touareg	2,007	d	230,000	0	0	gray	jeep	2,500	175	null	11,500
6381e3787e2e6ed2630b3654	Chevrolet	Spark	2,010	p	161,900	0	0	white	hatchback	1,200	70	4	7,200
640c42b6ba875d010d02b183	Audi	A4	1,998	d	183,000	0	0	blue	combi	2,490	150	2	3,200
636531d02d15c3a00501f6e7	Renault	Espace	2,004	d	247,000	0	0	gray	van	2,200	150	3	3,800
6404ea75aa450cafcc0ba2d5	Audi	A3	2,009	d	200,000	0	0	gray	hatchback	1,900	105	4	10,350
5f4f8702263e2a1f560eb348	Fiat	500	2,011	p	126,000	0	1	yellow	hatchback	900	86	5	7,990
64021989c6ec3185280120f3	Fiat	Idea	2,008	d	145,000	0	0	black	van	1,299	70	4	4,300
6404a2569d7040dae207c443	BMW	320	2,009	d	180,126	0	0	gray	combi	2,000	177	null	7,999
638100e2c88321632e0e54e3	Ssangyong	Kyron	2,006	d	169,752	0	0	gray	jeep	2,000	142	null	7,900
634d2ee15491093e1f0cb4b2	Honda	CR-V	2,000	p	200,000	0	0	black	jeep	2,000	128	null	7,700
63fcaa650a53d2f1f30bcfc2	Mazda	6	2,004	d	222,400	0	0	blue	hatchback	2,000	121	4	2,500
63ef9f677364a8a9bf02e5a2	Suzuki	Swift	2,011	p	89,400	0	0	white	hatchback	1,200	94	null	13,300
63c68f6b0576ba7a83001764	Ford	Galaxy	2,005	d	258,000	1	0	black	van	1,900	116	4	5,100
62556a89d56760f1090be334	Renault	Clio	2,014	d	208,000	0	0	white	hatchback	1,500	90	5	13,990
63971d530e15e04d2b0088f4	Opel	Astra	2,006	d	177,000	0	0	gold	hatchback	1,900	120	4	5,500
63aab94fd03036d5180b2c76	Fiat	Fiorino	2,012	d	121,354	0	0	white	pickup	1,248	75	5	8,295
638c76e4fba454d529082403	Peugeot	307	2,007	d	266,000	1	0	blue	combi	2,000	136	4	6,600
6401f0e913557180f20ce762	Nissan	Primera	2,003	p	257,784	0	0	gray	combi	2,000	140	4	4,850
6402e89e0bbde476320ae1d2	Audi	A6	2,002	d	256,000	0	0	bordo	sedan	1,900	90	3	14,100
6383235306f64eb1150855f2	Hyundai	Tucson	2,015	d	141,188	1	0	white	jeep	2,000	185	6	41,500
62b4d8a807b775b9550aeff4	Peugeot	307	2,006	p	123,444	0	0	green	combi	2,000	140	4	3,500
64073e3b88e31c31dc0512e3	Mercedes-Benz	C	2,003	p	250,000	0	0	blue	combi	2,400	170	null	5,500
63c7b4f2df05dd3e1b000735	Ford	Fiesta	2,010	g	163,000	0	0	blue	hatchback	1,400	97	null	8,900
6313a279b4324a7ee906da63	BMW	X5	2,008	d	225,000	1	0	gray	jeep	3,000	235	4	18,200
63f51798db6eb75dbd03b2a2	Volvo	V50	2,004	d	223,500	0	0	green	combi	2,000	136	3	5,500
6407693dcbfdc61fd708b603	Fiat	Scudo	2,002	d	256,700	0	0	white	van	2,000	94	null	3,800
63fc5721f9d1936cca009422	Peugeot	308	2,012	d	250,000	0	0	white	hatchback	100	null	5	9,750
62209735e744762778418e64	Ford	Focus	2,008	d	218,000	0	0	gray	hatchback	1,600	90	null	5,100
638c6dfde09ead318801cbe2	Audi	Q7	2,015	d	186,000	1	0	gray	jeep	3,000	245	6	52,500
62593f8e857ecf428703baa2	Audi	A3	2,006	d	188,000	0	0	chameleon	hatchback	2,000	140	null	7,300
621e3b0e77b1a81e172cdae3	Audi	TT	2,011	p	135,000	0	1	white	hatchback	1,800	160	5	21,600
63fc522ce16ce510db08c7b3	Dacia	Duster	2,014	p	71,000	0	0	black	jeep	1,600	115	6	19,900
63ee73aa13c9232b6a086c13	Suzuki	Wagon	2,003	p	115,432	0	0	blue	hatchback	1,300	75	null	3,400
6400d1705b9f7e3483057f87	Skoda	Yeti	2,011	p	116,000	0	0	gray	jeep	1,800	160	5	14,500
63ca4cebd949d7a99707d9a3	Daihatsu	Feroza/Sportrak	1,991	g	96,999	0	1	red	jeep	1,600	92	null	5,800
633c297e2e58888213041c76	Hyundai	i40	2,013	p	191,000	1	0	black	combi	2,000	177	5	20,900
6407f299e365b092ee02a4c2	Volvo	XC	2,018	p	107,409	1	0	blue	null	null	190	6	70,000
63a3aed629a83e18a907f512	Mitsubishi	Lancer	2,005	p	178,526	0	0	gray	combi	1,600	null	null	4,899
63f4d443fd5646ada0035e74	VW	Passat	2,015	d	203,000	1	0	gray	combi	2,000	240	6	33,900
63f4adcd85e9d3ab420b6e12	Dacia	Dokker	2,019	p	103,123	0	0	white	pickup	1,600	103	6	19,500
625fe166b8e1873cee0bdec2	AlfaRomeo	159	2,007	d	193,145	0	0	gold	combi	2,400	209	5	7,999
639e050cbd0bafce950f67b2	Volvo	XC	2,011	p	266,773	1	0	white	jeep	3,000	304	5	29,600
63f0d6c8e4e6c9f769033c13	Mitsubishi	Grandis	2,008	g	220,000	1	0	gray	van	2,400	165	null	8,999
63e94dfb689c9e1d9a0aca43	Hyundai	Terracan	2,004	d	1,234	0	0	black	jeep	null	null	null	3,000
6276ab39f5f7813b57047d04	Audi	A4	2,011	d	274,000	1	0	gray	combi	3,000	240	5	19,999
63de6bfdccf5186062019022	Ford	S-Max	2,007	d	260,000	0	0	gray	van	2,000	140	4	6,399
63627a14cbf6467d0f05d4d2	Kia	Sorento	2,005	d	204,798	1	0	black	jeep	2,500	140	3	5,800
640776c48aaf36b991069427	Ford	Focus	2,008	g	202,000	0	0	blue	combi	1,600	101	4	8,295
63524a8039adee97970516d2	Renault	Grand	2,007	d	245,000	0	0	gray	van	1,900	131	4	4,200
636569ea4f93920a5a06de72	Toyota	Corolla	2,007	p	184,904	0	0	gray	van	1,600	110	null	9,999
62d51e6b55e063c84e0b12b2	VW	Golf	2,003	d	196,000	0	0	bordo	hatchback	null	null	null	3,490
633db179ead8dc562c075382	Honda	CR-V	2,005	g	286,000	1	0	blue	jeep	2,000	150	3	9,300
63501f6332dd8ba3f3014662	Dodge	Challenger	2,015	p	140,000	1	1	black	hatchback	3,600	310	6	36,000
63136509d6e4c49ced0438c2	Kia	Ceed	2,009	d	246,000	0	0	bordo	hatchback	1,600	90	null	6,999
63ff7d438e31a70b06039592	BMW	320	2,008	d	204,500	0	0	perl	sedan	2,000	177	4	10,390
63ac4e44af2bd81273023022	Dodge	Challenger	2,016	p	117,231	1	1	orange	sedan	null	null	6	60,000
63f26c0793eef2f3490921f3	Lancia	Phedra	2,005	d	201	0	0	blue	van	2,200	127	4	5,050
63d10c0ce9f3002732023365	LandRover	Discovery	2,000	d	390,000	0	0	white	jeep	2,500	160	null	17,000
61d9a6bb7250b37a234c5993	Honda	CR-V	2,009	p	151,500	0	0	black	jeep	2,000	150	5	17,500
63f45769cdc616ec51083d03	Ford	Focus	2,009	d	248,000	0	0	gray	combi	1,600	90	null	5,700
63b55cada41fff56a608f8a3	LandRover	Discovery	2,010	d	210,000	1	0	black	jeep	3,000	211	null	26,999
630239dad2348428e404d225	Seat	Ibiza	2,009	p	99,457	0	0	gray	hatchback	1,200	70	5	7,800
62e2561e75304280ec075dd3	Opel	Astra	2,001	d	217,547	0	0	gray	combi	2,199	101	null	2,400
637ba85477b9e49e580e9593	Suzuki	Grand	2,004	d	210,350	0	0	silver	jeep	1,998	109	3	8,250
6385f89f9ab6249a03079b92	Seat	Leon	2,005	d	215,480	0	0	black	hatchback	1,900	150	2	6,000
63539f723fb16c030b024104	Citroen	C2	2,003	p	186,500	1	1	black	hatchback	1,600	120	5	4,500
62fb3e0d05b2e0ee3a0aab23	Kia	Sorento	2,008	d	156,998	0	0	black	jeep	2,500	170	4	8,590
63f4d48899bc944db4033302	Honda	CR-V	2,008	d	215,000	0	0	silver	jeep	2,200	150	4	12,800
640b999aee13358f5a044e84	Mazda	CX	2,013	g	198,300	0	0	blue	jeep	2,000	160	5	22,990
6297003aeafd12fd930f6182	Renault	Megane	2,003	p	177,000	0	0	blue	hatchback	1,600	113	4	2,999
63c81741261092f7c7093b45	Ssangyong	REXTON	2,007	d	260,000	1	0	black	jeep	2,700	186	4	9,000
6292d196bc3b498e140404c7	LandRover	Discovery	2,015	d	183,624	1	0	red	null	null	190	6	43,990
63bbc91b723d33528703a4a3	Audi	A6	2,012	d	240,000	1	0	gray	combi	3,000	245	null	31,999
63d90a1f616b0464d10e8155	Peugeot	508	2,015	d	165,000	1	0	blue	sedan	2,000	181	6	19,999

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YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/datasets-cards)

This is a webscraped dataset from the website cars.bg

The code for the webscraping you can find here : `https://github.com/MarioMarkov/cars-predict`

Using BeutifulSoup4 and Selenium for python

dataset_info: features: - name: id dtype: string - name: brand dtype: string - name: model dtype: string - name: year dtype: int64 - name: fuel dtype: string - name: kms dtype: float64 - name: transmission dtype: float64 - name: 2door dtype: float64 - name: color dtype: string - name: type dtype: string - name: displacement dtype: float64 - name: hp dtype: float64 - name: euro dtype: float64 - name: price dtype: float64 splits: - name: train num_bytes: 3111021 num_examples: 23103 - name: test num_bytes: 345669 num_examples: 2567 download_size: 1203060 dataset_size: 3456690 size_categories: - 10K<n<100K

Dataset Card for "cars-bg"

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Size of downloaded dataset files:

1.2 MB

Size of the auto-converted Parquet files:

1.2 MB

Number of rows:

25,670

This is a webscraped dataset from the website cars.bg

The code for the webscraping you can find here : https://github.com/MarioMarkov/cars-predict

Dataset Card for "cars-bg"

The code for the webscraping you can find here : `https://github.com/MarioMarkov/cars-predict`