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Another-Dataset-on-used-Fiat-500-(1538-rows)

Another-Dataset-on-used-Fiat-500-(1538-rows)

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Elif Ceren Gok
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This dataset has been created from a query done on an website specialized in used cars and contains 1538 rows Description of colums: model: Fiat 500 comes in several 'flavours' :'pop', 'lounge', 'sport' engine_power: number of Kw of the engine ageindays: age of the car in number of days (from the time the dataset has been created) km: kilometers of the car previous_owners: number of previous owners lat: latitude of the seller (the price of cars in Italy varies from North to South of the country) lon: longitude of the seller (the price of cars in Italy varies from North to South of the country) price: selling price (the target) I collected this dataset to train myself and test regression algorithms. Hope this can help people to train as well.

8 features

price (target)numeric222 unique values
0 missing
modelstring3 unique values
0 missing
engine_powernumeric8 unique values
0 missing
age_in_daysnumeric140 unique values
0 missing
kmnumeric988 unique values
0 missing
previous_ownersnumeric4 unique values
0 missing
latnumeric449 unique values
0 missing
lonnumeric450 unique values
0 missing

19 properties

1538
Number of instances (rows) of the dataset.
8
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
7
Number of numeric attributes.
0
Number of nominal attributes.
0.01
Number of attributes divided by the number of instances.
87.5
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
-2111.43
Average class difference between consecutive instances.
0
Percentage of missing values.

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