OpenML
Sample-of-Car-Data

Sample-of-Car-Data

active ARFF Database: Open Database, Contents: Database Contents Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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Context There's a story behind every dataset and here's your opportunity to share yours. Content What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research. Inspiration Your data will be in front of the world's largest data science community. What questions do you want to see answered?

23 features

Unnamed:_0numeric205 unique values
0 missing
makestring22 unique values
0 missing
fuel_typestring2 unique values
0 missing
aspirationstring2 unique values
0 missing
num_of_doorsstring2 unique values
2 missing
body_stylestring5 unique values
0 missing
drive_wheelsstring3 unique values
0 missing
engine_locationstring2 unique values
0 missing
wheel_basenumeric53 unique values
0 missing
lengthnumeric75 unique values
0 missing
widthnumeric44 unique values
0 missing
heightnumeric49 unique values
0 missing
curb_weightnumeric171 unique values
0 missing
engine_typestring7 unique values
0 missing
num_of_cylindersstring7 unique values
0 missing
engine_sizenumeric44 unique values
0 missing
fuel_systemstring8 unique values
0 missing
compression_rationumeric32 unique values
0 missing
horsepowerstring59 unique values
2 missing
peak_rpmstring23 unique values
2 missing
city_mpgnumeric29 unique values
0 missing
highway_mpgnumeric30 unique values
0 missing
pricestring186 unique values
4 missing

19 properties

205
Number of instances (rows) of the dataset.
23
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
10
Number of missing values in the dataset.
8
Number of instances with at least one value missing.
10
Number of numeric attributes.
0
Number of nominal attributes.
0.11
Number of attributes divided by the number of instances.
43.48
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.
3.9
Percentage of instances having missing values.
Average class difference between consecutive instances.
0.21
Percentage of missing values.

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