Data
Traffic_violations

Traffic_violations

active ARFF Public Domain (CC0) Visibility: public Uploaded 13-09-2019 by Guillaume Lemaitre
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This dataset contains traffic violation information from all electronic traffic violations issued in the County. Any information that can be used to uniquely identify the vehicle, the vehicle owner or the officer issuing the violation will not be published.

43 features

violation_type (target)nominal4 unique values
0 missing
seqidstring895102 unique values
0 missing
date_of_stopstring2810 unique values
0 missing
time_of_stopstring1440 unique values
0 missing
agencystring1 unique values
0 missing
subagencystring9 unique values
0 missing
descriptionstring14267 unique values
9 missing
locationstring214968 unique values
2 missing
latitudenumeric302145 unique values
0 missing
longitudenumeric343293 unique values
0 missing
accidentstring2 unique values
0 missing
beltsstring2 unique values
0 missing
personal_injurystring2 unique values
0 missing
property_damagestring2 unique values
0 missing
fatalstring2 unique values
0 missing
commercial_licensestring2 unique values
0 missing
hazmatstring2 unique values
0 missing
commercial_vehiclestring2 unique values
0 missing
alcoholstring2 unique values
0 missing
work_zonestring2 unique values
0 missing
search_conductedstring2 unique values
600828 missing
search_dispositionstring5 unique values
1509055 missing
search_outcomestring5 unique values
619994 missing
search_reasonstring9 unique values
1509055 missing
search_reason_for_stopstring751 unique values
600998 missing
search_typestring4 unique values
1509063 missing
search_arrest_reasonstring9 unique values
1531303 missing
statestring70 unique values
59 missing
vehicletypenominal33 unique values
0 missing
yearnumeric354 unique values
9647 missing
makestring3984 unique values
9762 missing
modelstring19462 unique values
9909 missing
colorstring26 unique values
18657 missing
chargestring1086 unique values
0 missing
articlestring4 unique values
76873 missing
contributed_to_accidentnominal2 unique values
0 missing
racenominal6 unique values
0 missing
genderstring3 unique values
0 missing
driver_citystring8087 unique values
387 missing
driver_statestring68 unique values
11 missing
dl_statestring70 unique values
929 missing
arrest_typenominal19 unique values
0 missing
geolocationstring774176 unique values
0 missing

62 properties

1578154
Number of instances (rows) of the dataset.
43
Number of attributes (columns) of the dataset.
4
Number of distinct values of the target attribute (if it is nominal).
8006541
Number of missing values in the dataset.
1532400
Number of instances with at least one value missing.
3
Number of numeric attributes.
5
Number of nominal attributes.
789812
Number of instances belonging to the most frequent class.
0.16
Minimal entropy among attributes.
3.3
Second quartile (Median) of skewness among attributes of the numeric type.
2.02
Maximum entropy among attributes.
8.9
Minimum kurtosis among attributes of the numeric type.
2.33
Percentage of binary attributes.
19.98
Second quartile (Median) of standard deviation of attributes of the numeric type.
4077.72
Maximum kurtosis among attributes of the numeric type.
-71.53
Minimum of means among attributes of the numeric type.
97.1
Percentage of instances having missing values.
1.78
Third quartile of entropy among attributes.
2006.01
Maximum of means among attributes of the numeric type.
0
Minimal mutual information between the nominal attributes and the target attribute.
11.8
Percentage of missing values.
4077.72
Third quartile of kurtosis among attributes of the numeric type.
0.02
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
6.98
Percentage of numeric attributes.
2006.01
Third quartile of means among attributes of the numeric type.
33
The maximum number of distinct values among attributes of the nominal type.
-3.3
Minimum skewness among attributes of the numeric type.
11.63
Percentage of nominal attributes.
0.02
Third quartile of mutual information between the nominal attributes and the target attribute.
38.39
Maximum skewness among attributes of the numeric type.
10.12
Minimum standard deviation of attributes of the numeric type.
0.33
First quartile of entropy among attributes.
38.39
Third quartile of skewness among attributes of the numeric type.
86.34
Maximum standard deviation of attributes of the numeric type.
0.06
Percentage of instances belonging to the least frequent class.
8.9
First quartile of kurtosis among attributes of the numeric type.
86.34
Third quartile of standard deviation of attributes of the numeric type.
1.02
Average entropy of the attributes.
899
Number of instances belonging to the least frequent class.
-71.53
First quartile of means among attributes of the numeric type.
13.1
Standard deviation of the number of distinct values among attributes of the nominal type.
1365.17
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
0
First quartile of mutual information between the nominal attributes and the target attribute.
656.91
Mean of means among attributes of the numeric type.
-3.3
First quartile of skewness among attributes of the numeric type.
0.62
Average class difference between consecutive instances.
0.01
Average mutual information between the nominal attributes and the target attribute.
10.12
First quartile of standard deviation of attributes of the numeric type.
1.23
Entropy of the target attribute values.
95.53
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
0.94
Second quartile (Median) of entropy among attributes.
0
Number of attributes divided by the number of instances.
12.8
Average number of distinct values among the attributes of the nominal type.
8.9
Second quartile (Median) of kurtosis among attributes of the numeric type.
117.15
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
12.8
Mean skewness among attributes of the numeric type.
36.25
Second quartile (Median) of means among attributes of the numeric type.
50.05
Percentage of instances belonging to the most frequent class.
38.81
Mean standard deviation of attributes of the numeric type.
0.01
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.

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