DEVELOPMENT... OpenML
Data
Highway-Rail-Grade-Cross-Accidents-1975---2016-USA

Highway-Rail-Grade-Cross-Accidents-1975---2016-USA

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Stewart
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Context Interesting data about accidents with cars on railroad crossing. Content This data covering the period from 1975 to 2016. It has a lot of info about every single accident like time, date, coordinates, victims, railroad owner, city, state and etc. 229 665 records. Acknowledgements Department of Transportation of the USA made this dataset, Inspiration It's interesting to discover the answers with ML methods. Also heatmaps, plots.

24 features

Rail_Equipment_Typestring14 unique values
501 missing
GeoLocationstring84253 unique values
0 missing
Longitudenumeric83302 unique values
21667 missing
Latitudenumeric83158 unique values
21664 missing
State_Namestring52 unique values
0 missing
Citystring17645 unique values
39482 missing
nonsuicideinjurynumeric43 unique values
0 missing
nonsuicidefatalitynumeric13 unique values
0 missing
idnumeric229665 unique values
0 missing
Display_Timestring1460 unique values
0 missing
Releasing_Hazmatstring7 unique values
0 missing
Carrying_Hazmatstring5 unique values
0 missing
Reporting_Railroadstring980 unique values
0 missing
Highway_User_Typestring11 unique values
2 missing
DisplayDatestring15188 unique values
0 missing
Highwaystring101595 unique values
2472 missing
Countystring2303 unique values
278 missing
CrossingIDstring96085 unique values
0 missing
Fiscal_Yearnumeric42 unique values
0 missing
Calendar_Yearnumeric42 unique values
0 missing
Highway_User_Speednumeric83 unique values
26548 missing
Track_Owner_Codestring1766 unique values
19262 missing
Track_Ownerstring1766 unique values
19262 missing
Reporting_Railroad_Codestring980 unique values
0 missing

19 properties

229665
Number of instances (rows) of the dataset.
24
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
151138
Number of missing values in the dataset.
89278
Number of instances with at least one value missing.
8
Number of numeric attributes.
0
Number of nominal attributes.
0
Percentage of nominal attributes.
Average class difference between consecutive instances.
33.33
Percentage of numeric attributes.
2.74
Percentage of missing values.
38.87
Percentage of instances having missing values.
0
Percentage of binary attributes.
0
Number of binary attributes.
Number of instances belonging to the least frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the most frequent class.
0
Number of attributes divided by the number of instances.

0 tasks

Define a new task