Data
Radar-Traffic-Data

Radar-Traffic-Data

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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Context Traffic data collected from the several Wavetronix radar sensors deployed by the City of Austin. Dataset is augmented with geo coordinates from sensor location dataset. Source: https://data.austintexas.gov/ 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 Data Source: https://data.austintexas.gov/ Photo by Jeremy Banks on Unsplash Inspiration Your data will be in front of the world's largest data science community. What questions do you want to see answered?

12 features

location_namestring23 unique values
0 missing
location_latitudenumeric18 unique values
0 missing
location_longitudenumeric18 unique values
0 missing
Yearnumeric3 unique values
0 missing
Monthnumeric12 unique values
0 missing
Daynumeric31 unique values
0 missing
Day_of_Weeknumeric7 unique values
0 missing
Hournumeric24 unique values
0 missing
Minutenumeric60 unique values
0 missing
Time_Binstring96 unique values
0 missing
Directionstring5 unique values
0 missing
Volumenumeric256 unique values
0 missing

19 properties

4603861
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
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.
9
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
75
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.
Average class difference between consecutive instances.
0
Percentage of missing values.

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