Table 4 Statistical features of the dataset a
From: Enhancing correlated big data privacy using differential privacy and machine learning
Features \(\rightarrow\) | Count | Mean | SD | Min | Max |
|---|---|---|---|---|---|
Attributes \(\downarrow\) | |||||
VendorID | 9999 | 1.8638863 | 0.34292631 | 1.0 | 9998.0 |
RateCodeID | 9999 | 1.0482048 | 0.4243966 | 1.0 | 5.0 |
Pickup longitude | 9999 | − 73.899834 | 1.65348802 | − 74.073845 | 0.0 |
Pickup latitude | 9999 | 40.7194723 | 0.91256991 | 0.0 | 40.92078 |
DropOff longitude | 9999 | − 73.8976524 | 1.653648802 | − 74.07387 | 0.0 |
DroffOff latitude | 9999 | 40.72007131 | 0.91274002 | 0.0 | 41.178898 |
Passenger count | 9999 | 1.4497449 | 1.1375009 | 0.0 | 6.0 |
Trip distance | 9999 | 3.05243424 | 2.83776974 | 0.0 | 61.7 |
Fare amount | 9999 | 12.485061506 | 8.74345086 | 70.0 | 222.5 |
Extra | 9999 | 0.49219921 | 0.07028614 | − 0.5 | 0.5 |
MTA tax | 9999 | 1.1725532 | 2.09252519 | 0.0 | 33.37 |
Tip amount | 9999 | 1.17255325 | 2.09252194 | 0.0 | 58.0 |
Toll amount | 9999 | 0.0592209 | 0.5719925 | 0.0 | 41.178898 |
Improvement surcharge | 9999 | 0.2957995 | 0.03912370 | 1.0 | 5.0 |
Total amount | 9999 | 14.99873372 | 9.860037110 | 1.0 | 229.34 |
Payment type | 9999 | 1.58855885 | 0.51321125 | 1.0 | 5.0 |
Trip type | 9999 | 1.010601 | 0.1024193 | 1.0 | 2.0 |