## 'data.frame': 182349 obs. of 15 variables:
## $ Device.Name : Factor w/ 25 levels "Retired","YMu1502f?",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ Device.ID : int 39273 39273 39273 39273 39273 39273 39273 39273 39273 39273 ...
## $ Date...Time..GMT. : num 42257 42257 42257 42257 42257 ...
## $ Date...Time..Local.: num 42256 42257 42257 42257 42257 ...
## $ time.gmt : POSIXct, format: "2015-09-09 19:58:00" "2015-09-09 20:00:00" ...
## $ time.local : POSIXct, format: "2015-09-09 11:58:00" "2015-09-09 12:00:00" ...
## $ Latitude : num 64.1 64.1 64.1 64.1 64.1 ...
## $ Longitude : num -139 -139 -139 -139 -139 ...
## $ Altitude : num 321 320 357 343 351 ...
## $ Fix.Status : Factor w/ 13 levels "0","1_SV KF",..: 8 8 8 8 8 8 8 8 8 8 ...
## $ DOP : num 3.2 3.2 1.8 3.8 2.2 3.4 2 3.2 2 1.8 ...
## $ Temp..C. : num 16 16 14 19 17 20 17 16 13 10 ...
## $ Main..V. : num 3.36 3.36 3.36 3.44 3.44 3.44 3.44 3.44 3.44 3.44 ...
## $ Back..V. : num 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 3.52 ...
## $ id : Factor w/ 25 levels "Retired","YMu1502f?",..: 1 1 1 1 1 1 1 1 1 1 ...
Outlier problems! Mainly with YMu1827 & YMu1825.
There are still some odd/wrong data:
We’ll keep only those within a constrained range: longitude [-150, -135], Latitude [67.5,73]. Also, we trim off YMu1825 to more recent locations.
id | n.loc | start | end | duration | dT.median |
---|---|---|---|---|---|
Retired | 4885 | 2015-09-21 | 2016-10-22 | 397 days | 1 hours |
YMu1502f? | 10224 | 2015-09-21 | 2018-03-14 | 906 days | 1 hours |
YMu1503mRI | 10670 | 2015-09-21 | 2018-05-08 | 959 days | 1 hours |
YMu1504 | 13784 | 2015-09-21 | 2018-09-17 | 1091 days | 1 hours |
YMu1505 | 13781 | 2015-09-21 | 2018-09-17 | 1091 days | 1 hours |
YMu1506 | 13780 | 2015-09-22 | 2018-09-17 | 1091 days | 1 hours |
YMu1508 | 6022 | 2015-09-22 | 2018-09-16 | 1090 days | 1 hours |
YMu1508rRD | 10287 | 2015-09-22 | 2018-03-28 | 919 days | 1 hours |
YMu150711f | 3624 | 2016-09-17 | 2017-08-08 | 325 days | 1 hours |
YMu1609mRI | 5934 | 2016-09-17 | 2018-04-10 | 570 days | 1 hours |
YMu1610 | 9366 | 2016-09-17 | 2018-09-17 | 729 days | 1 hours |
YMu1615 | 9320 | 2016-09-17 | 2018-09-17 | 730 days | 1 hours |
YMu1827 | 8322 | 2016-09-18 | 2018-09-17 | 730 days | 1 hours |
YMu1613 | 9321 | 2016-09-19 | 2018-09-17 | 728 days | 1 hours |
YMu1614 | 9317 | 2016-09-19 | 2018-09-17 | 727 days | 1 hours |
YMu1817 | 4179 | 2018-03-27 | 2018-09-17 | 174 days | 1 hours |
YMu1818 | 4178 | 2018-03-27 | 2018-09-17 | 174 days | 1 hours |
YMu1819 | 4151 | 2018-03-27 | 2018-09-16 | 173 days | 1 hours |
YMu1820 | 4149 | 2018-03-27 | 2018-09-16 | 173 days | 1 hours |
YMu1816 | 4111 | 2018-03-28 | 2018-09-17 | 173 days | 1 hours |
YMu1821 | 4147 | 2018-03-28 | 2018-09-16 | 173 days | 1 hours |
YMu1822 | 4165 | 2018-03-28 | 2018-09-17 | 174 days | 1 hours |
YMu1823 | 4074 | 2018-03-28 | 2018-09-14 | 170 days | 1 hours |
YMu1824 | 4144 | 2018-03-28 | 2018-09-17 | 173 days | 1 hours |
YMu1825 | 3867 | 2018-03-28 | 2018-09-17 | 172 days | 1 hours |
Total number of locations: 179802 for 25 animals. Date range 2015-09-21, 2018-09-17. Still plenty to analyze!
There are helpful - on an individual basis - for seeing any seasonal patterns. (Apologies for the obnoxious 80’s colors!)