Using the ts_id codes and by providing a given date period, download the corresponding time series from the waterinfo.be website

get_timeseries_tsid(ts_id, period = NULL, from = NULL, to = NULL,
  datasource = 1, token = NULL)

Arguments

ts_id

waterinfo.be database ts_id, defining a timeserie variable and frequency it is defined.

period

input string according to format required by waterinfo: De period string is provided as P#Y#M#DT#H#M#S, with P defines `Period`, each # is an integer value and the codes define the number of... Y - years M - months D - days T required if information about sub-day resolution is present H - hours D - days M - minutes S - seconds Instead of D (days), the usage of W - weeks is possible as well Examples of valid period strings: P3D, P1Y, P1DT12H, PT6H, P1Y6M3DT4H20M30S.

from

date of datestring as start of the time series

to

date of datestring as end of the time series

datasource

int [0-4] defines the `meetnet` of which the measurement station is part of. VMM based stations are net '1', MOW-HIC is net '2'

token

token to use with the call (optional, can be retrieved via get_token)

Format

A data.frame with 3 variables:

Timestamp

Datetime of the measurement.

Value

Measured value.

Quality Code

Quality code of the measurement, dependent on the data source used:

  • VMM Quality Code Interpretation (datasource 1)

    • 10/110 - Excellent

    • 30/100/130 - Good

    • 50/150 - Moderate

    • 70/170 - Poor

    • 80/180 - Estimated

    • 90/190 - Suspect

    • 220 - Default

    • -1 - Missing

  • HIC Quality Code Interpretation (datasource 2)

    • 40 - Good

    • 80 - Estimated

    • 120 - Suspect

    • 200 - Unchecked

    • 60 - Complete

    • 160 - Incomplete

    • -1 - Missing

  • Aggregated timeseries

    • 40 - Good

    • 100 - Estimated

    • 120 - Suspect

    • 200 - Unchecked

    • -1 - Missing

The URL of the specific request is provided as a comment attribute to the returned data.frame. Use comment(df) to get the request URL.

Value

data.frame with the timestamps, values and quality code

Examples

get_timeseries_tsid("35055042", from = "2017-01-01", to = "2017-01-02")
#> Timestamp Value Quality Code #> 1 2016-12-31 23:00:00 0.00 130 #> 2 2016-12-31 23:15:00 0.00 130 #> 3 2016-12-31 23:30:00 0.00 130 #> 4 2016-12-31 23:45:00 0.00 130 #> 5 2017-01-01 00:00:00 0.00 130 #> 6 2017-01-01 00:15:00 0.00 130 #> 7 2017-01-01 00:30:00 0.00 130 #> 8 2017-01-01 00:45:00 0.00 130 #> 9 2017-01-01 01:00:00 0.00 130 #> 10 2017-01-01 01:15:00 0.00 130 #> 11 2017-01-01 01:30:00 0.00 130 #> 12 2017-01-01 01:45:00 0.00 130 #> 13 2017-01-01 02:00:00 0.00 130 #> 14 2017-01-01 02:15:00 0.00 130 #> 15 2017-01-01 02:30:00 0.00 130 #> 16 2017-01-01 02:45:00 0.00 130 #> 17 2017-01-01 03:00:00 0.00 130 #> 18 2017-01-01 03:15:00 0.00 130 #> 19 2017-01-01 03:30:00 0.00 130 #> 20 2017-01-01 03:45:00 0.00 130 #> 21 2017-01-01 04:00:00 0.00 130 #> 22 2017-01-01 04:15:00 0.00 130 #> 23 2017-01-01 04:30:00 0.00 130 #> 24 2017-01-01 04:45:00 0.00 130 #> 25 2017-01-01 05:00:00 0.00 130 #> 26 2017-01-01 05:15:00 0.00 130 #> 27 2017-01-01 05:30:00 0.00 130 #> 28 2017-01-01 05:45:00 0.00 130 #> 29 2017-01-01 06:00:00 0.00 130 #> 30 2017-01-01 06:15:00 0.00 130 #> 31 2017-01-01 06:30:00 0.00 130 #> 32 2017-01-01 06:45:00 0.00 130 #> 33 2017-01-01 07:00:00 0.00 130 #> 34 2017-01-01 07:15:00 0.00 130 #> 35 2017-01-01 07:30:00 0.00 130 #> 36 2017-01-01 07:45:00 0.00 130 #> 37 2017-01-01 08:00:00 0.00 130 #> 38 2017-01-01 08:15:00 0.00 130 #> 39 2017-01-01 08:30:00 0.00 130 #> 40 2017-01-01 08:45:00 0.00 130 #> 41 2017-01-01 09:00:00 0.00 130 #> 42 2017-01-01 09:15:00 0.00 130 #> 43 2017-01-01 09:30:00 0.00 130 #> 44 2017-01-01 09:45:00 0.00 130 #> 45 2017-01-01 10:00:00 0.00 130 #> 46 2017-01-01 10:15:00 0.00 130 #> 47 2017-01-01 10:30:00 0.00 130 #> 48 2017-01-01 10:45:00 0.00 130 #> 49 2017-01-01 11:00:00 0.00 130 #> 50 2017-01-01 11:15:00 0.00 130 #> 51 2017-01-01 11:30:00 0.00 130 #> 52 2017-01-01 11:45:00 0.00 130 #> 53 2017-01-01 12:00:00 0.00 130 #> 54 2017-01-01 12:15:00 0.00 130 #> 55 2017-01-01 12:30:00 0.00 130 #> 56 2017-01-01 12:45:00 0.00 130 #> 57 2017-01-01 13:00:00 0.00 130 #> 58 2017-01-01 13:15:00 0.00 130 #> 59 2017-01-01 13:30:00 0.00 130 #> 60 2017-01-01 13:45:00 0.00 130 #> 61 2017-01-01 14:00:00 0.00 130 #> 62 2017-01-01 14:15:00 0.00 130 #> 63 2017-01-01 14:30:00 0.00 130 #> 64 2017-01-01 14:45:00 0.00 130 #> 65 2017-01-01 15:00:00 0.00 130 #> 66 2017-01-01 15:15:00 0.00 130 #> 67 2017-01-01 15:30:00 0.00 130 #> 68 2017-01-01 15:45:00 0.00 130 #> 69 2017-01-01 16:00:00 0.00 130 #> 70 2017-01-01 16:15:00 0.00 130 #> 71 2017-01-01 16:30:00 0.00 130 #> 72 2017-01-01 16:45:00 0.00 130 #> 73 2017-01-01 17:00:00 0.00 130 #> 74 2017-01-01 17:15:00 0.00 130 #> 75 2017-01-01 17:30:00 0.00 130 #> 76 2017-01-01 17:45:00 0.03 130 #> 77 2017-01-01 18:00:00 0.00 130 #> 78 2017-01-01 18:15:00 0.04 130 #> 79 2017-01-01 18:30:00 0.00 130 #> 80 2017-01-01 18:45:00 0.03 130 #> 81 2017-01-01 19:00:00 0.00 130 #> 82 2017-01-01 19:15:00 0.03 130 #> 83 2017-01-01 19:30:00 0.03 130 #> 84 2017-01-01 19:45:00 0.00 130 #> 85 2017-01-01 20:00:00 0.03 130 #> 86 2017-01-01 20:15:00 0.00 130 #> 87 2017-01-01 20:30:00 0.00 130 #> 88 2017-01-01 20:45:00 0.00 130 #> 89 2017-01-01 21:00:00 0.00 130 #> 90 2017-01-01 21:15:00 0.03 130 #> 91 2017-01-01 21:30:00 0.00 130 #> 92 2017-01-01 21:45:00 0.00 130 #> 93 2017-01-01 22:00:00 0.00 130 #> 94 2017-01-01 22:15:00 0.11 130 #> 95 2017-01-01 22:30:00 0.82 130 #> 96 2017-01-01 22:45:00 0.69 130 #> 97 2017-01-01 23:00:00 0.34 130
get_timeseries_tsid("5156042", period = "P3D")
#> Timestamp Value Quality Code #> 1 2020-11-09 18:00:00 17.798 110 #> 2 2020-11-09 18:15:00 17.798 110 #> 3 2020-11-09 18:30:00 17.798 110 #> 4 2020-11-09 18:45:00 17.798 110 #> 5 2020-11-09 19:00:00 17.798 110 #> 6 2020-11-09 19:15:00 17.798 110 #> 7 2020-11-09 19:30:00 17.798 110 #> 8 2020-11-09 19:45:00 17.798 110 #> 9 2020-11-09 20:00:00 17.798 110 #> 10 2020-11-09 20:15:00 17.798 110 #> 11 2020-11-09 20:30:00 17.798 110 #> 12 2020-11-09 20:45:00 17.798 110 #> 13 2020-11-09 21:00:00 17.799 110 #> 14 2020-11-09 21:15:00 17.799 110 #> 15 2020-11-09 21:30:00 17.798 110 #> 16 2020-11-09 21:45:00 17.798 110 #> 17 2020-11-09 22:00:00 17.799 110 #> 18 2020-11-09 22:15:00 17.798 110 #> 19 2020-11-09 22:30:00 17.798 110 #> 20 2020-11-09 22:45:00 17.799 110 #> 21 2020-11-09 23:00:00 17.798 110 #> 22 2020-11-09 23:15:00 17.798 110 #> 23 2020-11-09 23:30:00 17.798 110 #> 24 2020-11-09 23:45:00 17.798 110 #> 25 2020-11-10 00:00:00 17.798 110 #> 26 2020-11-10 00:15:00 17.798 110 #> 27 2020-11-10 00:30:00 17.798 110 #> 28 2020-11-10 00:45:00 17.798 110 #> 29 2020-11-10 01:00:00 17.798 110 #> 30 2020-11-10 01:15:00 17.799 110 #> 31 2020-11-10 01:30:00 17.799 110 #> 32 2020-11-10 01:45:00 17.799 110 #> 33 2020-11-10 02:00:00 17.799 110 #> 34 2020-11-10 02:15:00 17.799 110 #> 35 2020-11-10 02:30:00 17.799 110 #> 36 2020-11-10 02:45:00 17.799 110 #> 37 2020-11-10 03:00:00 17.799 110 #> 38 2020-11-10 03:15:00 17.799 110 #> 39 2020-11-10 03:30:00 17.799 110 #> 40 2020-11-10 03:45:00 17.799 110 #> 41 2020-11-10 04:00:00 17.799 110 #> 42 2020-11-10 04:15:00 17.799 110 #> 43 2020-11-10 04:30:00 17.799 110 #> 44 2020-11-10 04:45:00 17.799 110 #> 45 2020-11-10 05:00:00 17.800 110 #> 46 2020-11-10 05:15:00 17.800 110 #> 47 2020-11-10 05:30:00 17.799 110 #> 48 2020-11-10 05:45:00 17.799 110 #> 49 2020-11-10 06:00:00 17.799 110 #> 50 2020-11-10 06:15:00 17.799 110 #> 51 2020-11-10 06:30:00 17.799 110 #> 52 2020-11-10 06:45:00 17.799 110 #> 53 2020-11-10 07:00:00 17.799 110 #> 54 2020-11-10 07:15:00 17.799 110 #> 55 2020-11-10 07:30:00 17.799 110 #> 56 2020-11-10 07:45:00 17.799 110 #> 57 2020-11-10 08:00:00 17.799 110 #> 58 2020-11-10 08:15:00 17.799 110 #> 59 2020-11-10 08:30:00 17.798 110 #> 60 2020-11-10 08:45:00 17.798 110 #> 61 2020-11-10 09:00:00 17.798 110 #> 62 2020-11-10 09:15:00 17.798 110 #> 63 2020-11-10 09:30:00 17.797 110 #> 64 2020-11-10 09:45:00 17.796 110 #> 65 2020-11-10 10:00:00 17.796 110 #> 66 2020-11-10 10:15:00 17.796 110 #> 67 2020-11-10 10:30:00 17.796 110 #> 68 2020-11-10 10:45:00 17.795 110 #> 69 2020-11-10 11:00:00 17.795 110 #> 70 2020-11-10 11:15:00 17.795 110 #> 71 2020-11-10 11:30:00 17.795 110 #> 72 2020-11-10 11:45:00 17.795 110 #> 73 2020-11-10 12:00:00 17.795 110 #> 74 2020-11-10 12:15:00 17.794 110 #> 75 2020-11-10 12:30:00 17.794 110 #> 76 2020-11-10 12:45:00 17.794 110 #> 77 2020-11-10 13:00:00 17.794 110 #> 78 2020-11-10 13:15:00 17.794 110 #> 79 2020-11-10 13:30:00 17.794 110 #> 80 2020-11-10 13:45:00 17.794 110 #> 81 2020-11-10 14:00:00 17.794 110 #> 82 2020-11-10 14:15:00 17.794 110 #> 83 2020-11-10 14:30:00 17.794 110 #> 84 2020-11-10 14:45:00 17.794 110 #> 85 2020-11-10 15:00:00 17.795 110 #> 86 2020-11-10 15:15:00 17.796 110 #> 87 2020-11-10 15:30:00 17.796 110 #> 88 2020-11-10 15:45:00 17.796 110 #> 89 2020-11-10 16:00:00 17.797 110 #> 90 2020-11-10 16:15:00 17.797 110 #> 91 2020-11-10 16:30:00 17.798 110 #> 92 2020-11-10 16:45:00 17.798 110 #> 93 2020-11-10 17:00:00 17.798 110 #> 94 2020-11-10 17:15:00 17.798 110 #> 95 2020-11-10 17:30:00 17.799 110 #> 96 2020-11-10 17:45:00 17.799 110 #> 97 2020-11-10 18:00:00 17.799 110 #> 98 2020-11-10 18:15:00 17.799 110 #> 99 2020-11-10 18:30:00 17.798 110 #> 100 2020-11-10 18:45:00 17.798 110 #> 101 2020-11-10 19:00:00 17.798 110 #> 102 2020-11-10 19:15:00 17.797 110 #> 103 2020-11-10 19:30:00 17.797 110 #> 104 2020-11-10 19:45:00 17.797 110 #> 105 2020-11-10 20:00:00 17.796 110 #> 106 2020-11-10 20:15:00 17.795 110 #> 107 2020-11-10 20:30:00 17.795 110 #> 108 2020-11-10 20:45:00 17.794 110 #> 109 2020-11-10 21:00:00 17.794 110 #> 110 2020-11-10 21:15:00 17.794 110 #> 111 2020-11-10 21:30:00 17.793 110 #> 112 2020-11-10 21:45:00 17.793 110 #> 113 2020-11-10 22:00:00 17.792 110 #> 114 2020-11-10 22:15:00 17.792 110 #> 115 2020-11-10 22:30:00 17.792 110 #> 116 2020-11-10 22:45:00 17.792 110 #> 117 2020-11-10 23:00:00 17.791 110 #> 118 2020-11-10 23:15:00 17.791 110 #> 119 2020-11-10 23:30:00 17.791 110 #> 120 2020-11-10 23:45:00 17.790 110 #> 121 2020-11-11 00:00:00 17.790 110 #> 122 2020-11-11 00:15:00 17.790 110 #> 123 2020-11-11 00:30:00 17.790 110 #> 124 2020-11-11 00:45:00 17.789 110 #> 125 2020-11-11 01:00:00 17.789 110 #> 126 2020-11-11 01:15:00 17.789 110 #> 127 2020-11-11 01:30:00 17.789 110 #> 128 2020-11-11 01:45:00 17.789 110 #> 129 2020-11-11 02:00:00 17.789 110 #> 130 2020-11-11 02:15:00 17.790 110 #> 131 2020-11-11 02:30:00 17.789 110 #> 132 2020-11-11 02:45:00 17.789 110 #> 133 2020-11-11 03:00:00 17.790 110 #> 134 2020-11-11 03:15:00 17.790 110 #> 135 2020-11-11 03:30:00 17.790 110 #> 136 2020-11-11 03:45:00 17.790 110 #> 137 2020-11-11 04:00:00 17.790 110 #> 138 2020-11-11 04:15:00 17.790 110 #> 139 2020-11-11 04:30:00 17.790 110 #> 140 2020-11-11 04:45:00 17.790 110 #> 141 2020-11-11 05:00:00 17.790 110 #> 142 2020-11-11 05:15:00 17.790 110 #> 143 2020-11-11 05:30:00 17.790 110 #> 144 2020-11-11 05:45:00 17.790 110 #> 145 2020-11-11 06:00:00 17.790 110 #> 146 2020-11-11 06:15:00 17.789 110 #> 147 2020-11-11 06:30:00 17.789 110 #> 148 2020-11-11 06:45:00 17.789 110 #> 149 2020-11-11 07:00:00 17.789 110 #> 150 2020-11-11 07:15:00 17.789 110 #> 151 2020-11-11 07:30:00 17.789 110 #> 152 2020-11-11 07:45:00 17.789 110 #> 153 2020-11-11 08:00:00 17.789 110 #> 154 2020-11-11 08:15:00 17.789 110 #> 155 2020-11-11 08:30:00 17.789 110 #> 156 2020-11-11 08:45:00 17.789 110 #> 157 2020-11-11 09:00:00 17.788 110 #> 158 2020-11-11 09:15:00 17.788 110 #> 159 2020-11-11 09:30:00 17.787 110 #> 160 2020-11-11 09:45:00 17.787 110 #> 161 2020-11-11 10:00:00 17.786 110 #> 162 2020-11-11 10:15:00 17.786 110 #> 163 2020-11-11 10:30:00 17.785 110 #> 164 2020-11-11 10:45:00 17.785 110 #> 165 2020-11-11 11:00:00 17.784 110 #> 166 2020-11-11 11:15:00 17.784 110 #> 167 2020-11-11 11:30:00 17.783 110 #> 168 2020-11-11 11:45:00 17.783 110 #> 169 2020-11-11 12:00:00 17.783 110 #> 170 2020-11-11 12:15:00 17.783 110 #> 171 2020-11-11 12:30:00 17.783 110 #> 172 2020-11-11 12:45:00 17.783 110 #> 173 2020-11-11 13:00:00 17.783 110 #> 174 2020-11-11 13:15:00 17.783 110 #> 175 2020-11-11 13:30:00 17.783 110 #> 176 2020-11-11 13:45:00 17.782 110 #> 177 2020-11-11 14:00:00 17.782 110 #> 178 2020-11-11 14:15:00 17.782 110 #> 179 2020-11-11 14:30:00 17.782 110 #> 180 2020-11-11 14:45:00 17.782 110 #> 181 2020-11-11 15:00:00 17.782 110 #> 182 2020-11-11 15:15:00 17.783 110 #> 183 2020-11-11 15:30:00 17.783 110 #> 184 2020-11-11 15:45:00 17.783 110 #> 185 2020-11-11 16:00:00 17.782 110 #> 186 2020-11-11 16:15:00 17.783 110 #> 187 2020-11-11 16:30:00 17.783 110 #> 188 2020-11-11 16:45:00 17.783 110 #> 189 2020-11-11 17:00:00 17.783 110 #> 190 2020-11-11 17:15:00 17.783 110 #> 191 2020-11-11 17:30:00 17.783 110 #> 192 2020-11-11 17:45:00 17.783 110 #> 193 2020-11-11 18:00:00 17.783 110 #> 194 2020-11-11 18:15:00 17.783 110 #> 195 2020-11-11 18:30:00 17.782 110 #> 196 2020-11-11 18:45:00 17.782 110 #> 197 2020-11-11 19:00:00 17.782 110 #> 198 2020-11-11 19:15:00 17.782 110 #> 199 2020-11-11 19:30:00 17.781 110 #> 200 2020-11-11 19:45:00 17.781 110 #> 201 2020-11-11 20:00:00 17.780 110 #> 202 2020-11-11 20:15:00 17.780 110 #> 203 2020-11-11 20:30:00 17.780 110 #> 204 2020-11-11 20:45:00 17.780 110 #> 205 2020-11-11 21:00:00 17.780 110 #> 206 2020-11-11 21:15:00 17.780 110 #> 207 2020-11-11 21:30:00 17.780 110 #> 208 2020-11-11 21:45:00 17.780 110 #> 209 2020-11-11 22:00:00 17.780 110 #> 210 2020-11-11 22:15:00 17.781 110 #> 211 2020-11-11 22:30:00 17.781 110 #> 212 2020-11-11 22:45:00 17.781 110 #> 213 2020-11-11 23:00:00 17.781 110 #> 214 2020-11-11 23:15:00 17.781 110 #> 215 2020-11-11 23:30:00 17.781 110 #> 216 2020-11-11 23:45:00 17.782 110 #> 217 2020-11-12 00:00:00 17.782 110 #> 218 2020-11-12 00:15:00 17.782 110 #> 219 2020-11-12 00:30:00 17.782 110 #> 220 2020-11-12 00:45:00 17.782 110 #> 221 2020-11-12 01:00:00 17.782 110 #> 222 2020-11-12 01:15:00 17.782 110 #> 223 2020-11-12 01:30:00 17.782 110 #> 224 2020-11-12 01:45:00 17.782 110 #> 225 2020-11-12 02:00:00 17.782 110 #> 226 2020-11-12 02:15:00 17.782 110 #> 227 2020-11-12 02:30:00 17.782 110 #> 228 2020-11-12 02:45:00 17.782 110 #> 229 2020-11-12 03:00:00 17.782 110 #> 230 2020-11-12 03:15:00 17.782 110 #> 231 2020-11-12 03:30:00 17.782 110 #> 232 2020-11-12 03:45:00 17.782 110 #> 233 2020-11-12 04:00:00 17.783 110 #> 234 2020-11-12 04:15:00 17.783 110 #> 235 2020-11-12 04:30:00 17.783 110 #> 236 2020-11-12 04:45:00 17.783 110 #> 237 2020-11-12 05:00:00 17.783 110 #> 238 2020-11-12 05:15:00 17.783 110 #> 239 2020-11-12 05:30:00 17.784 110 #> 240 2020-11-12 05:45:00 17.784 110 #> 241 2020-11-12 06:00:00 17.784 110 #> 242 2020-11-12 06:15:00 17.784 110 #> 243 2020-11-12 06:30:00 17.784 110 #> 244 2020-11-12 06:45:00 17.785 110 #> 245 2020-11-12 07:00:00 17.786 110 #> 246 2020-11-12 07:15:00 17.786 110 #> 247 2020-11-12 07:30:00 17.786 110 #> 248 2020-11-12 07:45:00 17.786 110 #> 249 2020-11-12 08:00:00 17.786 110 #> 250 2020-11-12 08:15:00 17.786 110 #> 251 2020-11-12 08:30:00 17.786 110 #> 252 2020-11-12 08:45:00 17.785 110 #> 253 2020-11-12 09:00:00 17.784 110 #> 254 2020-11-12 09:15:00 17.784 110 #> 255 2020-11-12 09:30:00 17.783 110 #> 256 2020-11-12 09:45:00 17.782 110 #> 257 2020-11-12 10:00:00 17.781 110 #> 258 2020-11-12 10:15:00 17.782 110 #> 259 2020-11-12 10:30:00 17.781 110 #> 260 2020-11-12 10:45:00 17.781 110 #> 261 2020-11-12 11:00:00 17.782 110 #> 262 2020-11-12 11:15:00 17.782 110 #> 263 2020-11-12 11:30:00 17.781 110 #> 264 2020-11-12 11:45:00 17.782 110 #> 265 2020-11-12 12:00:00 17.782 110 #> 266 2020-11-12 12:15:00 17.781 110 #> 267 2020-11-12 12:30:00 17.781 110 #> 268 2020-11-12 12:45:00 17.782 110 #> 269 2020-11-12 13:00:00 17.782 110 #> 270 2020-11-12 13:15:00 17.782 110 #> 271 2020-11-12 13:30:00 17.782 110 #> 272 2020-11-12 13:45:00 17.782 110 #> 273 2020-11-12 14:00:00 17.782 110 #> 274 2020-11-12 14:15:00 17.782 110 #> 275 2020-11-12 14:30:00 17.782 110 #> 276 2020-11-12 14:45:00 17.782 110 #> 277 2020-11-12 15:00:00 17.782 110 #> 278 2020-11-12 15:15:00 17.782 110 #> 279 2020-11-12 15:30:00 17.782 110 #> 280 2020-11-12 15:45:00 17.781 110 #> 281 2020-11-12 16:00:00 17.781 110 #> 282 2020-11-12 16:15:00 17.782 110 #> 283 2020-11-12 16:30:00 17.782 110 #> 284 2020-11-12 16:45:00 17.782 110 #> 285 2020-11-12 17:00:00 17.782 110 #> 286 2020-11-12 17:15:00 17.782 110 #> 287 2020-11-12 17:30:00 17.782 110
get_timeseries_tsid("55419010", from = "2017-06-01", to = "2017-06-03", datasource = 4)
#> Timestamp Value Quality Code #> 1 2017-05-31 22:00:00 3.97 11 #> 2 2017-05-31 22:10:00 3.80 11 #> 3 2017-05-31 22:20:00 3.63 11 #> 4 2017-05-31 22:30:00 3.48 11 #> 5 2017-05-31 22:40:00 3.32 11 #> 6 2017-05-31 22:50:00 3.17 11 #> 7 2017-05-31 23:00:00 3.02 11 #> 8 2017-05-31 23:10:00 2.87 11 #> 9 2017-05-31 23:20:00 2.74 11 #> 10 2017-05-31 23:30:00 2.60 11 #> 11 2017-05-31 23:40:00 2.48 11 #> 12 2017-05-31 23:50:00 2.35 11 #> 13 2017-06-01 00:00:00 2.23 11 #> 14 2017-06-01 00:10:00 2.11 11 #> 15 2017-06-01 00:20:00 1.99 11 #> 16 2017-06-01 00:30:00 1.87 11 #> 17 2017-06-01 00:40:00 1.75 11 #> 18 2017-06-01 00:50:00 1.64 11 #> 19 2017-06-01 01:00:00 1.53 11 #> 20 2017-06-01 01:10:00 1.42 11 #> 21 2017-06-01 01:20:00 1.31 11 #> 22 2017-06-01 01:30:00 1.20 11 #> 23 2017-06-01 01:40:00 1.09 11 #> 24 2017-06-01 01:50:00 0.99 11 #> 25 2017-06-01 02:00:00 0.90 11 #> 26 2017-06-01 02:10:00 0.80 11 #> 27 2017-06-01 02:20:00 0.71 11 #> 28 2017-06-01 02:30:00 0.62 11 #> 29 2017-06-01 02:40:00 0.53 11 #> 30 2017-06-01 02:50:00 0.44 11 #> 31 2017-06-01 03:00:00 0.36 11 #> 32 2017-06-01 03:10:00 0.28 11 #> 33 2017-06-01 03:20:00 0.20 11 #> 34 2017-06-01 03:30:00 0.13 11 #> 35 2017-06-01 03:40:00 0.07 11 #> 36 2017-06-01 03:50:00 0.01 11 #> 37 2017-06-01 04:00:00 -0.02 11 #> 38 2017-06-01 04:10:00 0.08 11 #> 39 2017-06-01 04:20:00 0.38 11 #> 40 2017-06-01 04:30:00 0.69 11 #> 41 2017-06-01 04:40:00 0.94 11 #> 42 2017-06-01 04:50:00 1.14 11 #> 43 2017-06-01 05:00:00 1.31 11 #> 44 2017-06-01 05:10:00 1.47 11 #> 45 2017-06-01 05:20:00 1.63 11 #> 46 2017-06-01 05:30:00 1.79 11 #> 47 2017-06-01 05:40:00 1.95 11 #> 48 2017-06-01 05:50:00 2.11 11 #> 49 2017-06-01 06:00:00 2.26 11 #> 50 2017-06-01 06:10:00 2.43 11 #> 51 2017-06-01 06:20:00 2.58 11 #> 52 2017-06-01 06:30:00 2.75 11 #> 53 2017-06-01 06:40:00 2.92 11 #> 54 2017-06-01 06:50:00 3.13 11 #> 55 2017-06-01 07:00:00 3.36 11 #> 56 2017-06-01 07:10:00 3.62 11 #> 57 2017-06-01 07:20:00 3.91 11 #> 58 2017-06-01 07:30:00 4.19 11 #> 59 2017-06-01 07:40:00 4.47 11 #> 60 2017-06-01 07:50:00 4.71 11 #> 61 2017-06-01 08:00:00 4.92 11 #> 62 2017-06-01 08:10:00 5.09 11 #> 63 2017-06-01 08:20:00 5.21 11 #> 64 2017-06-01 08:30:00 5.31 11 #> 65 2017-06-01 08:40:00 5.37 11 #> 66 2017-06-01 08:50:00 5.39 11 #> 67 2017-06-01 09:00:00 5.39 11 #> 68 2017-06-01 09:10:00 5.36 11 #> 69 2017-06-01 09:20:00 5.27 11 #> 70 2017-06-01 09:30:00 5.14 11 #> 71 2017-06-01 09:40:00 4.96 11 #> 72 2017-06-01 09:50:00 4.76 11 #> 73 2017-06-01 10:00:00 4.56 11 #> 74 2017-06-01 10:10:00 4.37 11 #> 75 2017-06-01 10:20:00 4.18 11 #> 76 2017-06-01 10:30:00 4.01 11 #> 77 2017-06-01 10:40:00 3.83 11 #> 78 2017-06-01 10:50:00 3.66 11 #> 79 2017-06-01 11:00:00 3.49 11 #> 80 2017-06-01 11:10:00 3.34 11 #> 81 2017-06-01 11:20:00 3.18 11 #> 82 2017-06-01 11:30:00 3.03 11 #> 83 2017-06-01 11:40:00 2.88 11 #> 84 2017-06-01 11:50:00 2.73 11 #> 85 2017-06-01 12:00:00 2.60 11 #> 86 2017-06-01 12:10:00 2.46 11 #> 87 2017-06-01 12:20:00 2.33 11 #> 88 2017-06-01 12:30:00 2.20 11 #> 89 2017-06-01 12:40:00 2.07 11 #> 90 2017-06-01 12:50:00 1.95 11 #> 91 2017-06-01 13:00:00 1.84 11 #> 92 2017-06-01 13:10:00 1.72 11 #> 93 2017-06-01 13:20:00 1.61 11 #> 94 2017-06-01 13:30:00 1.50 11 #> 95 2017-06-01 13:40:00 1.39 11 #> 96 2017-06-01 13:50:00 1.29 11 #> 97 2017-06-01 14:00:00 1.19 11 #> 98 2017-06-01 14:10:00 1.09 11 #> 99 2017-06-01 14:20:00 0.99 11 #> 100 2017-06-01 14:30:00 0.89 11 #> 101 2017-06-01 14:40:00 0.80 11 #> 102 2017-06-01 14:50:00 0.72 11 #> 103 2017-06-01 15:00:00 0.63 11 #> 104 2017-06-01 15:10:00 0.55 11 #> 105 2017-06-01 15:20:00 0.47 11 #> 106 2017-06-01 15:30:00 0.40 11 #> 107 2017-06-01 15:40:00 0.33 11 #> 108 2017-06-01 15:50:00 0.27 11 #> 109 2017-06-01 16:00:00 0.23 11 #> 110 2017-06-01 16:10:00 0.22 11 #> 111 2017-06-01 16:20:00 0.33 11 #> 112 2017-06-01 16:30:00 0.66 11 #> 113 2017-06-01 16:40:00 0.93 11 #> 114 2017-06-01 16:50:00 1.16 11 #> 115 2017-06-01 17:00:00 1.35 11 #> 116 2017-06-01 17:10:00 1.51 11 #> 117 2017-06-01 17:20:00 1.65 11 #> 118 2017-06-01 17:30:00 1.79 11 #> 119 2017-06-01 17:40:00 1.95 11 #> 120 2017-06-01 17:50:00 2.10 11 #> 121 2017-06-01 18:00:00 2.24 11 #> 122 2017-06-01 18:10:00 2.37 11 #> 123 2017-06-01 18:20:00 2.51 11 #> 124 2017-06-01 18:30:00 2.64 11 #> 125 2017-06-01 18:40:00 2.77 11 #> 126 2017-06-01 18:50:00 2.90 11 #> 127 2017-06-01 19:00:00 3.04 11 #> 128 2017-06-01 19:10:00 3.18 11 #> 129 2017-06-01 19:20:00 3.33 11 #> 130 2017-06-01 19:30:00 3.49 11 #> 131 2017-06-01 19:40:00 3.66 11 #> 132 2017-06-01 19:50:00 3.87 11 #> 133 2017-06-01 20:00:00 4.08 11 #> 134 2017-06-01 20:10:00 4.31 11 #> 135 2017-06-01 20:20:00 4.52 11 #> 136 2017-06-01 20:30:00 4.72 11 #> 137 2017-06-01 20:40:00 4.89 11 #> 138 2017-06-01 20:50:00 5.02 11 #> 139 2017-06-01 21:00:00 5.11 11 #> 140 2017-06-01 21:10:00 5.17 11 #> 141 2017-06-01 21:20:00 5.20 11 #> 142 2017-06-01 21:30:00 5.19 11 #> 143 2017-06-01 21:40:00 5.12 11 #> 144 2017-06-01 21:50:00 5.00 11 #> 145 2017-06-01 22:00:00 4.82 11 #> 146 2017-06-01 22:10:00 4.62 11 #> 147 2017-06-01 22:20:00 4.41 11 #> 148 2017-06-01 22:30:00 4.21 11 #> 149 2017-06-01 22:40:00 4.03 11 #> 150 2017-06-01 22:50:00 3.86 11 #> 151 2017-06-01 23:00:00 3.70 15 #> 152 2017-06-01 23:10:00 3.54 11 #> 153 2017-06-01 23:20:00 3.38 11 #> 154 2017-06-01 23:30:00 3.23 11 #> 155 2017-06-01 23:40:00 3.08 11 #> 156 2017-06-01 23:50:00 2.93 11 #> 157 2017-06-02 00:00:00 2.79 11 #> 158 2017-06-02 00:10:00 2.65 11 #> 159 2017-06-02 00:20:00 2.52 11 #> 160 2017-06-02 00:30:00 2.39 11 #> 161 2017-06-02 00:40:00 2.27 11 #> 162 2017-06-02 00:50:00 2.14 11 #> 163 2017-06-02 01:00:00 2.02 11 #> 164 2017-06-02 01:10:00 1.91 11 #> 165 2017-06-02 01:20:00 1.79 11 #> 166 2017-06-02 01:30:00 1.68 11 #> 167 2017-06-02 01:40:00 1.57 11 #> 168 2017-06-02 01:50:00 1.46 11 #> 169 2017-06-02 02:00:00 1.35 11 #> 170 2017-06-02 02:10:00 1.25 11 #> 171 2017-06-02 02:20:00 1.15 11 #> 172 2017-06-02 02:30:00 1.05 11 #> 173 2017-06-02 02:40:00 0.95 11 #> 174 2017-06-02 02:50:00 0.86 11 #> 175 2017-06-02 03:00:00 0.77 11 #> 176 2017-06-02 03:10:00 0.68 11 #> 177 2017-06-02 03:20:00 0.59 11 #> 178 2017-06-02 03:30:00 0.51 11 #> 179 2017-06-02 03:40:00 0.43 11 #> 180 2017-06-02 03:50:00 0.35 11 #> 181 2017-06-02 04:00:00 0.28 11 #> 182 2017-06-02 04:10:00 0.21 11 #> 183 2017-06-02 04:20:00 0.15 11 #> 184 2017-06-02 04:30:00 0.09 11 #> 185 2017-06-02 04:40:00 0.04 11 #> 186 2017-06-02 04:50:00 0.02 11 #> 187 2017-06-02 05:00:00 0.11 11 #> 188 2017-06-02 05:10:00 0.37 11 #> 189 2017-06-02 05:20:00 0.66 11 #> 190 2017-06-02 05:30:00 0.90 11 #> 191 2017-06-02 05:40:00 1.10 11 #> 192 2017-06-02 05:50:00 1.27 11 #> 193 2017-06-02 06:00:00 1.43 11 #> 194 2017-06-02 06:10:00 1.60 11 #> 195 2017-06-02 06:20:00 1.77 11 #> 196 2017-06-02 06:30:00 1.94 11 #> 197 2017-06-02 06:40:00 2.10 11 #> 198 2017-06-02 06:50:00 2.26 11 #> 199 2017-06-02 07:00:00 2.42 11 #> 200 2017-06-02 07:10:00 2.59 11 #> 201 2017-06-02 07:20:00 2.76 11 #> 202 2017-06-02 07:30:00 2.95 11 #> 203 2017-06-02 07:40:00 3.15 11 #> 204 2017-06-02 07:50:00 3.36 11 #> 205 2017-06-02 08:00:00 3.59 11 #> 206 2017-06-02 08:10:00 3.83 11 #> 207 2017-06-02 08:20:00 4.08 11 #> 208 2017-06-02 08:30:00 4.33 11 #> 209 2017-06-02 08:40:00 4.57 11 #> 210 2017-06-02 08:50:00 4.79 11 #> 211 2017-06-02 09:00:00 4.97 11 #> 212 2017-06-02 09:10:00 5.11 11 #> 213 2017-06-02 09:20:00 5.23 11 #> 214 2017-06-02 09:30:00 5.31 11 #> 215 2017-06-02 09:40:00 5.38 11 #> 216 2017-06-02 09:50:00 5.41 11 #> 217 2017-06-02 10:00:00 5.41 11 #> 218 2017-06-02 10:10:00 5.39 11 #> 219 2017-06-02 10:20:00 5.31 11 #> 220 2017-06-02 10:30:00 5.19 11 #> 221 2017-06-02 10:40:00 5.03 11 #> 222 2017-06-02 10:50:00 4.84 11 #> 223 2017-06-02 11:00:00 4.66 11 #> 224 2017-06-02 11:10:00 4.48 11 #> 225 2017-06-02 11:20:00 4.30 11 #> 226 2017-06-02 11:30:00 4.11 11 #> 227 2017-06-02 11:40:00 3.95 11 #> 228 2017-06-02 11:50:00 3.78 11 #> 229 2017-06-02 12:00:00 3.63 11 #> 230 2017-06-02 12:10:00 3.46 11 #> 231 2017-06-02 12:20:00 3.30 11 #> 232 2017-06-02 12:30:00 3.15 11 #> 233 2017-06-02 12:40:00 3.00 11 #> 234 2017-06-02 12:50:00 2.86 11 #> 235 2017-06-02 13:00:00 2.72 11 #> 236 2017-06-02 13:10:00 2.59 11 #> 237 2017-06-02 13:20:00 2.46 11 #> 238 2017-06-02 13:30:00 2.33 11 #> 239 2017-06-02 13:40:00 2.20 11 #> 240 2017-06-02 13:50:00 2.09 11 #> 241 2017-06-02 14:00:00 1.97 11 #> 242 2017-06-02 14:10:00 1.86 11 #> 243 2017-06-02 14:20:00 1.75 11 #> 244 2017-06-02 14:30:00 1.64 11 #> 245 2017-06-02 14:40:00 1.54 11 #> 246 2017-06-02 14:50:00 1.44 11 #> 247 2017-06-02 15:00:00 1.33 11 #> 248 2017-06-02 15:10:00 1.23 11 #> 249 2017-06-02 15:20:00 1.14 11 #> 250 2017-06-02 15:30:00 1.04 11 #> 251 2017-06-02 15:40:00 0.95 11 #> 252 2017-06-02 15:50:00 0.87 11 #> 253 2017-06-02 16:00:00 0.78 11 #> 254 2017-06-02 16:10:00 0.71 11 #> 255 2017-06-02 16:20:00 0.63 11 #> 256 2017-06-02 16:30:00 0.57 11 #> 257 2017-06-02 16:40:00 0.51 11 #> 258 2017-06-02 16:50:00 0.46 11 #> 259 2017-06-02 17:00:00 0.45 11 #> 260 2017-06-02 17:10:00 0.53 11 #> 261 2017-06-02 17:20:00 0.75 11 #> 262 2017-06-02 17:30:00 1.04 11 #> 263 2017-06-02 17:40:00 1.26 11 #> 264 2017-06-02 17:50:00 1.46 11 #> 265 2017-06-02 18:00:00 1.62 11 #> 266 2017-06-02 18:10:00 1.77 11 #> 267 2017-06-02 18:20:00 1.91 11 #> 268 2017-06-02 18:30:00 2.07 11 #> 269 2017-06-02 18:40:00 2.21 11 #> 270 2017-06-02 18:50:00 2.35 11 #> 271 2017-06-02 19:00:00 2.48 11 #> 272 2017-06-02 19:10:00 2.62 11 #> 273 2017-06-02 19:20:00 2.74 11 #> 274 2017-06-02 19:30:00 2.87 11 #> 275 2017-06-02 19:40:00 2.99 11 #> 276 2017-06-02 19:50:00 3.11 11 #> 277 2017-06-02 20:00:00 3.24 11 #> 278 2017-06-02 20:10:00 3.37 11 #> 279 2017-06-02 20:20:00 3.52 11 #> 280 2017-06-02 20:30:00 3.67 11 #> 281 2017-06-02 20:40:00 3.84 11 #> 282 2017-06-02 20:50:00 4.01 11 #> 283 2017-06-02 21:00:00 4.20 11 #> 284 2017-06-02 21:10:00 4.39 11 #> 285 2017-06-02 21:20:00 4.58 11 #> 286 2017-06-02 21:30:00 4.75 11 #> 287 2017-06-02 21:40:00 4.91 11 #> 288 2017-06-02 21:50:00 5.03 11 #> 289 2017-06-02 22:00:00 5.13 11