{ "cells": [ { "cell_type": "markdown", "id": "f4a64783", "metadata": {}, "source": [ "### Exploratory work " ] }, { "cell_type": "code", "execution_count": 1, "id": "8038e84b", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import xarray as xr\n", "import matplotlib as mpl\n", "#mpl.use('Agg') # Must be before importing matplotlib.pyplot or pylab!\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import os\n", "import seaborn as sns\n", "import timeit\n", "#start_time = timeit.default_timer()\n", "from datetime import datetime,timedelta\n", "\n" ] }, { "cell_type": "markdown", "id": "9b2d89ea", "metadata": {}, "source": [ "Plot parameters" ] }, { "cell_type": "code", "execution_count": 2, "id": "d00f70ed", "metadata": {}, "outputs": [], "source": [ "mpl.rcParams['axes.linewidth'] = 2.0 #set the value globally\n", "\n", "plt.rc('font', family='serif',size = 16) # controls default text layout\n", "plt.rc('axes', titlesize=16) # fontsize of the axes title\n", "plt.rc('axes', labelsize=16) # fontsize of the x and y labels\n", "plt.rc('xtick', labelsize=10) # fontsize of the tick labels\n", "plt.rc('ytick', labelsize=16) # fontsize of the tick labels\n", "plt.rc('legend', fontsize=16) # legend fontsize\n", "plt.rc('figure', titlesize=16) # fontsize of the figure title\n", "\n", "#plt.minorticks_on()\n", "plt.rc('text', usetex=False)\n", "#sns.set(font = \"Garamond\",font_scale=1.5,style=\"whitegrid\")\n", "sns.set(font_scale=1.5,style=\"whitegrid\")\n", "#sns.set(font = \"Cambria\",font_scale=1.5,style=\"white\")\n", "\n", "#mpl.rc_file_defaults() #undos seaborn effects\n", "\n", "#custom fontsize, if needed\n", "font = 12\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "id": "c5abdac1", "metadata": {}, "source": [ "## Plot the simulated tower data at the WLEF tall tower for 32 and 122m heights. Both 1 minute, high frequency data and 1 hour averaged data. For winds, T and q. For both the IOP test cases. " ] }, { "cell_type": "markdown", "id": "b6da7564", "metadata": {}, "source": [ "### Redoing IOP03 code for IOP02, to make half hourly averaged plots." ] }, { "cell_type": "code", "execution_count": 3, "id": "e0b1b04c", "metadata": {}, "outputs": [], "source": [ "tower_data = xr.open_dataset('tower_and_meta_data.nc')\n", "tower_data.close()\n", "\n", "#calculate time variable and offset for UTC\n", "tower_data['time'] = (tower_data.DOY+tower_data.hour/24+tower_data.minute/60/24 - 5/24)\n", "tower_data['time'] = tower_data['time']\n", "#set local(CDT) time as a coordinate\n", "tower_data = tower_data.set_coords(['time'])\n", "\n", "#subset for 2019 Sep 24 and Sep25\n", "#f1 = tower_data.time>=267\n", "#f2 = tower_data.time<=269\n", "#subset for 2019 Aug 23 and 24\n", "f1 = tower_data.time>=235\n", "f2 = tower_data.time<=237\n", "tower_data = tower_data.where(f1 & f2, drop=True)\n", "\n", "#subset all >30m towers \n", "tower_data = tower_data.where(tower_data.z_meas>=30, drop=True)\n", "\n", "tower_name_list = tower_data.tower.values\n", "\n", "#subset for time, because simulated tower data only start at 5:00 CDT on 23rd and go on till 20:00 on 24\n", "#for IOP02\n", "tower_data = tower_data.isel(timestep=slice(9,88))\n", "\n" ] }, { "cell_type": "code", "execution_count": 11, "id": "313fc071", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
<xarray.Dataset>\n", "Dimensions: (timestep: 79, tower: 12)\n", "Coordinates:\n", " * timestep (timestep) float32 3092.0 3093.0 3094.0 ... 3168.0 3169.0 3170.0\n", " * tower (tower) |S3 b'nw1' b'nw4' b'ne1' b'ne2' ... b'se2' b'se3' b'se6'\n", " time (timestep) float64 235.2 235.2 235.3 235.3 ... 236.8 236.8 236.8\n", "Data variables:\n", " cov_wT (timestep, tower) float32 nan nan nan ... nan -0.040575635\n", " cov_wH2O (timestep, tower) float32 nan nan ... 0.00011012288 0.008371787\n", " cov_wCO2 (timestep, tower) float32 nan 3.2873006 nan ... nan 4.218367\n", " f_Hs (timestep, tower) float32 nan nan nan ... nan -46.565163\n", " f_Hl (timestep, tower) float32 nan nan nan ... 0.19211948 14.62629\n", " f_CO2 (timestep, tower) float32 nan 3.2873006 nan ... nan 4.218367\n", " ustar (timestep, tower) float32 0.093750365 nan ... 0.1663326 0.22997157\n", " wstar (timestep, tower) float32 9.96921e+36 9.96921e+36 ... 9.96921e+36\n", " R_net (timestep, tower) float32 nan nan nan ... -77.62585 -81.11471\n", " ghf (timestep, tower) float32 -9.8621435 -13.070833 ... -7.9857564\n", " S_store (timestep, tower) float32 -10.726784 -13.613643 ... -28.955198\n", " T_store (timestep, tower) float32 nan -2.380881 ... -22.817564 -17.578283\n", " Q_store (timestep, tower) float32 nan -0.68177795 ... -5.123493 -6.606099\n", " u (timestep, tower) float32 -0.82647675 -0.58485526 ... -1.487267\n", " v (timestep, tower) float32 -0.35459593 -0.54859847 ... 1.6453543\n", " w (timestep, tower) float32 -0.021794753 0.0252656 ... -0.011205262\n", " T (timestep, tower) float32 283.0763 281.3218 ... 291.24847\n", " q (timestep, tower) float32 nan 11.239947 ... 14.322884 14.491939\n", " year (timestep, tower) float32 2019.0 2019.0 2019.0 ... 2019.0 2019.0\n", " month (timestep, tower) float32 8.0 8.0 8.0 8.0 8.0 ... 8.0 8.0 8.0 8.0\n", " day (timestep, tower) float32 23.0 23.0 23.0 23.0 ... 25.0 25.0 25.0\n", " DOY (timestep, tower) float64 235.0 235.0 235.0 ... 237.0 237.0 237.0\n", " hour (timestep, tower) float32 10.0 10.0 10.0 10.0 ... 1.0 1.0 1.0 1.0\n", " minute (timestep, tower) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n", " z_meas (tower, timestep) float32 32.0 32.0 32.0 32.0 ... 32.0 32.0 32.0
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array([b'nw1', b'nw4', b'ne1', b'ne2', b'ne3', b'ne4', b'sw1', b'sw3', b'sw4',\n", " b'se2', b'se3', b'se6'], dtype='|S3')
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<xarray.Dataset>\n", "Dimensions: (time: 15, tower: 12)\n", "Coordinates:\n", " x (tower) float64 2.217e+03 3.981e+03 ... 8.091e+03 9.537e+03\n", " y (tower) float64 9.147e+03 9.951e+03 ... 4.161e+03 3.333e+03\n", " * time (time) timedelta64[ns] 01:00:00.600000035 ... 08:00:00.600000279\n", " zw_3d float64 32.0\n", " * tower (tower) object 'nw1' 'nw4' 'ne1' 'ne2' ... 'sw4' 'se2' 'se3' 'se6'\n", "Data variables:\n", " wtheta (tower, time) float64 0.001542 0.0003295 ... 0.001311 0.0205
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array(32.)
array(['nw1', 'nw4', 'ne1', 'ne2', 'ne3', 'ne4', 'sw1', 'sw3', 'sw4', 'se2',\n", " 'se3', 'se6'], dtype=object)
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<xarray.Dataset>\n", "Dimensions: (time: 72, tower: 12)\n", "Coordinates:\n", " x (tower) float64 2.217e+03 3.981e+03 ... 8.091e+03 9.537e+03\n", " y (tower) float64 9.147e+03 9.951e+03 ... 4.161e+03 3.333e+03\n", " * time (time) timedelta64[ns] 08:30:00.600000297 ... 1 days 20:00:00.21...\n", " zw_3d float64 32.0\n", " * tower (tower) object 'nw1' 'nw4' 'ne1' 'ne2' ... 'sw4' 'se2' 'se3' 'se6'\n", "Data variables:\n", " wtheta (tower, time) float64 -0.00398 -0.002288 ... 0.0007246 0.0008322
array([2217., 3981., 6159., 8619., 9225., 9669., 723., 3249., 5391., 6801.,\n", " 8091., 9537.])
array([9147., 9951., 9309., 7335., 9465., 8019., 2799., 3441., 5499., 5199.,\n", " 4161., 3333.])
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array(32.)
array(['nw1', 'nw4', 'ne1', 'ne2', 'ne3', 'ne4', 'sw1', 'sw3', 'sw4', 'se2',\n", " 'se3', 'se6'], dtype=object)
array([[-3.979859e-03, -2.287970e-03, -1.823552e-02, ..., 1.129043e-03,\n", " -7.249397e-04, -5.025688e-05],\n", " [-1.852676e-02, -1.063194e-02, 8.535469e-03, ..., 6.462872e-04,\n", " 1.213541e-03, 4.950357e-03],\n", " [ 7.170535e-03, -2.015406e-02, -1.613993e-02, ..., 8.224494e-04,\n", " -1.956572e-03, -1.448551e-03],\n", " ...,\n", " [-9.355817e-03, -3.278338e-03, -9.821190e-03, ..., 4.450839e-04,\n", " -4.277487e-04, 1.450405e-04],\n", " [-1.385320e-03, -2.072331e-02, 1.293597e-02, ..., -3.427458e-05,\n", " 3.512514e-04, -8.083697e-05],\n", " [-6.755380e-03, -2.489367e-03, 3.367695e-04, ..., 5.991494e-04,\n", " 7.245942e-04, 8.321922e-04]])
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\n", " | tower | \n", "time | \n", "x | \n", "y | \n", "zw_3d | \n", "theta_simulated | \n", "T_measured | \n", "hour | \n", "day_night | \n", "
---|---|---|---|---|---|---|---|---|---|
0 | \n", "nw1 | \n", "2019-08-23 05:00:00.600000175 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "284.974014 | \n", "283.241241 | \n", "5 | \n", "night | \n", "
1 | \n", "nw1 | \n", "2019-08-23 05:30:00.600000192 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "284.963089 | \n", "282.651825 | \n", "5 | \n", "night | \n", "
2 | \n", "nw1 | \n", "2019-08-23 06:00:00.600000210 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "284.274216 | \n", "282.120392 | \n", "6 | \n", "day | \n", "
3 | \n", "nw1 | \n", "2019-08-23 06:30:00.600000227 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "283.334152 | \n", "282.207031 | \n", "6 | \n", "day | \n", "
4 | \n", "nw1 | \n", "2019-08-23 07:00:00.600000244 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "282.686829 | \n", "282.715790 | \n", "7 | \n", "day | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
943 | \n", "se6 | \n", "2019-08-24 18:00:00.210999692 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "296.130295 | \n", "293.342163 | \n", "18 | \n", "day | \n", "
944 | \n", "se6 | \n", "2019-08-24 18:30:00.210999622 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "296.187225 | \n", "293.353394 | \n", "18 | \n", "day | \n", "
945 | \n", "se6 | \n", "2019-08-24 19:00:00.210999552 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "296.127747 | \n", "292.626953 | \n", "19 | \n", "day | \n", "
946 | \n", "se6 | \n", "2019-08-24 19:30:00.210999482 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "295.972092 | \n", "291.760864 | \n", "19 | \n", "day | \n", "
947 | \n", "se6 | \n", "2019-08-24 20:00:00.210999411 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "295.671799 | \n", "291.086945 | \n", "20 | \n", "night | \n", "
948 rows × 9 columns
\n", "\n", " | tower | \n", "time | \n", "x | \n", "y | \n", "zw_3d | \n", "q_simulated | \n", "q_measured | \n", "hour | \n", "day_night | \n", "
---|---|---|---|---|---|---|---|---|---|
0 | \n", "nw1 | \n", "2019-08-23 05:00:00.600000175 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "0.008546 | \n", "NaN | \n", "5 | \n", "night | \n", "
1 | \n", "nw1 | \n", "2019-08-23 05:30:00.600000192 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "0.008553 | \n", "NaN | \n", "5 | \n", "night | \n", "
2 | \n", "nw1 | \n", "2019-08-23 06:00:00.600000210 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "0.008326 | \n", "NaN | \n", "6 | \n", "day | \n", "
3 | \n", "nw1 | \n", "2019-08-23 06:30:00.600000227 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "0.008244 | \n", "NaN | \n", "6 | \n", "day | \n", "
4 | \n", "nw1 | \n", "2019-08-23 07:00:00.600000244 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "0.008231 | \n", "NaN | \n", "7 | \n", "day | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
943 | \n", "se6 | \n", "2019-08-24 18:00:00.210999692 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.006203 | \n", "13.352215 | \n", "18 | \n", "day | \n", "
944 | \n", "se6 | \n", "2019-08-24 18:30:00.210999622 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.006148 | \n", "13.626987 | \n", "18 | \n", "day | \n", "
945 | \n", "se6 | \n", "2019-08-24 19:00:00.210999552 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.006344 | \n", "13.880861 | \n", "19 | \n", "day | \n", "
946 | \n", "se6 | \n", "2019-08-24 19:30:00.210999482 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.006562 | \n", "14.175860 | \n", "19 | \n", "day | \n", "
947 | \n", "se6 | \n", "2019-08-24 20:00:00.210999411 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.006640 | \n", "14.114041 | \n", "20 | \n", "night | \n", "
948 rows × 9 columns
\n", "\n", " | \n", " | x | \n", "y | \n", "zw_3d | \n", "wtheta_simulated | \n", "cov_wT_measured | \n", "DOY | \n", "Time_of_day | \n", "
---|---|---|---|---|---|---|---|---|
tower | \n", "time | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
nw1 | \n", "2019-08-23 05:00:00.600000175 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "-0.002164 | \n", "NaN | \n", "235.208333 | \n", "0.208333 | \n", "
2019-08-23 05:30:00.600000192 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "-0.003089 | \n", "NaN | \n", "235.229167 | \n", "0.229167 | \n", "|
2019-08-23 06:00:00.600000210 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "-0.004218 | \n", "NaN | \n", "235.250000 | \n", "0.250000 | \n", "|
2019-08-23 06:30:00.600000227 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "0.002145 | \n", "NaN | \n", "235.270833 | \n", "0.270833 | \n", "|
2019-08-23 07:00:00.600000244 | \n", "2217.0 | \n", "9147.0 | \n", "32.0 | \n", "0.010347 | \n", "-0.000788 | \n", "235.291667 | \n", "0.291667 | \n", "|
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
se6 | \n", "2019-08-24 18:00:00.210999692 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.031190 | \n", "0.010077 | \n", "236.750000 | \n", "0.750000 | \n", "
2019-08-24 18:30:00.210999622 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.006935 | \n", "-0.002774 | \n", "236.770833 | \n", "0.770833 | \n", "|
2019-08-24 19:00:00.210999552 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.000599 | \n", "-0.009599 | \n", "236.791667 | \n", "0.791667 | \n", "|
2019-08-24 19:30:00.210999482 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.000725 | \n", "-0.014315 | \n", "236.812500 | \n", "0.812500 | \n", "|
2019-08-24 20:00:00.210999411 | \n", "9537.0 | \n", "3333.0 | \n", "32.0 | \n", "0.000832 | \n", "-0.022617 | \n", "236.833333 | \n", "0.833333 | \n", "
948 rows × 7 columns
\n", "<xarray.Dataset>\n", "Dimensions: (time: 234001, x: 3, xu: 3, y: 3, yv: 3, zu_3d: 9, zw_3d: 9)\n", "Coordinates:\n", " * x (x) float64 6.069e+03 6.075e+03 6.081e+03\n", " * y (y) float64 6.177e+03 6.183e+03 6.189e+03\n", " * xu (xu) float64 6.066e+03 6.072e+03 6.078e+03\n", " * yv (yv) float64 6.174e+03 6.18e+03 6.186e+03\n", " * time (time) datetime64[ns] 2019-08-23T05:00:00.000000175 ... 2019-08-...\n", " * zu_3d (zu_3d) float64 26.0 30.0 34.0 94.0 98.0 102.0 194.0 198.0 202.0\n", " * zw_3d (zw_3d) float64 28.0 32.0 36.0 96.0 100.0 104.0 196.0 200.0 204.0\n", "Data variables:\n", " E_UTM (time, x) float64 4.989e+05 4.989e+05 ... 4.989e+05 4.989e+05\n", " N_UTM (time, y) float64 6.082e+05 6.082e+05 ... 6.082e+05 6.082e+05\n", " Eu_UTM (time, xu) float64 4.989e+05 4.989e+05 ... 4.989e+05 4.989e+05\n", " Nu_UTM (time, y) float64 6.082e+05 6.082e+05 ... 6.082e+05 6.082e+05\n", " Ev_UTM (time, x) float64 4.989e+05 4.989e+05 ... 4.989e+05 4.989e+05\n", " Nv_UTM (time, yv) float64 6.081e+05 6.082e+05 ... 6.082e+05 6.082e+05\n", " lon (time, y, x) float64 -93.01 -93.01 -93.01 ... -93.01 -93.01 -93.01\n", " lat (time, y, x) float64 5.502 5.502 5.502 5.502 ... 5.502 5.502 5.502\n", " lonu (time, y, xu) float64 -93.01 -93.01 -93.01 ... -93.01 -93.01 -93.01\n", " latu (time, y, xu) float64 5.502 5.502 5.502 5.502 ... 5.502 5.502 5.502\n", " lonv (time, yv, x) float64 -93.01 -93.01 -93.01 ... -93.01 -93.01 -93.01\n", " latv (time, yv, x) float64 5.502 5.502 5.502 5.502 ... 5.502 5.502 5.502\n", " crs (time) int32 -2147483647 -2147483647 ... -2147483647 -2147483647\n", " u (time, zu_3d, y, xu) float32 -1.0559956 -1.0432243 ... -0.07362391\n", " v (time, zu_3d, yv, x) float32 -0.8337311 -0.80854285 ... -0.35641006\n", " w (time, zw_3d, y, x) float32 0.07919971 0.068178974 ... -0.31850612\n", " theta (time, zu_3d, y, x) float32 283.39307 283.4112 ... 296.09335\n", " q (time, zu_3d, y, x) float32 0.008521782 0.008525057 ... 0.00599272\n", " s (time, zu_3d, y, x) float32 438.24213 438.22574 ... 408.302\n", "Attributes:\n", " title: PALM 21.10-rc.2 run: ches_IOP2.06 nest-id: 03 host: b...\n", " Conventions: CF-1.7\n", " creation_time: 2022-06-22 12:28:01 -06\n", " data_content: podsmasked\n", " version: 7\n", " origin_time: 2019-08-22 05:00:00 +00\n", " origin_lat: 45.710569\n", " origin_lon: -90.5842512\n", " origin_x: 492825.33\n", " origin_y: 601975.59\n", " origin_z: 470.0\n", " rotation_angle: 0.0\n", " dependencies: \n", " history: \n", " author: Luise Wanner, luise.wanner at kit.edu, Sreenath Paleri, ...\n", " contact_person: \n", " institution: IMK-IFU,Karlsruhe Institute of Technology, AOSS UW Madison\n", " acronym: \n", " campaign: \n", " location: \n", " site: \n", " source: PALM 21.10-rc.2\n", " references: \n", " keywords: example, PALM-4U\n", " licence: \n", " comment: Generic crossing example\n", " VAR_LIST: ;u;v;w;theta;q;s;
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2019-09-24 00:00:00 | \n", "1.74 | \n", "0.21 | \n", "250.67 | \n", "6.97 | \n", "17.60 | \n", "60.05 | \n", "7.94 | \n", "6.41 | \n", "0.13 | \n", "266.82 | \n", "... | \n", "8.66 | \n", "0.15 | \n", "270.20 | \n", "0.56 | \n", "15.79 | \n", "57.19 | \n", "6.73 | \n", "95.77 | \n", "0.0 | \n", "5.17 | \n", "
2019-09-24 00:01:00 | \n", "1.43 | \n", "0.23 | \n", "245.86 | \n", "8.79 | \n", "17.57 | \n", "60.24 | \n", "7.95 | \n", "6.34 | \n", "0.25 | \n", "264.77 | \n", "... | \n", "8.80 | \n", "0.15 | \n", "270.25 | \n", "1.09 | \n", "15.79 | \n", "57.39 | \n", "6.75 | \n", "95.77 | \n", "0.0 | \n", "4.44 | \n", "
2019-09-24 00:02:00 | \n", "1.47 | \n", "0.21 | \n", "247.24 | \n", "8.24 | \n", "17.54 | \n", "60.37 | \n", "7.96 | \n", "6.44 | \n", "0.29 | \n", "264.66 | \n", "... | \n", "8.49 | \n", "0.20 | \n", "271.00 | \n", "0.95 | \n", "15.79 | \n", "57.59 | \n", "6.78 | \n", "95.77 | \n", "0.0 | \n", "3.76 | \n", "
2019-09-24 00:03:00 | \n", "1.53 | \n", "0.31 | \n", "252.22 | \n", "5.67 | \n", "17.48 | \n", "60.92 | \n", "8.00 | \n", "6.67 | \n", "0.22 | \n", "266.08 | \n", "... | \n", "8.04 | \n", "0.17 | \n", "269.08 | \n", "1.45 | \n", "15.79 | \n", "57.73 | \n", "6.79 | \n", "95.78 | \n", "0.0 | \n", "3.06 | \n", "
2019-09-24 00:04:00 | \n", "1.49 | \n", "0.26 | \n", "248.44 | \n", "6.26 | \n", "17.41 | \n", "60.97 | \n", "7.97 | \n", "6.76 | \n", "0.12 | \n", "266.08 | \n", "... | \n", "8.30 | \n", "0.22 | \n", "270.94 | \n", "1.37 | \n", "15.79 | \n", "57.88 | \n", "6.81 | \n", "95.78 | \n", "0.0 | \n", "2.45 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
2019-09-24 23:55:00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "21.24 | \n", "76.71 | \n", "12.98 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "19.31 | \n", "79.57 | \n", "11.93 | \n", "94.65 | \n", "0.0 | \n", "2.99 | \n", "
2019-09-24 23:56:00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "21.20 | \n", "76.63 | \n", "12.94 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "19.31 | \n", "79.66 | \n", "11.95 | \n", "94.64 | \n", "0.0 | \n", "2.72 | \n", "
2019-09-24 23:57:00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "21.19 | \n", "76.70 | \n", "12.94 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "19.31 | \n", "79.71 | \n", "11.95 | \n", "94.64 | \n", "0.0 | \n", "2.40 | \n", "
2019-09-24 23:58:00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "21.19 | \n", "76.86 | \n", "12.97 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "19.31 | \n", "79.75 | \n", "11.96 | \n", "94.63 | \n", "0.0 | \n", "2.11 | \n", "
2019-09-24 23:59:00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "-999.0 | \n", "-999.00 | \n", "
1440 rows × 24 columns
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2019-09-24 05:00:00 | \n", "2.53 | \n", "0.35 | \n", "223.11 | \n", "7.12 | \n", "12.46 | \n", "82.10 | \n", "7.80 | \n", "9.99 | \n", "0.06 | \n", "257.23 | \n", "... | \n", "0.02 | \n", "264.51 | \n", "0.07 | \n", "15.88 | \n", "53.50 | \n", "6.33 | \n", "95.77 | \n", "0.0 | \n", "0.00 | \n", "2019-09-24 00:00:00 | \n", "
2019-09-24 05:01:00 | \n", "2.28 | \n", "0.51 | \n", "222.09 | \n", "7.41 | \n", "12.48 | \n", "81.90 | \n", "7.79 | \n", "10.02 | \n", "0.12 | \n", "257.85 | \n", "... | \n", "0.02 | \n", "264.70 | \n", "0.11 | \n", "15.88 | \n", "53.46 | \n", "6.32 | \n", "95.77 | \n", "0.0 | \n", "0.01 | \n", "2019-09-24 00:01:00 | \n", "
2019-09-24 05:02:00 | \n", "2.24 | \n", "0.50 | \n", "225.87 | \n", "7.84 | \n", "12.55 | \n", "81.60 | \n", "7.80 | \n", "9.88 | \n", "0.09 | \n", "257.72 | \n", "... | \n", "0.04 | \n", "265.11 | \n", "0.14 | \n", "15.88 | \n", "53.43 | \n", "6.32 | \n", "95.77 | \n", "0.0 | \n", "0.06 | \n", "2019-09-24 00:02:00 | \n", "
2019-09-24 05:03:00 | \n", "2.08 | \n", "0.54 | \n", "226.14 | \n", "8.71 | \n", "12.59 | \n", "81.50 | \n", "7.81 | \n", "9.55 | \n", "0.13 | \n", "255.64 | \n", "... | \n", "0.02 | \n", "265.59 | \n", "0.17 | \n", "15.89 | \n", "53.36 | \n", "6.32 | \n", "95.77 | \n", "0.0 | \n", "0.11 | \n", "2019-09-24 00:03:00 | \n", "
2019-09-24 05:04:00 | \n", "2.02 | \n", "0.31 | \n", "222.46 | \n", "7.22 | \n", "12.58 | \n", "81.60 | \n", "7.81 | \n", "9.21 | \n", "0.14 | \n", "253.02 | \n", "... | \n", "0.03 | \n", "266.15 | \n", "0.15 | \n", "15.93 | \n", "53.31 | \n", "6.33 | \n", "95.77 | \n", "0.0 | \n", "0.12 | \n", "2019-09-24 00:04:00 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
2019-09-26 04:56:00 | \n", "2.88 | \n", "0.76 | \n", "270.15 | \n", "14.76 | \n", "9.57 | \n", "72.34 | \n", "5.68 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "0.20 | \n", "295.05 | \n", "0.64 | \n", "8.21 | \n", "65.51 | \n", "4.69 | \n", "95.27 | \n", "0.0 | \n", "0.11 | \n", "2019-09-25 23:56:00 | \n", "
2019-09-26 04:57:00 | \n", "3.30 | \n", "0.65 | \n", "277.63 | \n", "12.01 | \n", "9.57 | \n", "72.63 | \n", "5.71 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "0.18 | \n", "295.22 | \n", "0.51 | \n", "8.22 | \n", "65.25 | \n", "4.67 | \n", "95.27 | \n", "0.0 | \n", "0.10 | \n", "2019-09-25 23:57:00 | \n", "
2019-09-26 04:58:00 | \n", "2.68 | \n", "0.53 | \n", "275.87 | \n", "12.52 | \n", "9.54 | \n", "72.69 | \n", "5.70 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "0.10 | \n", "294.42 | \n", "0.50 | \n", "8.28 | \n", "64.84 | \n", "4.66 | \n", "95.27 | \n", "0.0 | \n", "0.11 | \n", "2019-09-25 23:58:00 | \n", "
2019-09-26 04:59:00 | \n", "3.03 | \n", "0.82 | \n", "281.42 | \n", "14.56 | \n", "9.54 | \n", "72.62 | \n", "5.69 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "0.12 | \n", "294.93 | \n", "0.53 | \n", "8.31 | \n", "65.11 | \n", "4.69 | \n", "95.27 | \n", "0.0 | \n", "0.09 | \n", "2019-09-25 23:59:00 | \n", "
2019-09-26 05:00:00 | \n", "2.99 | \n", "0.99 | \n", "267.06 | \n", "15.81 | \n", "9.51 | \n", "72.84 | \n", "5.70 | \n", "-999.00 | \n", "-999.00 | \n", "-999.00 | \n", "... | \n", "0.11 | \n", "294.60 | \n", "0.48 | \n", "8.31 | \n", "65.32 | \n", "4.71 | \n", "95.27 | \n", "0.0 | \n", "0.09 | \n", "2019-09-26 00:00:00 | \n", "
2881 rows × 25 columns
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