GGU_GW_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'lib.WellUtil' from '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Personnel_Folders/Dillon_Ragar/QualityZone2/lib/WellUtil.py'>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import importlib\n",
    "importlib.reload(WellUtil)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dropbox\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pecos\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import numpy as np\n",
    "import sys\n",
    "import missingno as msno\n",
    "import plotly\n",
    "import tempfile\n",
    "import dtale\n",
    "import pprint\n",
    "import fnmatch\n",
    "import io\n",
    "import matplotlib\n",
    "import webbrowser\n",
    "import wellapplication as wa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lib import ArchivalZone, WellUtil\n",
    "import lib.QualityZone2 as QZ2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Duplicates found: 0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "103"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files_1 = WellUtil.match_path(rootdir=path, pattern='*.xle', remove_comp=True); len(files_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2016/GGU_GW1_Level_Raw_WY2016/GGU_GW1_level_20151031.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2016/GGU_GW1_Level_Raw_WY2016/GGU_GW1_level_20160211.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2016/GGU_GW1_Level_Raw_WY2016/GGU_GW1_level_20160520.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2016/GGU_GW1_Level_Raw_WY2016/GGU_GW_1_level_20160409.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/1058174_GG Well 1_2017_02_13.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/1058174_GG Well 1_2017_04_06.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/1058174_GG Well 1_2017_06_14.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20160615_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20160706_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20160916_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20161028_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20161119_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20161218_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170225_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170309_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170406_GGU_GW_1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170512_GGU_GW1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170524_GGU_GW_1_level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170801_GGU_GW_1_level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170831_GGU_GW_1_level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2017/GGU_GW1_Level_Raw_WY2017/20170929_GGU_GW_1_level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2018/GGU_GW1_Level_Comped_WY2018/20180302_GGU_GW_1.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2018/GGU_GW1_Level_Comped_WY2018/20180405_GGU_GW_1.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2018/GGU_GW_1_Level_raw_WY2018/20171109_GGU_GW1_Level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2018/GGU_GW_1_Level_raw_WY2018/20171211_GGU_GW_1.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2018/GGU_GW_1_Level_raw_WY2018/20180302_GGU_GW_1.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2018/GGU_GW_1_Level_raw_WY2018/20180410_GGU_GW_1_level.xle',\n",
       " '/Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2018/GGU_GW_1_Level_raw_WY2018/20180505_GGU_GW_1_level.xle']"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(files_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for counter, f in enumerate(files_1):\n",
    "    print(f)\n",
    "    print(counter)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unknown units, no conversion\n",
      "0\n",
      "Unknown units, no conversion\n",
      "1\n",
      "Unknown units, no conversion\n",
      "2\n",
      "Unknown units, no conversion\n",
      "3\n",
      "Unknown units, no conversion\n",
      "4\n",
      "Unknown units, no conversion\n",
      "5\n",
      "Unknown units, no conversion\n",
      "6\n",
      "Unknown units, no conversion\n",
      "7\n",
      "Unknown units, no conversion\n",
      "8\n",
      "Unknown units, no conversion\n",
      "9\n",
      "Unknown units, no conversion\n",
      "10\n",
      "Unknown units, no conversion\n",
      "11\n",
      "Unknown units, no conversion\n",
      "12\n",
      "Unknown units, no conversion\n",
      "13\n",
      "Unknown units, no conversion\n",
      "14\n",
      "Unknown units, no conversion\n",
      "15\n",
      "Unknown units, no conversion\n",
      "16\n",
      "Unknown units, no conversion\n",
      "17\n",
      "Unknown units, no conversion\n",
      "18\n",
      "Unknown units, no conversion\n",
      "19\n",
      "Unknown units, no conversion\n",
      "20\n",
      "Unknown units, no conversion\n",
      "21\n",
      "Unknown units, no conversion\n",
      "22\n",
      "Unknown units, no conversion\n",
      "23\n",
      "Unknown units, no conversion\n",
      "24\n",
      "Unknown units, no conversion\n",
      "25\n",
      "Unknown units, no conversion\n",
      "26\n",
      "Unknown units, no conversion\n",
      "27\n",
      "Unknown units, no conversion\n",
      "28\n",
      "Unknown units, no conversion\n",
      "29\n",
      "Unknown units, no conversion\n",
      "30\n",
      "Unknown units, no conversion\n",
      "31\n",
      "Unknown units, no conversion\n",
      "32\n",
      "Unknown units, no conversion\n",
      "33\n",
      "Unknown units, no conversion\n",
      "34\n",
      "Unknown units, no conversion\n",
      "35\n",
      "Unknown units, no conversion\n",
      "36\n",
      "Unknown units, no conversion\n",
      "37\n",
      "Unknown units, no conversion\n",
      "38\n",
      "Unknown units, no conversion\n",
      "39\n",
      "Unknown units, no conversion\n",
      "40\n",
      "Unknown units, no conversion\n",
      "41\n",
      "Unknown units, no conversion\n",
      "42\n",
      "Unknown units, no conversion\n",
      "43\n",
      "Units in kpa, converting 20170524_GGU_GW_1_level.xle to ft...\n",
      "44\n",
      "Unknown units, no conversion\n",
      "45\n",
      "Unknown units, no conversion\n",
      "46\n",
      "Unknown units, no conversion\n",
      "47\n",
      "Unknown units, no conversion\n",
      "48\n",
      "Unknown units, no conversion\n",
      "49\n",
      "Unknown units, no conversion\n",
      "50\n",
      "Unknown units, no conversion\n",
      "51\n",
      "Unknown units, no conversion\n",
      "52\n",
      "Unknown units, no conversion\n",
      "53\n",
      "Unknown units, no conversion\n",
      "54\n",
      "Unknown units, no conversion\n",
      "55\n",
      "Unknown units, no conversion\n",
      "56\n",
      "Unknown units, no conversion\n",
      "57\n",
      "Unknown units, no conversion\n",
      "58\n",
      "Unknown units, no conversion\n",
      "59\n",
      "Unknown units, no conversion\n",
      "60\n",
      "Unknown units, no conversion\n",
      "61\n",
      "Unknown units, no conversion\n",
      "62\n",
      "Unknown units, no conversion\n",
      "63\n",
      "Unknown units, no conversion\n",
      "64\n",
      "Unknown units, no conversion\n",
      "65\n",
      "Unknown units, no conversion\n",
      "66\n",
      "Unknown units, no conversion\n",
      "67\n",
      "Unknown units, no conversion\n",
      "68\n",
      "Unknown units, no conversion\n",
      "69\n",
      "Unknown units, no conversion\n",
      "70\n",
      "Unknown units, no conversion\n",
      "71\n",
      "Unknown units, no conversion\n",
      "72\n",
      "Unknown units, no conversion\n",
      "73\n",
      "Unknown units, no conversion\n",
      "74\n",
      "Unknown units, no conversion\n",
      "75\n",
      "Unknown units, no conversion\n",
      "76\n",
      "Unknown units, no conversion\n",
      "77\n",
      "Unknown units, no conversion\n",
      "78\n",
      "xle file /Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2013/GGU_GW1_Raw_WY2013/GGU_GW1_20131122_2of2.xle incomplete\n",
      "79\n",
      "Unknown units, no conversion\n",
      "80\n",
      "Unknown units, no conversion\n",
      "81\n",
      "Unknown units, no conversion\n",
      "82\n",
      "Unknown units, no conversion\n",
      "83\n",
      "Unknown units, no conversion\n",
      "84\n",
      "Unknown units, no conversion\n",
      "85\n",
      "Unknown units, no conversion\n",
      "86\n",
      "Unknown units, no conversion\n",
      "87\n",
      "xle file /Users/dillon/Dropbox (Boulder Creek CZO)/CZO/BcCZO/Data/GordonGulch/GGU_GWW/GGU_GW1/GGU_GW1_Archival/GGU_GW1_WY2013/GGU_GW1_WY2013/GGU_GW1_20131122_2of2.xle incomplete\n",
      "88\n",
      "Unknown units, no conversion\n",
      "89\n",
      "Unknown units, no conversion\n",
      "90\n",
      "Unknown units, no conversion\n",
      "91\n",
      "Unknown units, no conversion\n",
      "92\n",
      "Unknown units, no conversion\n",
      "93\n",
      "Unknown units, no conversion\n",
      "94\n",
      "Unknown units, no conversion\n",
      "95\n",
      "Unknown units, no conversion\n",
      "96\n",
      "Unknown units, no conversion\n",
      "97\n",
      "Unknown units, no conversion\n",
      "98\n",
      "Unknown units, no conversion\n",
      "99\n",
      "Unknown units, no conversion\n",
      "100\n",
      "Unknown units, no conversion\n",
      "101\n",
      "Unknown units, no conversion\n",
      "102\n"
     ]
    }
   ],
   "source": [
    "df_list = WellUtil.solinst_df(files_1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_baro = pd.concat(df_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 348213 entries, 2011-09-21 10:00:00 to 2018-05-05 13:20:00\n",
      "Freq: 10T\n",
      "Data columns (total 7 columns):\n",
      " #   Column          Non-Null Count   Dtype  \n",
      "---  ------          --------------   -----  \n",
      " 0   Temperature     323224 non-null  float64\n",
      " 1   Level           323224 non-null  float64\n",
      " 2   name            323224 non-null  object \n",
      " 3   model           323224 non-null  object \n",
      " 4   sn              323224 non-null  object \n",
      " 5   location        323224 non-null  object \n",
      " 6   Ggu_Gw2_Pducer  0 non-null       float64\n",
      "dtypes: float64(3), object(4)\n",
      "memory usage: 21.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df_baro.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2011-09-21 10:00:00', '2011-09-21 10:10:00',\n",
       "               '2011-09-21 10:20:00', '2011-09-21 10:30:00',\n",
       "               '2011-09-21 10:40:00', '2011-09-21 10:50:00',\n",
       "               '2011-09-21 11:00:00', '2011-09-21 11:10:00',\n",
       "               '2011-09-21 11:20:00', '2011-09-21 11:30:00',\n",
       "               ...\n",
       "               '2018-05-05 11:50:00', '2018-05-05 12:00:00',\n",
       "               '2018-05-05 12:10:00', '2018-05-05 12:20:00',\n",
       "               '2018-05-05 12:30:00', '2018-05-05 12:40:00',\n",
       "               '2018-05-05 12:50:00', '2018-05-05 13:00:00',\n",
       "               '2018-05-05 13:10:00', '2018-05-05 13:20:00'],\n",
       "              dtype='datetime64[ns]', name='DateTime', length=348213, freq='10T')"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_baro.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_baro.sort_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_baro = QZ2.drop_dup(df_baro)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_baro = df_baro.asfreq('10min')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x12f378438>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "msno.matrix(df_baro, freq='Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x145e5b518>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_baro.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}