Notebook4_proxies.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notebook #4: The proxy database\n",
    "\n",
    "In this script, we'll take a look at one of the LMR inputs: the proxy database.\n",
    "\n",
    "One of the initial steps of running the LMR is to preprocess the proxy network.  This step puts the data into a standard format and calculates annual-mean values, among other things.  Let's take a look at these standard files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A non-python command to make sure all figures are plotted on this page.\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the necessary python packages \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the proxy data and metadata using the pandas library.\n",
    "proxies = pd.read_pickle('../LMR_data/data/proxies/Pages2kv1_Proxies.df.pckl')\n",
    "metadata = pd.read_pickle('../LMR_data/data/proxies/Pages2kv1_Metadata.df.pckl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "(2512, 577)\n"
     ]
    }
   ],
   "source": [
    "# The \"type\" and \"shape\" commands can be used to learn more about the data set.\n",
    "# The proxy data:\n",
    "print(type(proxies))\n",
    "print(proxies.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "(522, 15)\n"
     ]
    }
   ],
   "source": [
    "# The proxy metadata:\n",
    "print(type(metadata))\n",
    "print(metadata.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          Ant_01   Ant_02 Ant_03 Ant_04 Ant_05 Ant_06 Ant_07 Ant_08 Ant_09  \\\n",
      "Year C.E.                                                                    \n",
      "-500         NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-499         NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-498         NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-497         NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-496         NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "...          ...      ...    ...    ...    ...    ...    ...    ...    ...   \n",
      " 2007        NaN -21.6681    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2008        NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2009        NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2010        NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2011        NaN      NaN    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "\n",
      "          Ant_10  ... SAm_14  SAm_15 SAm_16 SAm_17 SAm_18 SAm_19 SAm_20  \\\n",
      "Year C.E.         ...                                                     \n",
      "-500         NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-499         NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-498         NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-497         NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "-496         NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "...          ...  ...    ...     ...    ...    ...    ...    ...    ...   \n",
      " 2007     -158.1  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2008        NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2009        NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2010        NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      " 2011        NaN  ...    NaN     NaN    NaN    NaN    NaN    NaN    NaN   \n",
      "\n",
      "          SAm_21 SAm_22 SAm_23  \n",
      "Year C.E.                       \n",
      "-500         NaN    NaN    NaN  \n",
      "-499         NaN    NaN    NaN  \n",
      "-498         NaN    NaN    NaN  \n",
      "-497         NaN    NaN    NaN  \n",
      "-496         NaN    NaN    NaN  \n",
      "...          ...    ...    ...  \n",
      " 2007        NaN    NaN    NaN  \n",
      " 2008        NaN    NaN    NaN  \n",
      " 2009        NaN    NaN    NaN  \n",
      " 2010        NaN    NaN    NaN  \n",
      " 2011        NaN    NaN    NaN  \n",
      "\n",
      "[2512 rows x 577 columns]\n"
     ]
    }
   ],
   "source": [
    "# Let's look at the contents of the proxy file.\n",
    "print(proxies)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Ant_01', 'Ant_02', 'Ant_03', 'Ant_04', 'Ant_05', 'Ant_06', 'Ant_07',\n",
      "       'Ant_08', 'Ant_09', 'Ant_10',\n",
      "       ...\n",
      "       'SAm_14', 'SAm_15', 'SAm_16', 'SAm_17', 'SAm_18', 'SAm_19', 'SAm_20',\n",
      "       'SAm_21', 'SAm_22', 'SAm_23'],\n",
      "      dtype='object', length=577)\n"
     ]
    }
   ],
   "source": [
    "# The \"keys\" command shows all of the keys for this dataset.\n",
    "print(proxies.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['PAGES 2k Region', 'Proxy ID', 'Country/Region', 'Area', 'Site',\n",
      "       'Lat (N)', 'Lon (E)', 'Archive type', 'Proxy measurement',\n",
      "       'Proxy other info', 'Sign relation to temp', 'Oldest (C.E.)',\n",
      "       'Youngest (C.E.)', 'Resolution (yr)', 'Reference'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Display all of the fields in the metadata file.\n",
    "print(metadata.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            PAGES 2k Region :                 Asia\n",
      "                   Proxy ID :              Asi_021\n",
      "             Country/Region : Altai Mountains (AT)\n",
      "                       Area :              RUSS139\n",
      "                       Site :               UKHEWD\n",
      "                    Lat (N) :                50.15\n",
      "                    Lon (E) :     85.3666666666667\n",
      "               Archive type :            Tree ring\n",
      "          Proxy measurement :    Earlywood density\n",
      "           Proxy other info :                  nan\n",
      "      Sign relation to temp :             Positive\n",
      "              Oldest (C.E.) :               1581.0\n",
      "            Youngest (C.E.) :               1994.0\n",
      "            Resolution (yr) :                  1.0\n",
      "                  Reference :    Schweingruber, FH\n"
     ]
    }
   ],
   "source": [
    "# As an example, plot the metadata of the first record.\n",
    "# Loop through every element of the metadata and print it to screen.\n",
    "for key in metadata.keys():\n",
    "    print('%27s : %20s' % (key, metadata.loc[101][key]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "index:                 Site:       Country/Region:         Archive type:\n",
      "   81:               AAT2LS, Altai Mountains (AT),            Tree ring\n",
      "   82:               DJAZLS, Altai Mountains (AT),            Tree ring\n",
      "   83:               JABELS, Altai Mountains (AT),            Tree ring\n",
      "   84:               KUR2LS, Altai Mountains (AT),            Tree ring\n",
      "   85:               KUR3LS, Altai Mountains (AT),            Tree ring\n",
      "   86:               MSALLS, Altai Mountains (AT),            Tree ring\n",
      "   87:               NCHALS, Altai Mountains (AT),            Tree ring\n",
      "   88:               TUT2LS, Altai Mountains (AT),            Tree ring\n",
      "   89:               UGLALS, Altai Mountains (AT),            Tree ring\n",
      "   90:               ULAGLS, Altai Mountains (AT),            Tree ring\n",
      "   91:               UULTRW, Altai Mountains (AT),            Tree ring\n",
      "   92:               UULEWW, Altai Mountains (AT),            Tree ring\n",
      "   93:               UULLWW, Altai Mountains (AT),            Tree ring\n",
      "   94:               UULEWD, Altai Mountains (AT),            Tree ring\n",
      "   95:               UULLWD, Altai Mountains (AT),            Tree ring\n",
      "   96:               UULMND, Altai Mountains (AT),            Tree ring\n",
      "   97:               UULMXD, Altai Mountains (AT),            Tree ring\n",
      "   98:               UKHTRW, Altai Mountains (AT),            Tree ring\n",
      "   99:               UKHEWW, Altai Mountains (AT),            Tree ring\n",
      "  100:               UKHLWW, Altai Mountains (AT),            Tree ring\n",
      "  101:               UKHEWD, Altai Mountains (AT),            Tree ring\n",
      "  102:               UKHLWD, Altai Mountains (AT),            Tree ring\n",
      "  103:               UKHMND, Altai Mountains (AT),            Tree ring\n",
      "  104:               UKHMXD, Altai Mountains (AT),            Tree ring\n",
      "  105:               GAYTTD,          Bhutan (BT),            Tree ring\n",
      "  106:               NASPTD,          Bhutan (BT),            Tree ring\n",
      "  107:               PHUMTD,          Bhutan (BT),            Tree ring\n",
      "  108:               ZACHTD,          Bhutan (BT),            Tree ring\n",
      "  109:               BHUTTD,          Bhutan (BT),            Tree ring\n",
      "  110:               CAMGSP,          Bhutan (BT),            Tree ring\n",
      "  111:               DHURPS,          Bhutan (BT),            Tree ring\n",
      "  112:               GEYZSP,          Bhutan (BT),            Tree ring\n",
      "  113:               PEMBSP,          Bhutan (BT),            Tree ring\n",
      "  114:               BHUTSP,          Bhutan (BT),            Tree ring\n",
      "  115:               LAYAJR,          Bhutan (BT),            Tree ring\n",
      "  116:               TSHEPS,          Bhutan (BT),            Tree ring\n",
      "  117:               TSHETD,          Bhutan (BT),            Tree ring\n",
      "  118:               TANSIC,           China (CH),            Tree ring\n",
      "  119:               XCHSIC,           China (CH),            Tree ring\n",
      "  120:               DAOSIC,           China (CH),            Tree ring\n",
      "  121:               MAXSIC,           China (CH),            Tree ring\n",
      "  122:               WXIYUN,           China (CH),            Tree ring\n",
      "  123:               DEZQIN,           China (CH),            Tree ring\n",
      "  124:               GOUQIN,           China (CH),            Tree ring\n",
      "  125:               HEBQIN,           China (CH),            Tree ring\n",
      "  126:               LAJQIN,           China (CH),            Tree ring\n",
      "  127:               GHEGAN,           China (CH),            Tree ring\n",
      "  128:               DULAJP,           China (CH),            Tree ring\n",
      "  129:               SHENJP,           China (CH),            Tree ring\n",
      "  130:               DUSHJP,           China (CH),            Tree ring\n",
      "  131:               MQAXJP,           China (CH),            Tree ring\n",
      "  132:               MQBXJP,           China (CH),            Tree ring\n",
      "  133:               MQDXJP,           China (CH),            Tree ring\n",
      "  134:               MQFXJP,           China (CH),            Tree ring\n",
      "  135:               MQRXJP,           China (CH),            Tree ring\n",
      "  136:               TDAXJP,           China (CH),            Tree ring\n",
      "  137:               TDBXJP,           China (CH),            Tree ring\n",
      "  138:               HBLXJP,           China (CH),            Tree ring\n",
      "  139:               HBMXJP,           China (CH),            Tree ring\n",
      "  140:               HBHXJP,           China (CH),            Tree ring\n",
      "  141:               BARELC,           China (CH),            Tree ring\n",
      "  142:               HUASPI,           China (CH),            Tree ring\n",
      "  143:               SANGTS,           China (CH),            Tree ring\n",
      "  144:               BLKALS,           China (CH),            Tree ring\n",
      "  145:               TIANMU,           China (CH),            Tree ring\n",
      "  146:               WULANJ,           China (CH),            Tree ring\n",
      "  147:               QUMAJP,           China (CH),            Tree ring\n",
      "  148:               ZHIDJP,           China (CH),            Tree ring\n",
      "  149:               ZHANGX,           China (CH),            Tree ring\n",
      "  150:               XIANGC,           China (CH),            Tree ring\n",
      "  151:               BAWSIC,           China (CH),            Tree ring\n",
      "  152:               PTCYUN,           China (CH),            Tree ring\n",
      "  153:               WEXYUN,           China (CH),            Tree ring\n",
      "  154:               HXBURU,           China (CH),            Tree ring\n",
      "  155:               DQHZHO,           China (CH),            Tree ring\n",
      "  156:               SMASLY,           China (CH),            Tree ring\n",
      "  157:               HYGJUP,           China (CH),            Tree ring\n",
      "  158:               MQACJP,           China (CH),            Tree ring\n",
      "  159:               10GK_P,           China (CH),            Tree ring\n",
      "  160:               11YC_T,           China (CH),            Tree ring\n",
      "  161:               12YM_A,           China (CH),            Tree ring\n",
      "  162:               13YE_T,           China (CH),            Tree ring\n",
      "  163:               22DL_T,           China (CH),            Tree ring\n",
      "  164:                 DLH1,           China (CH),            Tree ring\n",
      "  165:                 DLH2,           China (CH),            Tree ring\n",
      "  166:                 DLH3,           China (CH),            Tree ring\n",
      "  167:                 DLH4,           China (CH),            Tree ring\n",
      "  168:                 DLH5,           China (CH),            Tree ring\n",
      "  169:                 DLH6,           China (CH),            Tree ring\n",
      "  170:                  HSE,           China (CH),            Tree ring\n",
      "  171:                  HSS,           China (CH),            Tree ring\n",
      "  172:                  HSW,           China (CH),            Tree ring\n",
      "  173:                  QML,           China (CH),            Tree ring\n",
      "  174:                  TJ1,           China (CH),            Tree ring\n",
      "  175:                  WL1,           China (CH),            Tree ring\n",
      "  176:                  WL2,           China (CH),            Tree ring\n",
      "  177:                  WL3,           China (CH),            Tree ring\n",
      "  178:                  WL4,           China (CH),            Tree ring\n",
      "  179:                 ZD31,           China (CH),            Tree ring\n",
      "  180:                  ZHD,           China (CH),            Tree ring\n",
      "  181:               MUNATG,       Indonesia (ID),            Tree ring\n",
      "  182:               GANGCD,           India (IN),            Tree ring\n",
      "  183:               RANGCD,           India (IN),            Tree ring\n",
      "  184:               NARKAB,           India (IN),            Tree ring\n",
      "  185:               NARANG,           India (IN),            Tree ring\n",
      "  186:               KERALA,           India (IN),            Tree ring\n",
      "  187:                JANCD,           India (IN),            Tree ring\n",
      "  188:               MTASSP,           Japan (JP),            Tree ring\n",
      "  189:               MTASMD,           Japan (JP),            Tree ring\n",
      "  190:               KUNASH,           Japan (JP),            Tree ring\n",
      "  191:                  YKS,           Japan (JP),            Tree ring\n",
      "  192:                  MSR,           Japan (JP),            Tree ring\n",
      "  193:                  ONB,           Japan (JP),            Tree ring\n",
      "  194:                  SJT,           Japan (JP),            Tree ring\n",
      "  195:                  TKC,           Japan (JP),            Tree ring\n",
      "  196:                  TSO,           Japan (JP),            Tree ring\n",
      "  197:                YKCOM,           Japan (JP),            Tree ring\n",
      "  198:                  YKA,           Japan (JP),            Tree ring\n",
      "  199:                  YKC,           Japan (JP),            Tree ring\n",
      "  200:                  KMD,           Japan (JP),            Tree ring\n",
      "  201:               BONKJT,       Kyrgystan (KG),            Tree ring\n",
      "  202:               GEFKJT,       Kyrgystan (KG),            Tree ring\n",
      "  203:               GRAKJT,       Kyrgystan (KG),            Tree ring\n",
      "  204:               HOCKJT,       Kyrgystan (KG),            Tree ring\n",
      "  205:               MURKJT,       Kyrgystan (KG),            Tree ring\n",
      "  206:               AJTMJT,       Kyrgystan (KG),            Tree ring\n",
      "  207:               KJTRJT,       Kyrgystan (KG),            Tree ring\n",
      "  208:               MJTQJT,       Kyrgystan (KG),            Tree ring\n",
      "  209:               XJTCJT,       Kyrgystan (KG),            Tree ring\n",
      "  210:               SHIYAT,       Kyrgystan (KG),            Tree ring\n",
      "  211:               ESPERG,       Kyrgystan (KG),            Tree ring\n",
      "  212:               SHIESP,       Kyrgystan (KG),            Tree ring\n",
      "  213:               KRNKAM,       Kamchatka (KM),            Tree ring\n",
      "  214:               ULKEPS,      Kazakhstan (KZ),            Tree ring\n",
      "  215:               KOELIU,      Kazakhstan (KZ),            Tree ring\n",
      "  216:               ENGILC,      Kazakhstan (KZ),            Tree ring\n",
      "  217:               KOKKIY,      Kazakhstan (KZ),            Tree ring\n",
      "  218:               NANENG,      Kazakhstan (KZ),            Tree ring\n",
      "  219:               ANKHLS,        Mongolia (MG),            Tree ring\n",
      "  220:               BAYHLS,        Mongolia (MG),            Tree ring\n",
      "  221:               BIGELS,        Mongolia (MG),            Tree ring\n",
      "  222:               BIARLS,        Mongolia (MG),            Tree ring\n",
      "  223:               BULGLS,        Mongolia (MG),            Tree ring\n",
      "  224:               DAYNLS,        Mongolia (MG),            Tree ring\n",
      "  225:               HENTLS,        Mongolia (MG),            Tree ring\n",
      "  226:               HORBLS,        Mongolia (MG),            Tree ring\n",
      "  227:               KHELLS,        Mongolia (MG),            Tree ring\n",
      "  228:               KHOGLS,        Mongolia (MG),            Tree ring\n",
      "  229:               KHOTLS,        Mongolia (MG),            Tree ring\n",
      "  230:               KHOVLS,        Mongolia (MG),            Tree ring\n",
      "  231:               MANDLS,        Mongolia (MG),            Tree ring\n",
      "  232:               MANHPS,        Mongolia (MG),            Tree ring\n",
      "  233:               ONONLS,        Mongolia (MG),            Tree ring\n",
      "  234:               OVOOLS,        Mongolia (MG),            Tree ring\n",
      "  235:               SODAPS,        Mongolia (MG),            Tree ring\n",
      "  236:               SPKRLS,        Mongolia (MG),            Tree ring\n",
      "  237:               SUBALS,        Mongolia (MG),            Tree ring\n",
      "  238:               SUMELS,        Mongolia (MG),            Tree ring\n",
      "  239:               TUCHLS,        Mongolia (MG),            Tree ring\n",
      "  240:               UNDULS,        Mongolia (MG),            Tree ring\n",
      "  241:               ZMGLPS,        Mongolia (MG),            Tree ring\n",
      "  242:               ZNMDLS,        Mongolia (MG),            Tree ring\n",
      "  243:               ZSMDLS,        Mongolia (MG),            Tree ring\n",
      "  244:               ZURTLS,        Mongolia (MG),            Tree ring\n",
      "  245:               Hushre,        Mongolia (MG),            Tree ring\n",
      "  246:               TERELJ,        Mongolia (MG),            Tree ring\n",
      "  247:               AGHERI,           Nepal (NP),            Tree ring\n",
      "  248:               BHULJR,           Nepal (NP),            Tree ring\n",
      "  249:               CHDAND,           Nepal (NP),            Tree ring\n",
      "  250:               DEORLA,           Nepal (NP),            Tree ring\n",
      "  251:               DDANJR,           Nepal (NP),            Tree ring\n",
      "  252:               GHURCH,           Nepal (NP),            Tree ring\n",
      "  253:               KATKUW,           Nepal (NP),            Tree ring\n",
      "  254:               LANGTD,           Nepal (NP),            Tree ring\n",
      "  255:               LUKUTD,           Nepal (NP),            Tree ring\n",
      "  256:               MUMBAS,           Nepal (NP),            Tree ring\n",
      "  257:               RACHAS,           Nepal (NP),            Tree ring\n",
      "  258:               BURGPW,           Nepal (NP),            Tree ring\n",
      "  259:               GHUNAB,           Nepal (NP),            Tree ring\n",
      "  260:               LAMIAB,           Nepal (NP),            Tree ring\n",
      "  261:               YAKHTD,           Nepal (NP),            Tree ring\n",
      "  262:               ENEPAB,           Nepal (NP),            Tree ring\n",
      "  263:               ESPPAK,        Pakistan (PK),            Tree ring\n",
      "  264:               ASTABP,        Pakistan (PK),            Tree ring\n",
      "  265:               ASTPIW,        Pakistan (PK),            Tree ring\n",
      "  266:               BAG1JU,        Pakistan (PK),            Tree ring\n",
      "  267:               BAG2JU,        Pakistan (PK),            Tree ring\n",
      "  268:               BAG4JU,        Pakistan (PK),            Tree ring\n",
      "  269:               BAG5JU,        Pakistan (PK),            Tree ring\n",
      "  270:               BUKCDD,        Pakistan (PK),            Tree ring\n",
      "  271:               BUKPIG,        Pakistan (PK),            Tree ring\n",
      "  272:               CGPCDD,        Pakistan (PK),            Tree ring\n",
      "  273:               CGPPIG,        Pakistan (PK),            Tree ring\n",
      "  274:               CHEPCS,        Pakistan (PK),            Tree ring\n",
      "  275:               CHP2JU,        Pakistan (PK),            Tree ring\n",
      "  276:               CHP3JU,        Pakistan (PK),            Tree ring\n",
      "  277:               DskJUE,        Pakistan (PK),            Tree ring\n",
      "  278:               ISBCDD,        Pakistan (PK),            Tree ring\n",
      "  279:               JOTPIG,        Pakistan (PK),            Tree ring\n",
      "  280:               JUTPCS,        Pakistan (PK),            Tree ring\n",
      "  281:               KARPCS,        Pakistan (PK),            Tree ring\n",
      "  282:               MOR1JU,        Pakistan (PK),            Tree ring\n",
      "  283:               MOR2JU,        Pakistan (PK),            Tree ring\n",
      "  284:               MOR3JU,        Pakistan (PK),            Tree ring\n",
      "  285:               MOR4JU,        Pakistan (PK),            Tree ring\n",
      "  286:               MSFCDD,        Pakistan (PK),            Tree ring\n",
      "  287:               MUSPIG,        Pakistan (PK),            Tree ring\n",
      "  288:               NLTJUE,        Pakistan (PK),            Tree ring\n",
      "  289:               NLTPCS,        Pakistan (PK),            Tree ring\n",
      "  290:               SAT1JU,        Pakistan (PK),            Tree ring\n",
      "  291:               SAT2JU,        Pakistan (PK),            Tree ring\n",
      "  292:               SAT3JU,        Pakistan (PK),            Tree ring\n",
      "  293:               TKACDD,        Pakistan (PK),            Tree ring\n",
      "  294:               ZACCDD,        Pakistan (PK),            Tree ring\n",
      "  295:               HRPCSM,        Pakistan (PK),            Tree ring\n",
      "  296:               NOGSAK, Sakhalin Island (SK),            Tree ring\n",
      "  297:               CHOLPB,           Tibet (TB),            Tree ring\n",
      "  298:               QAMDPB,           Tibet (TB),            Tree ring\n",
      "  299:               RIWOPB,           Tibet (TB),            Tree ring\n",
      "  300:               DENSJT,           Tibet (TB),            Tree ring\n",
      "  301:               QAMDJT,           Tibet (TB),            Tree ring\n",
      "  302:               MAINJT,           Tibet (TB),            Tree ring\n",
      "  303:               NYINJT,           Tibet (TB),            Tree ring\n",
      "  304:               RETIJT,           Tibet (TB),            Tree ring\n",
      "  305:               CENTIB,           Tibet (TB),            Tree ring\n",
      "  306:               MHGSTG,        Thailand (TH),            Tree ring\n",
      "  307:               CILAUP,          Taiwan (TW),            Tree ring\n",
      "  308:               MCCHFH,         Vietnam (VM),            Tree ring\n",
      "  309:               BDFLON,         Vietnam (VM),            Tree ring\n",
      "  310:              Mt Read,            Australia,            Tree ring\n",
      "  311:                Oroko,          New Zealand,            Tree ring\n",
      "  312:              Palmyra,    Northern Line Ids,                Coral\n",
      "  313: Celery Top Pine East,            Australia,            Tree ring\n",
      "  314:            Pink Pine,          New Zealand,            Tree ring\n",
      "  315:              Urewera,          New Zealand,            Tree ring\n",
      "  316:     Buckley's Chance,            Australia,            Tree ring\n",
      "  317: North Island_LIBI_Composite_1,          New Zealand,            Tree ring\n",
      "  318: Celery Top Pine West,            Australia,            Tree ring\n",
      "  319:           Mangawhero,          New Zealand,            Tree ring\n",
      "  320:                Kauri,          New Zealand,            Tree ring\n",
      "  321:              Fiji_AB,                 Fiji,                Coral\n",
      "  322:  NI_LIBI_Composite_2,          New Zealand,            Tree ring\n",
      "  323:        New_Caledonia,        New Caledonia,                Coral\n",
      "  324: Stewart_Island_HABI_composite,          New Zealand,            Tree ring\n",
      "  325:            Rarotonga,         Cook Islands,                Coral\n",
      "  326: Great Barrier Reef Rainfall recon,            Australia,                Coral\n",
      "  327:             Havannah,            Australia,                Coral\n",
      "  328:              Fiji_1F,                 Fiji,                Coral\n",
      "  329:                  Moa,          New Zealand,            Tree ring\n",
      "  330:             Abrolhos,            Australia,                Coral\n",
      "  331:             Savusavu,                 Fiji,                Coral\n",
      "  332:              Bunaken,            Indonesia,                Coral\n",
      "  333:         Rarotonga.3R,         Cook Islands,                Coral\n",
      "  334:               BawBaw,            Australia,            Tree ring\n",
      "  335:               Avaiki,                 Niue,           Speleothem\n",
      "  336:                Laing,     Papua New Guinea,                Coral\n",
      "  337:             Ningaloo,             Ningaloo,                Coral\n"
     ]
    }
   ],
   "source": [
    "# We can write some code to search the metadata for a proxy we're interested in.\n",
    "#search_string = 'Europe'\n",
    "#field_to_search = 'PAGES 2k Region'\n",
    "\n",
    "search_string = 'Asia'\n",
    "field_to_search = 'PAGES 2k Region'\n",
    "\n",
    "#search_string = \"Ice Core\"\n",
    "#field_to_search = \"Archive type\"\n",
    "\n",
    "#search_string = 'lake'\n",
    "#field_to_search = 'Archive type'\n",
    "\n",
    "# Loop through every key.  If part of the key matches the the search string, print the index and the key.\n",
    "n_proxies = metadata.shape[0]\n",
    "print('%5s: %20s: %20s: %20s:' % ('index','Site','Country/Region','Archive type'))\n",
    "for i in range(n_proxies):\n",
    "    if isinstance(metadata.loc[i][field_to_search], str):\n",
    "        if search_string.lower() in metadata.loc[i][field_to_search].lower():\n",
    "            print('%5s: %20s, %20s, %20s' % (i, metadata.loc[i]['Site'], metadata.loc[i]['Country/Region'],\\\n",
    "                                              metadata.loc[i]['Archive type']))\n",
    "            \n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Choose the index of a record you're interested in.\n",
    "index_selected = 101\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            PAGES 2k Region :                 Asia\n",
      "                   Proxy ID :              Asi_021\n",
      "             Country/Region : Altai Mountains (AT)\n",
      "                       Area :              RUSS139\n",
      "                       Site :               UKHEWD\n",
      "                    Lat (N) :                50.15\n",
      "                    Lon (E) :     85.3666666666667\n",
      "               Archive type :            Tree ring\n",
      "          Proxy measurement :    Earlywood density\n",
      "           Proxy other info :                  nan\n",
      "      Sign relation to temp :             Positive\n",
      "              Oldest (C.E.) :               1581.0\n",
      "            Youngest (C.E.) :               1994.0\n",
      "            Resolution (yr) :                  1.0\n",
      "                  Reference :    Schweingruber, FH\n"
     ]
    }
   ],
   "source": [
    "# Loop through every element of the metadata and print it to screen.\n",
    "for key in metadata.keys():\n",
    "    print('%27s : %20s' % (key, metadata.loc[index_selected][key]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Asi_021\n"
     ]
    }
   ],
   "source": [
    "# Get the key of the desired record.\n",
    "proxyID_selected = metadata.loc[index_selected]['Proxy ID']\n",
    "print(proxyID_selected)\n",
    "\n",
    "# Get the data for this record.\n",
    "proxy_data = proxies[proxyID_selected]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save some useful metadata to new variables.\n",
    "reference    = metadata.loc[index_selected]['Reference']\n",
    "site_name    = metadata.loc[index_selected]['Site']\n",
    "lat          = metadata.loc[index_selected]['Lat (N)']\n",
    "lon          = metadata.loc[index_selected]['Lon (E)']\n",
    "archive_type = metadata.loc[index_selected]['Archive type']\n",
    "measurement  = metadata.loc[index_selected]['Proxy measurement']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a figure of the proxy record.\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "plt.figure(figsize=(15,5))\n",
    "ax = plt.axes([.1,.1,.8,.8])\n",
    "plt.plot(proxy_data,color='k',marker='o',linewidth=1)\n",
    "plt.title(str(site_name)+\" (\"+str(archive_type)+\").  Lat: \"+str(lat)+\"$^\\circ$N, Lon: \"+\\\n",
    "          str(lon)+\"$^\\circ$E\\nReference: \"+reference[0:100])\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(measurement)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Further exploration\n",
    "\n",
    "Search for a different record and look at the results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Discussion\n",
    "\n",
    "Use of data from both proxy records and climate models is crucial to the advancement of paleoclimate research.\n",
    "* How many of you primarily work with proxy records?\n",
    "* How many of you primarily work with model output?\n",
    "* Do you often use data from both areas?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "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",
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