11072022.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "69e42b5c-2520-4fd2-8a24-8e1479d8ced8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6973e57c-4269-4105-8a8a-f5022eb62304",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sqlite3 import connect\n",
    "opsim_db = connect('baseline_v2.0_10yrs.db')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c51337d1-b553-4cf2-b5b3-4182717d5bf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "opsim_file = pd.read_sql('select * from observations limit 1000', opsim_db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cc40390f-6800-4255-9948-0243b95764d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['observationId', 'fieldRA', 'fieldDec', 'observationStartMJD',\n",
       "       'flush_by_mjd', 'visitExposureTime', 'filter', 'rotSkyPos',\n",
       "       'numExposures', 'airmass', 'seeingFwhm500', 'seeingFwhmEff',\n",
       "       'seeingFwhmGeom', 'skyBrightness', 'night', 'slewTime', 'visitTime',\n",
       "       'slewDistance', 'fiveSigmaDepth', 'altitude', 'azimuth', 'paraAngle',\n",
       "       'cloud', 'moonAlt', 'sunAlt', 'note', 'fieldId', 'proposalId',\n",
       "       'block_id', 'observationStartLST', 'rotTelPos', 'moonAz', 'sunAz',\n",
       "       'sunRA', 'sunDec', 'moonRA', 'moonDec', 'moonDistance', 'solarElong',\n",
       "       'moonPhase', 'cummTelAz'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opsim_file.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "119a8657-02c2-41fd-80c1-1bc6a6d0af4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('observationId',\n",
       " 'fieldRA',\n",
       " 'fieldDec',\n",
       " 'observationStarMJD',\n",
       " 'fieldId',\n",
       " 'filter',\n",
       " 'fiveSigmaDepth')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'observationId', 'fieldRA', 'fieldDec', 'observationStarMJD', 'fieldId', 'filter', 'fiveSigmaDepth'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4b3278c3-9baa-4708-bfca-40972e16b11b",
   "metadata": {},
   "outputs": [],
   "source": [
    "r_band_observations = pd.read_sql_query('SELECT observationId, fieldRA, fieldDec, observationStartMJD,' +\n",
    "                                        'fieldId, filter, fiveSigmaDepth FROM observations WHERE filter == \"r\"', opsim_db)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bfa89f02-d26b-4e50-9782-0ddc4f1aa085",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>observationId</th>\n",
       "      <th>fieldRA</th>\n",
       "      <th>fieldDec</th>\n",
       "      <th>observationStartMJD</th>\n",
       "      <th>fieldId</th>\n",
       "      <th>filter</th>\n",
       "      <th>fiveSigmaDepth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>770</td>\n",
       "      <td>355.783117</td>\n",
       "      <td>-79.644018</td>\n",
       "      <td>60218.356921</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>22.039985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>771</td>\n",
       "      <td>338.205026</td>\n",
       "      <td>-80.387745</td>\n",
       "      <td>60218.357414</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>22.053388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>772</td>\n",
       "      <td>349.857034</td>\n",
       "      <td>-82.633511</td>\n",
       "      <td>60218.357890</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>22.115278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>773</td>\n",
       "      <td>336.319706</td>\n",
       "      <td>-85.448079</td>\n",
       "      <td>60218.358364</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>22.025564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>774</td>\n",
       "      <td>9.600147</td>\n",
       "      <td>-87.474001</td>\n",
       "      <td>60218.358911</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>22.023105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464846</th>\n",
       "      <td>2086903</td>\n",
       "      <td>324.507982</td>\n",
       "      <td>-0.970535</td>\n",
       "      <td>63870.068633</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>23.669905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464847</th>\n",
       "      <td>2086904</td>\n",
       "      <td>322.189374</td>\n",
       "      <td>0.548445</td>\n",
       "      <td>63870.069080</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>23.655921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464848</th>\n",
       "      <td>2086905</td>\n",
       "      <td>319.880983</td>\n",
       "      <td>2.065350</td>\n",
       "      <td>63870.069526</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>23.635941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464849</th>\n",
       "      <td>2086906</td>\n",
       "      <td>322.437543</td>\n",
       "      <td>3.728057</td>\n",
       "      <td>63870.069973</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>23.508767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464850</th>\n",
       "      <td>2086907</td>\n",
       "      <td>324.779111</td>\n",
       "      <td>2.195206</td>\n",
       "      <td>63870.070420</td>\n",
       "      <td>-1</td>\n",
       "      <td>r</td>\n",
       "      <td>23.525283</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>464851 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        observationId     fieldRA   fieldDec  observationStartMJD  fieldId  \\\n",
       "0                 770  355.783117 -79.644018         60218.356921       -1   \n",
       "1                 771  338.205026 -80.387745         60218.357414       -1   \n",
       "2                 772  349.857034 -82.633511         60218.357890       -1   \n",
       "3                 773  336.319706 -85.448079         60218.358364       -1   \n",
       "4                 774    9.600147 -87.474001         60218.358911       -1   \n",
       "...               ...         ...        ...                  ...      ...   \n",
       "464846        2086903  324.507982  -0.970535         63870.068633       -1   \n",
       "464847        2086904  322.189374   0.548445         63870.069080       -1   \n",
       "464848        2086905  319.880983   2.065350         63870.069526       -1   \n",
       "464849        2086906  322.437543   3.728057         63870.069973       -1   \n",
       "464850        2086907  324.779111   2.195206         63870.070420       -1   \n",
       "\n",
       "       filter  fiveSigmaDepth  \n",
       "0           r       22.039985  \n",
       "1           r       22.053388  \n",
       "2           r       22.115278  \n",
       "3           r       22.025564  \n",
       "4           r       22.023105  \n",
       "...       ...             ...  \n",
       "464846      r       23.669905  \n",
       "464847      r       23.655921  \n",
       "464848      r       23.635941  \n",
       "464849      r       23.508767  \n",
       "464850      r       23.525283  \n",
       "\n",
       "[464851 rows x 7 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_band_observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eb3570cc-6054-4aee-b823-22c8bc1e6a57",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib Inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "fa7da74d-2503-4074-a09e-2a8dc02e5d59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'DEC')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(r_band_observations['fieldRA'], r_band_observations['fieldDec'])\n",
    "plt.xlabel('RA')\n",
    "plt.ylabel('DEC')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fbfba7d7-540b-4272-a3d6-91dd8b02b360",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as npl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e73206d7-5513-47a7-90c3-2337380953b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7fddb2d99f70>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist2d(r_band_observations['fieldRA'], r_band_observations['fieldDec'], bins = 50, norm=npl.colors.LogNorm())\n",
    "plt.xlabel('RA')\n",
    "plt.ylabel('DEC')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "738afab7-44a3-4976-bf32-b579054bba58",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "19338753-b1f9-43c2-8320-116663ec3484",
   "metadata": {},
   "outputs": [],
   "source": [
    "find_max_RA = np.max(r_band_observations['fieldRA'])\n",
    "find_min_RA = np.min(r_band_observations['fieldRA'])\n",
    "find_max_DEC = np.max(r_band_observations['fieldDec'])\n",
    "find_min_DEC = np.min(r_band_observations['fieldDec'])\n",
    "num_bins = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b3583c76-26bf-439f-80d7-f432a3652c87",
   "metadata": {},
   "outputs": [],
   "source": [
    "RA_set = np.linspace(find_min_RA, find_max_RA, num_bins+1)\n",
    "DEC_set = np.linspace(find_min_DEC, find_max_DEC, num_bins+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "2608f772-8db2-4c5f-a273-cf758bd8f9c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([50, 47, 49, ..., 45, 45, 46])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RA_bins = np.digitize(r_band_observations['fieldRA'], RA_set, right=True)\n",
    "RA_bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c3cf51e5-9411-41d1-bdf3-87cee50fb50f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5,  4,  3, ..., 37, 38, 37])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DEC_bins = np.digitize(r_band_observations['fieldDec'], DEC_set, right=True)\n",
    "DEC_bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cf492276-2780-40bc-9eb5-fc2dedea6477",
   "metadata": {},
   "outputs": [],
   "source": [
    "r_band_observations['RABins'] = RA_bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "97844863-6eec-49dd-b3c9-9ca4a9b5c474",
   "metadata": {},
   "outputs": [],
   "source": [
    "r_band_observations['DECBins'] = DEC_bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "21dd8d20-7804-43ea-aa7c-2ca5a80e756a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>observationId</th>\n",
       "      <th>fieldRA</th>\n",
       "      <th>fieldDec</th>\n",
       "      <th>observationStartMJD</th>\n",
       "      <th>fieldId</th>\n",
       "      <th>filter</th>\n",
       "      <th>fiveSigmaDepth</th>\n",
       "      <th>RABins</th>\n",
       "      <th>DECBins</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>770</td>\n",
       "      <td>355.783117</td>\n",
       "      <td>-79.644018</td>\n",
       "      <td>60218.356921</td>\n",
       "      <td>2455</td>\n",
       "      <td>r</td>\n",
       "      <td>22.039985</td>\n",
       "      <td>50</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>771</td>\n",
       "      <td>338.205026</td>\n",
       "      <td>-80.387745</td>\n",
       "      <td>60218.357414</td>\n",
       "      <td>2304</td>\n",
       "      <td>r</td>\n",
       "      <td>22.053388</td>\n",
       "      <td>47</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>772</td>\n",
       "      <td>349.857034</td>\n",
       "      <td>-82.633511</td>\n",
       "      <td>60218.357890</td>\n",
       "      <td>2403</td>\n",
       "      <td>r</td>\n",
       "      <td>22.115278</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>773</td>\n",
       "      <td>336.319706</td>\n",
       "      <td>-85.448079</td>\n",
       "      <td>60218.358364</td>\n",
       "      <td>2302</td>\n",
       "      <td>r</td>\n",
       "      <td>22.025564</td>\n",
       "      <td>47</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>774</td>\n",
       "      <td>9.600147</td>\n",
       "      <td>-87.474001</td>\n",
       "      <td>60218.358911</td>\n",
       "      <td>51</td>\n",
       "      <td>r</td>\n",
       "      <td>22.023105</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464846</th>\n",
       "      <td>2086903</td>\n",
       "      <td>324.507982</td>\n",
       "      <td>-0.970535</td>\n",
       "      <td>63870.068633</td>\n",
       "      <td>2286</td>\n",
       "      <td>r</td>\n",
       "      <td>23.669905</td>\n",
       "      <td>46</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464847</th>\n",
       "      <td>2086904</td>\n",
       "      <td>322.189374</td>\n",
       "      <td>0.548445</td>\n",
       "      <td>63870.069080</td>\n",
       "      <td>2237</td>\n",
       "      <td>r</td>\n",
       "      <td>23.655921</td>\n",
       "      <td>45</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464848</th>\n",
       "      <td>2086905</td>\n",
       "      <td>319.880983</td>\n",
       "      <td>2.065350</td>\n",
       "      <td>63870.069526</td>\n",
       "      <td>2237</td>\n",
       "      <td>r</td>\n",
       "      <td>23.635941</td>\n",
       "      <td>45</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464849</th>\n",
       "      <td>2086906</td>\n",
       "      <td>322.437543</td>\n",
       "      <td>3.728057</td>\n",
       "      <td>63870.069973</td>\n",
       "      <td>2238</td>\n",
       "      <td>r</td>\n",
       "      <td>23.508767</td>\n",
       "      <td>45</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464850</th>\n",
       "      <td>2086907</td>\n",
       "      <td>324.779111</td>\n",
       "      <td>2.195206</td>\n",
       "      <td>63870.070420</td>\n",
       "      <td>2287</td>\n",
       "      <td>r</td>\n",
       "      <td>23.525283</td>\n",
       "      <td>46</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>464851 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        observationId     fieldRA   fieldDec  observationStartMJD  fieldId  \\\n",
       "0                 770  355.783117 -79.644018         60218.356921     2455   \n",
       "1                 771  338.205026 -80.387745         60218.357414     2304   \n",
       "2                 772  349.857034 -82.633511         60218.357890     2403   \n",
       "3                 773  336.319706 -85.448079         60218.358364     2302   \n",
       "4                 774    9.600147 -87.474001         60218.358911       51   \n",
       "...               ...         ...        ...                  ...      ...   \n",
       "464846        2086903  324.507982  -0.970535         63870.068633     2286   \n",
       "464847        2086904  322.189374   0.548445         63870.069080     2237   \n",
       "464848        2086905  319.880983   2.065350         63870.069526     2237   \n",
       "464849        2086906  322.437543   3.728057         63870.069973     2238   \n",
       "464850        2086907  324.779111   2.195206         63870.070420     2287   \n",
       "\n",
       "       filter  fiveSigmaDepth  RABins  DECBins  \n",
       "0           r       22.039985      50        5  \n",
       "1           r       22.053388      47        4  \n",
       "2           r       22.115278      49        3  \n",
       "3           r       22.025564      47        2  \n",
       "4           r       22.023105       2        1  \n",
       "...       ...             ...     ...      ...  \n",
       "464846      r       23.669905      46       36  \n",
       "464847      r       23.655921      45       37  \n",
       "464848      r       23.635941      45       37  \n",
       "464849      r       23.508767      45       38  \n",
       "464850      r       23.525283      46       37  \n",
       "\n",
       "[464851 rows x 9 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_field_id = (RA_bins-1) * 50 + DEC_bins\n",
    "r_band_observations['fieldId'] = new_field_id\n",
    "r_band_observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2e8715c6-46b0-4ed3-912e-ed2049d39bc6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>observationId</th>\n",
       "      <th>fieldRA</th>\n",
       "      <th>fieldDec</th>\n",
       "      <th>observationStartMJD</th>\n",
       "      <th>fieldId</th>\n",
       "      <th>filter</th>\n",
       "      <th>fiveSigmaDepth</th>\n",
       "      <th>RABins</th>\n",
       "      <th>DECBins</th>\n",
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       "      <th>2</th>\n",
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       "      <td>349.857034</td>\n",
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       "      <td>60218.357890</td>\n",
       "      <td>2403</td>\n",
       "      <td>r</td>\n",
       "      <td>22.115278</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>187117</th>\n",
       "      <td>846124</td>\n",
       "      <td>349.132762</td>\n",
       "      <td>-83.345848</td>\n",
       "      <td>61682.142242</td>\n",
       "      <td>2403</td>\n",
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       "      <td>49</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>189023</th>\n",
       "      <td>860288</td>\n",
       "      <td>349.770490</td>\n",
       "      <td>-84.147058</td>\n",
       "      <td>61703.077226</td>\n",
       "      <td>2403</td>\n",
       "      <td>r</td>\n",
       "      <td>23.336416</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>373690</th>\n",
       "      <td>1680668</td>\n",
       "      <td>349.123067</td>\n",
       "      <td>-82.933787</td>\n",
       "      <td>63159.185750</td>\n",
       "      <td>2403</td>\n",
       "      <td>r</td>\n",
       "      <td>23.423731</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416803</th>\n",
       "      <td>1875208</td>\n",
       "      <td>346.865503</td>\n",
       "      <td>-83.230118</td>\n",
       "      <td>63536.152786</td>\n",
       "      <td>2403</td>\n",
       "      <td>r</td>\n",
       "      <td>23.918868</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        observationId     fieldRA   fieldDec  observationStartMJD  fieldId  \\\n",
       "2                 772  349.857034 -82.633511         60218.357890     2403   \n",
       "187117         846124  349.132762 -83.345848         61682.142242     2403   \n",
       "189023         860288  349.770490 -84.147058         61703.077226     2403   \n",
       "373690        1680668  349.123067 -82.933787         63159.185750     2403   \n",
       "416803        1875208  346.865503 -83.230118         63536.152786     2403   \n",
       "\n",
       "       filter  fiveSigmaDepth  RABins  DECBins  \n",
       "2           r       22.115278      49        3  \n",
       "187117      r       23.833470      49        3  \n",
       "189023      r       23.336416      49        3  \n",
       "373690      r       23.423731      49        3  \n",
       "416803      r       23.918868      49        3  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r_band_observations.query('fieldId == 2403')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f338e3f-bf45-4d9b-805d-1a7c9bb3d775",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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