Second_Question.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = open(\"data/temp.txt\", \"w\")\n",
    "\n",
    "with open(\"data/Dataset.txt\") as file:\n",
    "    for line in file:\n",
    "        if line[0] != '#':\n",
    "            f.write(line)\n",
    "\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>27</th>\n",
       "      <th>28</th>\n",
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       "      <th>30</th>\n",
       "      <th>31</th>\n",
       "      <th>32</th>\n",
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       "      <th>34</th>\n",
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       "      <th>36</th>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7111.1323</td>\n",
       "      <td>1756.4988</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.9999</td>\n",
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       "      <td>0</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.9991</td>\n",
       "      <td>-0.0041</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.522096</td>\n",
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       "      <td>R0000002</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6884.0669</td>\n",
       "      <td>1784.6356</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.9997</td>\n",
       "      <td>-0.0023</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.524928</td>\n",
       "      <td>28.341980</td>\n",
       "      <td>R0000003</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6604.6484</td>\n",
       "      <td>1786.4238</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.0</td>\n",
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       "      <th>4</th>\n",
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       "      <td>1819.0413</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.9999</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>99.9999</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>99</td>\n",
       "      <td>99</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.519938</td>\n",
       "      <td>28.342358</td>\n",
       "      <td>R0000005</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0          1        2        3    4       5   6   7        8   \\\n",
       "0  6954.4673  1738.9973 -99.9999  99.9999  0.0  9.9999   0   0 -99.9999   \n",
       "1  7111.1323  1756.4988 -99.9999  99.9999  0.0  9.9999   0   0 -99.9999   \n",
       "2  6884.0669  1784.6356 -99.9999  99.9999  0.0  9.9999   0   0 -99.9999   \n",
       "3  6604.6484  1786.4238 -99.9999  99.9999  0.0  9.9999   0   0 -99.9999   \n",
       "4  7284.2275  1819.0413 -99.9999  99.9999  0.0  9.9999   0   0 -99.9999   \n",
       "\n",
       "        9  ...   27      28      29  30  31   32          33         34  \\\n",
       "0  99.9999 ...  0.0  0.9999  0.0085   1   1 -1.0  205.524050  28.341480   \n",
       "1  99.9999 ...  0.0  0.9991 -0.0041   1   1 -1.0  205.522096  28.341672   \n",
       "2  99.9999 ...  0.0  0.9997 -0.0023   1   1 -1.0  205.524928  28.341980   \n",
       "3  99.9999 ...  0.0  1.0000  0.0086   1   1 -1.0  205.528412  28.342000   \n",
       "4  99.9999 ...  0.0  1.0000  0.0000  99  99 -1.0  205.519938  28.342358   \n",
       "\n",
       "         35  36  \n",
       "0  R0000001   1  \n",
       "1  R0000002   1  \n",
       "2  R0000003   1  \n",
       "3  R0000004   1  \n",
       "4  R0000005   1  \n",
       "\n",
       "[5 rows x 37 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_df = pd.read_csv('data/temp.txt', header=None, delimiter=r\"\\s+\")\n",
    "raw_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>f275w</th>\n",
       "      <th>f336w</th>\n",
       "      <th>f438w</th>\n",
       "      <th>f606w</th>\n",
       "      <th>f814w</th>\n",
       "      <th>prob</th>\n",
       "      <th>ra</th>\n",
       "      <th>dec</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>199621.000000</td>\n",
       "      <td>199621.000000</td>\n",
       "      <td>199621.000000</td>\n",
       "      <td>199621.000000</td>\n",
       "      <td>199621.000000</td>\n",
       "      <td>199621.000000</td>\n",
       "      <td>199621.000000</td>\n",
       "      <td>199621.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-20.770262</td>\n",
       "      <td>-8.363505</td>\n",
       "      <td>-8.390557</td>\n",
       "      <td>22.361134</td>\n",
       "      <td>21.434464</td>\n",
       "      <td>35.983431</td>\n",
       "      <td>205.547639</td>\n",
       "      <td>28.376351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>59.867925</td>\n",
       "      <td>54.505959</td>\n",
       "      <td>54.276369</td>\n",
       "      <td>8.054891</td>\n",
       "      <td>7.722576</td>\n",
       "      <td>47.294623</td>\n",
       "      <td>0.016237</td>\n",
       "      <td>0.014153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-99.999900</td>\n",
       "      <td>-99.999900</td>\n",
       "      <td>-99.999900</td>\n",
       "      <td>-99.999900</td>\n",
       "      <td>-99.999900</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>205.509822</td>\n",
       "      <td>28.340981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-99.999900</td>\n",
       "      <td>-99.999900</td>\n",
       "      <td>-99.999900</td>\n",
       "      <td>21.159400</td>\n",
       "      <td>20.510800</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>205.535806</td>\n",
       "      <td>28.366189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>21.428100</td>\n",
       "      <td>22.146700</td>\n",
       "      <td>22.281100</td>\n",
       "      <td>23.233600</td>\n",
       "      <td>22.206800</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>205.547975</td>\n",
       "      <td>28.376667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>26.051500</td>\n",
       "      <td>26.057700</td>\n",
       "      <td>25.366100</td>\n",
       "      <td>24.601000</td>\n",
       "      <td>23.380000</td>\n",
       "      <td>96.800000</td>\n",
       "      <td>205.559631</td>\n",
       "      <td>28.386789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>28.958100</td>\n",
       "      <td>29.655600</td>\n",
       "      <td>28.873300</td>\n",
       "      <td>31.504600</td>\n",
       "      <td>30.860600</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>205.584904</td>\n",
       "      <td>28.409850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               f275w          f336w          f438w          f606w  \\\n",
       "count  199621.000000  199621.000000  199621.000000  199621.000000   \n",
       "mean      -20.770262      -8.363505      -8.390557      22.361134   \n",
       "std        59.867925      54.505959      54.276369       8.054891   \n",
       "min       -99.999900     -99.999900     -99.999900     -99.999900   \n",
       "25%       -99.999900     -99.999900     -99.999900      21.159400   \n",
       "50%        21.428100      22.146700      22.281100      23.233600   \n",
       "75%        26.051500      26.057700      25.366100      24.601000   \n",
       "max        28.958100      29.655600      28.873300      31.504600   \n",
       "\n",
       "               f814w           prob             ra            dec  \n",
       "count  199621.000000  199621.000000  199621.000000  199621.000000  \n",
       "mean       21.434464      35.983431     205.547639      28.376351  \n",
       "std         7.722576      47.294623       0.016237       0.014153  \n",
       "min       -99.999900      -1.000000     205.509822      28.340981  \n",
       "25%        20.510800      -1.000000     205.535806      28.366189  \n",
       "50%        22.206800      -1.000000     205.547975      28.376667  \n",
       "75%        23.380000      96.800000     205.559631      28.386789  \n",
       "max        30.860600     100.000000     205.584904      28.409850  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cols = [2,8,14,20,26,32,33,34,35]\n",
    "df = raw_df.iloc[:,cols]\n",
    "df.columns = ['f275w', 'f336w', 'f438w', 'f606w', 'f814w', 'prob', 'ra', 'dec', 'id']\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_bol = df.loc[df['f606w'] >= (22-5*np.log10(1040))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "B = df_bol['f438w']\n",
    "V = df_bol['f606w']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = 10.4 * 100\n",
    "m_V = B['f606w'] - (5* np.log10(d)) \n",
    "m_V = m_V * -1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "B = df_bol.loc[df_bol['f438w']>= -20]\n",
    "# V = V.loc[V <= 10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "col_ind = B['f438w']-B['f606w']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>f275w</th>\n",
       "      <th>f336w</th>\n",
       "      <th>f438w</th>\n",
       "      <th>f606w</th>\n",
       "      <th>f814w</th>\n",
       "      <th>prob</th>\n",
       "      <th>ra</th>\n",
       "      <th>dec</th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>19.7336</td>\n",
       "      <td>19.1845</td>\n",
       "      <td>19.6350</td>\n",
       "      <td>19.0066</td>\n",
       "      <td>18.5563</td>\n",
       "      <td>96.4</td>\n",
       "      <td>205.552568</td>\n",
       "      <td>28.347170</td>\n",
       "      <td>R0000084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>19.7651</td>\n",
       "      <td>19.1469</td>\n",
       "      <td>19.5783</td>\n",
       "      <td>19.0561</td>\n",
       "      <td>18.5919</td>\n",
       "      <td>96.8</td>\n",
       "      <td>205.551394</td>\n",
       "      <td>28.347580</td>\n",
       "      <td>R0000094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>17.1627</td>\n",
       "      <td>16.4142</td>\n",
       "      <td>16.4120</td>\n",
       "      <td>15.4551</td>\n",
       "      <td>15.1804</td>\n",
       "      <td>97.5</td>\n",
       "      <td>205.556762</td>\n",
       "      <td>28.347629</td>\n",
       "      <td>R0000095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>26.3212</td>\n",
       "      <td>25.7852</td>\n",
       "      <td>28.5586</td>\n",
       "      <td>17.2976</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.549609</td>\n",
       "      <td>28.347648</td>\n",
       "      <td>R0000096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>19.6349</td>\n",
       "      <td>19.1156</td>\n",
       "      <td>19.5415</td>\n",
       "      <td>18.9347</td>\n",
       "      <td>18.4765</td>\n",
       "      <td>98.2</td>\n",
       "      <td>205.561437</td>\n",
       "      <td>28.347709</td>\n",
       "      <td>R0000100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>19.4162</td>\n",
       "      <td>18.8070</td>\n",
       "      <td>19.2426</td>\n",
       "      <td>18.6414</td>\n",
       "      <td>18.1412</td>\n",
       "      <td>97.8</td>\n",
       "      <td>205.556696</td>\n",
       "      <td>28.347791</td>\n",
       "      <td>R0000103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>19.7894</td>\n",
       "      <td>19.2225</td>\n",
       "      <td>19.6021</td>\n",
       "      <td>19.1019</td>\n",
       "      <td>18.6533</td>\n",
       "      <td>97.7</td>\n",
       "      <td>205.560831</td>\n",
       "      <td>28.347829</td>\n",
       "      <td>R0000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>17.3228</td>\n",
       "      <td>16.1864</td>\n",
       "      <td>16.2136</td>\n",
       "      <td>15.2493</td>\n",
       "      <td>14.6038</td>\n",
       "      <td>96.2</td>\n",
       "      <td>205.552637</td>\n",
       "      <td>28.347855</td>\n",
       "      <td>R0000106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>19.4104</td>\n",
       "      <td>18.7785</td>\n",
       "      <td>19.1166</td>\n",
       "      <td>18.6104</td>\n",
       "      <td>18.1407</td>\n",
       "      <td>97.2</td>\n",
       "      <td>205.553763</td>\n",
       "      <td>28.348086</td>\n",
       "      <td>R0000111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>19.4401</td>\n",
       "      <td>18.9050</td>\n",
       "      <td>19.2176</td>\n",
       "      <td>18.6969</td>\n",
       "      <td>18.2133</td>\n",
       "      <td>96.5</td>\n",
       "      <td>205.562551</td>\n",
       "      <td>28.348136</td>\n",
       "      <td>R0000114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>19.5996</td>\n",
       "      <td>19.0400</td>\n",
       "      <td>19.3280</td>\n",
       "      <td>18.8366</td>\n",
       "      <td>18.3780</td>\n",
       "      <td>97.2</td>\n",
       "      <td>205.563133</td>\n",
       "      <td>28.348146</td>\n",
       "      <td>R0000115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>19.4013</td>\n",
       "      <td>18.7041</td>\n",
       "      <td>19.0919</td>\n",
       "      <td>18.4130</td>\n",
       "      <td>17.8746</td>\n",
       "      <td>91.1</td>\n",
       "      <td>205.557253</td>\n",
       "      <td>28.348151</td>\n",
       "      <td>R0000116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>19.7443</td>\n",
       "      <td>19.2459</td>\n",
       "      <td>19.8367</td>\n",
       "      <td>19.1747</td>\n",
       "      <td>18.7244</td>\n",
       "      <td>97.4</td>\n",
       "      <td>205.549573</td>\n",
       "      <td>28.348181</td>\n",
       "      <td>R0000117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>19.4124</td>\n",
       "      <td>18.7517</td>\n",
       "      <td>19.0682</td>\n",
       "      <td>18.4747</td>\n",
       "      <td>17.9528</td>\n",
       "      <td>96.0</td>\n",
       "      <td>205.560471</td>\n",
       "      <td>28.348336</td>\n",
       "      <td>R0000121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>19.4562</td>\n",
       "      <td>18.9454</td>\n",
       "      <td>19.4100</td>\n",
       "      <td>18.7990</td>\n",
       "      <td>18.3102</td>\n",
       "      <td>98.1</td>\n",
       "      <td>205.547290</td>\n",
       "      <td>28.348410</td>\n",
       "      <td>R0000122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>19.3152</td>\n",
       "      <td>18.1086</td>\n",
       "      <td>18.3127</td>\n",
       "      <td>17.4400</td>\n",
       "      <td>16.8163</td>\n",
       "      <td>97.0</td>\n",
       "      <td>205.561664</td>\n",
       "      <td>28.348414</td>\n",
       "      <td>R0000124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>19.6603</td>\n",
       "      <td>19.1160</td>\n",
       "      <td>19.5354</td>\n",
       "      <td>18.9532</td>\n",
       "      <td>18.4894</td>\n",
       "      <td>98.0</td>\n",
       "      <td>205.552785</td>\n",
       "      <td>28.348426</td>\n",
       "      <td>R0000125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>25.7723</td>\n",
       "      <td>25.9386</td>\n",
       "      <td>19.8867</td>\n",
       "      <td>17.7734</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.552986</td>\n",
       "      <td>28.348455</td>\n",
       "      <td>R0000126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>19.7297</td>\n",
       "      <td>19.1223</td>\n",
       "      <td>19.5194</td>\n",
       "      <td>18.9853</td>\n",
       "      <td>18.5166</td>\n",
       "      <td>97.7</td>\n",
       "      <td>205.558263</td>\n",
       "      <td>28.348468</td>\n",
       "      <td>R0000127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>27.4259</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>26.3905</td>\n",
       "      <td>26.9212</td>\n",
       "      <td>27.4738</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.556404</td>\n",
       "      <td>28.348557</td>\n",
       "      <td>R0000130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>19.7445</td>\n",
       "      <td>19.2050</td>\n",
       "      <td>19.5969</td>\n",
       "      <td>19.0140</td>\n",
       "      <td>18.5548</td>\n",
       "      <td>98.1</td>\n",
       "      <td>205.545539</td>\n",
       "      <td>28.348637</td>\n",
       "      <td>R0000131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>19.4689</td>\n",
       "      <td>18.9028</td>\n",
       "      <td>19.3339</td>\n",
       "      <td>18.7417</td>\n",
       "      <td>18.2671</td>\n",
       "      <td>97.0</td>\n",
       "      <td>205.545257</td>\n",
       "      <td>28.348848</td>\n",
       "      <td>R0000139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>19.7263</td>\n",
       "      <td>19.2201</td>\n",
       "      <td>19.6328</td>\n",
       "      <td>19.0526</td>\n",
       "      <td>18.6003</td>\n",
       "      <td>97.2</td>\n",
       "      <td>205.556425</td>\n",
       "      <td>28.348905</td>\n",
       "      <td>R0000140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>19.4116</td>\n",
       "      <td>18.7266</td>\n",
       "      <td>19.0291</td>\n",
       "      <td>18.4061</td>\n",
       "      <td>17.8662</td>\n",
       "      <td>98.0</td>\n",
       "      <td>205.566188</td>\n",
       "      <td>28.348960</td>\n",
       "      <td>R0000143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>19.3807</td>\n",
       "      <td>18.8025</td>\n",
       "      <td>19.1801</td>\n",
       "      <td>18.7677</td>\n",
       "      <td>18.2912</td>\n",
       "      <td>97.6</td>\n",
       "      <td>205.543555</td>\n",
       "      <td>28.348966</td>\n",
       "      <td>R0000144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>18.1898</td>\n",
       "      <td>16.5288</td>\n",
       "      <td>16.2997</td>\n",
       "      <td>15.2254</td>\n",
       "      <td>14.4783</td>\n",
       "      <td>97.7</td>\n",
       "      <td>205.546020</td>\n",
       "      <td>28.348973</td>\n",
       "      <td>R0000145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>19.6205</td>\n",
       "      <td>18.5562</td>\n",
       "      <td>18.6757</td>\n",
       "      <td>17.8827</td>\n",
       "      <td>17.2221</td>\n",
       "      <td>97.4</td>\n",
       "      <td>205.560207</td>\n",
       "      <td>28.349030</td>\n",
       "      <td>R0000148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>19.2789</td>\n",
       "      <td>18.8392</td>\n",
       "      <td>19.2016</td>\n",
       "      <td>18.7445</td>\n",
       "      <td>18.3175</td>\n",
       "      <td>98.0</td>\n",
       "      <td>205.556264</td>\n",
       "      <td>28.349032</td>\n",
       "      <td>R0000149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>19.3508</td>\n",
       "      <td>18.7430</td>\n",
       "      <td>19.1465</td>\n",
       "      <td>18.4677</td>\n",
       "      <td>17.9611</td>\n",
       "      <td>97.0</td>\n",
       "      <td>205.547457</td>\n",
       "      <td>28.349041</td>\n",
       "      <td>R0000150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>18.6154</td>\n",
       "      <td>17.2621</td>\n",
       "      <td>17.1581</td>\n",
       "      <td>16.2332</td>\n",
       "      <td>15.5452</td>\n",
       "      <td>97.2</td>\n",
       "      <td>205.564991</td>\n",
       "      <td>28.349050</td>\n",
       "      <td>R0000151</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>195927</th>\n",
       "      <td>28.8479</td>\n",
       "      <td>24.9733</td>\n",
       "      <td>24.1717</td>\n",
       "      <td>22.9389</td>\n",
       "      <td>21.9773</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538559</td>\n",
       "      <td>28.403387</td>\n",
       "      <td>R0196069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195930</th>\n",
       "      <td>25.8906</td>\n",
       "      <td>27.1536</td>\n",
       "      <td>26.1211</td>\n",
       "      <td>25.0688</td>\n",
       "      <td>23.5200</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538299</td>\n",
       "      <td>28.403147</td>\n",
       "      <td>R0196072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195931</th>\n",
       "      <td>26.8731</td>\n",
       "      <td>24.6483</td>\n",
       "      <td>22.8146</td>\n",
       "      <td>22.5045</td>\n",
       "      <td>21.6829</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538291</td>\n",
       "      <td>28.403351</td>\n",
       "      <td>R0196073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195932</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>25.8154</td>\n",
       "      <td>26.8278</td>\n",
       "      <td>23.5226</td>\n",
       "      <td>22.4604</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538135</td>\n",
       "      <td>28.402950</td>\n",
       "      <td>R0196074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195934</th>\n",
       "      <td>23.2747</td>\n",
       "      <td>21.9062</td>\n",
       "      <td>22.1769</td>\n",
       "      <td>21.2311</td>\n",
       "      <td>20.6197</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538101</td>\n",
       "      <td>28.403471</td>\n",
       "      <td>R0196076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195936</th>\n",
       "      <td>24.5381</td>\n",
       "      <td>22.5184</td>\n",
       "      <td>22.6060</td>\n",
       "      <td>21.7179</td>\n",
       "      <td>20.9602</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.537980</td>\n",
       "      <td>28.403025</td>\n",
       "      <td>R0196078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195938</th>\n",
       "      <td>20.5748</td>\n",
       "      <td>20.0178</td>\n",
       "      <td>20.3849</td>\n",
       "      <td>19.8366</td>\n",
       "      <td>19.3316</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.537872</td>\n",
       "      <td>28.403053</td>\n",
       "      <td>R0196080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195939</th>\n",
       "      <td>23.4440</td>\n",
       "      <td>22.0315</td>\n",
       "      <td>22.1138</td>\n",
       "      <td>21.2629</td>\n",
       "      <td>20.5760</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.537846</td>\n",
       "      <td>28.403572</td>\n",
       "      <td>R0196081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195940</th>\n",
       "      <td>23.3431</td>\n",
       "      <td>22.0135</td>\n",
       "      <td>21.9082</td>\n",
       "      <td>21.1607</td>\n",
       "      <td>20.5191</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.537792</td>\n",
       "      <td>28.403453</td>\n",
       "      <td>R0196082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195941</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>26.2291</td>\n",
       "      <td>27.5824</td>\n",
       "      <td>24.9876</td>\n",
       "      <td>24.2892</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.537635</td>\n",
       "      <td>28.403128</td>\n",
       "      <td>R0196083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195944</th>\n",
       "      <td>26.5454</td>\n",
       "      <td>26.3812</td>\n",
       "      <td>25.8235</td>\n",
       "      <td>24.2395</td>\n",
       "      <td>22.9003</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.537368</td>\n",
       "      <td>28.402924</td>\n",
       "      <td>R0196086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196005</th>\n",
       "      <td>22.5371</td>\n",
       "      <td>21.2592</td>\n",
       "      <td>21.8636</td>\n",
       "      <td>20.9402</td>\n",
       "      <td>20.2849</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.540091</td>\n",
       "      <td>28.402970</td>\n",
       "      <td>R0196147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196006</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>-99.9999</td>\n",
       "      <td>25.3626</td>\n",
       "      <td>24.5905</td>\n",
       "      <td>23.5217</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.540089</td>\n",
       "      <td>28.403063</td>\n",
       "      <td>R0196148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196007</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>27.3704</td>\n",
       "      <td>25.0716</td>\n",
       "      <td>23.8282</td>\n",
       "      <td>22.5753</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539950</td>\n",
       "      <td>28.402923</td>\n",
       "      <td>R0196149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196009</th>\n",
       "      <td>23.7874</td>\n",
       "      <td>22.4246</td>\n",
       "      <td>22.4938</td>\n",
       "      <td>21.4118</td>\n",
       "      <td>20.7172</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539889</td>\n",
       "      <td>28.403007</td>\n",
       "      <td>R0196151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196011</th>\n",
       "      <td>20.8231</td>\n",
       "      <td>20.2500</td>\n",
       "      <td>20.7412</td>\n",
       "      <td>20.0583</td>\n",
       "      <td>19.5617</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539822</td>\n",
       "      <td>28.403145</td>\n",
       "      <td>R0196153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196013</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>27.6998</td>\n",
       "      <td>24.9800</td>\n",
       "      <td>23.5291</td>\n",
       "      <td>22.4711</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539729</td>\n",
       "      <td>28.403157</td>\n",
       "      <td>R0196155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196016</th>\n",
       "      <td>-99.9999</td>\n",
       "      <td>23.4689</td>\n",
       "      <td>23.0418</td>\n",
       "      <td>22.0197</td>\n",
       "      <td>21.1958</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539689</td>\n",
       "      <td>28.403026</td>\n",
       "      <td>R0196158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196019</th>\n",
       "      <td>25.6736</td>\n",
       "      <td>25.4096</td>\n",
       "      <td>26.4324</td>\n",
       "      <td>23.8401</td>\n",
       "      <td>22.6428</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539598</td>\n",
       "      <td>28.403233</td>\n",
       "      <td>R0196161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196024</th>\n",
       "      <td>20.5632</td>\n",
       "      <td>19.9895</td>\n",
       "      <td>20.3509</td>\n",
       "      <td>19.7781</td>\n",
       "      <td>19.2844</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539287</td>\n",
       "      <td>28.403117</td>\n",
       "      <td>R0196166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196026</th>\n",
       "      <td>27.4505</td>\n",
       "      <td>26.0955</td>\n",
       "      <td>26.2159</td>\n",
       "      <td>24.4614</td>\n",
       "      <td>23.3314</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539164</td>\n",
       "      <td>28.403070</td>\n",
       "      <td>R0196168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196027</th>\n",
       "      <td>25.4356</td>\n",
       "      <td>25.1084</td>\n",
       "      <td>24.8104</td>\n",
       "      <td>22.8467</td>\n",
       "      <td>21.9544</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539146</td>\n",
       "      <td>28.403282</td>\n",
       "      <td>R0196169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196029</th>\n",
       "      <td>25.2907</td>\n",
       "      <td>24.4177</td>\n",
       "      <td>23.2334</td>\n",
       "      <td>22.4142</td>\n",
       "      <td>21.5396</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.539031</td>\n",
       "      <td>28.403316</td>\n",
       "      <td>R0196171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196030</th>\n",
       "      <td>23.1889</td>\n",
       "      <td>21.6824</td>\n",
       "      <td>21.9160</td>\n",
       "      <td>21.1518</td>\n",
       "      <td>20.4940</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538990</td>\n",
       "      <td>28.402931</td>\n",
       "      <td>R0196172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196031</th>\n",
       "      <td>27.3469</td>\n",
       "      <td>26.6540</td>\n",
       "      <td>24.7679</td>\n",
       "      <td>23.7177</td>\n",
       "      <td>22.6739</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538992</td>\n",
       "      <td>28.403156</td>\n",
       "      <td>R0196173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196033</th>\n",
       "      <td>20.0316</td>\n",
       "      <td>19.5036</td>\n",
       "      <td>20.0295</td>\n",
       "      <td>19.3486</td>\n",
       "      <td>18.8927</td>\n",
       "      <td>97.8</td>\n",
       "      <td>205.538880</td>\n",
       "      <td>28.403238</td>\n",
       "      <td>R0196175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196035</th>\n",
       "      <td>20.6603</td>\n",
       "      <td>19.9830</td>\n",
       "      <td>20.4825</td>\n",
       "      <td>19.8260</td>\n",
       "      <td>19.3329</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538809</td>\n",
       "      <td>28.402918</td>\n",
       "      <td>R0196177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196036</th>\n",
       "      <td>26.3942</td>\n",
       "      <td>25.5697</td>\n",
       "      <td>25.1925</td>\n",
       "      <td>23.4042</td>\n",
       "      <td>22.2002</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.538771</td>\n",
       "      <td>28.403361</td>\n",
       "      <td>R0196178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196100</th>\n",
       "      <td>25.2698</td>\n",
       "      <td>23.3010</td>\n",
       "      <td>23.2111</td>\n",
       "      <td>21.9687</td>\n",
       "      <td>21.2271</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.540601</td>\n",
       "      <td>28.402904</td>\n",
       "      <td>R0196242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196101</th>\n",
       "      <td>21.8553</td>\n",
       "      <td>20.9249</td>\n",
       "      <td>21.3116</td>\n",
       "      <td>20.6568</td>\n",
       "      <td>20.0745</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>205.540427</td>\n",
       "      <td>28.403035</td>\n",
       "      <td>R0196243</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>147409 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          f275w    f336w    f438w    f606w    f814w  prob          ra  \\\n",
       "83      19.7336  19.1845  19.6350  19.0066  18.5563  96.4  205.552568   \n",
       "93      19.7651  19.1469  19.5783  19.0561  18.5919  96.8  205.551394   \n",
       "94      17.1627  16.4142  16.4120  15.4551  15.1804  97.5  205.556762   \n",
       "95     -99.9999  26.3212  25.7852  28.5586  17.2976  -1.0  205.549609   \n",
       "99      19.6349  19.1156  19.5415  18.9347  18.4765  98.2  205.561437   \n",
       "102     19.4162  18.8070  19.2426  18.6414  18.1412  97.8  205.556696   \n",
       "104     19.7894  19.2225  19.6021  19.1019  18.6533  97.7  205.560831   \n",
       "105     17.3228  16.1864  16.2136  15.2493  14.6038  96.2  205.552637   \n",
       "110     19.4104  18.7785  19.1166  18.6104  18.1407  97.2  205.553763   \n",
       "113     19.4401  18.9050  19.2176  18.6969  18.2133  96.5  205.562551   \n",
       "114     19.5996  19.0400  19.3280  18.8366  18.3780  97.2  205.563133   \n",
       "115     19.4013  18.7041  19.0919  18.4130  17.8746  91.1  205.557253   \n",
       "116     19.7443  19.2459  19.8367  19.1747  18.7244  97.4  205.549573   \n",
       "120     19.4124  18.7517  19.0682  18.4747  17.9528  96.0  205.560471   \n",
       "121     19.4562  18.9454  19.4100  18.7990  18.3102  98.1  205.547290   \n",
       "123     19.3152  18.1086  18.3127  17.4400  16.8163  97.0  205.561664   \n",
       "124     19.6603  19.1160  19.5354  18.9532  18.4894  98.0  205.552785   \n",
       "125    -99.9999  25.7723  25.9386  19.8867  17.7734  -1.0  205.552986   \n",
       "126     19.7297  19.1223  19.5194  18.9853  18.5166  97.7  205.558263   \n",
       "129     27.4259 -99.9999  26.3905  26.9212  27.4738  -1.0  205.556404   \n",
       "130     19.7445  19.2050  19.5969  19.0140  18.5548  98.1  205.545539   \n",
       "138     19.4689  18.9028  19.3339  18.7417  18.2671  97.0  205.545257   \n",
       "139     19.7263  19.2201  19.6328  19.0526  18.6003  97.2  205.556425   \n",
       "142     19.4116  18.7266  19.0291  18.4061  17.8662  98.0  205.566188   \n",
       "143     19.3807  18.8025  19.1801  18.7677  18.2912  97.6  205.543555   \n",
       "144     18.1898  16.5288  16.2997  15.2254  14.4783  97.7  205.546020   \n",
       "147     19.6205  18.5562  18.6757  17.8827  17.2221  97.4  205.560207   \n",
       "148     19.2789  18.8392  19.2016  18.7445  18.3175  98.0  205.556264   \n",
       "149     19.3508  18.7430  19.1465  18.4677  17.9611  97.0  205.547457   \n",
       "150     18.6154  17.2621  17.1581  16.2332  15.5452  97.2  205.564991   \n",
       "...         ...      ...      ...      ...      ...   ...         ...   \n",
       "195927  28.8479  24.9733  24.1717  22.9389  21.9773  -1.0  205.538559   \n",
       "195930  25.8906  27.1536  26.1211  25.0688  23.5200  -1.0  205.538299   \n",
       "195931  26.8731  24.6483  22.8146  22.5045  21.6829  -1.0  205.538291   \n",
       "195932 -99.9999  25.8154  26.8278  23.5226  22.4604  -1.0  205.538135   \n",
       "195934  23.2747  21.9062  22.1769  21.2311  20.6197  -1.0  205.538101   \n",
       "195936  24.5381  22.5184  22.6060  21.7179  20.9602  -1.0  205.537980   \n",
       "195938  20.5748  20.0178  20.3849  19.8366  19.3316  -1.0  205.537872   \n",
       "195939  23.4440  22.0315  22.1138  21.2629  20.5760  -1.0  205.537846   \n",
       "195940  23.3431  22.0135  21.9082  21.1607  20.5191  -1.0  205.537792   \n",
       "195941 -99.9999  26.2291  27.5824  24.9876  24.2892  -1.0  205.537635   \n",
       "195944  26.5454  26.3812  25.8235  24.2395  22.9003  -1.0  205.537368   \n",
       "196005  22.5371  21.2592  21.8636  20.9402  20.2849  -1.0  205.540091   \n",
       "196006 -99.9999 -99.9999  25.3626  24.5905  23.5217  -1.0  205.540089   \n",
       "196007 -99.9999  27.3704  25.0716  23.8282  22.5753  -1.0  205.539950   \n",
       "196009  23.7874  22.4246  22.4938  21.4118  20.7172  -1.0  205.539889   \n",
       "196011  20.8231  20.2500  20.7412  20.0583  19.5617  -1.0  205.539822   \n",
       "196013 -99.9999  27.6998  24.9800  23.5291  22.4711  -1.0  205.539729   \n",
       "196016 -99.9999  23.4689  23.0418  22.0197  21.1958  -1.0  205.539689   \n",
       "196019  25.6736  25.4096  26.4324  23.8401  22.6428  -1.0  205.539598   \n",
       "196024  20.5632  19.9895  20.3509  19.7781  19.2844  -1.0  205.539287   \n",
       "196026  27.4505  26.0955  26.2159  24.4614  23.3314  -1.0  205.539164   \n",
       "196027  25.4356  25.1084  24.8104  22.8467  21.9544  -1.0  205.539146   \n",
       "196029  25.2907  24.4177  23.2334  22.4142  21.5396  -1.0  205.539031   \n",
       "196030  23.1889  21.6824  21.9160  21.1518  20.4940  -1.0  205.538990   \n",
       "196031  27.3469  26.6540  24.7679  23.7177  22.6739  -1.0  205.538992   \n",
       "196033  20.0316  19.5036  20.0295  19.3486  18.8927  97.8  205.538880   \n",
       "196035  20.6603  19.9830  20.4825  19.8260  19.3329  -1.0  205.538809   \n",
       "196036  26.3942  25.5697  25.1925  23.4042  22.2002  -1.0  205.538771   \n",
       "196100  25.2698  23.3010  23.2111  21.9687  21.2271  -1.0  205.540601   \n",
       "196101  21.8553  20.9249  21.3116  20.6568  20.0745  -1.0  205.540427   \n",
       "\n",
       "              dec        id  \n",
       "83      28.347170  R0000084  \n",
       "93      28.347580  R0000094  \n",
       "94      28.347629  R0000095  \n",
       "95      28.347648  R0000096  \n",
       "99      28.347709  R0000100  \n",
       "102     28.347791  R0000103  \n",
       "104     28.347829  R0000105  \n",
       "105     28.347855  R0000106  \n",
       "110     28.348086  R0000111  \n",
       "113     28.348136  R0000114  \n",
       "114     28.348146  R0000115  \n",
       "115     28.348151  R0000116  \n",
       "116     28.348181  R0000117  \n",
       "120     28.348336  R0000121  \n",
       "121     28.348410  R0000122  \n",
       "123     28.348414  R0000124  \n",
       "124     28.348426  R0000125  \n",
       "125     28.348455  R0000126  \n",
       "126     28.348468  R0000127  \n",
       "129     28.348557  R0000130  \n",
       "130     28.348637  R0000131  \n",
       "138     28.348848  R0000139  \n",
       "139     28.348905  R0000140  \n",
       "142     28.348960  R0000143  \n",
       "143     28.348966  R0000144  \n",
       "144     28.348973  R0000145  \n",
       "147     28.349030  R0000148  \n",
       "148     28.349032  R0000149  \n",
       "149     28.349041  R0000150  \n",
       "150     28.349050  R0000151  \n",
       "...           ...       ...  \n",
       "195927  28.403387  R0196069  \n",
       "195930  28.403147  R0196072  \n",
       "195931  28.403351  R0196073  \n",
       "195932  28.402950  R0196074  \n",
       "195934  28.403471  R0196076  \n",
       "195936  28.403025  R0196078  \n",
       "195938  28.403053  R0196080  \n",
       "195939  28.403572  R0196081  \n",
       "195940  28.403453  R0196082  \n",
       "195941  28.403128  R0196083  \n",
       "195944  28.402924  R0196086  \n",
       "196005  28.402970  R0196147  \n",
       "196006  28.403063  R0196148  \n",
       "196007  28.402923  R0196149  \n",
       "196009  28.403007  R0196151  \n",
       "196011  28.403145  R0196153  \n",
       "196013  28.403157  R0196155  \n",
       "196016  28.403026  R0196158  \n",
       "196019  28.403233  R0196161  \n",
       "196024  28.403117  R0196166  \n",
       "196026  28.403070  R0196168  \n",
       "196027  28.403282  R0196169  \n",
       "196029  28.403316  R0196171  \n",
       "196030  28.402931  R0196172  \n",
       "196031  28.403156  R0196173  \n",
       "196033  28.403238  R0196175  \n",
       "196035  28.402918  R0196177  \n",
       "196036  28.403361  R0196178  \n",
       "196100  28.402904  R0196242  \n",
       "196101  28.403035  R0196243  \n",
       "\n",
       "[147409 rows x 9 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "def scatterPlot2D(x,y, title, xLabel, yLabel, alpha):\n",
    "    fig = plt.figure(figsize=(15,10))\n",
    "\n",
    "    plot = fig.add_subplot(111)\n",
    "    plot.set_title(\"Subplot1\")\n",
    "    plot.set_xlabel(xLabel)\n",
    "    plot.set_ylabel(yLabel)\n",
    "    plot.scatter(x, y, s=1, c='r', label=\"feature1\", alpha=alpha)\n",
    "    plt.grid()\n",
    "\n",
    "    plt.title(title)\n",
    "    plt.legend(loc=2)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatterPlot2D(col_ind,m_V,\"2D Scatter Plot\", \"x-axis\", \"y-axis\", 0.005)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp = pd.DataFrame({\"c\": col_ind, \"m\": m_V})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp1 = tmp.loc[(tmp['m']<=-2.5)&(tmp['m']>=-5)&(tmp['c']>=0)&(tmp['c']<=1.5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "scatterPlot2D(tmp1['c'].values,tmp1['m'].values,\"2D Scatter Plot\", \"x-axis\", \"y-axis\", 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp2 = tmp1.loc[(tmp1['c']>=0.54)&(tmp1['c']<=0.56)&(tmp1['m']>=-3.7)&(tmp1['m']<=-3.5)]\n",
    "row = df_bol.iloc[767]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "f275w     19.8044\n",
       "f336w     19.2178\n",
       "f438w     19.5916\n",
       "f606w     19.0475\n",
       "f814w     18.5914\n",
       "prob           97\n",
       "ra        205.548\n",
       "dec       28.3588\n",
       "id       R0000785\n",
       "Name: 779, dtype: object"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "row"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "main_mag_bol = row['f606w']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "L_ratio = np.e**((4.8-main_mag_bol + 5*np.log10(d))/2.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.398033601034543"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "M_sun = 1.9891e30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.9891e+30"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M_sun"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "M_star = (L_ratio ** (1/3.8)) * M_sun "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.1724546793151348e+30"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M_star"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "Age = ((M_star/M_sun) * (10) ) / L_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.812256574653119"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Turn Off point Magnitude:  3.9623333035060977\n"
     ]
    }
   ],
   "source": [
    "#Turn Off point Magnitude\n",
    "print(\"Turn Off point Magnitude: \", main_mag_bol - 5*np.log10(d))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Approximate Age of The Cluster:  7.812256574653119  Billion Years\n"
     ]
    }
   ],
   "source": [
    "#Age\n",
    "print(\"Approximate Age of The Cluster: \", Age, \" Billion Years\")"
   ]
  },
  {
   "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}