M2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0302b062",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c49d6c4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# byte-by-byte delimiters\n",
    "colspecs = [(0, 4), (4, 14), (14, 25), (25, 31), (31, 37),\n",
    "(37, 41), (41, 42), (42, 43), (43, 44), (44, 49),\n",
    "(49, 51), (51, 60), (60, 62), (62, 64), (64, 68),\n",
    "(68, 69), (69, 71), (71, 73), (73, 75), (75, 77),\n",
    "(77, 79), (79, 83), (83, 84), (84, 86), (86, 88),\n",
    "(88, 90), (90, 96), (96, 102), (102, 107), (107, 108),\n",
    "(108, 109), (109, 114), (114, 115), (115, 120), (120, 121),\n",
    "(121, 126), (126, 127), (127, 147), (147, 148), (148, 154),\n",
    "(154, 160), (160, 161), (161, 166), (166, 170), (170, 174),\n",
    "(174, 176), (176, 179), (179, 180), (180, 184), (184, 190),\n",
    "(190, 194), (194, 196), (196, 197)]\n",
    "catalog = pd.read_fwf(\"bsc5.dat\", header = None, colspecs = colspecs,\n",
    "names = [\"HR\",\n",
    "\"Name\",\n",
    "\"DM\",\n",
    "\"HD\",\n",
    "\"SAO\",\n",
    "\"FK5\",\n",
    "\"IRflag\",\n",
    "\"r_IRflag\",\n",
    "\"Multiple\",\n",
    "\"ADS\",\n",
    "\"ADScomp\",\n",
    "\"VarID\",\n",
    "\"RAh1900\",\n",
    "\"RAm1900\",\n",
    "\"RAs1900\",\n",
    "\"DE-1900\",\n",
    "\"DEd1900\",\n",
    "\"DEm1900\",\n",
    "\"DEs1900\",\n",
    "\"RAh\",\n",
    "\"RAm\",\n",
    "\"RAs\",\n",
    "\"DE-\",\n",
    "\"DEd\",\n",
    "\"DEm\",\n",
    "\"DEs\",\n",
    "\"GLON\",\n",
    "\"GLAT\",\n",
    "\"Vmag\",\n",
    "\"n_Vmag\",\n",
    "\"u_Vmag\",\n",
    "\"B-V\",\n",
    "\"u_B-V\",\n",
    "\"U-B\",\n",
    "\"u_U-B\",\n",
    "\"R-I\",\n",
    "\"n_R-I\",\n",
    "\"SpType\",\n",
    "\"n_SpType\",\n",
    "\"pmRA\",\n",
    "\"pmDE\",\n",
    "\"n_Parallax\",\n",
    "\"Parallax\",\n",
    "\"RadVel\",\n",
    "\"n_RadVel\",\n",
    "\"l_RotVel\",\n",
    "\"RotVel\",\n",
    "\"u_RotVel\",\n",
    "\"Dmag\",\n",
    "\"Sep\",\n",
    "\"MultID\",\n",
    "\"MultCnt\",\n",
    "\"NoteFlag\"])\n",
    "catalog.to_csv(\"bsc5.csv\")\n",
    "df = pd.read_csv(\"bsc5.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0f4067f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "dict = {'O':0,'B':0,'A':0,'F':0,'G':0,'K':0,'M':0}\n",
    "total_MS = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f22e3cee",
   "metadata": {},
   "outputs": [],
   "source": [
    "for e in df['SpType']:\n",
    "    e = str(e)\n",
    "    if (('V' in e) and ('I' not in e)):\n",
    "        total_MS+=1\n",
    "        \n",
    "        if 'O' in e:\n",
    "            dict['O']+=1\n",
    "        if 'B' in e:\n",
    "            dict['B']+=1\n",
    "        if 'A' in e:\n",
    "            dict['A']+=1\n",
    "        if 'F' in e:\n",
    "            dict['F']+=1\n",
    "        if 'G' in e:\n",
    "            dict['G']+=1\n",
    "        if 'K' in e:\n",
    "            dict['K']+=1\n",
    "        if 'M' in e:\n",
    "            dict['M']+=1\n",
    "            \n",
    "\n",
    "    \n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "29f47c20",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2910\n"
     ]
    }
   ],
   "source": [
    "print(total_MS) #Total number of stars in MS is 2910"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c06470d0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'O': 19, 'B': 832, 'A': 1179, 'F': 665, 'G': 214, 'K': 51, 'M': 3}\n"
     ]
    }
   ],
   "source": [
    "print(dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ff67f9de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(dict.keys(), dict.values(), width = 0.6)\n",
    "plt.xlabel('Spectral Class')\n",
    "plt.ylabel('Raw Frequency')\n",
    "plt.title('Distribution of Spectral Classes of Main Sequence Stars')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d5ec3f0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Percentages = [(dict['O']/total_MS),(dict['B']/total_MS),(dict['A']/total_MS),(dict['F']/total_MS),(dict['G']/total_MS),(dict['K']/total_MS),(dict['M']/total_MS)]\n",
    "plt.bar(dict.keys(), Percentages, width = 0.6)\n",
    "plt.xlabel('Spectral Class')\n",
    "plt.ylabel('Relative Frequency')\n",
    "plt.title('Relative Frequencies of Spectral Classes of Main Sequence Stars')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee808f41",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}