Python_Practise (1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from matplotlib import style\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "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.plot([1,2,6,9],[9,11,12,26]) #'x''y' axis\n",
    "plt.title('Info')# giving title to your chart\n",
    "plt.ylabel('Y Axis') #giving name to the X axis\n",
    "plt.xlabel(\"X Axis\") #giving name to the y axis\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "print(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#how to add style to your graph\n",
    "style.use(\"ggplot\")\n",
    "x=[5,8,10]\n",
    "y=[12,16,6]\n",
    "\n",
    "x2=[6,9,11]\n",
    "y2=[6,15,7]\n",
    "\n",
    "plt.plot(x,y,'g',label='lineOne', linewidth=5)\n",
    "plt.plot(x2,y2,'c',label='lineTwo', linewidth=5)\n",
    "\n",
    "plt.title('Epic info')\n",
    "plt.ylabel('Y Axis')\n",
    "plt.xlabel(\"x Axis\")\n",
    "\n",
    "plt.legend()\n",
    "plt.grid(True, color = 'k')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#bar graphs\n",
    "plt.bar([1,3,5,7,9],[5,2,7,8,2], label='example one')\n",
    "\n",
    "plt.bar([2,4,6,8,10],[8,5,2,5,6], label='example two', color='g')\n",
    "plt.legend()\n",
    "plt.xlabel('X Axis')\n",
    "plt.ylabel('Y Axis')\n",
    "plt.title('Bar Graph')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "population_age = [13,17,35,56,78,18,90,23,45,67,89,34]\n",
    "bins = [0,10,20,30,40,50,60,70,80,90,100]\n",
    "plt.hist(population_age, bins, histtype='bar', rwidth=0.8)\n",
    "\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.title('Histogram')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Stack Plot\n",
    "days = [1,2,3,4,5]\n",
    "\n",
    "sleeping=[7,8,6,11,7]\n",
    "eating=[2,3,4,3,2]\n",
    "wokring=[7,8,7,2,2]\n",
    "playing=[8,5,7,8,13]\n",
    "\n",
    "plt.plot([],[],color='m',label='sleeping', linewidth=5)\n",
    "plt.plot([],[],color='m',label='eating', linewidth=5)\n",
    "plt.plot([],[],color='m',label='wokring', linewidth=5)\n",
    "plt.plot([],[],color='m',label='playing', linewidth=5)\n",
    "\n",
    "plt.stackplot(days,sleeping,eating,wokring,playing,\n",
    "colors = ['m','c','r','k'])\n",
    "\n",
    "plt.xlabel('x Axis')\n",
    "plt.ylabel('y Axis')\n",
    "plt.title('Stack Plot')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Scatter Plot\n",
    "x= [1,2,3,4,5,6,7,8]\n",
    "y= [5,2,4,2,1,4,5,2]\n",
    "\n",
    "plt.scatter(x,y, label='skitscat', color='k') #'k' is black and 'g' is green\n",
    "plt.xlabel('x Axis')\n",
    "plt.ylabel('y Axis')\n",
    "plt.title('Scatter Plot')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'plt' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-f078cad8675c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mcols\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'm'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'r'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'b'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m plt.pie(slices,\n\u001b[0m\u001b[1;32m      8\u001b[0m         \u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mactivities\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m         \u001b[0mcolors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcols\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'plt' is not defined"
     ]
    }
   ],
   "source": [
    "#pie chart\n",
    "\n",
    "slices=[7,2,2,13]\n",
    "activities = ['sleeping','eating','working','playing']\n",
    "cols=['c','m','r','b']\n",
    "\n",
    "plt.pie(slices,\n",
    "        labels=activities,\n",
    "        colors=cols,\n",
    "        startang=90,\n",
    "        shadow=True,\n",
    "        explode=(0,0.1,0,0),\n",
    "        autopct='%1.1f%%')\n",
    "\n",
    "plt.title(\"Pie Chart\")\n",
    "plt.show()\n",
    "\n",
    "#  https://www.youtube.com/watch?v=yZTBMMdPOww"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX REG"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['MyName123@website.com', '8@company.net', 'Smith@outlook.com', 'santanu@biomoneta.com', 'kasinathan@waycool.in', 'mukundan@stellapps.com', 'ravi@letstransport.in', 'ragini@leap.club', 'ved@khatabook.com', 'balaji@vakilsearch.com', 'mukul@lendingkart.com', 'parikh@nykaa.com']\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "\n",
    "text = 'A radom text 9654836613 A random string. MyName123@website.com. Your_Name.8-8-8@company.net Jane.Smith@outlook.com adriel@jai-kisan.com\tsantanu@biomoneta.com\tavinash.kasinathan@waycool.in\tranjith.mukundan@stellapps.com\travi@letstransport.in\tragini@leap.club\tved@khatabook.com\tbalaji@vakilsearch.com\tmukul@lendingkart.com\tnihir.parikh@nykaa.com'\n",
    "pattern= re.compile(\"[a-zA-Z0-9]+\\@[a-zA-Z0-9]+\\.[a-zA-Z0-9]+\")\n",
    "result= pattern.findall(text)\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX LIST COMPREHENSIONS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['jatin', 'anil', 'sangeeta', 'nitika', 'raghav']\n",
      "\n",
      "['jatin', 'anil', 'sangeeta', 'nitika', 'raghav']\n",
      "\n",
      "['jatin loves me', 'anil loves me', 'sangeeta loves me', 'nitika loves me', 'raghav loves me']\n"
     ]
    }
   ],
   "source": [
    "name = ['jatin','anil','sangeeta','nitika','raghav']\n",
    "l=[]\n",
    "for family in name:\n",
    "    l.append(family)\n",
    "print(l)\n",
    "print()\n",
    "print([family for family in name])\n",
    "print()\n",
    "l=[]\n",
    "for family in name:\n",
    "    l.append(family+' loves me')\n",
    "print(l)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "['interstellar', 'dark knight', 'fifty shades']\n"
     ]
    }
   ],
   "source": [
    "#Movies Rating \n",
    "print()\n",
    "l=[]\n",
    "movie_rating = {\"interstellar\":9, \"dark knight\":8, \"fifty shades\":2}\n",
    "\n",
    "for movies in movie_rating:\n",
    "    if movie_rating[movies]>1:\n",
    "        l.append(movies)\n",
    "print(l)"
   ]
  }
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