6.Matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=np.arange(0,10)\n",
    "y=np.arange(11,21)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Graph')"
      ]
     },
     "execution_count": 8,
     "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(x,y,c='g')\n",
    "plt.xlabel(\"x axis\")\n",
    "plt.ylabel(\"y axis\")\n",
    "plt.title(\"Graph\") \n",
    "# plt.savefig(\"Graph.png\") To save the figure locally\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "y=x*x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2d65a18ad30>]"
      ]
     },
     "execution_count": 17,
     "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.plot(x,y,\"ro\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2d65ae01b50>]"
      ]
     },
     "execution_count": 25,
     "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.plot(x,y,\"ro\",linestyle='dashed',linewidth=2,markersize=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2d65be93340>]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2,2,1)\n",
    "plt.plot(x,y,\"r--\")\n",
    "plt.subplot(2,2,2)\n",
    "plt.plot(x,y,\"b-o\")\n",
    "plt.subplot(2,2,3)\n",
    "plt.plot(x,y,\"g-x\")\n",
    "plt.subplot(2,2,4)\n",
    "plt.plot(x,y,\"r-v\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2d65bf4cd00>]"
      ]
     },
     "execution_count": 31,
     "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": [
    "x=np.arange(0,4*np.pi,0.1)\n",
    "y=np.sin(x)\n",
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 3 artists>"
      ]
     },
     "execution_count": 33,
     "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": [
    "x=[5,6,7]\n",
    "y=[3,6,9]\n",
    "plt.bar(x,y,align='center')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([6., 0., 0., 0., 0., 0., 0., 0., 0., 2.]),\n",
       " array([ 3. , 10.5, 18. , 25.5, 33. , 40.5, 48. , 55.5, 63. , 70.5, 78. ]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 36,
     "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": [
    "x=np.array([6,7,78,77,4,3,3,7])\n",
    "plt.hist(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    " #Data to plot\n",
    "labels = 'Python', 'C++', 'Ruby', 'Java'\n",
    "sizes = [215, 130, 245, 210]\n",
    "colors = ['gold', 'yellowgreen', 'lightcoral', 'lightskyblue']\n",
    "explode = (0.4, 0, 0, 0)  # explode 1st slice\n",
    "\n",
    "# Plot\n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors,\n",
    "autopct='%1.1f%%', shadow=False)\n",
    "\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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": [
    "#Box Plot\n",
    "data = [np.random.normal(0, std, 100) for std in range(1, 4)]\n",
    "\n",
    "# rectangular box plot\n",
    "plt.boxplot(data,vert=True,patch_artist=False);"
   ]
  },
  {
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}