exercise3_issue4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cf5973d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f2b35506",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [0, 1, 2, 3, 4, 5]\n",
    "y = [1, 1, 5, 10, 17, 26]\n",
    "plt.plot(x,y)\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6ab2eda6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [0, 1, 2, 3, 4, 5]\n",
    "y = [1, 1, 5, 10, 17, 26]\n",
    "\n",
    "plt.scatter(x,y)\n",
    "\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "\n",
    "plt.grid()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "907e2beb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fruit = ['apple', 'orange', 'kiwi', 'manggo', 'tomato']\n",
    "amount = [10, 15, 5, 25, 20]\n",
    "colors = ['red', 'blue', 'yellow', 'green', 'magenta']\n",
    "\n",
    "plt.bar(fruit, amount, color=colors)\n",
    "\n",
    "plt.xlabel('Fruits')\n",
    "plt.ylabel('Amount')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "48667546",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [\n",
    "    2, 2, 2, 2, 7, 7, 7, 7,\n",
    "    7, 7, 7, 7, 2, 2, 2, 2,\n",
    "    3, 3, 3, 3, 3,\n",
    "    5, 5, 5, 5, 5, 5,\n",
    "    1, 1, 9, 9, 1,\n",
    "    4, 4, 4, 4,\n",
    "    6, 6, 6, 6, 6, 6, 6,\n",
    "    8, 8, 8, 8, 8, 8,\n",
    "    6, 6, 6, 6, 6,\n",
    "]\n",
    "\n",
    "bins = np.linspace(0.5, 9.5, 10)\n",
    "plt.hist(x, bins=bins, color='#484', ec='white')\n",
    "\n",
    "plt.xticks(range(1, 10))\n",
    "plt.yticks(range(0, 13))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d99a89df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fruits = ['apple', 'orange', 'kiwi', 'manggo', 'tomato']\n",
    "amount = [1, 2, 3, 2, 2]\n",
    "colors = ['red', 'blue', 'yellow', 'green', 'magenta']\n",
    "\n",
    "plt.pie(amount, labels=fruits, colors=colors)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2539cd6",
   "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}