numpy/MatPlotLib.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a = np.array([20, 87, 4, 40, 53, 74, 56, 52, 11, 20, 40, 15, 79, 25, 27])\n",
    "\n",
    "# In a histogram bins = buckets\n",
    "plt.hist(a, bins=[0, 20, 40, 60, 80, 100])\n",
    "plt.title(\"Histogram\")\n",
    "# plt.show isn't required in jupyter notebooks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(a, bins=[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100])\n",
    "plt.title(\"Histogram\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting a sin graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Sin graph')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(0, 3 * np.pi, 0.1)\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.plot(x, y)\n",
    "plt.title(\"Sin graph\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "aml",
   "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": "3.10.11"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}