{ "cells": [ { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "x = np.arange(0,10)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "y = x**2" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Y label')" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(x,y,'r--')\n", "plt.xlim(0,4)\n", "plt.ylim(0,10)\n", "plt.title('TITLE')\n", "plt.xlabel('X label')\n", "plt.ylabel('Y label')" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "mat = np.arange(0,100).reshape(10,10)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],\n", " [10, 11, 12, 13, 14, 15, 16, 17, 18, 19],\n", " [20, 21, 22, 23, 24, 25, 26, 27, 28, 29],\n", " [30, 31, 32, 33, 34, 35, 36, 37, 38, 39],\n", " [40, 41, 42, 43, 44, 45, 46, 47, 48, 49],\n", " [50, 51, 52, 53, 54, 55, 56, 57, 58, 59],\n", " [60, 61, 62, 63, 64, 65, 66, 67, 68, 69],\n", " [70, 71, 72, 73, 74, 75, 76, 77, 78, 79],\n", " [80, 81, 82, 83, 84, 85, 86, 87, 88, 89],\n", " [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mat" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.imshow(mat)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "mat = np.random.randint(0,1000,(10,10))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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PffDFUuJ+7a7zC4/57GW3FR4TYNqy3sJjDo4ZeYVpLPisRqXyiMqsznz3BDNLnUdUZpa2CvWoyvnWSTOrgMa1fnm2ZiRNkfSIpDWSVkual+0/TtLPJT2b/Xlstl+SvitpnaSnJZ3bKlMXKrM6i8i3NbcPuD4izgRmAtdIOhO4AXgoIqYDD2XPAT4ETM+2XqDlWQwXKrO6yr6ANM/WNEzE5oh4Inv8OrAW6AbmAHdkh90BXJo9ngP8OBp+AUySdEqzz3CPyqzO8jfTT5C0csjzBRGx4I0HSZoKnAOsAE6OiM3ZS1uAk7PH3cDGIW/ry/ZtZhi5CpWkLwCfotF6ewa4KiJ253mvmSUsfzN9W0T0NDtA0lHAz4D5EfGapD99TERIh37BTsupn6Ru4DqgJyLOAkYBcw/1A80sHRoczLW1jCONplGkFkfE0mz37/dP6bI/96/+3QRMGfL2ydm+YeXtUXUBR0rqAsYDv8v5PjNLVdBY8Jlna0KNodMiYG1EfGfIS8uAK7LHVwD3Dtn/yezs30zg1SFTxANqOfWLiE2Svg1sAHYBD0bEgwdItpdGB59xjG8V1szaTERRCz5nAZcDz0h6Ktt3I/CvwD2SrgZeAD6evbYcuAhYB+wErmr1AS0LVbb2YQ4wDXgF+A9Jl0XEnUOPyxprCwCO0XEVWUZmVnMFFKqIeJzGpYMHMvsAxwdwzcF8Rp6p3wXAcxGxNSL2AkuBdx/Mh5hZoopZR1W6PGf9NgAzJY2nMfWbDaxs/hYzS97+HlUF5OlRrZC0BHiCxgrUJ8mmeGZWbXnO6KUg1zqqiLgJuKnkXMzssEpjWpeHV6ab1VXgQmVmFVCNmZ8LlVmd+cZ5ZpY+FyozS1oEDFRj7ldKoeo/ZQIbP/XOwuO+efGewmMCxB92FB7zhflnFB4T4M7FC0uJO/rdA6XEvWb7daXEfeZ9WwuP+dgThYcEYNLTxf+Ybd013ELwg+QRlZklz4XKzJIWgL8p2czSFhA17lGZWQUE9W6mm1lFuEdlZslzoTKztPmiZDNLXQCddJsXM+tQHlGZWdpqfgmNmVVAQHgdlZklzyvTzSx57lGZWdIifNbPzCrAIyozS1sQA+Xch6xoLlRmdeXbvJhZJXh5gpmlLIDwiMrMkha+cZ6ZVUBVmumKEk5PStoKvJDj0BOAbYUnUJ4q5VulXKFa+aaQ6+kRceJIAki6n8bfJY9tEXHhSD5vJEopVLk/XFoZET1tS+AgVSnfKuUK1cq3Srl2iiPanYCZWSsuVGaWvHYXqgVt/vyDVaV8q5QrVCvfKuXaEdraozIzy6PdIyozs5ZcqMwseW0rVJIulPRbSesk3dCuPFqRNEXSI5LWSFotaV67c8pD0ihJT0q6r925NCNpkqQlkn4jaa2kd7U7p2YkfSH7f/BrST+VNK7dOdVBWwqVpFHA94EPAWcCfyPpzHbkksM+4PqIOBOYCVyTcK5DzQPWtjuJHG4F7o+ItwFnk3DOkrqB64CeiDgLGAXMbW9W9dCuEdX5wLqIWB8R/cBdwJw25dJURGyOiCeyx6/T+EHqbm9WzUmaDFwMLGx3Ls1Imgi8B1gEEBH9EfFKe7NqqQs4UlIXMB74XZvzqYV2FapuYOOQ530k/sMPIGkqcA6wor2ZtHQL8GUg9StOpwFbgduzaepCSRPandRwImIT8G1gA7AZeDUiHmxvVvXgZnpOko4CfgbMj4jX2p3PcCRdArwYEavanUsOXcC5wG0RcQ6wA0i5X3ksjZH/NOBUYIKky9qbVT20q1BtAqYMeT4525ckSaNpFKnFEbG03fm0MAv4sKTnaUyp3y/pzvamNKw+oC8i9o9Ql9AoXKm6AHguIrZGxF5gKfDuNudUC+0qVL8CpkuaJmkMjYbksjbl0pQk0eihrI2I77Q7n1Yi4qsRMTkiptL4d304IpL8rR8RW4CNkmZku2YDa9qYUisbgJmSxmf/L2aTcPO/k7TlflQRsU/StcADNM6c/CgiVrcjlxxmAZcDz0h6Ktt3Y0Qsb2NOneTzwOLsF9Z64Ko25zOsiFghaQnwBI2zwU/iy2kOC19CY2bJczPdzJLnQmVmyXOhMrPkuVCZWfJcqMwseS5UZpY8FyozS97/Aa0C8uRaZ2HyAAAAAElFTkSuQmCC\n", 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" ], "text/plain": [ " Name Salary Age\n", "0 John 50000 34\n", "1 Sally 120000 45\n", "2 Alyssa 80000 27" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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