{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "A6iFUUQLNDlE" }, "source": [ "\n", " \n", " \n", " \n", "
\n", " Run in Google Colab\n", " \n", " View on Github\n", " \n", " View raw on Github\n", "
" ] }, { "cell_type": "markdown", "metadata": { "id": "jBcmxL63L-4J" }, "source": [ "# Module 7: 1D data\n", "\n", "Let's first import basic packages and then load a dataset from `vega_datasets` package. If you don't have `vega_datasets` or `altair` installed yet, use `pip` or `conda` to install them. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "executionInfo": { "elapsed": 26, "status": "ok", "timestamp": 1664924274830, "user": { "displayName": "Vincent Wong", "userId": "06927694896148305320" }, "user_tz": 240 }, "id": "U0t_SjSDL-4S" }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "\n", "from vega_datasets import data" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "executionInfo": { "elapsed": 239, "status": "ok", "timestamp": 1664924275046, "user": { "displayName": "Vincent Wong", "userId": "06927694896148305320" }, "user_tz": 240 }, "id": "TAw9u-tDL-4X", "outputId": "44fbf0ce-fede-401c-b3e4-1c5853724536" }, "outputs": [ { "data": { "text/html": [ "
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NameMiles_per_GallonCylindersDisplacementHorsepowerWeight_in_lbsAccelerationYearOrigin
0chevrolet chevelle malibu18.08307.0130.0350412.01970-01-01USA
1buick skylark 32015.08350.0165.0369311.51970-01-01USA
2plymouth satellite18.08318.0150.0343611.01970-01-01USA
3amc rebel sst16.08304.0150.0343312.01970-01-01USA
4ford torino17.08302.0140.0344910.51970-01-01USA
\n", "
" ], "text/plain": [ " Name Miles_per_Gallon Cylinders Displacement \\\n", "0 chevrolet chevelle malibu 18.0 8 307.0 \n", "1 buick skylark 320 15.0 8 350.0 \n", "2 plymouth satellite 18.0 8 318.0 \n", "3 amc rebel sst 16.0 8 304.0 \n", "4 ford torino 17.0 8 302.0 \n", "\n", " Horsepower Weight_in_lbs Acceleration Year Origin \n", "0 130.0 3504 12.0 1970-01-01 USA \n", "1 165.0 3693 11.5 1970-01-01 USA \n", "2 150.0 3436 11.0 1970-01-01 USA \n", "3 150.0 3433 12.0 1970-01-01 USA \n", "4 140.0 3449 10.5 1970-01-01 USA " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cars = data.cars()\n", "cars.head()" ] }, { "cell_type": "markdown", "metadata": { "id": "FLuNEZG2L-4Z" }, "source": [ "## 1D scatter plot" ] }, { "cell_type": "markdown", "metadata": { "id": "D5jSlFa8L-4a" }, "source": [ "Let's consider the `Acceleration` column as our 1D data. If we ask pandas to plot this series, it'll produce a line graph where the index becomes the horizontal axis. " ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "id": "dDEr9LKBL-4c", "outputId": "31ed15df-01b8-4a41-968d-24b7ae24afbd" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cars.Acceleration.plot()" ] }, { "cell_type": "markdown", "metadata": { "id": "pu8hiRIXL-4d" }, "source": [ "Because the index is not really meaningful, drawing line between subsequent values is misleading! This is definitely not the plot we want! \n", "\n", "It's actually not trivial to use pandas to create an 1-D scatter plot. Instead, we can use `matploblib`'s `scatter` function. We can first create an array with zeros that we can use as the vertical coordinates of the points that we will plot. `np.zeros_like` returns an array with zeros that matches the shape of the input array. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "id": "LtVSWMRQL-4e", "outputId": "6e085ebb-f8a5-4fbb-d440-ae6c96adbd44" }, "outputs": [ { "data": { "text/plain": [ "array([0, 0, 0])" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.zeros_like([1,2,3])" ] }, { "cell_type": "markdown", "metadata": { "id": "TQK5Ox8GL-4g" }, "source": [ "**Q: now can you create an 1D scatter plot wit `matplotlib`'s scatter function?** Make the figure wide (e.g. set `figsize=(10,2)`) and then remove the y tics. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "id": "RTAe1rCZL-4h", "outputId": "75162af4-c3db-41f3-899e-eaf9d4fa91bd" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "XAG9yjjSL-4j" }, "source": [ "As you can see, there are lots of occlusions. So this plot cannot show the distribution properly and we would like to fix it. How about adding some jitters? You can use `numpy`'s `random.rand()` function to generate random numbers, instead of using an array with zeros. \n", "\n", "**Q: create a jittered 1D scatter plot.**" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "id": "qzKs2J7dL-4k", "outputId": "68245e86-bcb8-4d2f-947e-10b19166bfd3" }, "outputs": [ { "data": { "image/png": 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2NgFEFAAAOfJooOJDfEyVEwX65qeKVS+uB8oVqu570d/yTcrErQs6VrGh65v/Wrg3gLar3Ie45ZdlqxrdMm+19HnqqpblXisnP6N4rOk7SEkqbgxJ84N+36eSnxBtysJsQlDjzveJI2qd8DBKJPdCn887+Ril8woKAyuePmTMeWDpZv0hdowysrpC3tJAdxW6uCAKAICceDRQ8UEfJru55hWd81PFqhe38zQHUkK+d/7J7Qm5nOpOKoUFdCVeuhbgB5fUO16ZKKFr+aZdYtwwXp6EjJU5zDMTdK1CwtsYdg6k9MYR8nVYmE0IalzP7J6WNic8rHgfUgr+9OZfpc9LpnSyuw/dGuq3mKQHOetWeBNNAFVBFAAAOVA0gl7GJMSg4kP2H+RZx0RFElllMEog1KF8kHD2yLLN7WEtJoQZ3eWXaZ+mfeGWXRfyQskqGu53BClSYQooXQNXaI0S6oPOQYeQH9cwwSmRS7kkMoIaRwGaPmlEZNiYrBIgUzq52NPBUdRUwwVL0QqvqwpdKYZzAZAlrFc0oixI9Hv0fcj2gzzLmOxLIqsMugLhjPnrnNwDFxKWSOj6we9WR4ZTRLFld6tRYcZM+WWFMl4JKKA3TDyRLbSqeht1WWNNGyZU7nyUAhTVR0NWCYjjAfjmuMHiD2saQhU1P6W0tlc3cdnZA8Xgmkqpew4rvF4QBQBACSsapsIzAMhCXxI1ZbCjaFEgk60mBlX3aP//mYP6dEqALYa2035cTHhJzhlyNCv/gfZLUgF96M/BSfRerv/cMHHj509UEup1WmNVDROcfAHarrJGdISNcZSAuB4AOsd/mTRCOoSuoblN3F63XjocE1Z4/SAKAIASVTQamvZp3Q+AUo2FDhJWdjS3ievmBFcm4kLv0yvHftIEjSpUReVP03bajytAmvCSdCnOBI65ny4FlOtdonCuOMJM2tZY2TUiGz4UN2wsSgnwIpsL5fUcBJ2nTN6HTDimyXHXFeKVNRAFAEAJKhq7Ww5o3Q8AnZiOhea+0Dm9CuIytagzswklixPPL1v/X6UvSVy419y7e7mTQ2I6vCVNa6zMGlEpqhC0RmTCh7gCpEzpZK7nQCbvQzYc08S4ozALAKCkFI3qo7pp3S8J8mrtySMmY6FlXugqSap+nDmot3hly/udfv/5Ecd26qORVsKp7EqKc56qa5n7nX83bnCH0BgvBc3hLWlZY2UqRE2b86pUUYWoNWIifCjIU1AcRsj1HMh6O2XDMXWOu4nCFwCA0sZ6RaO4Pnzc/UwDa0++MBULLftCjxuaRWdX1aNcrPRRMoi6dTudc/J+pwklS6b+P1d4Uj3POGuZ+53Dj+0pSt24EbdCVJAVn7tGTIQP+XkKKBeJwgRNKaXFcNe8rrlhsvAFAKB0sV7RcF/YYdbaqIZRSQFrTz6hMaWmYNRnwpt3TSH/FG4kO+YqL3QZYSWs/K1MB2kTSpaJcCyV85RZy0GCXLRwfYojXAfBFdyyYNyIWyGq2Iovs0ZMhY35eQpUPAeccEE/OGte59wwXfgCAFCaWN8Z3H1hlwV0si6zpHoGJ0aetqObeel1hKeXOTUF8+uoTb/ndrNWeaHLdnD+xeWn+3bcvXHi8FBBJ6iDtO4uvqbCsWTOU2Yth3Uwj/rOPpXdYnXtDutS7SpEsnPPJHQ/ltw0QcydOkbcOWW085M+0+9lFUzZNcLtqJ0FON3YTcwNmwpfAACyg/UeDRuqpnCAtccMtltrORVjZMMJVF7oXKs93bMLRvbrZN19+vVtyudGx5xwcl+nmR/12aASuFSdyps4bkPOC/c8uWt59qL14o669ZFeDxNduw98eFj86s+bxe0L385UKIuuxoKlJPRywgVlPYUmwpxKoQkgACB5MqFoZKGGdSm9+GwhC6FoJhRM1Rd6HIU8jhDhpwzev6ReSRk0Wf+fc54koC3d8FfW8R5aupktyOns2n3rgnVOmF6UYy9Lxg1ZBbOUhF6ZdwLXuGbiuYQmgACAklY0bK9hXUovPhvISuKhqRKvqi/0KIU8yENE+QIquVAmlMGwDueqnizOeRLF9yaM9/fxQs2Cnlkq40xKxr0v8Br96TZumEw4dxXMax9dyarAVUpCL/edQGv0qnFDWPfcllwnAACwPkcjK3Bj5LPw4rMhn0IlT6FUFEz3hS4C8pKiXuhB8ehhMdtUVnRk/16h5zX5tH4dvtN8XpKeDuec87x53mrfexOXMEFOdpwpXIo8GbLoMG6E5aKkQdw1ksV3B1fJsCXXCQAACCgamiilF58NwkhWQtFMKZi6X+hRwjb9+9MbO0OPMf+17R2UBlPKoKsQNTS3depwrpLEyu3SbaLEQJQgJzPOlFsio7PpMm4kkXBO84qUvTBumbe6w/xLW+jVZVQx8e6QeS5FXUfxdvKYBiX1AwBApkOnbCcLSeum0B1Ck5VQNJPhBDrzkjgN/aLkpOJQIBPKoImQOVPKaHVludjTEr+rN3ecKYFdBh0N/5IKYVy+aRerfwrtN25YTeq5e/S8mzF/bQdluLZXNzFj8qlKz3nd7w7uc2nhuobQYhu2F+MAANgPFI2cJa2bwIQwkqUYbJMKpq68JF3CtnscGvPGvR09DkHQfrQ/Z+zTTK7n4s49ipmnkDMdCiZnnKlKVqlW0yNLOXc/r6KRRu4eCd9+uSSkdNDv71H0pnDeHTJ5MlHPJSLMOES9gag8t83FOAAoFQ5Z3HQ1LlA0cpa0nhVhxHTioe5FbbuCqUvYpuP4WTnDmPnMG+wqVGkk18vgzsUpZx0vDh4uiBsmDhdzXtoiduw90L5P3xiW7TCoFO9PF7zBDp/S4W3g3udfPLdBrNvWpFzWOLxVpMp+ZuCEeNF2E0UqVLwLQc8lgsJaw4xDTgNSy4txAFAKPFvinkMoGiA2pvIpTHkKTC1qmxVMjrBN8gLlW4d5kPa0tDlWfFlxj2sFNZlcH6S00mfqzNzEyNOo6lHu/Ly9bn377zrLWfEFLz9FmAR46jTPrTolq+D7fSf3Pr+4vtH5R4oQneMtF31kMecydmiNmL14I2u/NFm+MTrEi7bTfuOG12h7LhGqoal+zyXyDEUZh8JqL2SpdDIANvNsBsr4xwWKBoiNyXwK3Z6CPCxqVQ8RCYgUKhG0ffqkEWLmM+HNCYPgWkFNhcxxw0iCFJFvjhssqrpXiDvqOjfIK/YwUEleCqG5etxgMXFErfR8DRM4XQGe00cjSsH3KhabG1vF3BVbO5QT9pY95nqD6JxcRUhG2RhzwtGOshcmxNN22i9Nlm1qZO8no2iEPZdoLtG125i3lHYxDgCyzKGMlPGPC6pOAetL+waVa5XFfDlWu4mq0kOCYdj2PpUVscq/cqpQmazeRtcfVC0n7N5QzP2/TBohHn95q5SS9cDSzdKV1zgVnmic3pz5BXHlmIGxmix6K8TdXvd2ByXD/U7yXlFZY0LmjpMiROV4udB4zrpkVOg+tD39ly33+8u0PpfCFDCV6m46QykBAKKky/jHBR4NEJusNHJKKrHVZqI8RGHbqbxlElbQIO8D5T5cdvZA0fbhYSf0Q8WzFRbeFnbtUaEmYXC9ZTLWLQqjmv6/TxWPvbQ11LNBt+fMQX1Y1vOg76SyxnddfobjzeLeAzonKsd79fihggvdG1LqdFZz0g3NndmLN7D201kRLo2moGVlwZXobCrGAUBW2ZmRMv5xgaIBclPaNy+LOm4uSdD2JK2gxUK/G9rjzY0wkSwXdO1x5oTXWxbmApdVhF/ZsicyfIq20360P3kYfvXneuceyqRe03eSN4u8P/Tddy3eIJZsiA4h2rxLrhxvFooqjBkaHeLVh0K8hvIVDV3PG515S0RYPpCO0smATylXJMozx2akjH9coGgAbdguJORlUZsiaSsovVypktEL6xvF82//tdN2E3k1QS90HXMiylsmqwjL7H/rgnVSeR1+x3CVsAWrt4klG8xViLK5qIIb4uVX3tblVskQr7hzy2TekhDyneh1AeE6HxWJ8szZGSrjHwcoGkArNgsJ7qIOsxrr6KRsO6ovcE71ps+ddIxY9OZfY4fQcQRj3clyYS90Or6OErnFeRBxFGHu/gvX7RBPvx6ve7f3u0YP6C0eEVsj/4b2K0U+CfFa1yl5XkX44wgbVR9XRRMJNQUlKIcnCNNJqhCu8128JC90zUjYeVygaIDcQIuVElvDyoPSdlt6c5gg7gs8yApKngwqh0lKhvezSggdKRmmSrjGeaEHvRBk2P1BcJNDyqWg6cLNueAIqJTXsmC1upLhZ1E7rg+vcSB3v7ikse50em9dYSPIS0Jj6ybKJ9UUlFP+1lQ+G4TrfFUkyjsXZiDsPC5QNEBuoAc3JbaGQdv/+cJTpB/cWbDA6XqBe4WsunUNTnWlYuHY/Sxb4pXyCMiTIUucOHfuC51yFPxeCFHKgZfqyorAbbI5Fxxr2GeGHSP+e+W7QoUgixqNJSdPIQnPYJrrLmnvrapyo6KIpZXPBuH6E1C8JD9caHnYeVygaIDcwKnuovLgzoIFTvcLnPahB+F3n1gVuA8dZcGaBvGDSXzXL1UqUskjiBPnLvNC93shkIeBzps6oEdRW9Vdq3AXZQ3788ZdrGP6n6u6wJ5EgegsrDuZtRlE8dqUfTapKGI1ld1Yx+fuxwXC9SegeEm+6Gpx2HlcoGiA3GDiwZ0VC5yJF7iJY27ZLVepSEeynOy88HshXDVuiLh/SX2s/B/VYgVh1rD39uwTXGo/Lh88uKYy1KJG38Ppjm1SGEx63ZkMzzIlXMdSxPS3C2EB4foTULwElApQNEBuMPHg5goJDy+td4TRtJQNEy9wE8ccVM2P69eVLKdjXnjDmILyJaLOM04FkiBr2JVjB4ufLngj1EtEx/2vb54tPj2shnUfG5p4ygt3P9st36bDs2w0gDSG5BJ5+ePaBtGl7CPvpo5nG4Tr/FUkAqUPOoOD3GCigzn35U9hNTIdonVj4gVu4pgkGHPlFbdjeVxhT9e8cMOYaF8v/ZjnaaIrOjX2o34IYVxz7hAx/sRj2Mfd3XJA6342W745ndqzbAAJ6jjM/a7/WrbF6S6v69lm4hmdVUw8DwBIAygaIDeYeHDLvPx1Cic2vMBNHJME4/NOOTZ0n5H9e4m5U8c4ydk6LMqy84KsxVSVhzql00/67ELnQ+dF53fnlNHS5+kqK1Qtygt9VlWqbrlohPj7c4d0UuDoM/2etstQfVQ3rfv5FQR44MVN4odPrXF+0uc0LN9RXgGCtnvHP2sGkKD9os7J1LMNwrX/84CMKiaMLAAkAUKngPXojI/WXUouyr1tQ86Ge/8uGlnrVIgKOjfZF7iJGuB0rmveaw7dZ9cHB7RX5ODOC78wmtpeR36c29CjfX7Gz00IErPUIGXie+ef7CStUx4MhaiR94gUO1noenXuF9U/hUK/yCvjVYiSCCtJKjzLxDqKq4iFnZPpZ1seyn3KUOoViUDpU1YoeKvd+9Pc3CyqqqpEU1OT6NWrVzJnBoDB+GidyosbXkFwbZtk6U6iwoTf/QuCmpCp3FOdY0QeAgrFSOv+hc2LoOTaYuLMz6DvcGemDVZMukcUKhOV+E6eHJk1FdU/pdj7ErTudN0r8lh95/Hgqmou5Lm6eHR/ERed68gdoyhFLGqMZJ4futdmFvoSAZBnmpm6ATwawFpMlq/UWUouyAKXdtUUrmAsYloj6fonnNxXi7XcdOx9lPASNC/CwmiEpvnJDdVJu4KZicaXFB71y4j+KbSdvDLuvDJt+U46MdlEE8C4XhLvOf1hzXYnJyOpZ1spl/sEIE9A0QBWkpWyscUvZKouxemnYLpqioxgHDcMxM/qSaVeVYS9GmZcP3c/XRZjTg+WuPPTVJ+XLDS+/NWfN3foJO8Hbaf9pp47NJGwkjSq/iRhAJFVxLznxFE08lARCgDAB8ngwEriVk1JA3ohUwlbG6qmyAjGcayR2qvyyGhGCZ6n7H1RmZ8Nzfu17ldMWBK7DDIKEZeXN+9i71d8HQQJwhS+5HZM10EpJCbHLU7gBRWhAAAqwKMBrCSrjZtMJHaqoHpfZKyRJrxOjS1tWveTPU/CzzquaqWVGYfdzN4F3P1Mxf+bWJs9KnivImoEWJwforOnRSkmJuvyktjybAMAZAsoGsBKTMdHm0w0tEE4kb0vKmEgJqrypNlTYPaiDeLxl7f6CrGkhHCri6meZ3Vlhdb9TOU6mRijS88YIH63alvkfis27+n0Ox05W2Gg6o9dzzYAQLaAogGsxGR8tOlOvzYIJzJld1WtkSYs2ybGnfv9t9e9HSrEypT7JHr3KJc6z9qq7lr3M+V1MjFG1JW8R0VX0XrgkJAliZyttBKTbay8lPazDQCQLZCjAazEVHx0Ep1+i4UT3bHjce9fMarNn0xYttNuqhhV7cmveVYQZZIC5eFCQfTuXh66X1AMfFD+hYlcJxNjRPv+/KunCVVszNmKCz2LKEyMyj1TmV2dHbiz/GwDAGQLKBogN11RTXf61ZVsa/r+kbB648QTrU0O1T3usl2Ow4RYN7l2+qRTIv9uT+tBluDrCpRX3P+SeH/fwcD9ygIE+DCB1FSuk4mOxfQ31Mulb8+OFcVqe3UTV48bnMmcLVWSNIjYgG3PTgCAPhA6BazGz01/5qA+4pUte5yXkozb3mSn3yTCsWwLczCZHJpkTwGuSOMKsXS8miJhOOpvgojbBDAq/+KGiSca8/qYmltlPn/eK8LT40LnYGO4USmX9o6Lrc9OAIAeoGgA6/HGR9NL6bO3LVZ6KZmy7gYJe9s1JKnqEJpMxpebTA5NqqfAlLOOF7fXrZcSxnWEjXF6nVDewo0Th4tvfHpIpwaIHIGUktvJI7Cjuc1ILwidYxS0jujcaXwo56Wp9WDodexpaUu0KpUJTBpE8tSUFQBgB1A0QG5eSiZyCqKExUIM62NWLH1ZSQ4NOk/i8ZffkUpuJq8aWd7DmszRdtovSFnk9KOg5OifLnhTPLh0c6dx5wqkpKjcUbfeSElSXd4DjtLkPW+/66Bu5NPmvJp5oTWrpb1lyZvnBoC8AkUD5OalZKJajqluzlmz9KVVlUfXecqGgL28eTerk/UvFm8Qv/7LO77KYtuHh9nn7TfuXEFzcE2luObcIeK+F+s7nDMpQlPHD1GeRzRHZ8xfKxqaP+nrQd6TGZNPlT4mR2miHhqUW1RcgpjW7PRJI8TMZ0pDaDVd2tsW8uS5ASDPIBkcZELJeHhpfezqOSaq5TQ07dO6XxJJ66AzJBiTMF6cH0Cf6ffFgrPbkTqKO/60PjChd3NjK/v8/MadK2hubmwRv3yhXhRPF/pMv1dJLKa/ufbRlR2UDII+0+9lj8lVmg4eOiSe//7nOnW67lNZob26Vlok3YE7rUTsvHhuAMg7UDSA1bgVdWY+84aWl5Luajm7Ww5o3c9USVIQPc/khHF1Ycz9Szd/gqvWFo87VyCdu2JrZGifjHBJ+948b3XoPrRd5phcpWn24o1OjlbTvgMdSquWktBqqrS3bSV0s+i5QXUsAOSBogEyV+Ix7kvJLVFabBVVCSGpPqqb1v2IUhKaknypqwoBnKTsYmF87NAaEQdXabjs7IHOZxmR0Vv9KkognXLWwE5eh2JkldblG3c5YUxh0HbajwvlsnDlZr8Sr1kUWpMuH2xbCd2kPTel3NcEAJtBjgawEo7wFye/QldOQW2vI7Xul4TQZEP5z6hzkE2Ej5M4rxIrPuaEo50qSFECNyd/wq8aFnfco6p+7WN22pYJ7Vu2qZG937jhPIWMylVzjcN+ORcm8q9KuciCDYnYJstj6yZrOXMA2AQUDWAlnCRrG15KroATdq6yVrkooYmgDtLUSZoEBplrtqGSVdQ5yL7U4woBKh4kuuezLhnl5CPEgYRHUl5IoFu+aZeY9tjKwKZ9QcJymED6wIubtIf28f0v/Hkp650rVv6yJLTaUGRBdyK2qvHCZHlsXdiglAGQZRA6BaxERvDQGU4giyvglAWErwR1c+Yc0z2GHySMUidpGdd92qESnHNY8Pp2qUR42cR5v/AqVQ+S28ma8iy80OdfXH66VFgIjfm4YTVi1qWjAueSCJlLrkDqzVswFdrHFXxlBGRV75z3OZFEuFEW8ZvzOsMz44YU6QxlNQFy5gCIBzwawEq4gsf0SaeIq8YNSdWSZMIqF3RMoWi1t8EqxzmH6U+tEbtCrOvFllYZIYASiP08KTSHVMNuwrwJXbqUSVvY3XEvLhvbV7FsrInQvjFDo8PG+vQod/bT6cXjKn9Z6OmSFEHeQ2pSqeM5rCukyOby2MiZAyAeUDQygg1x9UnCjblOW8kwKeC4x6Sk2mlz/ENquEqC6Zr1nPnJOYcwJcPvpc59udeta3Ca3vkJRNTkjUrYUnUplbCbICEpngIa5NNIP7SPEzZ26yWjWHPfO28ocf2Ourc7jYGQVP5sFlqTJEwJ4HZaD5sXNhgvkqDUCg0AkDRQNDKADXH1SZPFmGsTAo5rGQ+K2+cqCSatctz5qdPi577UuS/3J1e9FyoQzX9tu7jr8jOcpm86Y8VlFdAg4XBHs1rSqXcduddryzrymzck/BJh3pK0zzsL6Oi0HnV/89JwrxQLDQCQJFA0LCfP1S6ykCiYBDqUBN1WOdcSTZ6CB5Zu7rTdb35yj11dWS72tPAsrRwhoLqyghWORU3fKDZc1isV5c3hKqDcfBNZC7GudeReZ0PzfjHz6bWB+3kt2YTfvQl6rrkW9hsnDncqclFTQ+oDQt+pet559BDH7bTOub95CSnKotELAJuAomExeXFNh5GlmGtTwosOJcHtUxBWQpS2034qlmidJUgpZ4LCmTgvdY4QcPHo45ywqSho3GS9Ujq9jZxKa6oW4rjriDPmxYrb7EUbOgmxH+XEjHA8R2HPtcdffsdR+uj8rp8wTOu6yoOHmCvcD67poaRc5y2kiOYFhVfe92K9KHgmblmZEFPHDymZeQOACaBoWEwWXdMmhO0sxFybFF50uO45fQpoO+0Xdq+DLNE6S5A6FvguZWwLfJTFvqp7BUvRkBWIdHsbvVZ7HfvpWkcyY+7l9rq3O/2O7s11c1ZKz5uw85Z55uTFQyyjBKjOizyFFNG8oRyugs8zk35/+sA+JTFvADABFA2LyZprOg+WwjSEFx2uex1zSbaJot8xuWE89PMzw44RN/76VbF1zz4xsE93cfvXThdHHXmEtMWezlu3QGTC27j7gzat++lAdcyDkDkOt7Qq95mTJw9xEkqA7SFFuoxenDVQKvOmFCj1sMgsAkXDYrLkms6LpbCYpISXuHH2OuaSTBPFsGNywnim/tfLYuG6ne2f32rYK0bO+KP4/IhjxX1fP8v3e4IssyYEIhPeRsol0bmfDlTHXAe6S6tm0UNsuxJgax5dkiGNpTRvsk5ejZ22A0XDYrLims6TpTDNl1CcOHsdc0nFc0b9FGRLkBYrGV7o97SdlA0Zy5UrEE1/crX4a8snFY2OOapc/ORLo6RfQnE8REHnXVvVnXVM7n46SMNbaqq0atIe4rQtq7p7smQlj0630StrkQVZmZ+6yauxMwtA0bAY213TNvVoSAvTLyG/a1e5hzrmkornTDbkZt+BQ4FKhgttpy7Hs/7wppTl6hfPbeigZBA7Pzjo/F72BaTqIQqzuJGwprvnRVxMe0uTLK2apIfYLsuqnp4sWcijM2H0ylJkQTbnZ3zybOzMAl3SPgHAs0qRhc8LfbZFQzfdo+Ez/7ZIXHbfcvGdx1c5P+kz/d4GTL6EdF973LnkekVkHtNUQpOEPS7/b8E61n50P4oFTddy5Xd/Js9+Ubz+brPvsej3tF0G916EUawUuBa3oPNeuK7BedEH3d+yFAwLKmNO0CmGXQcd8xeXn648F1WeOVHXUqZJkYsa56SeXe55FBcPcHuy2PIM1YmMAsrFrdgXBrdin07BetnGXY7BhX7S56zNT9vHHegDHo0MYMo1rctTYErY1ukKNeUVMRXeZsoNHGcuhXlFdCmY9Y0tQpUgy9UH+z8MVDJcaDvtF5RsXgwde/Jp/cS9L9QH7kPb3XPgWtyo1KhfzHta1kbVMT/vlGNF3bqdkdXFLhjZL7HSqkl4iG2xrNpyHqVg9NJVsc8Gb0SpzgvZcbc5SqIUyb2ikZUJp9s1rdN1akLY1vlANOkmNiG8mH4ZxJlLQcmfuhTM7uVdRRz8QmaochUH2u++b/gnmvuNEXUTD4O2//OFpzj3W8bipsuwUPxsI4srCUOyx1QZ8zXvNbM6rSddWtV08rIticO2nEfSmDB62ZSjEdcAVarzQmbcSy1sLAvkWtHI64TTbS23uapPEgliuoUX218GriC8fNMuMe2xleL9fR3zHuIomOefWisWvhGeoyH70qfyuBy4+6k015MVVuIaFvyebcUNG2WedV7lZ+mGRjF78YbQ/bmd1lUNPXGeOSaTl20RSm05j6QxYfSyJUdDhwGqVOcFd9z3tBwQ0+YgYTxpcpujUYpxijoeVgRtl4n5NJFLYrrvQ5xr9YOuj4SquVPHiDunjHZ+0meVh1YWXgb0Ihs3rEbMunSU8xAPSjeVVTAH9Omh5fy8L33qwcGBu5/KGCWdiOz3bCue5rLPOlf5Gd73KNb+3k7rF4/u3958T1cOUpxnTth5xYmTt0UorTmqm9b9soKrgAqNz6SkcnuSyEOwZX6mMe7TJ53ieFiTkAdAR3Lp0SjVOMW0reU6LYVJ9H1wr/XhpfXiqnFDrOlgnqWXgW5vjvtSDxs3GqZCQbAtltToj3pwREH7cZ8fjXvbpMYoqVLVMg320qzCo8vTmFZp1SBvOAkzVpQk58pKJShT6X4m2VL9UYcBKisl802Me1X3CqsjBUqZXCoatoemmMS0tVyXsM0ROKOsSNxrmPnMG+L+JfXWhMzpfhmYzkOiezbh5L7ikWWbxZbdrWJQdQ9x5djBouIIeYep96UedO1Txw8Rv3yhnv3S717RVRzRpUx8GGKpou20n4qAyZmfssKK6pjJNthTedbRufTuUe5UFAuiR0VXcbhQcK6j+Lx1G3qSLq0apiRNm/OquOZcuflpgsaWNq37ZQ3dCqgNjQl1KPi2KE1pjDt5HksxbCwL5FLRyEJoiimyYi2XreoT9xq2WxSjqfNlkEQekt93xFHcgl7q3vM+fWAf9kufXjphSgZB21XzfbjzkyusxBkz1WeW7mdd64FD4or7X/I9bxsNPVzFjqMkUREATiK8SbLynDeJbgU07caEugxQNihNaYw71kR65FLRqKnspnW/LJEV1ym90H/9l3dD96HtblUfv78ni2rv7uWBycrFFCwKmdPxMkgiET6tMrwyL30dXbypF8HMp9dKRZp4q05xryvu/VR9SXJi9d17sXTDX0O9GVHnbZuhR0ax4ypJnER4k2TlOZ810mxMqNMAlbbSlAZYE+mRS0WD3X3KojWnK/wlK67T5Rt3RQoztJ32Gze8Rjm8pRibQubivAySyENKuwwv96Wvs4u3jrkUdN467mfUyzSQiJ3pXsyYv1Y0NMuF2vidt02WRVnFTkZJKhWhFNiDTm+ELd3ckwJrIj1yqWg0ftCmdT/T6A5/yYLrdNmmRvZ+XkVDNrzFj4YmfplT06i+DJIIT7ExBEZXvo+OeRTlJSlWHnXcT9UGe2Gx+nQvrn10pVCl+LxtsSyqKHY2KUml8JwH8uTRG6ELrIl0yKWikaWXhY0dom11O8lU3Aljd8sBkXV0hAuZDElKEp1dvGXheElco0Hbh4e13E+dTRXpXtw8b7XQgbdHiA2WRRXFzhYlqXSe80CFvHkjdII1kTy5VDSy8rJIOzQlTei8opqCufupVtwJoroEasvrDBcK8p5lRWGX6eJNULnjuPPI7xkSZTS4YeKJ2u5ne1PFjbucBlWcpop+CiYnhJHLzua29ipUNlgWVRRlW5SkUnnOA5AGWBPJkktFIysvi6yEpphgzNCjI0to9ulR7uyn23Je2yt9T1YayrSs92z08b1Z5+K3n+mSuypdvGcv2iAef3mrFiXDr1xtlNGAvru2Vzexo7lNiwHEaao4/KOmikGhT4WPz3PhugZfBXP08VVCFz9d8IZ4cOkn1cjStiyqKsquklScs9K3VzcxY/KpCL8AAAAPue0MrruTtQmyEppiAhI2Zl0yKnSfWy8Z1UEo0WE5T6LDq40dclW6qM95aQvrXIr3i9sR2lTOze11b2vxiPk9Q7hGg8vOHqi1qzGHV7fu8e0kTgrmH9bs0Ppdxd3IdXToViV+x+egUQIAACDyrmgQJAhQCcK5U8eIO6eMdn7SZxuUjCyFppiCxuEeUgaLPAz08qffF48TR3AgL4j7/+JtZZZ4stJQpmW8Zy7UnI+Ddz/Xa+In1HoFUJ0kmXNDnaH9niFcY8Dgmkqn4VtZ0RSkz/R72WeTq0CGcd+L9aEKpk6ClNYsKOPFc5hKHnvZ0WxuDgOgG1p/yzbuchrZ0c+01yMoXXIZOpWVWL2s5JKYRCa8ghMSR14QIi9VJ7j3T8V7Rh3AObj7JVFyN+2cm5qe3XzPnWsM2NzY4nSVLr5HJAPQ76lRocwc5YSNxZUvenc/QhxZfoQjaHMOpTvkM04YnmyuSFpzGACdJNHIFQCX3CsaNpOVXBKb4AoOE07uKx5ZttmxtpMgfOXYwaLiiC65VaZVvGd0zyjuPkxQpalJ+6WZc5Rkzk3QfeQaDeau2BoorKs0lEwirHLWpZ9yfsqW1NVxbjoEJhljRp7z5kBpkEQjVwC8QNGwHBuqs6SJX6Ow2oikS0735eL7ef+ST5JU84iK94wUs6njh4SWjaXtrgKXVs4Rp48Gh55HdhV79x/y3RblXeQYDaacNdDJEwlDVojVFVZ548ThYu6KdzqECxUL9LpK6nI9GJTA/uDSzZ22qwhMXM92nvPmQPaBRw6kARSNDJB2dZa0CGoURkoH/d7N0wgKnfATHGDN0es9u+WiEe1x/l7PBu1GSoa7XUawXL9jrxMzrGuOe69N+FwbfaYKZ02tB0OVLMq/mDbnVd9jcLyLUUaDfQd5fTSKcwPC4HQKp1MuFETotV8/YbjzL+wZ1F5Sd9MuMe0xXkldWTjd2k0KTHnPmwPZBh45kAZQNDKCzbkkJuA0CqPthw8LMfMZXuhEFq05SZaBVfWekTLxvfNPjgxF4wi9xOzFG51/OmOGo66NiFKynGN0KYvlXQwyGhAz5q9hXcvuD4K7eEcpWcXQ9ZFCSPkfQXgVqKhnkFNSd9hHJXWDFLviY3KR6dZuSmBC3hzIMvDIgTSAogGshNMojLZfN8fH4xHgnciaNSeNhD1V7xkpFVePH6rsNfFDt5cp6to4SpYO72Kx0YBjpfdSXVkhcdUfnTNVrIryOgVtV7n3ukM+Vbu16xaYZDx/SRoJsgbuTTrAIwfSAIoGsJJlmxqV/zbIO5Ela06aIV4mvWdBAqhIyMsUdm1cJULn/ZGx0rvUVnWX/g6/SlYULuV6MsK2y1a6MhHyyameZSIPxO+8vYob3SNvCWJXMUNVn2Bwb9IDHjmQBlA0gKXEEyr9vBNcoaNxb5sjaKRlYTMd4pW2NdErgC7d0ChmL95gjZcpyRBFFSs95ZLICAGcRoxhfTTizjVd91NW+dedB+IVhIMUN7cEMeG3Pe95YARy5NIFlSxBGpRmPU+QeXQJe14BJaqhn8vMZ94w2qk6CpXmeVyS7sodJYAO73uUUS+TzU2pVKz0ZZLXFbePRpy5phMZz4SOPJCghpILXv9ICQkrQRzVANGGZoVpwFF683pvbG3kCoAO4NEAVjJm6NGO9TYqT0NGQJHJEUjTwmYqxMtGa6JJL5PtIRoqytOe1oNi9qIN4vGXt7KuS1cYYNrhhNxCAqbyQFzvzvSn1ohdEZ3muYqbDXlgSZK1HLlSJq+VLEE6wKORY2y29tID72v/a0DoPpUVXQO9E/T7fj6hE0HWHJssbCYS9my1JpryMkVZpuN4cHStG9X8Aeq1wb0uXUmddJw0nxeukYAImitXjxss5k4dI5bcNEFJkeQIwlFKRlYUNy9JjWuWcuTygOtVvnh0f+cnlAxgCng0cort1l562c1/LVwYLKfyqQcOSceautach5fWOwKsbRY2Ewl7tloTTXiZTOa46Fw3Mlb6KIKuS1cfjT0tbY6il+bzIqiQgK7zSFLAtaWqT5LvAVQ8AiCfwKORQ0xae3XBiS2nsKobJp6oFGtKglhNz25WWtjCrLeq8ec2WxN1e5m4ShUpmjLWW93rhmOll8Evn8L9jrCrpEpJfufgfp58Wj+nUaENzwuaK+SxIM/FnVNGx/JgqAq41ZXloeNFy1LW05qH90CU99KmewMA0AcUjZxhawiNqsA7uKaHsuBhs4VNd8KezdfqFSCp+3YYnORk7tyRCccytW64SpYMssoila8Nmmt3XX6G41kMum769y9PrhFPrnw3sXAqUyEfXEH4/148sv1z8Xa3AWLQdluq+qTxHjBhQMlqaDAAeQKhUznD1hCaOIKxaglN3SFKusvG6kzYy0L9dF1eJhlliRuOZXLduONMncEfWb5VxMV7/TQnb563OnR/2v7Kv37ed65xPIuUt3DjE69ZF34puza5pT85HeJJeZsxf51oaI7frLCU3gO6GzlmNTQYgDwBRSNn2BxCk7RgrLOmuKkXm4oSFSRUZaF+ug7Pi0zug9d6G5azYXrd0PeeMag6lqJRvCZoHjy4pD6ychttX75xlxg3vKbTXPMKyhxs7Icgsza5gjD9nHByX/HIss1iy+5WMai6h7hy7GBRQXlj7XScfQVvd7+UiTuf4xhVTFc8kqmul3ZPIQBkyOp8haKRM2wPoXFJSjDWYWGzqWxslFCVhDUxbQVTJsHcJcp6m8S6qe0l1ysibE34zYMwlm1qdBSNYnZ/0CZkMNHNPQ4qa5MjCPvd3/uX1LeHBvl9547mNu3PA1XBI8581mFUMdUYU6YQxMJ1DVZ4PbIqPIJkeTbDXjooGjkjCyE0LkkJxnE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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# jittered_y = ...\n", "\n", "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "I30M1oReL-4m" }, "source": [ "We can further improve this by adding transparency to the symbols. The transparency option for `scatter` function is called `alpha`. Set it to be 0.2.\n", "\n", "**Q: create a jittered 1D scatter plot with transparency (alpha=0.2)**" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "id": "97OidszmL-4n", "outputId": "fd4f965c-bf95-4535-de83-718ee658ae15" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "Fyc15W1lL-4o" }, "source": [ "Another strategy is using empty symbols. The option is `facecolors`. You can also change the stroke color (`edgecolors`). \n", "\n", "**Q: create a jittered 1D scatter plot with empty symbols.**" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "id": "gzEeZRsBL-4p", "outputId": "9af8f759-6517-4e56-b7f3-f542498a20fb" }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "I_Tsr7snL-4q" }, "source": [ "## What happens if you have lots and lots of points?\n", "\n", "Whatever strategy that you use, it's almost useless if you have too many data points. Let's play with different number of data points and see how it looks. \n", "\n", "It not only becomes completely useless, it also take a while to draw the plot itself. " ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "id": "PC1f8sXCL-4q", "outputId": "7cce93ab-2a79-4300-be8e-5ad48babb20a" }, "outputs": [ { "data": { "image/png": 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JtU7yv8uguJ4wkQFyR3bUHzozZeroqyP8zgg4u2o61XsNJY0djeFWn9p0Uif4nzxRzo7CMhKOweBsn7MKtk22p+ivI390yDqe6A/hW66E46CSy2A0sC0j7tcZ0Gm27mmUk3faXOOxHXK5jrMP6mNbPsrEumlbbltoO2F77oi7Ti4Yrkau9dN0KlcHIYzHOkh52oa35Wzf57Inl5giRwbxkNOwg6x+tPl1WQnobLnUxzZAp5I0ONhie8/3GtqOIDtLa/zqtu2Pjq8jy6SJMjY8ytVrrdMO2LisiDC5zhkB6yXx2+eMwllv6/xwu6g+aPCq+y4V1HBUpzUgucYBv1YHMaZtB/hdHdEhpJxshzT2rXOtKdcuGbWe6vA5W2h/ZJ/s8i37D8JHVjp4Lsu27TddraxcfuYAJEY36dKJtZ1xlsO62TrK6KODD8SPDCkjR/ax+eyv1BP7EvVUO8wBSW0UByXUG/XXOtzWgXYA0fqq4+SyWJ0G5EI7SxjWyfbzi82y2HYQz+XA2rU6GTrR5sfl7tiP6I+z8jgbH/5wtX/WgOPH0UD5b7qpjkpiWKI4TMvr8dt5axi0hQsuBRiGQrcBXQooqIZ+u7ZPRWjX0baooO1aeZTVdZrtyLKdOWExssF3dHptGu0k27S3ex5slNuO2+k3DS0bT75HwdtGypFT5dk2JBqkbYNr42F6DKdds+g6WfeCeE8bn6PolBWNLJWJiuU0JOVtuu3sdLQIl8rvCKajOsNlIS5hcCkJOJKvsY4c3f+xFGwMNH403tQTdaQd1VwudmDOqg1jo6mRpjOpcazjh6y833T5rl6oQ2CZ2jk66uh3lp8jes56OCvlqK3h2clo7C2VdvmEeuQIj3uM3P/ifisd82HHzPA0SBYqT9fL867DqMGggd2uGbfTbzssOxhnmywbOxKNUY0eHWDLzU7LOq0R2jo+hOVyR+qKcsWxaI1IBzRGyd12aHjtsnIgLkYmqWOOEg7Xd+VK+6WuUNeoZ+4B4ndnWZ3l1aAdNpicsRi+xhlcjXj3K1iWGpHqIbJhcEo5j2qnHVxp429nuXUIdDwsv3YQy3tbg1T5uWzLvqltL0eVhWG2eRbvtZ1RbuqZn41P/Wzz7Sy+SwXtW1ojUIPLezXSxCWOrf4oj9ZwG1XHjhYNSXXfPTDEqcPdtsfKX5npINnuqTtt+KPKxe8X+h000l0d4BK1Ngy+19lyhkFdUodMnw6NbSx1wBF+BzqWKzuXzELr0Kkb7jXUttKBd0C3nTEz/TC8l6wdTGtXilhfdXBcsszsFWG4xNH64sy5dgcoP2eenG207WwH1IYH53S0uU9nuh2EWgjbXe6337A/sq61bYDyPeGwY6495bIxV6y0Tonx2Ka3qywIh9m9K66oTg0D1rStP/iDpXzwgy8dkFwljh9HgxFqlulce22d1WAUzM1wGjyur7Uxbo1eG5K1ot3joGergzGqY3GUwYq6lLQPN3yO6OtctBW+3fDZLhlaqsN1NNjxLFSZHeWwwnqP35k+GwZol9GAFXWpja8GYHt9K0ca24UcjcU6miOxkntbuRytszKcBuuLcteYaeu5S1RcV982fmAdXKoeHa0MHByQNox2T4VpspNpjSPrVpvnhTA8nF7rpXsOHMkU5dYuc1uoY9do9Xc6WkYaXWppfswL5d3OZlpvpR15b5ffrRTLtMVO80gds8bdsEHv0jFnGqy/GloLhdXOMLfp08BoR/wJywEhnRrbkVHhLBTnYo7AMG0n7z3tXig3/K+kXNoZOOMblT5l0RpmR0KDclh+GlX2X8Pya9O02ugcKoNhh6F1/tpVCivt6xaT/fB1o67R8HV03bZ8VNocnNTAbZeYrRTbrLZsbbt8b3W5fdlvtnq/WLvqChIHgtr86yw6A9POjrYDGa7U0JkxXfY/7UDh8G+gIweuQHBmZ7k6Ydgr7c+XCzJj7y2rPFh6hu5cdVUp/+//zR9QsYos1TfofzO4expYs+yGaZcmtUuUxBHVXtAjbz3eUTjCOfx5KQwrunG0xozv/uZoBZXbtaDHinZvwULpbw1+RxyHy3F4DSi4R6YdKVwKo8Jv5bjYbMZKGpaVNkrkfyVOxnAa2jXIYDm50VKDy5kf0SixPEbVuYWMzaOVwWL1WgeoddKlddaX6ry39w0vqxh2MqCtr8MzkG18o+qChlzrILSdpc6L3w+3DS4VsQ6My/AbZVDq7ByJdlR8uAxdkwytk7BYWAulz3rqyHorb9veFh3SI+nAcmU4Kv1tOzw8O3w0tPcvJq+j6f80mJDLKPk58orT3bYFazCK+k3atI4y+FY6wDjK0V5O+7XQdZbjYv2uRn87+HY0MxiL0bYj7QwWuBysnRl34Ga4fVMHFpO3+t/K0yW22iXmzzja0X5tguFB2ra9dN/t8G/2C8PtlifaHQ2GvZpOBiAjDsNhP56D2J5ItQaOxlLp39FAmKy7ZjbDk24QbLsWva2w7ejqWo62tIxj9GEltCM+LctZGrSaDI9WtN+Pqtg2Fj2U9aSxkFHSzlwcjfPoNY4mrRajDPtxc7Sd0yjU8VFGhB3wQku/RqVpXPkdNtzaDn2lcYwaQFgpCy0HW65eHwuGB1KOJUc7wtoettAyrAPD+wJXW5YLcSwMvrXMm4M/q92ntXVoVH0alZ6lyH6hAZ5Rs4Z+1+Z/1MDg8D1LbSOHP08as82Rxy5BXW2H57hzNHAsaNwYRfEcZUfVEO5wwzfKow2TWbGGy6/zyhRGsJbLFieBxdqodpngapO6Npkcbbm1m9EXYhxOZghr0fYcL+3Z7OxLl5m57619jkqH9O9ouMnLExrckOTRZZNoQIcQQgghhLBUdPTZz+fpmdjHPkCyU/p3NIDTRVxL7ublnvZhhBBCCCGEcKw5cHjfCi8f1Nsxy9g9u0a42dfTQyBORgghhBBCmDY2HD4ljgH4jjeBT46j4VNGOYrseFprF0IIIYQQwnLxGVYcFz68V7kz+nc0PHmFzS6uSQshhBBCCGHaOHj4lDge2Mfg+0qPvC/T7mj4GHqPeWQjeAghhBBCCNPIunWlXHllfaZG59sJ1k+EMC+6aP6BVDocOWYvhBBCCCFMA5s21RczGDysj2NuOX11OQ8rXgP6Tp2cfXYVLuvRjuZx8SGEEEIIIUwq69bV2QveTz21lN27q8PR+YxG/44GTsV995XyylfWnfZH++TTEEIIIYQQJpHnnquzGTgWPBmcxz1cdln3K3z6dzQQJjvqN2+u+zWyRyOEEEIIIUwTBw/OP0duz55Stm+vz9Ho3C7u39HQc3v88bp0Cg+u8/VoIYQQQgghjB1mMHjGHKt8eMfh6Jj+LXacC3bV33FH3fjC/51PE4UQQgghhDA2GGTHucAWZmbja1+rezU6307Qv6PBlBBTRI8+Wh/exx6NzGiEEEIIIYRp4dCheiCSK3v4zB7mPEdjhbCr/rHH6me9tsxohBBCCCGEaWFm5qX/43D8z//U2Y2O6d/ReOSRUvbuLeXMM+uMBq8QQgghhBCmhQ0b6kwGx9uuX1/3L99zTz2NqmMmw9FgQzhr0hBq5+cFhxBCCCGEMFaYwWBWg+fKscIHe3jfvnpYUsf072js3FmFyYZwdteHEEIIIYQwrUfcbthQbWMcD1b9dEz/jsa551Zh4rFlNiOEEEIIIUwrzz1XN4LjZPDiNNaO6d/RYMnUli11yohN4K5RCyGEEEIIYdp4+ulqF2Mf5zkaK4TN36xH07nAe2MjTAghhBBCCNPGoUP1hX3Myp+OWV8m5dxgp4bYAMP/IYQQQgghTCvr+zfj+5/R0KnYurXOZPDK0qkQQgghhDCtbNhQH9aXU6dWCBvAzzrrpZ7b8ENLQgghhBBCmAZmZ6tNzPaCOBorhPVn27ZVofLC8fDJ4HE4QgghhBDCNHHosB3sM+Y6pn9H49RT6xnBmzfXz+DSKfZrhBBCCCGEME2sO7yVoPNB99mJWIP25JNVkCyh6vwYrxBCCCGEEI4pOBnsY2ZWo2P6367+2GP1xKlTTpk/zounIoYQQgghhDBNzMzUQXhW9fDiWRod0/+MBrMZOBpnnFGdDh/aF0IIIYQQwjSyaVP3TsZkOBpMC7EZnN31bHjJMzRCCCGEEMI0781Yt64um8JG7pj+HQ32ZeCxPfpodTJ8gF8IIYQQQgjTxCmnlHLRRaU8/3x9xtzJJ5ee6d/RYPP3jh2l3HNP3ZvxwgtrnaIQQgghhBBWlxNOKOXEE0vZt6+u9Dn//Dqz0TH9OxoI8IIL6kNJnCoKIYQQQghhWli/vi6VYr8y+5fPOae+On/UQ/+OBtx5Z/Xg2GnPA/tCCCGEEEKYBtatK+Wkk+YPQ8IWdkaD946ZDEfjoYfqZpc8ETyEEEIIIUwTBw/WPRk4GtjDzGywfIo9Gp3bxP07GkwJ4bmxbIq1aQi082miEEIIIYQQxgZ2sHuVmd3gxf7lzunf0cCxYEc9gmXqKHs0QgghhBDCNPHss6U89VS1i889t5TXvraUW2/t/iHW/TsacNppdY8G00Y5dSqEEEIIIUwb69aVsnlz/cyDrLGJn3669MxkOBo4Gbt21ednZNlUCCGEEEKYtqVTzx8ecGd24+ab6yMg3L/cKf07Ghxry8NJeGDfc8+tdWpCCCGEEEJYXQaDesIU2wn27i3lllvq7IYnUXVK32diAWvPHnmklLvv7t5rCyGEEEIIYezMHD5dasuWag8zw3H//fX/junf0di0qZR/+7c6m5FlUyGEEEIIYdo4cKAOvj/xRCkXXVSdDfZn8AA/9jJ3yuxEbHy56ab5U6fw6Hh1/oCSEEIIIYQQxgb2L84FTgcnT/HYB5411zH9OxoIdM+e+hnnAqGyOXwCHlISQgghhBDCWGA/Bkumdu+un7GHO6d/R+NrX6sOBWvQECpTRZw+xdRRllKFEEIIIYRp4ODBupWAzeAPP1zt4LPOKj3Tv6PBUw953Lq76pkuwtEIIYQQQghhWjhw2AbeuLFuBGdLwamnlp7p39HAW+N4W5wNBJqTp0IIIYQQwjTy7LP1eRrYx+efXz93TP+Oxnnn1fVoTBfhyfE5hBBCCCGEaWMwqLMaPE+Dvct5MvgKueyy6mBwfBcwqxFCCCGEEMK0MTNTnQ1mMp58svRO/2fEMoPBSVOAUHE6QgghhBBCmDY2bKi2MIci8egHVvx0TP8zGgqSjS8hhBBCCCFMKy+8UPcrP/PMRByQ1L+j8dRTddkUZwXjbGSPRgghhBBCmDZmD9vAOBosn+KY284PSerfavcJiCybQphxNEIIIYQQwrRxqHEq2FbAszQ637u8fiKEyovjvDZtqgJlumgC1qWFEEIIIYQwVhh058VgfOdbC2YnYnc9DgbvvJwuipMRQgghhBCmjQMHqi28ZUv3K336Th3gZGzdWp98yPIpXyGEEEIIIUwb69fXPczsX+aB1h3Tv6Nx0knVY0OomzdXD46ZjRBCCCGEEKaF2dm6hYDlUmwjwDbufI9G/47GGWfUpx8iXDw3pos632EfQgghhBDCWGEDOC/2KbPi57TTqsPRMf07GjgYOBo4GXhu2ZsRQgghhBCmjeeeqy84++z6zobwjunf0UCg55xTH0jCK8umQgghhBDCtDE4vH2A5VIMxHMia+d2cf+OBoLcv7/u1WBmQ+F2vss+hBBCCCGEsaHt6ymsjz9e7eOO6d9aZ7kUMxn79s0L2WdrhBBCCCGEMA0cOjS/+ZslU5zKymB8x/TvaICOBk7Hhg1rnZoQQgghhBBWn5mZejASNjGD7xxz2zH9Oxo8MwMPDoHymfVpIYQQQgghTBsvvlgH3Xl+xhNP5HjbFcOxXR5ty4lTCJfnanS++SWEEEIIIYSx40ZwBuAZiO+Y/h0NnAs2gfOwPja9cHYwZwjjaMTZCCGEEEII08Khw3uUtYexkTumf0eDh5Ewg3HWWfWoW2Y42PiCk5FlVCGEEEIIYZo4eLA6GuedV2c2OqZ/R2P79lJ27CjlnnuqUCEzGSGEEEIIYRoZDOrejDPOyJPBxyJMHtj38MPzMxhshAkhhBBCCGHamJmp+zQYgO988L1/R4NjbW+6qU4TseEFZ4MX/4cQQghhsujcMAqha9avr/s02J+xe3f2aIzF0fjXf62fEWqeoxFCCCFMLtlfGcLRwXKpTZvqZw5IwmnPk8FXCEum7r23ChPhZiQkhBBCCCFM6ybwAwfqOwcldb7CZzIcDXbU42Ag1AlYjxZCCCGEEMLYwQ7m2XLMbvBU8M6fo9F36sC9GaxHe/rp+l2mXUMIIYQQwrQxM1OfCs5Wgvvvz5PBV8zZZ1dHg5OmctpUCCGEEEKYRtYfPhSJ58lx6tQE7Fvuf0bjkkvqRhce1odQfSJiCCGEEEII08DsbD0UiRkNBt75v/PZjMmY0di8uZSdO+sSKpdMIeiNG9c6ZSGEEEIIIRx7Dh0q5fnnqy28dWv9H2ejc/pPIYLE2WhPnELQPiU8hBBCCCGE450DB+ZnNNi3vH176Z3+HQ0erc6yqTPPnJ8yCiGEEEIIYdqYmal7NLCPTz219E7/joZH2zKjccYZcTRCCCGEEMJ0MjMz/8iHRx4pvdO/owE8Xp3lUqxFm4D1aCGEEEIIIRyT5VOcPsUqn5tvrqt+OqZ/q33Llrqrns3gTBPhxU3AcV4hhBBCCCGMHWxiBuHZp3H77aVn+j/eFo+NHfbMZDBNhHBzxG0IIYQQQpg2BoM64M6WAmzjzpdP9T+jsXdv9dpwMFg+hZPB0bY8fj2EEEIIIYRpcjSeO/xsOT7zrLmO6X9Gg+VSTz1V16PhcCDcHG0bQgghhBCmjcGg7tNgIJ5VP+efX3qm/xkNnIx9++oRXjgZPrQvhBBCCCGEaWMwqEfc8uA+Hv/QMf07GiyZQpjMZvCAkhBCCCGEEKaVmZn5R0B0PgDfv6PBfgxmMtjswr4MllCFEEIIIYQwbaxbV1f5bN5cyhNPZDP4imH9GUJ98slSzj03jkYIIYQQQpje2YxDh+Y3gd9/f+mZ/h0NNryccko9yotN4HlgXwghhBBCmOZTpw4e7P7EKejfakeQZ51VN7vcd1/3T0AMIYQQQgjhmDkazGhgH7N8avv20jP9OxoIkF31nDylcEMIIYQQQpg2Zmfr8ikOSNqxI47GisHJQKA+rM+d9iGEEEIIIUwTGzbUgXdmNM4+u/RO/46GJ05t2VKFm83gIYQQQghhGjl4sM5qnHZa/b/zRz/072jw5MPHH69HefEsDU6hCiGEEEIIYZqYmam2MKexshGcQ5J4sHXH9O9oIECmiHA0eH/mmbVOUQghhBBCCKvLYFDK00/X58phF+N48FDrjpmMPRo8tA+vjQ3hbgZn2ihH3YYQQgghhGnhxRfrdoLzzqvPmOvcFu47dbBpUym7dpXy8MP1f/do4HDkBKoQQgghhDAtnH56XTaFXYzTweMfOqZ/R4O1aFddVU+dwslguiiEEEIIIYRpY+/eelDS7t3zezU6pn9Hg4eRXHppKdu2VUej8931IYQQQgghHBMOHCjl0UfrnuVnn+1+AL5/RwMuu6yuR0OgcTRCCCGEEMI0MjMzvxn8zjur49Exk+FoIMidO+vn7MsIIYQQQgjTyJYtdckUDgbPl/vqV0vP9O9osA7tvvtKefDBuowK4YYQQgghhDCNsxnr19cTp3A6Hnqo9Ez/jgbnAyPEu+6qAs6TwUMIIYQQwjTy1FP1xWMfmNHg1TGzE/Fwkttuq/szeEgJnHJKfbZGCCGEEEII08C6dfUUVvYr88LZ4MCkjunf0WBaiLOC8d5wNpjRYGYDBySEEEIIIYRpYGamPqDv4MG64ocN4TxrrmP6dzQQKMLEc+PhfaedVjeEd77LPoQQQgghhLHhLAaD7djHV1xReqd/R4NzggEnAwfjscfqw0oyoxFCCCGEEKaJgwfrvowdO+rGcP7vmP4dDU6bYk0aj1xnFkPHI4QQQgghhGmc2Tjx8IP69u0rPdO/o4GnhnPBI9bZAJ7naIQQQgghhGnco6GjwWeOuM2MxgrBuUCIeGzsz2BNWgghhBBCCNPCxo31hR2Mk4FtzGFJOh+d0r/Vzt4MjvJi88vJJ+dY2xBCCCGEMF288EK1h9mjzAmsPNCa01j5rmP6dzROOKE6G3hsTzzR/RRRCCGEEEIIxwT2LbN06tFH60qfzk9h7d/ROOOMek4wHpxTRSGEEEIIIUwbBw7Mn7x6xx3dr/Tp39HgCK/XvrZODTGjkWNtQwghhBDCNDEzM78fg3fsY+xillB1TP+OBrzmNXWqiLVoCJe1aSGEEEIIIUwDg8H86h42hLN8iu0FLKHqmMlwNHAsON6WdwTc+Xq0EEIIIYQQxgp2MM4FjgZbCXh1vtJnMhyNp5+uu+0RLALu/CivEEIIIYQQxgpOxdat84ck8RyN7dtLz0yGo8HTwXE0WD4FCJgZjhBCCCGEEKaBmZn5I23ZBL5ly/wTwjtlMjY7PPLI/BPBeWcDDI5HCCGEEEII08CBA6U880wdeGdm4/LLS3nqqdIz/Tsa+/eX8vjj1YvDyWDzS+c77EMIIYQQQhg7DriffnopO3aU3ul/6RQzF3fdVb03XnmORgghhBBCmFZOOqmeNsVsBg/t65j+HQ1mL9gM7ixG5w8mCSGEEEII4ZjgIx5YRvXww6Wcckrpmf4dDdaiMYvBzAa77XO0bQghhBBCmEYGg2oTn3xyKdu2lbJnT+mZ/h0NHAt21bM3I8umQgghhBDCtHLwYJ3VOP/8UjZv7v6Bff1vBsdj49kZzmp4+lQIIYQQQgjTxrp1dUM4q346Z3YiHA2cCxwNn6MRQgghhBDCtDE7W+1iTmVlAJ7Tpzqmf0eDB5MgVOj8MeshhBBCCCEcUw4eLOWBB+oDrDs/JKl/R4Oju5ga4sEkIYQQQgghTCuHDtWBd+xj9i8zIN8x/TsaCPDJJ+vxXR7pFUIIIYQQwrSxcWPdn8GyqTvuqA+17pj+LXf2ZeBs8CwNNoXnqeAhhBBCCGGaWLeunsLK+4kn1lmNr3+9lL17S89MxmZwhIqjEUIIIYQQwrSxfn1dNuWLwXc2hLNXo2P6n9FgIziPWud5GpnNCCGEEEII08ZgUPdkCI4Gg/CdP8i6/xkNBIkQmSby9KkQQgghhBCmgdnZ+hTwM88s5ZWvrDMa+/bVU6ewkzumf8udJx7OzNTlUyyjQqhuCuf7EKZtE1gORTi2pF0JIciRBjhpjxe7ht+ORZuNTZS2avo2gM/O1gOSON6W8scu3rmz9MzsREwVIdxTT60CRbB4b9u31+9DWE3WclbNToWRjIVY7Yda0oEy23i8QH7adgWZb9587OIbp6EwHNZiuuDgzbjiCouT2fjJ5UjP72LFxWJtMu0JbQiDpMvhSPUTQ3Mani12vLQ169evLC/oGY968CF92MDo1FlnlbJrV+mZ/ls/KhKVlOkiXjgbrUGwUGUcLtBj6ZQQ9iQu7cJDXm7jt1I5nXFGLUc+H2kkaK2N6VGNwmIdyrEC3eI5MuxVoi4sNKuBLJ1CJe2j0j9u2Q3HQ/grGb1b607FAQz1crhz4H/KYiV55NQQIS7KbCl14Uhxcj/6YXoXG0mlXcVQGQeLpXupciLNR7r2SLo7rIdHGmUeNwuVIW0sOkO9Xa5+D4fn/eTPEc5xYL1dqN0Yjn/cLNaXryWki3YXu2NU2SKzI+kt9Zv6NryO/kg62NZP4keHeFfPeEdmR9L1HvbYDkOaaavo2xayQdQ1ZLfW/cJKmZmZ778Xu6atA8OfWTZl30Tdpx8599xSLr20DsR3TP9rMOj4zzmnrkWjkNgQ/thj1eCjIrpBnEJqvXsqoZtmKCR/o5D47P9tYRIm4bTGJNfzWmizDb/hUXLfgw/O30u4wx25cfmwleHGiPSOw5A1btKk8cn/pse8tJuKlB/3mj7uw3M+mlETKkQbvvEZHr/zbn6ff/7/nqqwUN6oYOjDKGx8jybdVmLkRPzmgc9OU4/Sg2HdM53jMOTsREiDDQwNFqMaHPtMPoXfKDNk6fWmQV1ovzsazCvx0OlR/5ARHYZya689/fT6/sQT/1cfFgqfNKqHynsheSqbhdLZQnkiI16EhZz4TBgeD+gx2sTrIAejSK1ucZ86TPtEWfAdHaYGhe/D6VY3hd/ULY1Gvmv1zN+Uix0S8uRavuezbZeOKP8vdFpfmy6uHdZr4mvLczgfrWy51vo7DNeRnjbP7X3oDfJVZsL36nF7/ai2E5CBcuEadJP00k6Mup48j0rTUiAuypr4SLvhD8sQ3aGOWjatQ2VZec9wezlKr4mzPW3GgSIe2jUsK4xS0mY/CaRTA5VXqxukx3rBO2EqU55hxTvLNdrwvE/95LdRfUor88X6UcLg96MtF+vGSp3oNt3kScNe3Wp/p4xPO63KEvlw3fChNfym3SH2cwu1X8NyYWkMcWFQ3nxzvYdyIU50jPJq6w7lsJCsFyuHUfEfjU2ivBxQ5GVbx7v595hW0tOmyaNbkSWf6fOQI3nV8TCspfbz6nOrG9QjwmlnpcaxsXq4vdxw2JG2LxnGtt+428Ei7mPGgs/UDernjh2lXHVVKQ8/XMqrXz0/AN8p/TsaNJhXX13KN74x37FrCNi4UngaDBSEDYGdkp2mjTyKy3W8/M2OztEnKjC/27BrAIFhEQ7xcj17STSe+U6niJcVzEZLg9Xw7HTaCjPKUBrVUGh8+owR4+JFXqyIhq8M2srUNqSgLAjTDhUwxgxjlGHtA2SgbZzaDoCGwgrPi4bTe4zXe+142rjID4YdkDavIe/EY6foEzOX02hYzo5Q2THbkWr0Ey4yN82jGmKcIfO7WOeqzG141V/DJwz0yxFR8o+ukV+uZ5RDfbIcW71qHUg+L8XYHzUaR7waQ4R19tlV/g89VNNCQ8d1lA1pMW47FctqlPFrR9Q6/8qMfBPncLoduUcGGv7m2bwqX41WZMt9F15YDdA9e+o9tB/tqCTOEeGSTsvD8rc+IXfC4p0Xgww6IsiC/9VdO1vl18pF+VK2Gmo6C4TP/+bNd8vZTof8DY9+8T15tk3QEFSuGjmOkCIP86pRoAzbztk0Kzd1YyFHcNRyLkf1qCPU17vvnq9HbZnZMfM99ygXfiNfGvyexEL6KTvuo5+gbfnyl+cdRpxd87IUQ1SjvL3e+uX3tr3I14dmuVTGgRryRvrUIdKsk6jsMKR80m/bF9gOe7oMv1H3gAE3+yh+1whDpsiBPow0WYamH7mTPuuJ6WgHI7hGh5XwSJdhmPfhAQH3T/qU4uH+rA1fvbGtsvyVHe2IMjcdbX88bCiqI7bRyop4qAe2Lwu1f22fNty3tbqJXFonjfvsj2gHyPuwY22/4jJM9Vp7A4YdRcP2XuTy8pfXMqfOkm+dDZwQdQEdB3VsscFLZa8+29Z4PWGTX9JKfSN8y0Qbg5e6aXmqbxjDrGC45556jYNchGWbB7ZP5pe0Ux+QJ/mxHbUfs3ycbdKZt98YLr+2L3BA1/aD/FlPKRvqDXkhXuNeLu2soOnduHE+D/Y1Ljkm/+QDHaCe8bt13P7Uk1eRJ2l805tqvonnu76r9E7/jgaF8brX1c7oppvmR2wROkpy0UW1QVVJNTz5juvssFAeC5nvNBD47pFHakfLvU5RsryHONsGxREkjRZHzlAOlIWOjTQRf7tph7D5TuNC5aMiEi7GGkqjMdAahW3F5147ANfpWdns7BxNIY8aWDYChkOF0inQcDDNXK+xpGHkC3kRl41Oa0yCDQH5Jj+twUCjxT169MRJeBrQQIOEvHRaNF64z4bCeLlXg5DO1M6W9Ol8Lua4uVSgHYWzodRQbhtVOzvi1YCD1hAcHq0k7xo4Xqehwf3k0Y7GWQHKl3d0g7h2765hkh9PmOAa9YXP6B/pczTQjpf0a6RoTChHrnc2wnJsP5tWy0LdIW12QKQHeVMHeeEA3X57Dde0kG4bdA1E7iEO8kLDSfp1QJUF9ztjoxHeGjrqhh2MhihhMPpDuDp5vDsL6r12MMqRWdNv+ZY6Wnj//fMdP/dzHc4JMmEEiTxRP5ADZcs7eowjTp6sSzoXdjQYCtRbwidMyljDiXQTFnkiDMMBDVWXRjkCSLyW7SteUeVDfpztssNydJt2wLLR+aMOOTtFPbIcWj22TdJI0gmi/Ck7Z4oM3zrTtmfWJe5jul+52uE7ckq52Ma2hqYDHlxH/tWH886r4VEunCXPfbapfKeD60yVxh3pth1u21cHUhxwMm/IDx0CB6eg1SP12jpHWigjyo58O+po/8Q9Go0OlFAehI8u6aS0M9Rcz0unqq0TvEgr91KW9netQ0O+GIEH+itexIFOkoZWRhrmyEpnnO81kHQuKBN0zrJvR+vVJcuXvLWju+pHqzP2a5Z3m4e2DSdu2kjS7Az3BRdUIwxH/5Zbahzoge0EYdpGamAq23bWyRFmZWZdol259955+8I6al0mLvtpyredAVKvkJN6ovzMt/XLQScHdSgzBkbIF3p22WVV5pQ1v/Eir9gyxIveESZyQfe51jCdSbQ8NHK1U4hfXVUvbcNaJ9Ole1yDfjt46iAIMtI2Iz32Yy4hMj3GYZtp3efzFVfU/CBX4DfkhnwdYCM8bRTSpOPhYFy7gsW0q4PcSz1Xd5Hf8OByuwS17ce1EYjTvhJ95H/1w7gOHQ6TuMy3DlWrg7Y77QZvZUTYL3vZfPvJ6wd+oOpe58wMBkeed9q3b1/Ztm1b2bt3bzl5LaZoKLCvfrWU666rT0GkE3G62DWAKDAK5hp2CoVGgc4BYw3lvPLKej3ftUYqSkGYVDQNVH4jvNYw1pjTY3d0zYrJZzsm0kEaCRvldISFe2nc+Z04nQ7UsNHwbY1dwmOEDmOH+zS8Sa8jyhoCfLZT1XunMTK8dmQArNwaM87UOJpq509D9prXVLnRaJEvIO333VcbgtZxoUzskDRidVDs7DSoqFgsPyNdOHcaME452ymAHb5GoyOKvNQLsGNrRxD4bBp1boDvlH/bKCkLO2bSo5FKXtoRj9Zxs7FrR4GRp2nRGWuNKRpiDUh0l+lQjChk+4UvzDe0ysGRzvYMbWWsoeA6TsqCeJ2Gpl5wD/dinFGeOuCOqrYGpx28nZJT87y/6lWlfPd31+vpBLnGjuG226oBow7b4FLel1xSyrd9W/2ODpR0oAPIif/Jt8YWYaETGgvt6JoOKy/KiXjoLIiDtatcwwAFuuEshe2GHSfxvva18yODtBdcixxID7+71Ir8kDYdcmdUHK3TqLItUE4udXI5GXUZOWkcI1edTvJGmbjxDznoDDsyaB2zfGl/GBwhHtJNOrmfTkjH36UX/O6SInXWkWhkz6tdZukooR0zOIgA6hrypz1l9tmy0ZlVd9yn4KyyTjLlRzgOoFje6rqjnrZVzlpghNHxqpN33lnLsHVSbBOt05aZgxbK1cEj6yzfOShjXVJnnL3TaOBa2sc3vKG2jcoWXbnrrpqm1oj0nTpOHNQV7iNvhGt7bjikk7ySTx18HGqNOORH+tBdXrRNLt/T8UQfWgcJuaEP6iQDeujKrbfOO6SEQx6Ik+uoV9yL7A3b2RkdEgdr2pk3DWvSTz5IP9fbZvC9TjIvB85cltg6A4RJfqlD9qs6LKSPtJEf7sMpcLCBuBx8sPzblQEa/e2qBOs4cjr//DqgYjzUE2bMqMM6D+450E6i3G2TTYczbNRNZOQ1yFXHybaPttrBJGSA7HAylCmDF+SXcGgnGey58cbaBloOtr/2bVzXLvdzgMC+nvDUT2cg1F3SR3uIzt1xR9UP7iEvvCMLwm/bGNsqB3J1kriXd9LsjJQOLjLhnfwTH2HzTv6Jw/6T69A56g4ysy0jzaYD3EOrHUR63vrW2keQBtos2kzCUJdcrcJ9yFPHUlmRXsLR1uB/rneA1zZ882EnzD6jnbHXsafdJD7aA2SrY49ceSFLbR50G7nQ1uCIrSFL9Q0mw9EAGjMU7Gtfq6OOGA58R8FSEDgRNJQUJgrmTALZc4TTTp+C15BBSQiD72hg//u/68g6FZkCZ6SQzxgrKBv5p0OlkSYu0tGOOlARiYdGjYqkYlFRnO1wqZejbW4GRdntKO2gSQMVzGlI0mtDSlroVHC+qCSOqnENnZsy0hAhj86ygAYo35H2iy+ulZCwkCHpQnYYhciBPFtZSStxIEfz4LSyHZ8VhmuodJQFI8cu93H6l5ejaaQTudH48HJamrxRXk4/awjj4XOmtA0/5Yc8yDdyw3hEzugC95Meyk1ZIUfKAllRxh6nTMdCR3b55bX8SAeNAR0XZavDRHopG0c1kR16onODXOmgnFXjXvcG6HTYcCAb5IyO4nARnx258aMb/E4D6TJCyhOddcYDg5Oy4N2ZE2ROOvhdx1bjn/L5yleqDDTieEcWOq12gk5pk2fXCJMmrqGRJF38hnyQBTpiI065UV7Ky1ko8q8BTB6HjUSNQ/SC8ChH8opsNZS4TsOc6zSUSC86QLzkBbnSjiBTdJt1rqQb3TEffO+yKNLC96SLeF2WgmGIzPnO0U9HshytB5dl2hlRdqTHgy0wFMiHzpOdpLNm1hPip4zo3LmOe90ISPpJB+Wl8eSMpp2vI+Xc53II5KBDT75IE/WI8qIe8bttl06QDi+ot458W395pw7aNqDX1EXkQ/2hDJET6SL/dPg41nyHkUQedSxIG2mkXF1WgLH3xjdW/ac+tQ6hy0X53n7AZW7IlPbStfQaU4606sRa3yw3ZINOkFby6uBOO/JIHtpRYNt/PpNnZvqQh04J95BnZwbJK2mgnjg45Awq5Uzc7tFwSSbpRf7OpJA/7rOdse105oO8kBaNM/LP/ThItHOO3JNv+ljKAhlqaJtfl3Kq4zqFzrY5wEZ/Sp5BOdIGUf9JE+VFXJ/7XI2LPBEu5cvv5JPyok/U+SKNtJGkWwOaF+mjXLhWeVKv0D3SjGyoH1zDCxm0y8E03O1rHRQwbPs1wqS/Ia/IBnnecENtP0gvdZH06wSiA8ys6OQgB2wFZEc/we/tPgEH1bifNovyJGzSikyooxqg/O7IPhA/4dHGkSbekQN5Qo+QBeknLNovXuTBdo10uWoAeTvQh65i0DrAhuycqdC4RkakjfLhPtJM2C7pst0jDfxGOtVDytIX6VMHaQeQLyBX8oxsyY8Otfu7tBHIc9sGk0Z0i3Bcaoyjw+CYsnDJFHlAT2hrXW5H2pGPKyuIw0ESZ4D53zKwjdduIx27d9d4dNKpy+SF/FNOyNpZf51pZ8Wd/XF21YE+0rvUgzaOIcefo9HSru90ucUweuMuAVgO7XrR9l6XUix0usiodLZTwy0uZRqVvuE1wU5F2xAtFF67Frf93uUAGjte147c98yR8j5OjiQTZdmuaW5/cxbItaY2Gs5iiN9ZDqP0pE1Lq3v+35aj+0lWgrNp7alL1qN2P8nRhu3yDcNWluOi3T+k3juLtFTZeF/biC9W79v11y3t/oxR14077zLOOt2OFI8Kz3aqXRozShaj0tguGRulV14zqk1bCsNpGxV+WxYLtdMLycPPi/Uvwzpv/XI5RdsHtO39cD05FjjCfqT+caF+5WgZ1W62daxdfjp8XyvvhfTDNrhd/jRMO5rfytnycQBosfq8Ulr9hHavykJ2zVLsnmE0wkcZpQvZSM74Oao/6j5n/rjP2VpYqnyW01a0bfLR6KE6gVPgYOhK7MNjyaER/WTHLNU3WJJLpC9CoFPF8OkRISyH9iSQSWKhE4TC8nFjbAgt0Yt+ZbxY+zdN5eZS3OXQs3xwKBY69SkcFfoER5qvWJKjsf/wFOyuzh8KEkIIIYQQQlgd8BGY2VjR0qlDhw6VBx54oGzdurXMrPE0Ex4UDs/u3bv7WMYVuic6E5ZLdCYsl+hMWC7RmTDJOoP7gJOxc+fOMrvIUq8lzWgQwLlsSOsIBLzWQg6TRXQmLJfoTFgu0ZmwXKIzYVJ1ZrGZDOl/t0kIIYQQQghh4oijEUIIIYQQQhg7E+donHDCCeWaa66Zew9hKURnwnKJzoTlEp0JyyU6E6ZBZ5a0GTyEEEIIIYQQjusZjRBCCCGEEEL/xNEIIYQQQgghjJ04GiGEEEIIIYSxE0cjhBBCCCGEMHbiaIQQQgghhBCmw9H4+Mc/Xs4///yyadOmcvXVV5cvfvGLi17/V3/1V+XSSy+du/6KK64o11577aqlNUyezvzhH/5hedvb3la2b98+9/rO7/zOI+pYOP5Ybjsjn/zkJ8vMzEz5/u///mOexjDZOvPkk0+W97///WXHjh1zx1FefPHF6Z+mjOXqzG//9m+XSy65pJx44oll165d5QMf+EB57rnnVi29Ye34/Oc/X975zneWnTt3zvUxf/M3f3PEe6677rpy1VVXzbUvF110UfnEJz5RumPQGZ/85CcHGzduHPzJn/zJ4Kabbhr8xE/8xOCUU04ZPPTQQyOv//d///fBunXrBh/96EcHN9988+CXfumXBhs2bBjceOONq572MBk68+53v3vw8Y9/fPCVr3xlcMsttwx+9Ed/dLBt27bBfffdt+ppD5OhM3L33XcPzjnnnMHb3va2wfd93/etWnrD5OnM888/P3j9618/eMc73jG4/vrr53TnuuuuG9xwww2rnvYwGTrz53/+54MTTjhh7h19+fu///vBjh07Bh/4wAdWPe1h9bn22msHH/rQhwaf+tSneOzE4NOf/vSi1991112DzZs3Dz74wQ/O2b+/8zu/M2cPf/aznx30RHeOxhvf+MbB+9///m/+f/DgwcHOnTsHv/mbvzny+h/6oR8afM/3fM9Lvrv66qsHP/mTP3nM0xomU2eGOXDgwGDr1q2DP/uzPzuGqQyTrjPoyZvf/ObBH/3RHw1+5Ed+JI7GlLFcnfm93/u9wQUXXDB44YUXVjGVYZJ1hmu/4zu+4yXfYUS+5S1vOeZpDX1RluBo/OzP/uzg8ssvf8l373rXuwZvf/vbBz3R1dKpF154oXzpS1+aW8ois7Ozc/9/4QtfGHkP37fXw9vf/vYFrw/HF0ejM8M888wz5cUXXyynnnrqMUxpmHSd+dVf/dVy5plnlh/7sR9bpZSGSdaZv/3bvy1vetOb5pZOnXXWWeVVr3pV+Y3f+I1y8ODBVUx5mCSdefOb3zx3j8ur7rrrrrmldu94xztWLd1hcvjChNi/60tHPProo3ONMI1yC//feuutI+/Zs2fPyOv5Phz/HI3ODPNzP/dzc2sihytsOD45Gp25/vrryx//8R+XG264YZVSGSZdZzAS//mf/7n88A//8JyxeMcdd5T3ve99c4Ma11xzzSqlPEySzrz73e+eu++tb30rq03KgQMHyk/91E+VX/zFX1ylVIdJYs8C9u++ffvKs88+O7fPpwe6mtEIYbX5yEc+Mre599Of/vTcZr0Qhtm/f395z3veM3eIwOmnn77WyQkTwqFDh+ZmwP7gD/6gvO51ryvvete7yoc+9KHy+7//+2udtNApbOxl1ut3f/d3y5e//OXyqU99qnzmM58pH/7wh9c6aSEcHzMadOLr1q0rDz300Eu+5/+zzz575D18v5zrw/HF0eiMfOxjH5tzNP7xH/+xvPrVrz7GKQ2TqjN33nlnueeee+ZOA2mNSFi/fn257bbbyoUXXrgKKQ+T1M5w0tSGDRvm7pPLLrtsbhSSZTUbN2485ukOk6Uzv/zLvzw3qPHjP/7jc/9ziubTTz9d3vve9845qSy9CuFI9u/JJ5/czWwGdKW1NLyM/PzTP/3TSzp0/met6yj4vr0ePve5zy14fTi+OBqdgY9+9KNzo0Sf/exny+tf//pVSm2YRJ3h6Owbb7xxbtmUr+/93u8t3/7t3z73mSMow/HN0bQzb3nLW+aWS+mUwu233z7ngMTJOP45Gp1hv+CwM6GjWvcHhzCB9u+gw+PgON7tE5/4xNxxXe9973vnjoPbs2fP3O/vec97Bj//8z//kuNt169fP/jYxz42d1TpNddck+Ntp4zl6sxHPvKRuSMH//qv/3rw4IMPfvO1f//+NcxF6FlnhsmpU9PHcnXm3nvvnTvN7qd/+qcHt9122+Dv/u7vBmeeeebg137t19YwF6FnncF+QWf+4i/+Yu7o0n/4h38YXHjhhXOna4bjn/37988du88L8/y3fuu35j5/4xvfmPsdXUFnho+3/Zmf+Zk5+5dj+3O87RLhLOCXvexlc8Ygx8P953/+5zd/+9Zv/da5Tr7lL//yLwcXX3zx3PUc9fWZz3xmDVIdJkVnzjvvvLlKPPyikQ/Tw3LbmZY4GtPJcnXmP/7jP+aOW8fY5KjbX//1X587JjlMD8vRmRdffHHwK7/yK3POxaZNmwa7du0avO997xs88cQTa5T6sJr8y7/8y0jbRB3hHZ0ZvufKK6+c0y/amD/90z8d9MYMf9Z6ViWEEEIIIYRwfNHVHo0QQgghhBDC8UEcjRBCCCGEEMLYiaMRQgghhBBCGDtxNEIIIYQQQghjJ45GCCGEEEIIYezE0QghhBBCCCGMnTgaIYQQQgghhLETRyOEEEIIIYQwduJohBBCCCGEEMZOHI0QQgghhBDC2ImjEUIIIYQQQijj5v8DVEq9P9vqHcEAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# TODO: play with N and see what happens. \n", "N = 100000\n", "x = np.random.rand(N)\n", "jittered_y = np.random.rand(N)\n", "\n", "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "TnQjanpUL-4r" }, "source": [ "## Histogram and boxplot\n", "\n", "When you have lots of data points, you can't no longer use the scatter plots. Even when you don't have millions of data points, you often want to get a quick summary of the distribution rather than seeing the whole dataset. For 1-D datasets, two major approaches are histogram and boxplot. Histogram is about aggregating and counting the data while boxplot is about summarizing the data. Let's first draw some histograms. " ] }, { "cell_type": "markdown", "metadata": { "id": "5IDYu2haL-4s" }, "source": [ "### Histogram\n", "\n", "It's very easy to draw a histogram with pandas. " ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "id": "v_ybN2u-L-4t", "outputId": "19d0077a-cb23-446b-85e8-dab90044bc34" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cars.Acceleration.hist()" ] }, { "cell_type": "markdown", "metadata": { "id": "FE0uzD6wL-4u" }, "source": [ "You can adjust the bin size, which is the main parameter of the histogram. " ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "id": "82El3ByNL-4v", "outputId": "a9db9941-9404-4ecf-f237-8fa28a157794" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cars.Acceleration.hist(bins=15)" ] }, { "cell_type": "markdown", "metadata": { "id": "URmajoCTL-4w" }, "source": [ "You can even specify the actual bins. " ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "id": "BrYgoqlSL-4x", "outputId": "9c96056d-6c31-43c4-af21-d6ac9fa3a64e" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "bins = [7.5, 8.5, 10, 15, 30]\n", "cars.Acceleration.hist(bins=bins)" ] }, { "cell_type": "markdown", "metadata": { "id": "dFT12811L-4x" }, "source": [ "Do you see anything funky going on with this histogram? What's wrong? Can you fix it? \n", "\n", "**Q: Explain what's wrong with this histogram and fix it.** \n", "\n", "(hints: do you remember what we discussed regarding histogram? Also [pandas documentation](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.hist.html) does not show the option that you should use. You should take a look at the `matplotlib`'s documentation. " ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "id": "I70dRbUlL-4y", "outputId": "609d2fc9-28a3-4fdb-ad50-22055c1f7374" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "B-hqyb4KL-4z" }, "source": [ "### Boxplot\n", "\n", "Boxplot can be created with pandas very easily. Check out the `plot` documentation: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html \n", "\n", "**Q: create a box plot of `Acceleration`**" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "id": "Rec5SXp8L-4z", "outputId": "021f26d2-6584-4542-f5a5-de48578642cb" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "1ZrtDTmcL-40" }, "source": [ "## 1D scatter plot with Seaborn and Altair\n", "\n", "As you may have noticed, it is not very easy to use `matplotlib`. The organization of plot functions and parameters are not very systematic. Whenever you draw something, you should search how to do it, what are the parameters you can tweak, etc. You need to manually tweak a lot of things when you work with `matplotlib`. \n", "\n", "There are more systematic approaches towards data visualization, such as the \"[Grammar of Graphics](https://www.amazon.com/Grammar-Graphics-Statistics-Computing/dp/0387245448)\". This idea of *grammar* led to the famous `ggplot2` (http://ggplot2.tidyverse.org) package in R as well as the [Vega & Vega-lite](https://vega.github.io) for the web. The grammar-based approach lets you work with *tidy data* in a natural way, and also lets you approach the data visualization systematically. In other words, they are very cool. 😎\n", "\n", "I'd like to introduce two nice Python libraries. One is called `seaborn` (https://seaborn.pydata.org), which is focused on creating complex statistical data visualizations, and the other is called `altair` (https://altair-viz.github.io/) and it is a Python library that lets you *define* a visualization and translates it into vega-lite json. \n", "\n", "Seaborn would be useful when you are doing exploratory data analysis; altair may be useful if you are thinking about creating and putting an interactive visualization on the web. \n", "\n", "If you don't have them yet, check the [installation page of altair](https://altair-viz.github.io/getting_started/installation.html). In `conda`, \n", "\n", " $ conda install -c conda-forge altair vega_datasets jupyterlab \n", "\n", "Let's play with it. " ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "executionInfo": { "elapsed": 3659, "status": "ok", "timestamp": 1664924274823, "user": { "displayName": "Vincent Wong", "userId": "06927694896148305320" }, "user_tz": 240 }, "id": "5CXJ0sdVL-42" }, "outputs": [], "source": [ "import seaborn as sns\n", "import altair as alt\n", "\n", "# Uncomment the following line if you are using Jupyter notebook\n", "# alt.renderers.enable('notebook')" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "executionInfo": { "elapsed": 200, "status": "ok", "timestamp": 1664924323402, "user": { "displayName": "Vincent Wong", "userId": "06927694896148305320" }, "user_tz": 240 }, "id": "SKJbEtT9L-43", "outputId": "bac41628-b0c2-4cf4-9a58-80d5e34da5fe" }, "outputs": [ { "data": { "text/html": [ "
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NameMiles_per_GallonCylindersDisplacementHorsepowerWeight_in_lbsAccelerationYearOrigin
0chevrolet chevelle malibu18.08307.0130.0350412.01970-01-01USA
1buick skylark 32015.08350.0165.0369311.51970-01-01USA
2plymouth satellite18.08318.0150.0343611.01970-01-01USA
3amc rebel sst16.08304.0150.0343312.01970-01-01USA
4ford torino17.08302.0140.0344910.51970-01-01USA
\n", "
" ], "text/plain": [ " Name Miles_per_Gallon Cylinders Displacement \\\n", "0 chevrolet chevelle malibu 18.0 8 307.0 \n", "1 buick skylark 320 15.0 8 350.0 \n", "2 plymouth satellite 18.0 8 318.0 \n", "3 amc rebel sst 16.0 8 304.0 \n", "4 ford torino 17.0 8 302.0 \n", "\n", " Horsepower Weight_in_lbs Acceleration Year Origin \n", "0 130.0 3504 12.0 1970-01-01 USA \n", "1 165.0 3693 11.5 1970-01-01 USA \n", "2 150.0 3436 11.0 1970-01-01 USA \n", "3 150.0 3433 12.0 1970-01-01 USA \n", "4 140.0 3449 10.5 1970-01-01 USA " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cars.head()" ] }, { "cell_type": "markdown", "metadata": { "id": "1mcAkxZiL-43" }, "source": [ "### Beeswarm plots with seaborn \n", "\n", "Seaborn has a built-in function to create 1D scatter plots with multiple categories. " ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 296 }, "executionInfo": { "elapsed": 492, "status": "ok", "timestamp": 1664924327056, "user": { "displayName": "Vincent Wong", "userId": "06927694896148305320" }, "user_tz": 240 }, "id": "Gs3FH1EkL-44", "outputId": "cfeba698-0e45-4a1b-d564-a0f511115a13" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.stripplot(x='Origin', y='Acceleration', data=cars)" ] }, { "cell_type": "markdown", "metadata": { "id": "21dYZ80YL-44" }, "source": [ "And you can easily add jitters or even create a beeswarm plot. " ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "id": "jERE2xD4L-45", "outputId": "77fe0723-b376-401e-b2a7-fbfb0ca18000" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.stripplot(x='Origin', y='Acceleration', data=cars, jitter=True)" ] }, { "cell_type": "markdown", "metadata": { "id": "6yZjfo57L-45" }, "source": [ "Seems like European cars tend to have good acceleration. 😎 Let's look at the beeswarm plot, which is a pretty nice option for fairly small datasets. " ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "id": "5UsgwUxCL-46", "outputId": "70fdfb73-3b7a-427a-9e45-d19fc821ed8f" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.swarmplot(x='Origin', y='Acceleration', data=cars)" ] }, { "cell_type": "markdown", "metadata": { "id": "uGtRr9boL-47" }, "source": [ "Seaborn also allows you to use colors for another categorical variable. The option is `hue`. \n", "\n", "**Q: can you create a beeswarm plot where the swarms are grouped by `Cylinders`, y-values are `Acceleration`, and colors represent the `Origin`?**" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "id": "-lOjrxFPL-47", "outputId": "0d7613c9-3524-40ef-c067-f6a8235cc226" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "xxjQ8B5QL-48" }, "source": [ "And of course you can create box plots too. \n", "\n", "**Q: Create boxplots to show the relationships between `Cylinders` and `Acceleration`.**\n" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "id": "Fe0_xjYlL-48", "outputId": "d91764a9-2714-4cbe-e8f4-071e63e8a9f5" }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "ZRyvuefeL-5D" }, "source": [ "### Altair basics" ] }, { "cell_type": "markdown", "metadata": { "id": "yLiPdxImL-5D" }, "source": [ "With `altair`, you're thinking in terms of a whole dataframe, rather than vectors for x or vectors for y. Passing the dataset to `Chart` creates an empty plot. If you try to run `alt.Chart(cars)`, it will complain. You need to say what's the visual encoding of the data. " ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 485 }, "executionInfo": { "elapsed": 313, "status": "ok", "timestamp": 1664924331727, "user": { "displayName": "Vincent Wong", "userId": "06927694896148305320" }, "user_tz": 240 }, "id": "eXhzMKi2L-5E", "outputId": "2585b927-5052-45dd-b179-94023b806e42" }, "outputs": [ { "ename": "SchemaValidationError", "evalue": "'{'data': {'name': 'data-583e73726c1545c56c203344161a975c'}}' is an invalid value.\n\n'mark' is a required property", "output_type": "error", "traceback": [ "\u001b[31m---------------------------------------------------------------------------\u001b[39m", "\u001b[31mSchemaValidationError\u001b[39m Traceback (most recent call last)", "\u001b[36mFile \u001b[39m\u001b[32m~/git/dataviz-solutions/.venv/lib/python3.12/site-packages/altair/vegalite/v5/api.py:4033\u001b[39m, in \u001b[36mChart.to_dict\u001b[39m\u001b[34m(self, validate, format, ignore, context)\u001b[39m\n\u001b[32m 4031\u001b[39m copy.data = core.InlineData(values=[{}])\n\u001b[32m 4032\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28msuper\u001b[39m(Chart, copy).to_dict(**kwds)\n\u001b[32m-> \u001b[39m\u001b[32m4033\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[43mto_dict\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n", "\u001b[36mFile \u001b[39m\u001b[32m~/git/dataviz-solutions/.venv/lib/python3.12/site-packages/altair/vegalite/v5/api.py:2004\u001b[39m, in \u001b[36mTopLevelMixin.to_dict\u001b[39m\u001b[34m(self, validate, format, ignore, context)\u001b[39m\n\u001b[32m 2001\u001b[39m \u001b[38;5;66;03m# remaining to_dict calls are not at top level\u001b[39;00m\n\u001b[32m 2002\u001b[39m context[\u001b[33m\"\u001b[39m\u001b[33mtop_level\u001b[39m\u001b[33m\"\u001b[39m] = \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[32m-> \u001b[39m\u001b[32m2004\u001b[39m vegalite_spec: Any = \u001b[43m_top_schema_base\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mTopLevelMixin\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[43mto_dict\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2005\u001b[39m \u001b[43m \u001b[49m\u001b[43mvalidate\u001b[49m\u001b[43m=\u001b[49m\u001b[43mvalidate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mignore\u001b[49m\u001b[43m=\u001b[49m\u001b[43mignore\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mdict\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpre_transform\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[32m 2006\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 2008\u001b[39m \u001b[38;5;66;03m# TODO: following entries are added after validation. Should they be validated?\u001b[39;00m\n\u001b[32m 2009\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m is_top_level:\n\u001b[32m 2010\u001b[39m \u001b[38;5;66;03m# since this is top-level we add $schema if it's missing\u001b[39;00m\n", "\u001b[36mFile \u001b[39m\u001b[32m~/git/dataviz-solutions/.venv/lib/python3.12/site-packages/altair/utils/schemapi.py:1169\u001b[39m, in \u001b[36mSchemaBase.to_dict\u001b[39m\u001b[34m(self, validate, ignore, context)\u001b[39m\n\u001b[32m 1167\u001b[39m \u001b[38;5;28mself\u001b[39m.validate(result)\n\u001b[32m 1168\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m jsonschema.ValidationError \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[32m-> \u001b[39m\u001b[32m1169\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m SchemaValidationError(\u001b[38;5;28mself\u001b[39m, err) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 1170\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m result\n", "\u001b[31mSchemaValidationError\u001b[39m: '{'data': {'name': 'data-583e73726c1545c56c203344161a975c'}}' is an invalid value.\n\n'mark' is a required property" ] }, { "data": { "text/plain": [ "alt.Chart(...)" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "alt.Chart(cars)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 51 }, "executionInfo": { "elapsed": 172, "status": "ok", "timestamp": 1664924338907, "user": { "displayName": "Vincent Wong", "userId": "06927694896148305320" }, "user_tz": 240 }, "id": "-OAXqT-CL-5E", "outputId": "15f0797a-d02a-4220-df0a-5db6fc7d81aa" }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "alt.Chart(cars).mark_point()" ] }, { "cell_type": "markdown", "metadata": { "id": "_yG9M57kL-5F" }, "source": [ "So you just see one *point*. But actually this is not a single point. This is every row of the dataset represented as a point at the same location. Because there is no specification about where to put the points, it simply draws everything on top of each other. Let's specify how to spread them across the horizontal axis. " ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "id": "67Zoa2aCL-5F", "outputId": "6115d701-15f8-4cd3-b839-a519bdbae281" }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "alt.Chart(cars).mark_point().encode(\n", " x='Acceleration',\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "nwld_6WNL-5F" }, "source": [ "There is another nice mark called `tick`:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "id": "LXwLLZk6L-5G", "outputId": "db974ef5-4dfa-4c33-b4b1-3cf85590a87a" }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "alt.Chart(cars).mark_tick().encode(\n", " x='Acceleration',\n", ")" ] }, { "cell_type": "markdown", "metadata": { "id": "HfSTSjHaL-5G" }, "source": [ "In `altair`, histogram is not a special type of visualization, but simply a plot with bars where a variable is binned and a counting aggregation function is used. " ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "id": "ptrRt3YmL-5H", "outputId": "efe9c567-7c58-429c-eac5-7cb3c4ca1287" }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "alt.Chart(cars).mark_bar().encode(\n", " x=alt.X('Acceleration', bin=True),\n", " y='count()'\n", ") " ] }, { "cell_type": "markdown", "metadata": { "id": "aUjfx0TiL-5H" }, "source": [ "**Q: can you create a 2D scatterplot with `Acceleration` and `Horsepower`? Use `Origin` for the colors.**" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "id": "vzYUZPheL-5I", "outputId": "399cd345-6ad9-4975-cb82-697d64185948" }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
\n", "" ], "text/plain": [ "alt.Chart(...)" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# YOUR SOLUTION HERE" ] }, { "cell_type": "markdown", "metadata": { "id": "LstfAIpnL-5I" }, "source": [ "Because altair/vega-lite/vega are essentially drawing the chart using javascript (and D3.js), it is very easy to export it on the web. Probably the simplest way is just exporting it into an HTML file: https://altair-viz.github.io/getting_started/starting.html#publishing-your-visualization\n", "\n", "**Save the chart to m07.html and upload it too.** " ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "id": "PpILKkQHL-5I" }, "outputs": [], "source": [ "# YOUR SOLUTION HERE" ] } ], "metadata": { "anaconda-cloud": {}, "colab": { "provenance": [] }, "kernel_info": { "name": "dviz" }, "kernelspec": { "display_name": ".venv", "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": "3.12.10" }, "nteract": { "version": "0.15.0" }, "toc": { "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 0 }