Python-basico-parte2-sem-respostas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sumário\n",
    "\n",
    "- Classes\n",
    "- Módulos\n",
    "- Pacotes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classes\n",
    "\n",
    "Classes proporcionam uma forma de organizar **dados e funcionalidades** juntos. Criar uma nova classe cria um novo **“tipo”** de objeto, permitindo que novas **“instâncias”** desse tipo sejam produzidas. Cada instância da classe pode ter **atributos** anexados a ela, para manter seu estado. Instâncias da classe também podem ter **métodos** (definidos pela classe) para modificar seu estado.\n",
    "\n",
    "Atributos -> Dados referentes ao objeto\n",
    "\n",
    "Métodos -> Funcionalidades daquele objeto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Número imag\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Atributo\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Método\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Objetos classe suportam dois tipos de operações: referências a atributos e instanciação.\n",
    "\n",
    "Referências a atributos de classe utilizam a sintaxe padrão utilizada para quaisquer referências a atributos em Python: `obj.nome`. Nomes de atributos válidos são todos os nomes presentes dentro do espaço de nomes da classe, quando o objeto classe foi criado. Portanto, se a definição de classe tem esta forma:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "então `MyClass.i` e `MyClass.f` são referências a atributo válidas, retornando, respectivamente, um inteiro e um objeto função. Atributos de classe podem receber valores, pode-se modificar o valor de `MyClass.i` num atribuição."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Instanciar\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A operação de instanciação (“invocar” um objeto classe) cria um objeto vazio. Muitas classes preferem criar novos objetos com um estado inicial predeterminado. Para tanto, a classe pode definir um método especial chamado `__init__()`, assim:\n",
    "\n",
    "```python\n",
    "def __init__(self):\n",
    "    self.data = []\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Square:\n",
    "    pass\n",
    "       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercício\n",
    "\n",
    "Crie uma classe `Circle` que tenha como argumento o raio (`radius`) e com um método `area` que calcule area = π * radius**2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.566"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Vector v1.0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.0"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Vector v2.0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.0"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercício\n",
    "\n",
    "Implemente o método `__repr__` na classe `Vetor2d` para \n",
    "que a representação do objeto em tela seja mais clara para o usuário.\n",
    "\n",
    "Dica:\n",
    "O método `__repr__` deve retornar uma string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Vector v3.0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Vector2d(x=3.0, y=4.0)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'Vector2d' and 'Vector2d'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-67-2608b2aceb31>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mv1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mv2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'Vector2d' and 'Vector2d'"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Herança \n",
    "\n",
    "Uma classe pode 'herdar' as funcionalidades de uma outra classe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Vector v4.0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'Vector2d' and 'Vector2d'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-55-2608b2aceb31>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mv1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mv2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'Vector2d' and 'Vector2d'"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Vector2d(x=-3.0, y=-4.0)"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'Vector2d' and 'Vector2d_improved'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-79-39eb1477ab62>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mv4\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mv3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'Vector2d' and 'Vector2d_improved'"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Módulos\n",
    "\n",
    "Um módulo é um arquivo contendo definições e instruções Python. O nome do arquivo é o nome do módulo acrescido do sufixo `.py`. Dentro de um módulo, o nome do módulo (como uma string) está disponível como o valor da variável global `__name__`. Por exemplo, use seu editor de texto favorito para criar um arquivo chamado `fibo.py` no diretório atual com o seguinte conteúdo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fibonacci numbers module\n",
    "\n",
    "def fib(n):    # write Fibonacci series up to n\n",
    "    a, b = 0, 1\n",
    "    while a < n:\n",
    "        print(a, end=' ')\n",
    "        a, b = b, a+b\n",
    "    print()\n",
    "\n",
    "def fib2(n):   # return Fibonacci series up to n\n",
    "    result = []\n",
    "    a, b = 0, 1\n",
    "    while a < n:\n",
    "        result.append(a)\n",
    "        a, b = b, a+b\n",
    "    return result\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import fibo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 \n"
     ]
    }
   ],
   "source": [
    "fibo.fib(1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fibo.fib2(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quando um módulo chamado `spam` é importado, o interpretador procura um módulo embutido com este nome. Se não encontra, procura um arquivo chamado `spam.py` em uma lista de diretórios incluídos na variável `sys.path`. A `sys.path` é inicializada com estes locais:\n",
    "\n",
    "O diretório que contém o script importador (ou o diretório atual quando nenhum arquivo é especificado).\n",
    "\n",
    "A variável de ambiente `PYTHONPATH` (uma lista de nomes de diretórios, com a mesma sintaxe da variável de ambiente `PATH`).\n",
    "\n",
    "Padrões dependentes da instalação."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/raphael/python-ross-tutorial',\n",
       " '/home/raphael/python-ross-tutorial',\n",
       " '/home/raphael/scripts',\n",
       " '/home/raphael/vibration_toolbox',\n",
       " '/home/raphael/prf',\n",
       " '/home/raphael/piplot',\n",
       " '/home/raphael/ross',\n",
       " '/home/raphael/anaconda3/lib/python37.zip',\n",
       " '/home/raphael/anaconda3/lib/python3.7',\n",
       " '/home/raphael/anaconda3/lib/python3.7/lib-dynload',\n",
       " '',\n",
       " '/home/raphael/anaconda3/lib/python3.7/site-packages',\n",
       " '/home/raphael/anaconda3/lib/python3.7/site-packages/gmsh-4.5.6-Linux64-sdk/lib',\n",
       " '/home/raphael/anaconda3/lib/python3.7/site-packages/gmsh-4.5.6-Linux64-sdk/bin',\n",
       " '/home/raphael/anaconda3/lib/python3.7/site-packages/IPython/extensions',\n",
       " '/home/raphael/.ipython']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sys.path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Os pacotes são uma maneira de estruturar o “espaço de nomes” dos módulos Python, usando “nomes de módulo com pontos”. Por exemplo, o nome do módulo A.B designa um submódulo chamado B, em um pacote chamado A. Assim como o uso de módulos evita que os autores de módulos diferentes tenham que se preocupar com nomes de variáveis globais, o uso de nomes de módulos com pontos evita que os autores de pacotes com muitos módulos, como NumPy ou Pillow, tenham que se preocupar com os nomes dos módulos uns dos outros."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "sound/                          Top-level package\n",
    "      __init__.py               Initialize the sound package\n",
    "      formats/                  Subpackage for file format \n",
    "              __init__.py\n",
    "              wavread.py\n",
    "              wavwrite.py\n",
    "              aiffread.py\n",
    "              aiffwrite.py\n",
    "              auread.py\n",
    "              auwrite.py\n",
    "              ...\n",
    "      effects/                  Subpackage for sound effects\n",
    "              __init__.py\n",
    "              echo.py\n",
    "              surround.py\n",
    "              reverse.py\n",
    "              ...\n",
    "      filters/                  Subpackage for filters\n",
    "              __init__.py\n",
    "              equalizer.py\n",
    "              vocoder.py\n",
    "              karaoke.py\n",
    "              ...\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Numpy\n",
    "\n",
    "Manipulação de arrays (matrizes/vetores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1,  2,  3,  4],\n",
       "       [ 5,  6,  7,  8,  9],\n",
       "       [10, 11, 12, 13, 14]])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "a = np.arange(15).reshape(3, 5)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 5)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6, 7, 8])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.array([6, 7, 8])\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2],\n",
       "       [3, 4, 5],\n",
       "       [6, 7, 8]])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.arange(9).reshape(3, 3)\n",
    "A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2],\n",
       "       [3, 4, 5],\n",
       "       [6, 7, 8]])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B = np.arange(9).reshape(3, 3)\n",
    "B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 15,  18,  21],\n",
       "       [ 42,  54,  66],\n",
       "       [ 69,  90, 111]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A @ B"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Scipy\n",
    "\n",
    "Funções para uso científico (algebra linear, fft, estatística etc.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import linalg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 1.33484692e+01+0.j, -1.34846923e+00+0.j, -1.15433316e-15+0.j]),\n",
       " array([[ 0.16476382,  0.79969966,  0.40824829],\n",
       "        [ 0.50577448,  0.10420579, -0.81649658],\n",
       "        [ 0.84678513, -0.59128809,  0.40824829]]))"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linalg.eig(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas\n",
    "\n",
    "Ferramenta para análise de dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>-2.637501</td>\n",
       "      <td>-0.821945</td>\n",
       "      <td>-0.608124</td>\n",
       "      <td>0.866742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.344998</td>\n",
       "      <td>-0.119371</td>\n",
       "      <td>-2.394231</td>\n",
       "      <td>-0.066661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.498703</td>\n",
       "      <td>-0.073905</td>\n",
       "      <td>-1.050301</td>\n",
       "      <td>0.007169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.619702</td>\n",
       "      <td>1.790046</td>\n",
       "      <td>-0.454258</td>\n",
       "      <td>-0.552774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.102440</td>\n",
       "      <td>0.079761</td>\n",
       "      <td>1.167384</td>\n",
       "      <td>-0.265825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.228154</td>\n",
       "      <td>0.732556</td>\n",
       "      <td>1.238892</td>\n",
       "      <td>-1.512511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01 -2.637501 -0.821945 -0.608124  0.866742\n",
       "2013-01-02  0.344998 -0.119371 -2.394231 -0.066661\n",
       "2013-01-03 -1.498703 -0.073905 -1.050301  0.007169\n",
       "2013-01-04 -0.619702  1.790046 -0.454258 -0.552774\n",
       "2013-01-05 -1.102440  0.079761  1.167384 -0.265825\n",
       "2013-01-06  0.228154  0.732556  1.238892 -1.512511"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates = pd.date_range('20130101', periods=6)\n",
    "df = pd.DataFrame(np.random.randn(6, 4), index=dates, columns=list('ABCD'))\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fd670e69668>]"
      ]
     },
     "execution_count": 40,
     "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": [
    "fig, ax = plt.subplots()\n",
    "ax.plot([1, 2], [1, 2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bokeh\n",
    "\n",
    "Visualização em gráficos interativos (web)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1001\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"1001\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      \n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };var element = document.getElementById(\"1001\");\n",
       "  if (element == null) {\n",
       "    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.0.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.0.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.0.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.0.0.min.js\"];\n",
       "  var css_urls = [];\n",
       "  \n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (var i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "    if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"1001\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      \n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };var element = document.getElementById(\"1001\");\n  if (element == null) {\n    console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n    return false;\n  }\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.0.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.0.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.0.0.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.0.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from bokeh.models import ColumnDataSource, LabelSet\n",
    "from bokeh.plotting import figure, output_notebook, show\n",
    "from bokeh.sampledata.periodic_table import elements\n",
    "\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"fb013b09-5d96-4f7d-ba43-8624efb0e277\" data-root-id=\"1002\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "  function embed_document(root) {\n",
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       "  var render_items = [{\"docid\":\"f6dae267-61c2-49cd-a05d-11a6268d2142\",\"root_ids\":[\"1002\"],\"roots\":{\"1002\":\"fb013b09-5d96-4f7d-ba43-8624efb0e277\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1002"
      }
     },
     "output_type": "display_data"
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   ],
   "source": [
    "\n",
    "elements = elements.copy()\n",
    "elements = elements[elements[\"atomic number\"] <= 82]\n",
    "elements = elements[~pd.isnull(elements[\"melting point\"])]\n",
    "mass = [float(x.strip(\"[]\")) for x in elements[\"atomic mass\"]]\n",
    "elements[\"atomic mass\"] = mass\n",
    "\n",
    "palette = [\"#053061\", \"#2166ac\", \"#4393c3\", \"#92c5de\", \"#d1e5f0\",\n",
    "           \"#f7f7f7\", \"#fddbc7\", \"#f4a582\", \"#d6604d\", \"#b2182b\", \"#67001f\"]\n",
    "\n",
    "melting_points = elements[\"melting point\"]\n",
    "low = min(melting_points)\n",
    "high = max(melting_points)\n",
    "melting_point_inds = [int(10*(x-low)/(high-low)) for x in melting_points] #gives items in colors a value from 0-10\n",
    "elements['melting_colors'] = [palette[i] for i in melting_point_inds]\n",
    "\n",
    "TITLE = \"Density vs Atomic Weight of Elements (colored by melting point)\"\n",
    "TOOLS = \"hover,pan,wheel_zoom,box_zoom,reset,save\"\n",
    "\n",
    "p = figure(tools=TOOLS, toolbar_location=\"above\", plot_width=800, title=TITLE)\n",
    "p.toolbar.logo = \"grey\"\n",
    "p.background_fill_color = \"#dddddd\"\n",
    "p.xaxis.axis_label = \"atomic weight (amu)\"\n",
    "p.yaxis.axis_label = \"density (g/cm^3)\"\n",
    "p.grid.grid_line_color = \"white\"\n",
    "p.hover.tooltips = [\n",
    "    (\"name\", \"@name\"),\n",
    "    (\"symbol:\", \"@symbol\"),\n",
    "    (\"density\", \"@density\"),\n",
    "    (\"atomic weight\", \"@{atomic mass}\"),\n",
    "    (\"melting point\", \"@{melting point}\")\n",
    "]\n",
    "\n",
    "source = ColumnDataSource(elements)\n",
    "\n",
    "p.circle(\"atomic mass\", \"density\", size=12, source=source,\n",
    "         color='melting_colors', line_color=\"black\", fill_alpha=0.8)\n",
    "\n",
    "labels = LabelSet(x=\"atomic mass\", y=\"density\", text=\"symbol\", y_offset=8,\n",
    "                  text_font_size=\"11px\", text_color=\"#555555\",\n",
    "                  source=source, text_align='center')\n",
    "p.add_layout(labels)\n",
    "\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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