{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "python_lista2.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gks6iZtGrwmw",
        "outputId": "32581c7b-1303-4813-a3db-92f68cf2f90b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Informe o 0 num? 3\n",
            "Informe o 1 num? 4\n",
            "Informe o 2 num? 5\n",
            "Informe o 3 num? 3\n",
            "Informe o 4 num? 4\n",
            "Informe o 5 num? 5\n",
            "Informe o 6 num? 5\n",
            "Informe o 7 num? 6\n",
            "Informe o 8 num? 3\n",
            "Informe o 9 num? 4\n",
            "[3, 4, 5, 3, 4, 5, 5, 6, 3, 4]\n",
            "Tamanho do vetor  10\n",
            "Soma 42 media 4.20\n",
            "Passo final, apresentar os valores maiores ou igual a media:\n",
            "5\n",
            "5\n",
            "5\n",
            "6\n",
            "[5, 5, 5, 6]\n"
          ]
        }
      ],
      "source": [
        "# 2) Faça um programa que leia 10 números, coloque-os em um vetor e apresente os valores que forem maior ou igual a média dos números lidos.\n",
        "vetor = []\n",
        "for i in range(0,10):\n",
        "  num = int(input('Informe o '+str(i)+\" num? \"))\n",
        "  vetor.append( num )\n",
        "\n",
        "print( vetor )\n",
        "# media\n",
        "soma = 0\n",
        "for valor in vetor:\n",
        "  soma = soma + valor\n",
        "\n",
        "print('Tamanho do vetor ', len(vetor))\n",
        "media = soma / len(vetor)\n",
        "print('Soma %d media %.2f'%(soma,media) )\n",
        "\n",
        "print('Passo final, apresentar os valores maiores ou igual a media:')\n",
        "for valor in vetor:\n",
        "  if valor >= media:\n",
        "    print(valor)\n",
        "\n",
        "v2 = [x for x in vetor if x>=media]\n",
        "print( v2 )\n",
        "\n",
        "#v2 = vetor >= media\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#\n",
        "mat = []\n",
        "num = 1\n",
        "for i in range(0,3):\n",
        "  novo2 = []\n",
        "  for j in range(0,3):\n",
        "    novo3 = []\n",
        "    for k in range(0,3):\n",
        "      novo3.append( num  )   # (i+1)*3 + (j+1)*3 + (k+1)\n",
        "      num = num + 1\n",
        "    novo2.append( novo3 )\n",
        "  mat.append(novo2)\n",
        "\n",
        "print(mat)\n",
        "print( mat[0][1][1] )\n",
        "\n",
        "\n",
        "lista = []\n",
        "num = 1\n",
        "for i in range(0,5):\n",
        "  lista2 = []\n",
        "  for j in range(0,i+1):\n",
        "    lista2.append( num )\n",
        "    num = num + 1\n",
        "  lista.append(lista2)\n",
        "\n",
        "print(lista)\n",
        "\n",
        "\n",
        "xml = \"\"\"\n",
        "<reg>\n",
        "   <nome>Joao da Silva</nome>\n",
        "   <nascimento>01/02/2000</nascimento>\n",
        "   <dependentes>\n",
        "      <dependente><nome>Pedro</nome></dependente>\n",
        "      <dependente><nome>Maria</nome></dependente>\n",
        "   </dependentes>\n",
        "</reg>\n",
        "\"\"\"\n",
        "\n",
        "\n",
        "#s = 'abc'\n",
        "#vs = [[s]*3]*3\n",
        "#print(vs)\n",
        "#vs[1][1] = 'xyz'\n",
        "#print(vs)\n",
        "\n",
        "#  3 linhas 4 colunas\n",
        "#   1  2  3  4         i*4+j+1  (0-3)\n",
        "#   5  6  7  8\n",
        "#   9 10 11 12\n",
        "\n",
        "# [[1], \n",
        "# [2, 3], \n",
        "# [4, 5, 6], \n",
        "# [7, 8, 9, 10], \n",
        "# [11, 12, 13, 14, 15]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M7JBopD9yPA1",
        "outputId": "2c6e9d86-e619-4277-fbb5-8109c0e00223"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[[1, 2, 3], [4, 5, 6], [7, 8, 9]], [[10, 11, 12], [13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24], [25, 26, 27]]]\n",
            "5\n",
            "[[1], [2, 3], [4, 5, 6], [7, 8, 9, 10], [11, 12, 13, 14, 15]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#!pip install biopython\n",
        "# from Bio import Align\n",
        "# print( Align.PairwiseAligner('ACCACCAAACC','ACCAAC') )\n",
        "#!pip install apyori\n",
        "#import apyori as ap\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5NB1XXBW94B8",
        "outputId": "2dc7fe1c-4b6c-406b-80ad-9ea7dd56e761"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting apyori\n",
            "  Downloading apyori-1.1.2.tar.gz (8.6 kB)\n",
            "Building wheels for collected packages: apyori\n",
            "  Building wheel for apyori (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for apyori: filename=apyori-1.1.2-py3-none-any.whl size=5974 sha256=2b4a5d386703567d95941174c31a7ec2e6d531e2f50de753587ecce975add36a\n",
            "  Stored in directory: /root/.cache/pip/wheels/cb/f6/e1/57973c631d27efd1a2f375bd6a83b2a616c4021f24aab84080\n",
            "Successfully built apyori\n",
            "Installing collected packages: apyori\n",
            "Successfully installed apyori-1.1.2\n"
          ]
        }
      ]
    }
  ]
}