Python_Fundamentals.ipynb

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      "cell_type": "markdown",
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      "source": [
        "**Python**:\n",
        "- Loops\n",
        "- Conditionals\n",
        "- Function\n",
        "- Data Scructures (pure Python) (https://docs.python.org/3/tutorial/datastructures.html)\n",
        "- Libraries (numpy, pandas, images)\n",
        "- Classes"
      ]
    },
    {
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      "source": [
        "\\**Major Source**: https://docs.python.org/3/contents.html\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-l12QUlECAwZ"
      },
      "source": [
        "## **Loops**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dz_bKuV3CJot"
      },
      "source": [
        "**Fonte 1**: https://www.w3schools.com/python/python_for_loops.asp"
      ]
    },
    {
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          "traceback": [
            "\u001b[1;31mRunning cells with 'Python 3.8.2 64-bit' requires ipykernel package.\n",
            "Run the following command to install 'ipykernel' into the Python environment. \n",
            "Command: '/usr/bin/python3 -m pip install ipykernel -U --user --force-reinstall'"
          ]
        }
      ],
      "source": [
        "fruits = [\"apple\", \"banana\", \"cherry\"]\n",
        "for x in fruits:\n",
        "  print(x)"
      ]
    },
    {
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      "source": [
        ""
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          "text": [
            "b\n",
            "a\n",
            "n\n",
            "a\n",
            "n\n",
            "a\n"
          ]
        }
      ],
      "source": [
        "for x in \"banana\":\n",
        "  print(x)"
      ]
    },
    {
      "cell_type": "code",
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      "outputs": [
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          "output_type": "stream",
          "text": [
            "apple\n",
            "banana\n"
          ]
        }
      ],
      "source": [
        "fruits = [\"apple\", \"banana\", \"cherry\"]\n",
        "for x in fruits:\n",
        "  print(x)\n",
        "  if x == \"banana\":\n",
        "    break"
      ]
    },
    {
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          "output_type": "stream",
          "text": [
            "apple\n"
          ]
        }
      ],
      "source": [
        "fruits = [\"apple\", \"banana\", \"cherry\"]\n",
        "for x in fruits:\n",
        "  if x == \"banana\":\n",
        "    break\n",
        "  print(x)"
      ]
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    {
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          "text": [
            "apple\n",
            "cherry\n"
          ]
        }
      ],
      "source": [
        "fruits = [\"apple\", \"banana\", \"cherry\"]\n",
        "for x in fruits:\n",
        "  if x == \"banana\":\n",
        "    continue\n",
        "  print(x)"
      ]
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            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n",
            "5\n"
          ]
        }
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      "source": [
        "for x in range(6):\n",
        "  print(x)"
      ]
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          "text": [
            "2\n",
            "3\n",
            "4\n",
            "5\n"
          ]
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      ],
      "source": [
        "for x in range(2, 6):\n",
        "  print(x)"
      ]
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            "2\n",
            "5\n",
            "8\n",
            "11\n",
            "14\n",
            "17\n",
            "20\n",
            "23\n",
            "26\n",
            "29\n"
          ]
        }
      ],
      "source": [
        "for x in range(2, 30, 3):\n",
        "  print(x)"
      ]
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    {
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          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n",
            "5\n",
            "Finally finished!\n"
          ]
        }
      ],
      "source": [
        "for x in range(6):\n",
        "  print(x)\n",
        "else:\n",
        "  print(\"Finally finished!\")"
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            "0\n",
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            "2\n"
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      "source": [
        "for x in range(6):\n",
        "  if x == 3: break\n",
        "  print(x)\n",
        "else:\n",
        "  print(\"Finally finished!\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "red apple\n",
            "red banana\n",
            "red cherry\n",
            "big apple\n",
            "big banana\n",
            "big cherry\n",
            "tasty apple\n",
            "tasty banana\n",
            "tasty cherry\n"
          ]
        }
      ],
      "source": [
        "adj = [\"red\", \"big\", \"tasty\"]\n",
        "fruits = [\"apple\", \"banana\", \"cherry\"]\n",
        "\n",
        "for x in adj:\n",
        "  for y in fruits:\n",
        "    print(x, y)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "UqTwV7w799g-"
      },
      "outputs": [],
      "source": [
        "for x in [0, 1, 2]:\n",
        "  pass"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f3WQ5TZGCeSE"
      },
      "source": [
        "**Fonte 2**: https://www.programiz.com/python-programming/for-loop"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The sum is 48\n"
          ]
        }
      ],
      "source": [
        "# Program to find the sum of all numbers stored in a list\n",
        "\n",
        "# List of numbers\n",
        "numbers = [6, 5, 3, 8, 4, 2, 5, 4, 11]\n",
        "\n",
        "# variable to store the sum\n",
        "sum = 0\n",
        "\n",
        "# iterate over the list\n",
        "for val in numbers:\n",
        "    sum = sum+val\n",
        "\n",
        "print(\"The sum is\", sum)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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        },
        "id": "Crkc0nVe-4dZ",
        "outputId": "5a1cdbdb-a427-4afb-e84f-abaed19cea53"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "range(0, 10)\n",
            "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n",
            "[2, 3, 4, 5, 6, 7]\n",
            "[2, 5, 8, 11, 14, 17]\n"
          ]
        }
      ],
      "source": [
        "print(range(10))\n",
        "\n",
        "print(list(range(10)))\n",
        "\n",
        "print(list(range(2, 8)))\n",
        "\n",
        "print(list(range(2, 20, 3)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EQ21hPWN-4a5",
        "outputId": "d8ec820f-2968-4224-df3a-f64e32007d6c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "I like pop\n",
            "I like rock\n",
            "I like jazz\n"
          ]
        }
      ],
      "source": [
        "# Program to iterate through a list using indexing\n",
        "\n",
        "genre = ['pop', 'rock', 'jazz']\n",
        "\n",
        "# iterate over the list using index\n",
        "for i in range(len(genre)):\n",
        "    print(\"I like\", genre[i])"
      ]
    },
    {
      "cell_type": "code",
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        "outputId": "fb0e6172-c76b-4579-8a68-93174ecaa2d2"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "0\n",
            "1\n",
            "5\n",
            "No items left.\n"
          ]
        }
      ],
      "source": [
        "digits = [0, 1, 5]\n",
        "\n",
        "for i in digits:\n",
        "    print(i)\n",
        "else:\n",
        "    print(\"No items left.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "No entry with that name found.\n"
          ]
        }
      ],
      "source": [
        "# program to display student's marks from record\n",
        "student_name = 'Soyuj'\n",
        "\n",
        "marks = {'James': 90, 'Jules': 55, 'Arthur': 77}\n",
        "\n",
        "for student in marks:\n",
        "    if student == student_name:\n",
        "        print(marks[student])\n",
        "        break\n",
        "else:\n",
        "    print('No entry with that name found.')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cx45FdFFC4UE"
      },
      "source": [
        "**Fonte 3**: https://www.geeksforgeeks.org/loops-in-python/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
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        },
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        "outputId": "b6260dc7-1ff9-4f4b-c8a8-436bea02e737"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Hello Geek\n",
            "Hello Geek\n",
            "Hello Geek\n"
          ]
        }
      ],
      "source": [
        "# Python program to illustrate\n",
        "# while loop\n",
        "count = 0\n",
        "while (count < 3):\n",
        "\tcount = count + 1\n",
        "\tprint(\"Hello Geek\")"
      ]
    },
    {
      "cell_type": "code",
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      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Hello Geek\n",
            "Hello Geek\n",
            "Hello Geek\n",
            "In Else Block\n"
          ]
        }
      ],
      "source": [
        "#Python program to illustrate\n",
        "# combining else with while\n",
        "count = 0\n",
        "while (count < 3):\n",
        "\tcount = count + 1\n",
        "\tprint(\"Hello Geek\")\n",
        "else:\n",
        "\tprint(\"In Else Block\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ei4zWIlN_VmP"
      },
      "outputs": [],
      "source": [
        "# Python program to illustrate\n",
        "# Single statement while block\n",
        "count = 0\n",
        "while (count == 0): print(\"Hello Geek\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tHyEUfM1_Vjx",
        "outputId": "5cd2600f-a837-4173-a249-3ad675fd2f08"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n"
          ]
        }
      ],
      "source": [
        "# Python program to illustrate\n",
        "# Iterating over range 0 to n-1\n",
        "\n",
        "n = 4\n",
        "for i in range(0, n):\n",
        "\tprint(i)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RC2tE8fv_Ven",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2f566160-9d20-4f81-ecb5-463e59952b1f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "List Iteration\n",
            "geeks\n",
            "for\n",
            "geeks\n",
            "\n",
            "Tuple Iteration\n",
            "geeks\n",
            "for\n",
            "geeks\n",
            "\n",
            "String Iteration\n",
            "G\n",
            "e\n",
            "e\n",
            "k\n",
            "s\n",
            "\n",
            "Dictionary Iteration\n",
            "xyz 123\n",
            "abc 345\n",
            "\n",
            "Set Iteration\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n",
            "5\n",
            "6\n"
          ]
        }
      ],
      "source": [
        "# Python program to illustrate\n",
        "# Iterating over a list\n",
        "print(\"List Iteration\")\n",
        "l = [\"geeks\", \"for\", \"geeks\"]\n",
        "for i in l:\n",
        "\tprint(i)\n",
        "\t\n",
        "# Iterating over a tuple (immutable)\n",
        "print(\"\\nTuple Iteration\")\n",
        "t = (\"geeks\", \"for\", \"geeks\")\n",
        "for i in t:\n",
        "\tprint(i)\n",
        "\t\n",
        "# Iterating over a String\n",
        "print(\"\\nString Iteration\")\n",
        "s = \"Geeks\"\n",
        "for i in s :\n",
        "\tprint(i)\n",
        "\t\n",
        "# Iterating over dictionary\n",
        "print(\"\\nDictionary Iteration\")\n",
        "d = dict()\n",
        "d['xyz'] = 123\n",
        "d['abc'] = 345\n",
        "for i in d :\n",
        "\tprint(\"%s %d\" %(i, d[i]))\n",
        "\t\n",
        "#Iterating over a set\n",
        "print(\"\\nSet Iteration\")\n",
        "set1 = {1,2,3,4,5,6}\n",
        "for i in set1:\n",
        "\tprint(i),\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "outputId": "95121c31-b3fc-491a-880d-0305f01ecb2e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "geeks\n",
            "for\n",
            "geeks\n"
          ]
        }
      ],
      "source": [
        "# Python program to illustrate\n",
        "# Iterating by index\n",
        "\n",
        "list = [\"geeks\", \"for\", \"geeks\"]\n",
        "for index in range(len(list)):\n",
        "\tprint(list[index])"
      ]
    },
    {
      "cell_type": "code",
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      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "geeks\n",
            "for\n",
            "geeks\n",
            "Inside Else Block\n"
          ]
        }
      ],
      "source": [
        "# Python program to illustrate\n",
        "# combining else with for\n",
        "\n",
        "list = [\"geeks\", \"for\", \"geeks\"]\n",
        "for index in range(len(list)):\n",
        "\tprint(list[index])\n",
        "else:\n",
        "\tprint(\"Inside Else Block\")\n"
      ]
    },
    {
      "cell_type": "code",
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      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1 \n",
            "2 2 \n",
            "3 3 3 \n",
            "4 4 4 4 \n"
          ]
        }
      ],
      "source": [
        "# Python program to illustrate\n",
        "# nested for loops in Python\n",
        "from __future__ import print_function\n",
        "for i in range(1, 5):\n",
        "\tfor j in range(i):\n",
        "\t\tprint(i, end=' ')\n",
        "\tprint()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rwwYrLqq_zWJ",
        "outputId": "caaf9df0-4336-40c9-9bdc-40cc107d6676"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Current Letter : g\n",
            "Current Letter : k\n",
            "Current Letter : f\n",
            "Current Letter : o\n",
            "Current Letter : r\n",
            "Current Letter : g\n",
            "Current Letter : k\n"
          ]
        }
      ],
      "source": [
        "# Prints all letters except 'e' and 's'\n",
        "for letter in 'geeksforgeeks':\n",
        "\tif letter == 'e' or letter == 's':\n",
        "\t\tcontinue\n",
        "\tprint('Current Letter :', letter)\n",
        "\tvar = 10"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6MIHuiX4AEUR",
        "outputId": "14289a78-cfaa-4933-fd86-39eb69fcbc58"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Current Letter : e\n"
          ]
        }
      ],
      "source": [
        "for letter in 'geeksforgeeks':\n",
        "\n",
        "\t# break the loop as soon it sees 'e'\n",
        "\t# or 's'\n",
        "\tif letter == 'e' or letter == 's':\n",
        "\t\tbreak\n",
        "\n",
        "print('Current Letter :', letter)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3-g24Yh3AERg",
        "outputId": "a688d5a8-8cb2-4f96-dc21-43a2458c3d90"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Last Letter : s\n"
          ]
        }
      ],
      "source": [
        "# An empty loop\n",
        "for letter in 'geeksforgeeks':\n",
        "\tpass\n",
        "print('Last Letter :', letter)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4hukrMLlAEOm",
        "outputId": "3300297c-ce04-4e8a-93ab-524c081f7c9b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "apple\n",
            "orange\n",
            "kiwi\n"
          ]
        }
      ],
      "source": [
        "# A simple for loop example\n",
        "\n",
        "fruits = [\"apple\", \"orange\", \"kiwi\"]\n",
        "\n",
        "for fruit in fruits:\n",
        "  print(fruit)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gcZpE2BhAELp",
        "outputId": "09e5fd1f-0e8b-4d7f-e45c-7b26aa80ca3a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "apple\n",
            "orange\n",
            "kiwi\n"
          ]
        }
      ],
      "source": [
        "fruits = [\"apple\", \"orange\", \"kiwi\"]\n",
        "\n",
        "# Creating an iterator object\n",
        "# from that iterable i.e fruits\n",
        "iter_obj = iter(fruits)\n",
        "\n",
        "# Infinite while loop\n",
        "while True:\n",
        "  try:\n",
        "    # getting the next item\n",
        "    fruit = next(iter_obj)\n",
        "    print(fruit)\n",
        "  except StopIteration:\n",
        "\n",
        "    # if StopIteration is raised,\n",
        "    # break from loop\n",
        "    break"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xXYoeAlBDbbl"
      },
      "source": [
        "## **Conditionals**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ezauXhnTDgyW"
      },
      "source": [
        "**Source 1**: https://www.w3schools.com/python/python_conditions.asp"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "v2lBxQ0GDdJC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "86078ad3-59c4-4524-e602-5b8cdc08b15b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "b is greater than a\n"
          ]
        }
      ],
      "source": [
        "a = 33\n",
        "b = 200\n",
        "if b > a:\n",
        "  print(\"b is greater than a\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "l6aNu_pLDiqO",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 131
        },
        "outputId": "bb8b4f3c-fa14-413b-dc64-0e596d6bd919"
      },
      "outputs": [
        {
          "output_type": "error",
          "ename": "IndentationError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-85-4276c1871af7>\"\u001b[0;36m, line \u001b[0;32m4\u001b[0m\n\u001b[0;31m    print(\"b is greater than a\") # you will get an error\u001b[0m\n\u001b[0m        ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m expected an indented block\n"
          ]
        }
      ],
      "source": [
        "a = 33\n",
        "b = 200\n",
        "if b > a:\n",
        "print(\"b is greater than a\") # you will get an error"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jp3htogQDinu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "146dd780-7bff-4a84-e423-a7ceee4e5185"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a and b are equal\n"
          ]
        }
      ],
      "source": [
        "a = 33\n",
        "b = 33\n",
        "if b > a:\n",
        "  print(\"b is greater than a\")\n",
        "elif a == b:\n",
        "  print(\"a and b are equal\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HRBeQluCDlsf"
      },
      "source": [
        " Else"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "osidOy7yDik2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e13e2283-9246-40e0-fffb-d582bc62e911"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a is greater than b\n"
          ]
        }
      ],
      "source": [
        "a = 200\n",
        "b = 33\n",
        "if b > a:\n",
        "  print(\"b is greater than a\")\n",
        "elif a == b:\n",
        "  print(\"a and b are equal\")\n",
        "else:\n",
        "  print(\"a is greater than b\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "P03fDg9zDmw-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "44d77a52-d8c1-4b04-b46e-e358504ccbe9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "b is not greater than a\n"
          ]
        }
      ],
      "source": [
        "a = 200\n",
        "b = 33\n",
        "if b > a:\n",
        "  print(\"b is greater than a\")\n",
        "else:\n",
        "  print(\"b is not greater than a\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "S9PLCRZEDmt-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0524a5e8-568a-4081-a8c2-2fed2ee53345"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "B\n"
          ]
        }
      ],
      "source": [
        "a = 2\n",
        "b = 330\n",
        "print(\"A\") if a > b else print(\"B\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = 200\n",
        "b = 33\n",
        "c = 500\n",
        "if a > b or a > c:\n",
        "  print(\"At least one of the conditions is True\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HnL4WDw-_LD9",
        "outputId": "fc0f48f7-0e72-45dd-8aa5-8c628a0602f6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "At least one of the conditions is True\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "If"
      ],
      "metadata": {
        "id": "WfFH6KcZW3q8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x = int(input(\"Please enter an integer: \"))\n",
        "\n",
        "if x < 0:\n",
        "    x = 0\n",
        "    print('Negative changed to zero')\n",
        "elif x == 0:\n",
        "    print('Zero')\n",
        "elif x == 1:\n",
        "    print('Single')\n",
        "else:\n",
        "    print('More')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bIN5wwKyWylJ",
        "outputId": "3a80ae34-b3de-4ebd-b588-267bf5bf8005"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Please enter an integer: 1\n",
            "Single\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "For"
      ],
      "metadata": {
        "id": "CD8nYfHvXCQq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a sample collection\n",
        "users = {'Hans': 'active', 'Éléonore': 'inactive', '景太郎': 'active'}\n",
        "\n",
        "# Strategy:  Iterate over a copy\n",
        "for user, status in users.copy().items():\n",
        "    if status == 'inactive':\n",
        "        del users[user]\n",
        "\n",
        "# Strategy:  Create a new collection\n",
        "active_users = {}\n",
        "for user, status in users.items():\n",
        "    if status == 'active':\n",
        "        active_users[user] = status"
      ],
      "metadata": {
        "id": "jehHKfh2XBnX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Function**"
      ],
      "metadata": {
        "id": "EkqoGb7j7tfc"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Source: https://www.w3schools.com/python/python_functions.asp\n",
        "\n",
        "http://excript.com/python/funcao-range-python.html"
      ],
      "metadata": {
        "id": "R_KfmJgvB-gj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function():\n",
        "  print(\"Hello from a function\")"
      ],
      "metadata": {
        "id": "YfNPquG876zg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function():\n",
        "  print(\"Hello from a function\")\n",
        "\n",
        "my_function()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1xqkgy6r_bzc",
        "outputId": "3955dbd6-46dc-4f24-a1b5-337b688acbdc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hello from a function\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Arguments**"
      ],
      "metadata": {
        "id": "9zEuPsB_B2jZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function(fname):\n",
        "  print(fname + \" Refsnes\")\n",
        "\n",
        "my_function(\"Emil\")\n",
        "my_function(\"Tobias\")\n",
        "my_function(\"Linus\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HdG6MfRD_biz",
        "outputId": "c7247f7d-4daf-437e-8d57-dd600e163df7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Emil Refsnes\n",
            "Tobias Refsnes\n",
            "Linus Refsnes\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Numbers of Arguments**"
      ],
      "metadata": {
        "id": "QSqZiMSrAUo2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function(fname, lname):\n",
        "  print(fname + \" \" + lname)\n",
        "\n",
        "my_function(\"Emil\", \"Refsnes\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hiPpzX0J_bRL",
        "outputId": "06d7b27b-af1d-4a7f-aa95-f3c1072d282a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Emil Refsnes\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Default Parameter Value** *texto em itálico*"
      ],
      "metadata": {
        "id": "wGCkQpDDwzmc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function(country = \"Norway\"):\n",
        "  print(\"I am from \" + country)\n",
        "\n",
        "my_function(\"Sweden\")\n",
        "my_function(\"India\")\n",
        "my_function()\n",
        "my_function(\"Brazil\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Atvq-JwwzRb",
        "outputId": "c3e58b31-0507-44ab-a16b-9c1a47991080"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "I am from Sweden\n",
            "I am from India\n",
            "I am from Norway\n",
            "I am from Brazil\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Let a Function Return Value**"
      ],
      "metadata": {
        "id": "oce71buQxUkj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function(x):\n",
        "  return 5 * x\n",
        "\n",
        "print(my_function(3))\n",
        "print(my_function(5))\n",
        "print(my_function(9))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KNn0TAtixUO_",
        "outputId": "b7cc16cc-b5b0-43b6-8874-3b7a0a658a3c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "15\n",
            "25\n",
            "45\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Passing a List as an Argument**"
      ],
      "metadata": {
        "id": "F-ZOn2ZPBgSa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def my_function(food):\n",
        "  for x in food:\n",
        "    print(x)\n",
        "\n",
        "fruits = [\"apple\", \"banana\", \"cherry\"]\n",
        "\n",
        "my_function(fruits)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ssMYrWpz_a6J",
        "outputId": "6f7cef45-6f12-4d77-c630-552b71c771ea"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "apple\n",
            "banana\n",
            "cherry\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#function definition\n",
        "def add(*params):\n",
        "    sum = 0\n",
        "    for num in params:\n",
        "        sum += num\n",
        "    print(sum)\n",
        "    \n",
        "#input list\n",
        "my_list = [1,2,3]\n",
        "#function call\n",
        "add(*my_list)\n",
        "  \n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dYhBbg55BwKn",
        "outputId": "888ed6c4-e1b0-4b4d-f3a0-25ba1c4d920c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "6\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def calculateTotalSum(*arguments): \n",
        "    totalSum = 0\n",
        "    for number in arguments: \n",
        "        totalSum += number \n",
        "    print(totalSum) \n",
        "  \n",
        "# function call\n",
        "calculateTotalSum(5,4,3,2,1) "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9fJy8V83Bwfn",
        "outputId": "b332b405-4472-4a93-de98-5d01e69a35b2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**List Comprehensions **"
      ],
      "metadata": {
        "id": "GRvQU5R3HRKD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "quadrados = []\n",
        "for numero in range(10):\n",
        "  quadrados.append(numero**2)\n",
        "\n",
        "  quadrados\n"
      ],
      "metadata": {
        "id": "Jqonkj_FBwpy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Range**"
      ],
      "metadata": {
        "id": "ysFZb8AaIiUe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(5):\n",
        "    print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tp9sDS_yIcFS",
        "outputId": "103380b8-3dd9-4b06-f288-5956b7df3835"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "list(range(5, 10))\n",
        "list(range(0, 10, 3))\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 201
        },
        "id": "aRn5vZBQImXF",
        "outputId": "41612aba-c285-4893-db61-3ddae5458e12"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-82-44194ea8aa26>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mTypeError\u001b[0m: 'list' object is not callable"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = ['Mary', 'had', 'a', 'little', 'lamb']\n",
        "for i in range(len(a)):\n",
        "    print(i, a[i])\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jzWvWBCFI93m",
        "outputId": "be00f01c-4bed-41a2-9c89-8f8192470c70"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 Mary\n",
            "1 had\n",
            "2 a\n",
            "3 little\n",
            "4 lamb\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def fib(n):    # write Fibonacci series up to n\n",
        "    \"\"\"Print a 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",
        "    fib(2000)"
      ],
      "metadata": {
        "id": "3tkI0XucLSjZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Data Structures**\n",
        "\n",
        "Source: https://python-guide-pt-br.readthedocs.io/pt_BR/latest/intro/learning.html\n",
        "\n",
        "https://docs.python.org/3/tutorial/datastructures.html"
      ],
      "metadata": {
        "id": "D0zZUhxx8IQQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        " fruits = ['orange', 'apple', 'pear', 'banana', 'kiwi', 'apple', 'banana']\n",
        " fruits.count('apple')\n",
        "2\n",
        " fruits.count('tangerine')\n",
        "0\n",
        " fruits.index('banana')\n",
        "3\n",
        " fruits.index('banana', 4)  # Find next banana starting a position 4\n",
        "6\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EQ3A8H288PYE",
        "outputId": "cf27eb7b-3ea4-46f6-f0ef-db7a5cf8f5dc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        " stack = [3, 4, 5]\n",
        " stack.append(6)\n",
        " stack.append(7)\n",
        " stack\n",
        "[3, 4, 5, 6, 7]\n",
        " stack.pop()\n",
        "7\n",
        " stack\n",
        "[3, 4, 5, 6]\n",
        " stack.pop()\n",
        "6\n",
        " stack.pop()\n",
        "5\n",
        " stack\n",
        "[3, 4]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iyDN5ZSsWutj",
        "outputId": "84c118bb-276e-4045-e31c-a6035faf28b6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[3, 4]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from collections import deque\n",
        "queue = deque([\"Eric\", \"John\", \"Michael\"])\n",
        "queue.append(\"Terry\")           # Terry arrives\n",
        "queue.append(\"Graham\")          # Graham arrives\n",
        "queue.popleft()                 # The first to arrive now leaves\n",
        "\n",
        "queue.popleft()                 # The second to arrive now leaves\n",
        "\n",
        "queue                           # Remaining queue in order of arrival"
      ],
      "metadata": {
        "id": "Hjc-r4FZWvoP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3875dfe1-b31d-484b-cf36-5cc659768689"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "deque(['Michael', 'Terry', 'Graham'])"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "squares = []\n",
        "for x in range(10):\n",
        "    squares.append(x**2)\n",
        "\n",
        "squares"
      ],
      "metadata": {
        "id": "_ZoDyy9oWvev",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1d03a647-ed73-4ddb-8118-2fc41957ee54"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combs = []\n",
        "for x in [1,2,3]:\n",
        "    for y in [3,1,4]:\n",
        "        if x != y:\n",
        "            combs.append((x, y))\n",
        "\n",
        "combs"
      ],
      "metadata": {
        "id": "e0ZCeOFCWvU1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c120956d-57af-4ea9-eb97-d645cdffa02b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(1, 3), (1, 4), (2, 3), (2, 1), (2, 4), (3, 1), (3, 4)]"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from math import pi\n",
        "[str(round(pi, i)) for i in range(1, 6)]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x16q9dZUPd6R",
        "outputId": "1af502d1-e6e1-41ee-f80c-23460416b08e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['3.1', '3.14', '3.142', '3.1416', '3.14159']"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**DEL**"
      ],
      "metadata": {
        "id": "F0sHjE_mQamk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "a = [-1, 1, 66.25, 333, 333, 1234.5]\n",
        "del a[0]\n",
        "a\n",
        "\n",
        "del a[2:4]\n",
        "a\n",
        "\n",
        "del a[:]\n",
        "a\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n8F5V2ClQaIf",
        "outputId": "211373b1-5c3f-424c-9600-2fc854a3a97d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del a"
      ],
      "metadata": {
        "id": "zug2YN1hQh3T"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Libraries**"
      ],
      "metadata": {
        "id": "-AQWK6478SPP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "NUMPY\n",
        "\n",
        "Source: https://medium.com/ensina-ai/entendendo-a-biblioteca-numpy-4858fde63355\n",
        "\n",
        "https://numpy.org/"
      ],
      "metadata": {
        "id": "XB7cg9jhkfVA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy"
      ],
      "metadata": {
        "id": "5v38d3bYJa7-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "numpy.ones(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XyMmrEJnJbN3",
        "outputId": "5ceb8006-d546-46f2-bd21-0e4aa9108024"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1., 1., 1., 1., 1.])"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "FrMKvFtEJbZV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "np.ones(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P0NCIv4eJ28A",
        "outputId": "1567207e-f114-478e-b906-430e864b3198"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1., 1., 1., 1., 1.])"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from numpy import ones"
      ],
      "metadata": {
        "id": "prStbOOMJ3EP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ones(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KUXb7rGUJ9oC",
        "outputId": "b841fd8e-5cc9-4f66-c2a1-bd0a4e49959c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1., 1., 1., 1., 1.])"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Instalando libraries"
      ],
      "metadata": {
        "id": "OtFJIp4gKDwB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install yfinance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 662
        },
        "id": "zVOnOExEKCUm",
        "outputId": "24958b15-db7d-42e3-e923-80bbdb06860b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting yfinance\n",
            "  Downloading yfinance-0.1.70-py2.py3-none-any.whl (26 kB)\n",
            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.3.5)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.21.6)\n",
            "Collecting lxml>=4.5.1\n",
            "  Downloading lxml-4.8.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (6.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 6.4 MB 7.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.10)\n",
            "Collecting requests>=2.26\n",
            "  Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)\n",
            "\u001b[K     |████████████████████████████████| 63 kB 1.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2022.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24.0->yfinance) (1.15.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.10)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.0.12)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2021.10.8)\n",
            "Installing collected packages: requests, lxml, yfinance\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.23.0\n",
            "    Uninstalling requests-2.23.0:\n",
            "      Successfully uninstalled requests-2.23.0\n",
            "  Attempting uninstall: lxml\n",
            "    Found existing installation: lxml 4.2.6\n",
            "    Uninstalling lxml-4.2.6:\n",
            "      Successfully uninstalled lxml-4.2.6\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Successfully installed lxml-4.8.0 requests-2.27.1 yfinance-0.1.70\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "requests"
                ]
              }
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "PANDA\n",
        "\n",
        "Source: https://github.com/TobiasGustavo/pandas\n",
        "\n",
        "https://pandas.pydata.org/\n",
        "\n",
        "https://www.w3schools.com/python/pandas/default.asp"
      ],
      "metadata": {
        "id": "GbUrISC9bcsr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas\n"
      ],
      "metadata": {
        "id": "FibfTbdIKCq-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n"
      ],
      "metadata": {
        "id": "GxpSdak8J-BY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas\n",
        "\n",
        "mydataset = {\n",
        "  'cars': [\"BMW\", \"Volvo\", \"Ford\"],\n",
        "  'passings': [3, 7, 2]\n",
        "}\n",
        "\n",
        "myvar = pandas.DataFrame(mydataset)\n",
        "\n",
        "print(myvar)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-mDY7sUtYSb2",
        "outputId": "4f2ea528-5418-4197-e7eb-a6f1d0075f6e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    cars  passings\n",
            "0    BMW         3\n",
            "1  Volvo         7\n",
            "2   Ford         2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "mydataset = {\n",
        "  'cars': [\"BMW\", \"Volvo\", \"Ford\"],\n",
        "  'passings': [3, 7, 2]\n",
        "}\n",
        "\n",
        "myvar = pd.DataFrame(mydataset)\n",
        "\n",
        "print(myvar)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0ASREErIY4fp",
        "outputId": "77238987-00df-4665-be02-73f42e044f93"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    cars  passings\n",
            "0    BMW         3\n",
            "1  Volvo         7\n",
            "2   Ford         2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "print(pd.__version__)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5nvIdXBDY9QA",
        "outputId": "b15d8bc0-ee6d-41a6-d7f7-4f1796adf2b2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1.3.5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Labels"
      ],
      "metadata": {
        "id": "q5usT9uAZFM0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(myvar[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-vTTIwnnZEzD",
        "outputId": "f066f87b-7435-43aa-d9b2-f1a538516a16"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "a = [1, 7, 2]\n",
        "\n",
        "myvar = pd.Series(a, index = [\"x\", \"y\", \"z\"])\n",
        "\n",
        "print(myvar)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o2qzWRtFZKsf",
        "outputId": "1a2259ad-aa06-4648-a8bf-efe7f98aa9bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "x    1\n",
            "y    7\n",
            "z    2\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(myvar[\"y\"])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WXDqaf8OZRbA",
        "outputId": "5ef0664a-c26f-4fe4-ff6e-1be254250ad2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "7\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Objects as Series"
      ],
      "metadata": {
        "id": "SGDv6eVxZXez"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "calories = {\"day1\": 420, \"day2\": 380, \"day3\": 390}\n",
        "\n",
        "myvar = pd.Series(calories)\n",
        "\n",
        "print(myvar)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O3UlNYaUZWbt",
        "outputId": "360a9cce-6b46-4710-a8ba-68ec5cb07fca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "day1    420\n",
            "day2    380\n",
            "day3    390\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "calories = {\"day1\": 420, \"day2\": 380, \"day3\": 390}\n",
        "\n",
        "myvar = pd.Series(calories, index = [\"day1\", \"day2\"])\n",
        "\n",
        "print(myvar)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h_iTiTz_ZeVm",
        "outputId": "5052b15b-e4b7-48d5-9c98-de0e42181571"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "day1    420\n",
            "day2    380\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "DataFrames"
      ],
      "metadata": {
        "id": "YPAa2vfCZi1D"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "data = {\n",
        "  \"calories\": [420, 380, 390],\n",
        "  \"duration\": [50, 40, 45]\n",
        "}\n",
        "\n",
        "myvar = pd.DataFrame(data)\n",
        "\n",
        "print(myvar)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WSHIgFMlZidZ",
        "outputId": "7f649a44-917c-4f74-f469-6d3c6b97087c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   calories  duration\n",
            "0       420        50\n",
            "1       380        40\n",
            "2       390        45\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "JSON"
      ],
      "metadata": {
        "id": "k8xvPyjra6Lf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "data = {\n",
        "  \"Duration\":{\n",
        "    \"0\":60,\n",
        "    \"1\":60,\n",
        "    \"2\":60,\n",
        "    \"3\":45,\n",
        "    \"4\":45,\n",
        "    \"5\":60\n",
        "  },\n",
        "  \"Pulse\":{\n",
        "    \"0\":110,\n",
        "    \"1\":117,\n",
        "    \"2\":103,\n",
        "    \"3\":109,\n",
        "    \"4\":117,\n",
        "    \"5\":102\n",
        "  },\n",
        "  \"Maxpulse\":{\n",
        "    \"0\":130,\n",
        "    \"1\":145,\n",
        "    \"2\":135,\n",
        "    \"3\":175,\n",
        "    \"4\":148,\n",
        "    \"5\":127\n",
        "  },\n",
        "  \"Calories\":{\n",
        "    \"0\":409.1,\n",
        "    \"1\":479.0,\n",
        "    \"2\":340.0,\n",
        "    \"3\":282.4,\n",
        "    \"4\":406.0,\n",
        "    \"5\":300.5\n",
        "  }\n",
        "}\n",
        "\n",
        "df = pd.DataFrame(data)\n",
        "\n",
        "print(df) \n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V36FuVNFa5uZ",
        "outputId": "430cf9d2-cd9c-4d19-cd07-19c6aecdd417"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   Duration  Pulse  Maxpulse  Calories\n",
            "0        60    110       130     409.1\n",
            "1        60    117       145     479.0\n",
            "2        60    103       135     340.0\n",
            "3        45    109       175     282.4\n",
            "4        45    117       148     406.0\n",
            "5        60    102       127     300.5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Images \n",
        "\n",
        "Source: https://pillow.readthedocs.io/en/stable/reference/Image.html\n",
        "\n",
        "https://www.geeksforgeeks.org/working-images-python/ **\n",
        "\n"
      ],
      "metadata": {
        "id": "1VALfpBQk2lF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from PIL import Image\n"
      ],
      "metadata": {
        "id": "HO1ZXUmQbjGR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from PIL import Image\n",
        "import glob, os\n",
        "\n",
        "size = 128, 128\n",
        "\n",
        "for infile in glob.glob(\"*.jpg\"):\n",
        "    file, ext = os.path.splitext(infile)\n",
        "    with Image.open(infile) as im:\n",
        "        im.thumbnail(size)\n",
        "        im.save(file + \".thumbnail\", \"JPEG\")"
      ],
      "metadata": {
        "id": "P9ko2puRbo1g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "ecDzxQyxbol6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##**Classes**\n",
        "\n",
        "Source: https://www.w3schools.com/python/python_classes.asp"
      ],
      "metadata": {
        "id": "r7fUhc-u8VtJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class MyClass:\n",
        "  x = 5\n",
        "\n",
        "print(MyClass)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sIr2iCwYxt0O",
        "outputId": "cfec250d-16fb-4b59-bd67-4879e6a490d8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class '__main__.MyClass'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Objetcts**"
      ],
      "metadata": {
        "id": "S_2mohkVykmg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class MyClass:\n",
        "  x = 5\n",
        "\n",
        "p1 = MyClass()\n",
        "print(p1.x)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GtP98ZY3x7zh",
        "outputId": "56620c5b-5197-48ea-cee9-5a6520f71f69"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Init Function**"
      ],
      "metadata": {
        "id": "B0ZJPiUczYqO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class Person:\n",
        "  def __init__(self, name, age):\n",
        "    self.name = name\n",
        "    self.age = age\n",
        "\n",
        "p1 = Person(\"John\", 36)\n",
        "\n",
        "print(p1.name)\n",
        "print(p1.age)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MZ0ZRIJ3x7kt",
        "outputId": "964f6039-151f-47c9-a09f-ba242fdf6dab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "John\n",
            "36\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Create Objects Methods** \n",
        "\n"
      ],
      "metadata": {
        "id": "8PaJyM4Jy_JY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class Person:\n",
        "  def __init__(self, name, age):\n",
        "    self.name = name\n",
        "    self.age = age\n",
        "\n",
        "  def myfunc(self):\n",
        "    print(\"Hello my name is \" + self.name)\n",
        "\n",
        "p1 = Person(\"John\", 36)\n",
        "p1.myfunc()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xcjA-DlVy-XP",
        "outputId": "b5082382-b1e9-4921-cdb0-fc7cd5761a4e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hello my name is John\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**The Self Parameter**"
      ],
      "metadata": {
        "id": "fuiKsWBRzuf7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class Person:\n",
        "  def __init__(mysillyobject, name, age):\n",
        "    mysillyobject.name = name\n",
        "    mysillyobject.age = age\n",
        "\n",
        "  def myfunc(abc):\n",
        "    print(\"Hello my name is \" + abc.name)\n",
        "\n",
        "p1 = Person(\"John\", 36)\n",
        "p1.myfunc()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L_3HJWnJzsNS",
        "outputId": "7c11e1fe-44b0-4983-9648-b8c78ea03bf5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hello my name is John\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Modify Object Properties**\n",
        "\n"
      ],
      "metadata": {
        "id": "J3qq7jas0O7G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "class Person:\n",
        "  def __init__(self, name, age):\n",
        "    self.name = name\n",
        "    self.age = age\n",
        "\n",
        "  def myfunc(self):\n",
        "    print(\"Hello my name is \" + self.name)\n",
        "\n",
        "p1 = Person(\"John\", 36)\n",
        "\n",
        "p1.age = 40\n",
        "\n",
        "print(p1.age)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "93pGj7Fdzr0I",
        "outputId": "eddaa028-c139-40c1-980a-968b2ebe2b68"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "40\n"
          ]
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "name": "Python Fundamentals.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.8.2"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}