Lesson_1.ipynb

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    {
      "cell_type": "markdown",
      "source": [
        "### Performing Arithmetic Operations using Python"
      ],
      "metadata": {
        "id": "ZDKkN6u3VKhe"
      }
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    {
      "cell_type": "code",
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14"
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          "metadata": {},
          "execution_count": 1
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      "source": [
        "2 + 3 + 9"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "99 - 73"
      ],
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        "outputId": "2633753a-a1d3-44a4-d5dc-c341fe9389a9"
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      "execution_count": null,
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        {
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          "data": {
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              "26"
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          "metadata": {},
          "execution_count": 2
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    {
      "cell_type": "code",
      "source": [
        "23.54 * -1432"
      ],
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            "text/plain": [
              "-33709.28"
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          "metadata": {},
          "execution_count": 3
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    {
      "cell_type": "code",
      "source": [
        "100 / 7"
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              "14.285714285714286"
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "100 // 7"
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          "execution_count": 5
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    {
      "cell_type": "code",
      "source": [
        "100 % 7"
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "ByVeIwsrVUw_",
        "outputId": "6c67b74c-6b3c-41d2-f84c-9296d5fb8603"
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              "2"
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    {
      "cell_type": "code",
      "source": [
        "5 ** 3"
      ],
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        "id": "S-WDQC9aVU0j",
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              "125"
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          "metadata": {},
          "execution_count": 7
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    },
    {
      "cell_type": "code",
      "source": [
        "((2 + 5) * (17 - 3)) / (4 ** 3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w-TNdviRVr37",
        "outputId": "0e5325c0-4050-41f3-a805-e0e1a95e0656"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.53125"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Solving multi-step problems using variables"
      ],
      "metadata": {
        "id": "BMXZLR6Bg-RC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Store input data in variables\n",
        "cost_of_ice_bag = 1.25\n",
        "profit_margin = .2\n",
        "number_of_bags = 500\n",
        "\n",
        "# Perform the required calculations\n",
        "profit_per_bag = cost_of_ice_bag * profit_margin\n",
        "total_profit = number_of_bags * profit_per_bag\n",
        "\n",
        "# Display the result\n",
        "print(\"The grocery store makes a total profit of $\", total_profit)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C9uVoC4bVr7b",
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The grocery store makes a total profit of $ 125.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Evaluating conditions using Python"
      ],
      "metadata": {
        "id": "YtQ0ZRHNgn_4"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AJSVeXl3dw0a"
      },
      "outputs": [],
      "source": [
        "my_favorite_number = 1\n",
        "my_least_favorite_number = 5\n",
        "a_neutral_number = 3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5pAx27PEdw0a",
        "outputId": "2ff3a8bf-ad18-4deb-e716-5a26f2b9432f",
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          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "# Equality check - False\n",
        "my_favorite_number == my_least_favorite_number"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5hFa8iJLdw0a",
        "outputId": "e0f529b5-5af9-4b26-d86a-bf89325d10cc"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Not equal check - True\n",
        "my_favorite_number != a_neutral_number"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "kJGIA-vYdw0b",
        "outputId": "514e29b5-82f9-4833-84b3-0789cf3a7114"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 29,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Greater than check - True\n",
        "my_least_favorite_number > a_neutral_number"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gk6mUFLRdw0d",
        "outputId": "08024118-24cd-4e84-a27d-afc757766e10"
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 35,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Less than or equal check - True\n",
        "3 + 6 <= 9"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Combining conditions with logical operators"
      ],
      "metadata": {
        "id": "gk5nQSPT__qo"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "id": "zrr_GfuJdw0e",
        "outputId": "3108a226-ecdd-4419-8ab6-dd0abd535c94"
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 39,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "my_favorite_number > 0 and my_favorite_number <= 3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "EtpbiXzEdw0f",
        "outputId": "4de03133-3886-4a83-ec52-9f85e6f3e17a"
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "execution_count": 42,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "True and False"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "sDFv24qDdw0g",
        "outputId": "f37add3b-01dd-4773-e801-02da8c32051e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 47,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "my_favorite_number < 0 or True"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DeazXSVSdw0h",
        "outputId": "e724a4aa-ddc0-4495-f454-7349fabf462e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "not my_favorite_number < 0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Jey34ptjeYTp",
        "outputId": "d4c42a31-a3ea-42d5-9aa4-bca9f0ccc67c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 53,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "(2 > 3 and 4 <= 5) or not (my_favorite_number < 0 and True)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "__bold__  (double underscore)\n",
        "_italic_  (single underscore)\n",
        "\n",
        "to add a link- [text](URL)\n",
        "\n",
        "### Adding text styles using Markdown\n",
        "\n",
        "For instance, you can use one or more # characters at the start of a line to create headers of different sizes:\n",
        "\n",
        "\n",
        "A bulleted list:\n",
        "\n",
        "* Item 1\n",
        "* Item 2\n",
        "\n",
        "A numbered list:\n",
        "\n",
        "1. Apple\n",
        "2. Banana\n",
        "\n",
        "You can make some text bold using `**`, e.g., **some bold text**, or make it italic using `*`, e.g., *some italic text.*\n",
        "\n",
        "You can also create links, e.g., [link](https://jovian.ai).\n",
        "\n",
        "Images are easily embedded too:\n",
        "\n",
        "![logo](https://i.imgur.com/3gjZMYK.png)"
      ],
      "metadata": {
        "id": "ufYesfQ0jjVF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Save and upload your notebook\n",
        "\n",
        "First, you need to install the Jovian python library if it isn't already installed."
      ],
      "metadata": {
        "id": "ZtAAQnmymG1X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install jovian --upgrade --quiet"
      ],
      "metadata": {
        "id": "h_ulsoRIg2P5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c275714b-0043-4b5e-afd1-b4686c4e2eba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/68.6 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m30.7/68.6 kB\u001b[0m \u001b[31m847.3 kB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━\u001b[0m \u001b[32m61.4/68.6 kB\u001b[0m \u001b[31m935.6 kB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m68.6/68.6 kB\u001b[0m \u001b[31m720.8 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for uuid (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import jovian"
      ],
      "metadata": {
        "id": "dMNoYvw2g2SD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "jovian.commit(project='lesson 1 : first-steps-with-python')"
      ],
      "metadata": {
        "id": "ny2Ewx8mg2UI",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5e311e35-e0ad-47b1-8ac7-0a382c2ca511"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[jovian] Detected Colab notebook...\u001b[0m\n",
            "[jovian] jovian.commit() is no longer required on Google Colab. If you ran this notebook from Jovian, \n",
            "then just save this file in Colab using Ctrl+S/Cmd+S and it will be updated on Jovian. \n",
            "Also, you can also delete this cell, it's no longer necessary.\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "CiUIe5Xag2Xr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "HjxXCenSnRT7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Storing information using variables"
      ],
      "metadata": {
        "id": "0c6G4MPK1ErO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "color1, color2, color3 = \"red\", \"green\", \"blue\""
      ],
      "metadata": {
        "id": "WN0c9jBHnRXY"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "You can change the value stored within a variable by assigning a new value to it using another assignment statement. Be careful while reassigning variables: when you assign a new value to the variable, the old value is lost and no longer accessible."
      ],
      "metadata": {
        "id": "JnFT-Hkq1kw2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "counter = 10\n",
        "# Same as `counter = counter + 4`\n",
        "counter += 4\n",
        "counter"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7GsqgUHM1J7s",
        "outputId": "f5f5d58a-b6bc-494f-a625-30d62a55957e"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "14"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Variable names can be short (a, x, y, etc.) or descriptive ( my_favorite_color, profit_margin, the_3_musketeers, etc.). However, you must follow these rules while naming Python variables:\n",
        "\n",
        "* A variable's name must start with a letter or the underscore character _. It cannot begin with a number.\n",
        "\n",
        "* A variable name can only contain lowercase (small) or uppercase (capital) letters, digits, or underscores (a-z, A-Z, 0-9, and _).\n",
        "\n",
        "* Variable names are case-sensitive, i.e., a_variable, A_Variable, and A_VARIABLE are all different variables."
      ],
      "metadata": {
        "id": "cjeD0Kdm11Sj"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "pgC7d5SC1J98"
      },
      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "qU1yQAwd1KBf"
      },
      "execution_count": null,
      "outputs": []
    }
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}