Assignment_1 (1).ipynb

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      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Basic Python"
      ],
      "metadata": {
        "id": "McSxJAwcOdZ1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 1. Split this string"
      ],
      "metadata": {
        "id": "CU48hgo4Owz5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "s = \"Hi there Sam!\""
      ],
      "metadata": {
        "id": "s07c7JK7Oqt-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "s=\"Hi there Sam!\"\n",
        "n=s.split()\n",
        "print(n)"
      ],
      "metadata": {
        "id": "6mGVa3SQYLkb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a403afd6-a247-477a-e05f-80412f730e3b"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['Hi', 'there', 'Sam!']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 2. Use .format() to print the following string. \n",
        "\n",
        "### Output should be: The diameter of Earth is 12742 kilometers."
      ],
      "metadata": {
        "id": "GH1QBn8HP375"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "planet = \"Earth\"\n",
        "diameter = 12742"
      ],
      "metadata": {
        "id": "_ZHoml3kPqic"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "planet = \"Earth\"\n",
        "diameter = 12742\n",
        "print('The diameter of {} is {} kilometers.'.format(planet,diameter))"
      ],
      "metadata": {
        "id": "HyRyJv6CYPb4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bf3300bf-835e-46d0-8aeb-533546541680"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The diameter of Earth is 12742 kilometers.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3. In this nest dictionary grab the word \"hello\""
      ],
      "metadata": {
        "id": "KE74ZEwkRExZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "d = {'k1':[1,2,3,{'tricky':['oh','man','inception',{'target':[1,2,3,'hello']}]}]}\n",
        "d['k1'][3]['tricky'][3]['target'][3]"
      ],
      "metadata": {
        "id": "fcVwbCc1QrQI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "outputId": "7977e67a-fbca-42e6-fb66-c2b7e8735606"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'hello'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "MvbkMZpXYRaw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Numpy"
      ],
      "metadata": {
        "id": "bw0vVp-9ddjv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "LLiE_TYrhA1O"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.1 Create an array of 10 zeros? \n",
        "## 4.2 Create an array of 10 fives?"
      ],
      "metadata": {
        "id": "wOg8hinbgx30"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "array=np.zeros(10)\n",
        "print(\"An array of 10 zeroes\")\n",
        "print (array)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EJPHzk7JQFH1",
        "outputId": "fea3d2b9-831d-4f8a-c492-f9ab8eff7adf"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "An array of 10 zeroes\n",
            "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "array=np.ones(10)*5\n",
        "print(\"An array of 10 fives\")\n",
        "print (array)"
      ],
      "metadata": {
        "id": "NHrirmgCYXvU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e6804047-6842-4da1-d597-b8f19c1d1097"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "An array of 10 fives\n",
            "[5. 5. 5. 5. 5. 5. 5. 5. 5. 5.]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "e4005lsTYXxx"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 5. Create an array of all the even integers from 20 to 35"
      ],
      "metadata": {
        "id": "gZHHDUBvrMX4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "a = np.arange(20,35,2)\n",
        "print(a)"
      ],
      "metadata": {
        "id": "oAI2tbU2Yag-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "52596eb1-cbf0-415d-fc5b-896611ec7bb6"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[20 22 24 26 28 30 32 34]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 6. Create a 3x3 matrix with values ranging from 0 to 8"
      ],
      "metadata": {
        "id": "NaOM308NsRpZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x=np.arange(0,9).reshape(3,3)\n",
        "print(x)"
      ],
      "metadata": {
        "id": "tOlEVH7BYceE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2f352e74-8aca-4dc4-eefd-c467f021d593"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[0 1 2]\n",
            " [3 4 5]\n",
            " [6 7 8]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 7. Concatenate a and b \n",
        "## a = np.array([1, 2, 3]), b = np.array([4, 5, 6])"
      ],
      "metadata": {
        "id": "hQ0dnhAQuU_p"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "a=np.array([1,2,3])\n",
        "b=np.array([4,5,6])\n",
        "print(a)\n",
        "print(b)"
      ],
      "metadata": {
        "id": "rAPSw97aYfE0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7504fd39-a8da-449b-9dd4-4204895b0c75"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1 2 3]\n",
            "[4 5 6]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Pandas"
      ],
      "metadata": {
        "id": "dlPEY9DRwZga"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 8. Create a dataframe with 3 rows and 2 columns"
      ],
      "metadata": {
        "id": "ijoYW51zwr87"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "data=[['Pavan',10],['Vamsi',20],['Sai',30]]\n",
        "a=pd.DataFrame(data,columns=['Name','Age'])\n",
        "print(a)\n"
      ],
      "metadata": {
        "id": "T5OxJRZ8uvR7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0f3606ea-d682-4d7d-c3be-03deb39461e9"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "    Name  Age\n",
            "0  Pavan   10\n",
            "1  Vamsi   20\n",
            "2    Sai   30\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "xNpI_XXoYhs0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 9. Generate the series of dates from 1st Jan, 2023 to 10th Feb, 2023"
      ],
      "metadata": {
        "id": "UXSmdNclyJQD"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import date,timedelta\n",
        "sdate =date(2023,1,1) #start date\n",
        "edate=date(2023,2,11) #end date\n",
        "[sdate+timedelta(days=x)for x in range((edate-sdate).days)]\n"
      ],
      "metadata": {
        "id": "dgyC0JhVYl4F",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6b973081-6a96-4647-c039-913e37783836"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[datetime.date(2023, 1, 1),\n",
              " datetime.date(2023, 1, 2),\n",
              " datetime.date(2023, 1, 3),\n",
              " datetime.date(2023, 1, 4),\n",
              " datetime.date(2023, 1, 5),\n",
              " datetime.date(2023, 1, 6),\n",
              " datetime.date(2023, 1, 7),\n",
              " datetime.date(2023, 1, 8),\n",
              " datetime.date(2023, 1, 9),\n",
              " datetime.date(2023, 1, 10),\n",
              " datetime.date(2023, 1, 11),\n",
              " datetime.date(2023, 1, 12),\n",
              " datetime.date(2023, 1, 13),\n",
              " datetime.date(2023, 1, 14),\n",
              " datetime.date(2023, 1, 15),\n",
              " datetime.date(2023, 1, 16),\n",
              " datetime.date(2023, 1, 17),\n",
              " datetime.date(2023, 1, 18),\n",
              " datetime.date(2023, 1, 19),\n",
              " datetime.date(2023, 1, 20),\n",
              " datetime.date(2023, 1, 21),\n",
              " datetime.date(2023, 1, 22),\n",
              " datetime.date(2023, 1, 23),\n",
              " datetime.date(2023, 1, 24),\n",
              " datetime.date(2023, 1, 25),\n",
              " datetime.date(2023, 1, 26),\n",
              " datetime.date(2023, 1, 27),\n",
              " datetime.date(2023, 1, 28),\n",
              " datetime.date(2023, 1, 29),\n",
              " datetime.date(2023, 1, 30),\n",
              " datetime.date(2023, 1, 31),\n",
              " datetime.date(2023, 2, 1),\n",
              " datetime.date(2023, 2, 2),\n",
              " datetime.date(2023, 2, 3),\n",
              " datetime.date(2023, 2, 4),\n",
              " datetime.date(2023, 2, 5),\n",
              " datetime.date(2023, 2, 6),\n",
              " datetime.date(2023, 2, 7),\n",
              " datetime.date(2023, 2, 8),\n",
              " datetime.date(2023, 2, 9),\n",
              " datetime.date(2023, 2, 10)]"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 10. Create 2D list to DataFrame\n",
        "\n",
        "lists = [[1, 'aaa', 22],\n",
        "         [2, 'bbb', 25],\n",
        "         [3, 'ccc', 24]]"
      ],
      "metadata": {
        "id": "ZizSetD-y5az"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lists = [[1, 'aaa', 22], [2, 'bbb', 25], [3, 'ccc', 24]]"
      ],
      "metadata": {
        "id": "_XMC8aEt0llB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "lists=[[1,'aaa',22],[2,'bbb',25],[3,'ccc',24]]\n",
        "df=pd.DataFrame(lists,columns=['Number','FName','Age'])\n",
        "print(df)"
      ],
      "metadata": {
        "id": "knH76sDKYsVX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "be437461-680e-4f4c-ada9-c11a5e347060"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   Number FName  Age\n",
            "0       1   aaa   22\n",
            "1       2   bbb   25\n",
            "2       3   ccc   24\n"
          ]
        }
      ]
    }
  ]
}