update

Functions_And_Dictionaries.ipynb

@@ -0,0 +1,1224 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "winJJbiUiIIO"
+      },
+      "source": [
+        "Data structures: Dictionaries"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "yih6CE4RiIrl"
+      },
+      "outputs": [],
+      "source": [
+        "Dictionaries = {\"key1\":\"value1\"}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "56RkusxohJDa"
+      },
+      "source": [
+        "Create Dictionaries"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "VLkxduR8hSQ_"
+      },
+      "outputs": [],
+      "source": [
+        "dic = {\n",
+        "  \"brand\": \"Ford\",\n",
+        "  \"model\": \"Mustang\",\n",
+        "  \"year\": 1964\n",
+        "}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Ihvoijply3U5",
+        "outputId": "9f69778d-96a9-40b7-c1b9-b9feb4b0bc6d"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'brand': 'Ford', 'model': 'Mustang', 'year': 1964}\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "dCW1nOWDiNRW",
+        "outputId": "693b217a-6e52-4b7c-f054-9c34119daa31"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'brand': 'Ford', 'model': 'Mustang', 'year': 1964}\n",
+            "3\n",
+            "<class 'dict'>\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(dic)\n",
+        "print(len(dic))\n",
+        "print(type(dic))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "cOUjZZdviN0G",
+        "outputId": "f2c4422e-453a-4f72-9bf0-f699c6339afd"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'brand': 'Ford', 'model': 'Mustang', 'year': 1964}\n"
+          ]
+        }
+      ],
+      "source": [
+        "dic = dict(brand = \"Ford\", model = \"Mustang\", year = 1964)\n",
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "k95vij2nkKLS"
+      },
+      "source": [
+        "Accessing Items"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Pq5DQvKGkJO7",
+        "outputId": "e5e8474c-75b8-4e59-dd4a-6c81c92901a6"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "1964\n"
+          ]
+        }
+      ],
+      "source": [
+        "x = dic[\"year\"]\n",
+        "print(x)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "id": "7NrgctylkR0D",
+        "outputId": "a1c24afa-80c7-4535-fda4-796de9986b9f"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "'Mustang'"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "x = dic.get(\"model\")\n",
+        "x"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "aKSZoGH-iYTm"
+      },
+      "source": [
+        "keys()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "t9pG91qkkYDk",
+        "outputId": "156acb1f-8197-4799-c6db-8cf4dc05a5b4"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "dict_keys(['brand', 'model', 'year'])\n"
+          ]
+        }
+      ],
+      "source": [
+        "x = dic.keys()\n",
+        "print(x)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "XIY6AocbifhJ",
+        "outputId": "ce5bbca4-2808-4d80-bfa2-91eb5321e8d4"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "dict_values(['Ford', 'Mustang', 1964])"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "x = dic.values()\n",
+        "x"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "r3UjUOwMir1v",
+        "outputId": "e9946a9b-d7e8-4e58-8e06-8772b0ca87ee"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "dict_items([('brand', 'Ford'), ('model', 'Mustang'), ('year', 1964)])"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "x = dic.items()\n",
+        "x"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "QNjHr3FxhhrI"
+      },
+      "source": [
+        "Add Items"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "P-jX07npkdWt",
+        "outputId": "41980110-ea06-4eec-f3ab-864c32906360"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'brand': 'Ford', 'model': 'Mustang', 'year': 1964, 'color': 'white'}"
+            ]
+          },
+          "execution_count": 11,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "dic[\"color\"] = \"white\"\n",
+        "dic"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "df2cHHGInqBE",
+        "outputId": "6c8a7c34-fad7-4075-ca3e-26fb94818e55"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'brand': 'Ford',\n",
+              " 'model': 'Mustang',\n",
+              " 'year': 1964,\n",
+              " 'color': 'white',\n",
+              " 'Power': '315 HP'}"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "d= {\"Power\":\"315 HP\"}\n",
+        "dic.update(d)\n",
+        "dic"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "MQQ-FXNhi1sm"
+      },
+      "source": [
+        "Modify"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "vTI0Js9Qk4i3",
+        "outputId": "fedbb0b2-c422-44dd-96a6-0e737cc1c601"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "dict_values(['Ford', 'Mustang', 1964, 'white', '315 HP'])\n",
+            "dict_values(['Ford', 'Mustang', 2020, 'white', '315 HP'])\n"
+          ]
+        }
+      ],
+      "source": [
+        "x = dic.values()\n",
+        "\n",
+        "print(x) #before the change\n",
+        "\n",
+        "dic[\"year\"] = 2020\n",
+        "\n",
+        "print(x) #after the change"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "uvPL_HxuoeYj",
+        "outputId": "26100336-0df1-475e-fe1d-43aa96310b02"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'brand': 'Ford',\n",
+              " 'model': 'Mustang',\n",
+              " 'year': 2020,\n",
+              " 'color': 'white',\n",
+              " 'Power': '400 HP'}"
+            ]
+          },
+          "execution_count": 14,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "dic.update({\"Power\":\"400 HP\"})\n",
+        "dic"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0H-RH2KAk01h"
+      },
+      "source": [
+        "IF condition on dictionary"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "RIKmYHRslRkZ",
+        "outputId": "25a74495-4db4-4dce-c157-f15ad5d609cf"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Mustang\n"
+          ]
+        }
+      ],
+      "source": [
+        "if \"model\" in dic:\n",
+        "  print(dic[\"model\"])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "aHCU62mgl42t"
+      },
+      "source": [
+        "Remove"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Tt7MiZJ4lbX6",
+        "outputId": "fb951324-8c71-4bf4-da40-c260cbcae871"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'brand': 'Ford', 'year': 2020, 'color': 'white', 'Power': '400 HP'}\n"
+          ]
+        }
+      ],
+      "source": [
+        "dic.pop(\"model\")\n",
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "5rLw_HJGluTk",
+        "outputId": "b0a40a0f-034b-4816-a8af-64d3b646bbb2"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'brand': 'Ford', 'year': 2020, 'color': 'white'}\n"
+          ]
+        }
+      ],
+      "source": [
+        "dic.popitem()\n",
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "HXjuyg0Kl2c1",
+        "outputId": "ebbd008f-6835-4a42-8426-54817e62e76d"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'brand': 'Ford', 'color': 'white'}\n"
+          ]
+        }
+      ],
+      "source": [
+        "del dic[\"year\"]\n",
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 19,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "NaGVNcQLl_Ct",
+        "outputId": "8f88b9c5-6606-44c4-86c9-bd0ed5d3cfb4"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{}\n"
+          ]
+        }
+      ],
+      "source": [
+        "dic.clear()\n",
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "2g18Gu0Ck-t9"
+      },
+      "source": [
+        "for loop in dictionary"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {
+        "id": "sjuLUjk4lMMW"
+      },
+      "outputs": [],
+      "source": [
+        "dic = {\n",
+        "  \"brand\": \"Ford\",\n",
+        "  \"model\": \"Mustang\",\n",
+        "  \"year\": 1964\n",
+        "}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "SfuHtH52lWkM"
+      },
+      "source": [
+        "for loop with keys"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 21,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "viXaYxIwlOED",
+        "outputId": "ca313f60-0338-40df-c3be-c125fca936de"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "brand\n",
+            "model\n",
+            "year\n"
+          ]
+        }
+      ],
+      "source": [
+        "for x in dic:\n",
+        "  print(x)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8tybG7eClb1A",
+        "outputId": "4d3545c0-b679-4522-b26d-70364c931348"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "brand\n",
+            "model\n",
+            "year\n"
+          ]
+        }
+      ],
+      "source": [
+        "for x in dic.keys():\n",
+        "  print(x)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_CT7BsxjlsjZ"
+      },
+      "source": [
+        "for loop with values"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 23,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "hWpbaVpQmFTG",
+        "outputId": "f7ab0e1a-2329-41ce-fb4c-747eee4605b7"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Ford\n",
+            "Mustang\n",
+            "1964\n"
+          ]
+        }
+      ],
+      "source": [
+        "for x in dic:\n",
+        "  print(dic[x])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "PFYLUr8GljJA",
+        "outputId": "b62871c8-9390-4f84-a783-0d5bfb17de3c"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Ford\n",
+            "Mustang\n",
+            "1964\n"
+          ]
+        }
+      ],
+      "source": [
+        "for x in dic.values():\n",
+        "  print(x)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "e8ttUHNPl2Ep"
+      },
+      "source": [
+        "for loop with items"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 25,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "7NEARCAimQmX",
+        "outputId": "ab8c1e97-025f-4619-bd8b-92731b8fdca3"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "brand : Ford\n",
+            "model : Mustang\n",
+            "year : 1964\n"
+          ]
+        }
+      ],
+      "source": [
+        "for x, y in dic.items():\n",
+        "  print(x,':', y)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "fq8j8EkwnbuQ"
+      },
+      "source": [
+        "Advanced Operations of dictionaries"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 26,
+      "metadata": {
+        "id": "GjgwAYbZmtFC"
+      },
+      "outputs": [],
+      "source": [
+        "child1 = {\n",
+        "  \"name\" : \"Rohan\",\n",
+        "  \"year\" : 2004\n",
+        "}\n",
+        "child2 = {\n",
+        "  \"name\" : \"Rakib\",\n",
+        "  \"year\" : 2007\n",
+        "}\n",
+        "child3 = {\n",
+        "  \"name\" : \"Rana\",\n",
+        "  \"year\" : 2011\n",
+        "}\n",
+        "\n",
+        "myfamily = {\n",
+        "  \"child1\" : child1,\n",
+        "  \"child2\" : child2,\n",
+        "  \"child3\" : child3\n",
+        "}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 27,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "28qYsQ-erbHA",
+        "outputId": "330b9c15-a7be-45bc-a02e-970daa992ff2"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'child1': {'name': 'Rohan', 'year': 2004},\n",
+              " 'child2': {'name': 'Rakib', 'year': 2007},\n",
+              " 'child3': {'name': 'Rana', 'year': 2011}}"
+            ]
+          },
+          "execution_count": 27,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "myfamily"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 28,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "k0_Fp2RrnHlY",
+        "outputId": "e15c1f6b-25d8-42a9-fa78-409dfe895b25"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}\n"
+          ]
+        }
+      ],
+      "source": [
+        "dic = {}\n",
+        "for x in range(1, 6):\n",
+        "    dic[x] = x ** 2\n",
+        "    # dic.update({x: x ** 2})\n",
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 29,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "MpLOphmoTesg",
+        "outputId": "14fab957-1055-421e-8e2c-b8d18eca45bc"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}\n"
+          ]
+        }
+      ],
+      "source": [
+        "squares = {x: x ** 2 for x in range(1, 6)}\n",
+        "print(squares)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 30,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "w6EtOS4wookU",
+        "outputId": "2a19cdd0-2f67-4b01-cbe6-28c5b1d193d5"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{2: 4, 4: 16, 6: 36, 8: 64, 10: 100}\n"
+          ]
+        }
+      ],
+      "source": [
+        "dic = {}\n",
+        "for x in range(1, 11):\n",
+        "  if x % 2 == 0:\n",
+        "    dic[x] = x ** 2\n",
+        "    # dic.update({x: x ** 2})\n",
+        "print(dic)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 31,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "dPjzWfdsau9g",
+        "outputId": "9460ce1d-0cbc-4449-82b8-53e11183df28"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{2: 4, 4: 16, 6: 36, 8: 64, 10: 100}\n"
+          ]
+        }
+      ],
+      "source": [
+        "squares = {x: x ** 2 for x in range(1, 11) if x % 2 == 0}\n",
+        "print(squares)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 39,
+      "metadata": {
+        "id": "9OtTs6tC7Zcf"
+      },
+      "outputs": [],
+      "source": [
+        "users = [\n",
+        "  {\n",
+        "    \"_id\": \"u12345\",\n",
+        "    \"name\": \"Rahman\",\n",
+        "    \"email\": \"rahman@example.com\",\n",
+        "    \"age\": 28,\n",
+        "    \"isActive\": True,\n",
+        "    \"address\": {\n",
+        "      \"street\": \"123 Lakeview Road\",\n",
+        "      \"city\": \"Dhaka\",\n",
+        "      \"zip\": \"1207\"\n",
+        "    },\n",
+        "    \"hobbies\": [\"reading\", \"gaming\", \"traveling\"],\n",
+        "    \"orders\": [\n",
+        "      {\n",
+        "        \"order_id\": \"ord1001\",\n",
+        "        \"date\": \"2025-05-01\",\n",
+        "        \"items\": [\n",
+        "          {\"product\": \"Book\", \"price\": 12.99, \"quantity\": 1},\n",
+        "          {\"product\": \"Pen\", \"price\": 1.99, \"quantity\": 3}\n",
+        "        ],\n",
+        "        \"total\": 18.96\n",
+        "      },\n",
+        "      {\n",
+        "        \"order_id\": \"ord1002\",\n",
+        "        \"date\": \"2025-05-04\",\n",
+        "        \"items\": [\n",
+        "          {\"product\": \"Shoes\", \"price\": 45.00, \"quantity\": 1}\n",
+        "        ],\n",
+        "        \"total\": 45.00\n",
+        "      }\n",
+        "    ]\n",
+        "  },\n",
+        "  {\n",
+        "    \"_id\": \"u12346\",\n",
+        "    \"name\": \"Fatima\",\n",
+        "    \"email\": \"fatima@example.com\",\n",
+        "    \"age\": 32,\n",
+        "    \"isActive\": False,\n",
+        "    \"address\": {\n",
+        "      \"street\": \"78 Rose Lane\",\n",
+        "      \"city\": \"Chittagong\",\n",
+        "      \"zip\": \"4000\"\n",
+        "    },\n",
+        "    \"hobbies\": [\"painting\", \"yoga\"],\n",
+        "    \"orders\": [\n",
+        "      {\n",
+        "        \"order_id\": \"ord1003\",\n",
+        "        \"date\": \"2025-05-02\",\n",
+        "        \"items\": [\n",
+        "          {\"product\": \"Canvas\", \"price\": 25.50, \"quantity\": 2}\n",
+        "        ],\n",
+        "        \"total\": 51.00\n",
+        "      }\n",
+        "    ]\n",
+        "  },\n",
+        "  {\n",
+        "    \"_id\": \"u12347\",\n",
+        "    \"name\": \"Karim\",\n",
+        "    \"email\": \"karim@example.com\",\n",
+        "    \"age\": 40,\n",
+        "    \"isActive\": True,\n",
+        "    \"address\": {\n",
+        "      \"street\": \"10 Green Street\",\n",
+        "      \"city\": \"Khulna\",\n",
+        "      \"zip\": \"9100\"\n",
+        "    },\n",
+        "    \"hobbies\": [\"fishing\", \"cycling\", \"chess\"],\n",
+        "    \"orders\": []\n",
+        "  },\n",
+        "  {\n",
+        "    \"_id\": \"u12348\",\n",
+        "    \"name\": \"Ayesha\",\n",
+        "    \"email\": \"ayesha@example.com\",\n",
+        "    \"age\": 25,\n",
+        "    \"isActive\": True,\n",
+        "    \"address\": {\n",
+        "      \"street\": \"56 Mango Street\",\n",
+        "      \"city\": \"Sylhet\",\n",
+        "      \"zip\": \"3100\"\n",
+        "    },\n",
+        "    \"hobbies\": [\"dancing\", \"baking\"],\n",
+        "    \"orders\": [\n",
+        "      {\n",
+        "        \"order_id\": \"ord1004\",\n",
+        "        \"date\": \"2025-05-05\",\n",
+        "        \"items\": [\n",
+        "          {\"product\": \"Dress\", \"price\": 30.00, \"quantity\": 1},\n",
+        "          {\"product\": \"Handbag\", \"price\": 40.00, \"quantity\": 1}\n",
+        "        ],\n",
+        "        \"total\": 70.00\n",
+        "      }\n",
+        "    ]\n",
+        "  }\n",
+        "]\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 46,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[{'_id': 'u12345',\n",
+              "  'name': 'Rahman',\n",
+              "  'email': 'rahman@example.com',\n",
+              "  'age': 28,\n",
+              "  'isActive': True,\n",
+              "  'address': {'street': '123 Lakeview Road', 'city': 'Dhaka', 'zip': '1207'},\n",
+              "  'hobbies': ['reading', 'gaming', 'traveling'],\n",
+              "  'orders': [{'order_id': 'ord1001',\n",
+              "    'date': '2025-05-01',\n",
+              "    'items': [{'product': 'Book', 'price': 12.99, 'quantity': 1},\n",
+              "     {'product': 'Pen', 'price': 1.99, 'quantity': 3}],\n",
+              "    'total': 18.96},\n",
+              "   {'order_id': 'ord1002',\n",
+              "    'date': '2025-05-04',\n",
+              "    'items': [{'product': 'Shoes', 'price': 45.0, 'quantity': 1}],\n",
+              "    'total': 45.0}]},\n",
+              " {'_id': 'u12347',\n",
+              "  'name': 'Karim',\n",
+              "  'email': 'karim@example.com',\n",
+              "  'age': 40,\n",
+              "  'isActive': True,\n",
+              "  'address': {'street': '10 Green Street', 'city': 'Khulna', 'zip': '9100'},\n",
+              "  'hobbies': ['fishing', 'cycling', 'chess'],\n",
+              "  'orders': []},\n",
+              " {'_id': 'u12348',\n",
+              "  'name': 'Ayesha',\n",
+              "  'email': 'ayesha@example.com',\n",
+              "  'age': 25,\n",
+              "  'isActive': True,\n",
+              "  'address': {'street': '56 Mango Street', 'city': 'Sylhet', 'zip': '3100'},\n",
+              "  'hobbies': ['dancing', 'baking'],\n",
+              "  'orders': [{'order_id': 'ord1004',\n",
+              "    'date': '2025-05-05',\n",
+              "    'items': [{'product': 'Dress', 'price': 30.0, 'quantity': 1},\n",
+              "     {'product': 'Handbag', 'price': 40.0, 'quantity': 1}],\n",
+              "    'total': 70.0}]}]"
+            ]
+          },
+          "execution_count": 46,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "active_users = [user for user in users if user[\"isActive\"]]\n",
+        "active_users"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 47,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[{'name': 'Rahman', 'email': 'rahman@example.com'},\n",
+              " {'name': 'Fatima', 'email': 'fatima@example.com'},\n",
+              " {'name': 'Ayesha', 'email': 'ayesha@example.com'}]"
+            ]
+          },
+          "execution_count": 47,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "users_with_orders = [\n",
+        "    {\"name\": user[\"name\"], \"email\": user[\"email\"]}\n",
+        "    for user in users if len(user[\"orders\"]) > 0\n",
+        "]\n",
+        "users_with_orders"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 48,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "[{'name': 'Rahman', 'total_spent': 63.96},\n",
+              " {'name': 'Fatima', 'total_spent': 51.0},\n",
+              " {'name': 'Karim', 'total_spent': 0},\n",
+              " {'name': 'Ayesha', 'total_spent': 70.0}]"
+            ]
+          },
+          "execution_count": 48,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "user_spending = [\n",
+        "    {\n",
+        "        \"name\": user[\"name\"],\n",
+        "        \"total_spent\": sum(order[\"total\"] for order in user[\"orders\"])\n",
+        "    }\n",
+        "    for user in users\n",
+        "]\n",
+        "user_spending"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 53,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Book\n",
+            "Pen\n",
+            "Shoes\n"
+          ]
+        }
+      ],
+      "source": [
+        "for user in users:\n",
+        "    if user['name'] == 'Rahman':\n",
+        "        for i in user['orders']:\n",
+        "            for j in i['items']:\n",
+        "                print(j['product'])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 55,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "31.25"
+            ]
+          },
+          "execution_count": 55,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "avg_age = sum(user[\"age\"] for user in users) / len(users)\n",
+        "avg_age"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 63,
+      "metadata": {},
+      "outputs": [
+        {
+          "ename": "SyntaxError",
+          "evalue": "invalid syntax (3403861915.py, line 5)",
+          "output_type": "error",
+          "traceback": [
+            "  \u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[63]\u001b[39m\u001b[32m, line 5\u001b[39m\n\u001b[31m    \u001b[39m\u001b[31mproduct_summary.update({[item[\"product\"]] += item[\"quantity\"]})\u001b[39m\n                                              ^\n\u001b[31mSyntaxError\u001b[39m\u001b[31m:\u001b[39m invalid syntax\n"
+          ]
+        }
+      ],
+      "source": [
+        "product_summary = {}\n",
+        "for user in users:\n",
+        "    for order in user[\"orders\"]:\n",
+        "        for item in order[\"items\"]:\n",
+        "            product_summary.update({[item[\"product\"]] += item[\"quantity\"]})\n",
+        "product_summary"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 65,
+      "metadata": {},
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "1"
+            ]
+          },
+          "execution_count": 65,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "dhaka_count = sum(1 for user in users if user[\"address\"][\"city\"] == \"Dhaka\")\n",
+        "dhaka_count"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "all",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.9"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}