Lug'atdan_Series_yaratishva_Series_metodlari.ipynb

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      "execution_count": 21,
      "metadata": {
        "id": "j1nnPjodDNy4"
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      "source": [
        "import pandas as pd # pandas library chaqirildi"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np # numpy library chaqirildi"
      ],
      "metadata": {
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      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from pandas import Series  # pandas librarydan Series import qilindi"
      ],
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        "id": "AUrjsBj2CtsZ"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cars_price = {                  # oddiy lug'at\n",
        "    \"Malibu\" : 23000,\n",
        "    \"BMW\" : 45000,\n",
        "    \"Spark\" : 6000,\n",
        "    \"Nexia 3\" : 12000\n",
        "}\n",
        "cars_price"
      ],
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      "execution_count": 6,
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            "text/plain": [
              "{'Malibu': 23000, 'BMW': 45000, 'Spark': 6000, 'Nexia 3': 12000}"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type (cars_price)  # lug'at ma'lumot turi"
      ],
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        },
        "id": "AtfZ6R66_kkt",
        "outputId": "39b157f8-be32-4c27-f09e-63fe37028c9e"
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      "execution_count": 7,
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          "data": {
            "text/plain": [
              "dict"
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          },
          "metadata": {},
          "execution_count": 7
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars = Series (cars_price)   # Series ga o'zgartirish\n",
        "cars\n"
      ],
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              "Malibu     23000\n",
              "BMW        45000\n",
              "Spark       6000\n",
              "Nexia 3    12000\n",
              "dtype: int64"
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      "source": [
        "next_cars = {\n",
        "    \"Mercedes\", \"Honda\", \"Matiz\", \"Malibu\"\n",
        "}\n",
        "next_cars"
      ],
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            "text/plain": [
              "{'Honda', 'Malibu', 'Matiz', 'Mercedes'}"
            ]
          },
          "metadata": {},
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      "cell_type": "code",
      "source": [
        "new = Series (cars_price, index = next_cars)    # index biz kiritilgan ma'lumotga asosan o'zgartirsak bo'ladi\n",
        "new"
      ],
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            "text/plain": [
              "Honda           NaN\n",
              "Matiz           NaN\n",
              "Malibu      23000.0\n",
              "Mercedes        NaN\n",
              "dtype: float64"
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      "cell_type": "code",
      "source": [
        "new.isnull() # NaN ma'lumot bo'lsa true chiqaradi"
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              "Honda        True\n",
              "Matiz        True\n",
              "Malibu      False\n",
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              "Honda       False\n",
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        "cars_price"
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      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Malibu': 23000, 'BMW': 45000, 'Spark': 6000, 'Nexia 3': 12000}"
            ]
          },
          "metadata": {},
          "execution_count": 38
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      ]
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        "new"
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              "Honda           NaN\n",
              "Matiz           NaN\n",
              "Malibu      23000.0\n",
              "Mercedes        NaN\n",
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      "source": [
        "new.name = \"AvtoShop\"           # jadvalimizning nomi\n",
        "new.index.name = \"Modellar\"     # indexlar nomi\n",
        "new"
      ],
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              "Modellar\n",
              "Honda           NaN\n",
              "Matiz           NaN\n",
              "Malibu      23000.0\n",
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              "Name: AvtoShop, dtype: float64"
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      "cell_type": "code",
      "source": [
        "cars_dict = {'Malibu':40000, 'Lacetti':20000, 'Toyota':45000, 'Mazda':52000, 'Honda':38000} # bu lug'at\n",
        "cars1 = Series (cars_dict)\n",
        "cars1"
      ],
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      "execution_count": 42,
      "outputs": [
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          "data": {
            "text/plain": [
              "Malibu     40000\n",
              "Lacetti    20000\n",
              "Toyota     45000\n",
              "Mazda      52000\n",
              "Honda      38000\n",
              "dtype: int64"
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        "new_prices = Series({\"Honda\":5000, \"Mazda\":-3000, \"Malibu\":4500, \"Toyota\":5200, 'Lacetti':-1200})\n",
        "cars2 = Series (new_prices)\n",
        "cars2"
      ],
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      "execution_count": 43,
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            "text/plain": [
              "Honda      5000\n",
              "Mazda     -3000\n",
              "Malibu     4500\n",
              "Toyota     5200\n",
              "Lacetti   -1200\n",
              "dtype: int64"
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              "      <th>Honda</th>\n",
              "      <td>5000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mazda</th>\n",
              "      <td>-3000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Malibu</th>\n",
              "      <td>4500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Toyota</th>\n",
              "      <td>5200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lacetti</th>\n",
              "      <td>-1200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1 + cars2    # Series turidagi jadvallarda ham arifmetik amallarni ham bajarsak bo'ladi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "RApTQjt4GH_2",
        "outputId": "4d2f4a3c-7bb7-4483-cee6-e6c4822105b0"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Honda      43000\n",
              "Lacetti    18800\n",
              "Malibu     44500\n",
              "Mazda      49000\n",
              "Toyota     50200\n",
              "dtype: int64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Honda</th>\n",
              "      <td>43000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Lacetti</th>\n",
              "      <td>18800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Malibu</th>\n",
              "      <td>44500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Mazda</th>\n",
              "      <td>49000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Toyota</th>\n",
              "      <td>50200</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.index    # indexni nomini aniqlaydi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8DkIuM4gGM3z",
        "outputId": "b3e4d8e6-5c95-4d5b-df3d-e970fdb62bd6"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Malibu', 'Lacetti', 'Toyota', 'Mazda', 'Honda'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.values  # qiymatlarni nomini aniqlaydi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EYO3ubAYGjtq",
        "outputId": "ecf00150-a4c0-4e00-8d39-2fd210a3c769"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([40000, 20000, 45000, 52000, 38000])"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.hasnans     # NaN ma'lumot bormi yoki yo'qmi aniqlaydi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z7HM6-gcGpp7",
        "outputId": "be492e9c-05ed-42ec-83f3-6ba667295328"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.dtype   # turini aniqlaydi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9OVyODF2G0H6",
        "outputId": "12a4818e-0c44-4b9a-9020-cdedd8f78895"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('int64')"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.is_unique  # takrorlanmas ma'lumot bo'lmasa True qiymat beradi, va aksincha"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AInSgCmZG3Y8",
        "outputId": "665833fe-29a7-4356-fb29-618ccd227562"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.shape  # Series hajmi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iMicKpxbG_V2",
        "outputId": "896ca720-0d1d-4419-ca91-ab76e8970270"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5,)"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.size"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IpK1RJEdHCoy",
        "outputId": "bc5cdb79-fdd6-4768-f933-251a04fbcc57"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.iloc[-1]    # index bo'yicha ma'lumotni topib beradi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vXJl57SAHE8O",
        "outputId": "ad10817a-1f60-4fd1-a5dc-990ed66f8876"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "38000"
            ]
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.max()    # Series ichidagi maximum qiymatni beradi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rlI4Hin5HMXe",
        "outputId": "d51c71dc-92df-49a8-8a38-1628b8ea5561"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "52000"
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.min()    # Series ichidagi minimum qiymatni beradi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GLpy6WVfHTlU",
        "outputId": "c14bae7d-7fff-4bca-fecd-782270ec6297"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "20000"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cars1.mean()        # Series ichidagi o'rtacha qiymatni beradi"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3maIsdaRHWor",
        "outputId": "8f07bc1a-1508-468a-c38b-6f2c79e3f668"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "39000.0"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    }
  ]
}