04_Lab_Assignment_Lab02.ipynb

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      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv(\"cereal.csv\")"
      ]
    },
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      "cell_type": "code",
      "source": [
        "df"
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              "                         name mfr type  calories  protein  fat  sodium  fiber  \\\n",
              "0                   100% Bran   N    C        70        4    1     130   10.0   \n",
              "1           100% Natural Bran   Q    C       120        3    5      15    2.0   \n",
              "2                    All-Bran   K    C        70        4    1     260    9.0   \n",
              "3   All-Bran with Extra Fiber   K    C        50        4    0     140   14.0   \n",
              "4              Almond Delight   R    C       110        2    2     200    1.0   \n",
              "..                        ...  ..  ...       ...      ...  ...     ...    ...   \n",
              "72                    Triples   G    C       110        2    1     250    0.0   \n",
              "73                       Trix   G    C       110        1    1     140    0.0   \n",
              "74                 Wheat Chex   R    C       100        3    1     230    3.0   \n",
              "75                   Wheaties   G    C       100        3    1     200    3.0   \n",
              "76        Wheaties Honey Gold   G    C       110        2    1     200    1.0   \n",
              "\n",
              "    carbo  sugars  potass  vitamins  shelf  weight  cups     rating  \n",
              "0     5.0       6     280        25      3     1.0  0.33  68.402973  \n",
              "1     8.0       8     135         0      3     1.0  1.00  33.983679  \n",
              "2     7.0       5     320        25      3     1.0  0.33  59.425505  \n",
              "3     8.0       0     330        25      3     1.0  0.50  93.704912  \n",
              "4    14.0       8      -1        25      3     1.0  0.75  34.384843  \n",
              "..    ...     ...     ...       ...    ...     ...   ...        ...  \n",
              "72   21.0       3      60        25      3     1.0  0.75  39.106174  \n",
              "73   13.0      12      25        25      2     1.0  1.00  27.753301  \n",
              "74   17.0       3     115        25      1     1.0  0.67  49.787445  \n",
              "75   17.0       3     110        25      1     1.0  1.00  51.592193  \n",
              "76   16.0       8      60        25      1     1.0  0.75  36.187559  \n",
              "\n",
              "[77 rows x 16 columns]"
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              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>mfr</th>\n",
              "      <th>type</th>\n",
              "      <th>calories</th>\n",
              "      <th>protein</th>\n",
              "      <th>fat</th>\n",
              "      <th>sodium</th>\n",
              "      <th>fiber</th>\n",
              "      <th>carbo</th>\n",
              "      <th>sugars</th>\n",
              "      <th>potass</th>\n",
              "      <th>vitamins</th>\n",
              "      <th>shelf</th>\n",
              "      <th>weight</th>\n",
              "      <th>cups</th>\n",
              "      <th>rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100% Bran</td>\n",
              "      <td>N</td>\n",
              "      <td>C</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>130</td>\n",
              "      <td>10.0</td>\n",
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              "      <td>6</td>\n",
              "      <td>280</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>68.402973</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100% Natural Bran</td>\n",
              "      <td>Q</td>\n",
              "      <td>C</td>\n",
              "      <td>120</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>15</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8</td>\n",
              "      <td>135</td>\n",
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              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>33.983679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>All-Bran</td>\n",
              "      <td>K</td>\n",
              "      <td>C</td>\n",
              "      <td>70</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>260</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5</td>\n",
              "      <td>320</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.33</td>\n",
              "      <td>59.425505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>All-Bran with Extra Fiber</td>\n",
              "      <td>K</td>\n",
              "      <td>C</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>140</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0</td>\n",
              "      <td>330</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.50</td>\n",
              "      <td>93.704912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Almond Delight</td>\n",
              "      <td>R</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>200</td>\n",
              "      <td>1.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>-1</td>\n",
              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>34.384843</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>72</th>\n",
              "      <td>Triples</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>250</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>3</td>\n",
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              "      <td>25</td>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>39.106174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>73</th>\n",
              "      <td>Trix</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>140</td>\n",
              "      <td>0.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>12</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>27.753301</td>\n",
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              "    <tr>\n",
              "      <th>74</th>\n",
              "      <td>Wheat Chex</td>\n",
              "      <td>R</td>\n",
              "      <td>C</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>230</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3</td>\n",
              "      <td>115</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.67</td>\n",
              "      <td>49.787445</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75</th>\n",
              "      <td>Wheaties</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>100</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17.0</td>\n",
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              "      <td>1.0</td>\n",
              "      <td>1.00</td>\n",
              "      <td>51.592193</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>76</th>\n",
              "      <td>Wheaties Honey Gold</td>\n",
              "      <td>G</td>\n",
              "      <td>C</td>\n",
              "      <td>110</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>200</td>\n",
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              "      <td>1.0</td>\n",
              "      <td>0.75</td>\n",
              "      <td>36.187559</td>\n",
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              "<p>77 rows × 16 columns</p>\n",
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      "cell_type": "code",
      "source": [
        "#data frame to python list\n",
        "List1=df['calories'].values.tolist()\n",
        "List1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T_UX2n1srwtl",
        "outputId": "6a8f3406-f37b-49d6-a395-590446fa12ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[70,\n",
              " 120,\n",
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              " 110]"
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def mean_Rifat(l):\n",
        "  sum=0\n",
        "  for i in l:\n",
        "    sum+=i\n",
        "  length=len(l)\n",
        "  return sum/length"
      ],
      "metadata": {
        "id": "F8IAEoKFsb-N"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_Rifat(List1)"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RQhd0Vc7sc6V",
        "outputId": "dd03f8bb-2fb0-46c8-f894-3617901191d6"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "106.88311688311688"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def sort_Rifat(l):\n",
        "  for i in range(len(l)):\n",
        "    for j in range(len(l)):\n",
        "     if l[i]<l[j]:\n",
        "       l[i],l[j]=l[j],l[i]"
      ],
      "metadata": {
        "id": "ItNOFUkFshUW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def Median_Rifat(List1):\n",
        " sort_Rifat(List1)\n",
        " length=len(List1)\n",
        " if (length%2!=0):\n",
        "  num=int((length+1)/2)\n",
        "  print(List1[num])\n",
        " else:\n",
        "  num=int(((length/2)+((length/2)+1))/2)\n",
        "  print(List1[num])"
      ],
      "metadata": {
        "id": "gQUGXdDUtBWF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Median_Rifat(List1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1MRSbacZtI0N",
        "outputId": "02e29097-f618-4ce6-86ed-8c91f6afe049"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "110\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def variance_Rifat(l):\n",
        "  s=0\n",
        "  for i in range(len(l)):\n",
        "    s+=(l[i]-mean_Rifat(l))**2\n",
        "  s/=(len(l)-1)\n",
        "  return s"
      ],
      "metadata": {
        "id": "GgJ8NBX8tWp9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "variance_Rifat(List1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TGzKHJA_tclU",
        "outputId": "650423da-a6db-4464-d094-1338a3f775a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "379.630895420369"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    }
  ]
}