TRC_Case_Study.ipynb

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      "source": [
        "#TRC Data Analyst Case Study\n",
        "\n",
        "## Import TV Data"
      ],
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        "id": "Iu1FX6TQh9Yz"
      }
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        "import io\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import statsmodels.api as sm\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import sklearn\n",
        "from google.colab import files\n",
        "sns.set()\n",
        "\n",
        "#Upload TV Data\n",
        "uploaded = files.upload()"
      ],
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              "// See the License for the specific language governing permissions and\n",
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              "\n",
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          "name": "stdout",
          "text": [
            "Saving Copy of Example Data - Example Data.csv.csv to Copy of Example Data - Example Data.csv (2).csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Convert TV Data to Pandas Dataframe\n",
        "TV = pd.read_csv(io.BytesIO(uploaded.get('Copy of Example Data - Example Data.csv (2).csv')))\n",
        "TV.head()"
      ],
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              "     Brand                             Item Description Model Number TV type  \\\n",
              "0  Samsung  32\" QN32LS03T Widescreen LCD Ultra HDTV Ref    QN32LS03T     LCD   \n",
              "1  Samsung     50\" HG50Q60AAN Widescreen LCD Ultra HDTV   HG50Q60AAN     LCD   \n",
              "2  Samsung      55\" QN55Q90TD Widescreen LCD Ultra HDTV    QN55Q90TD     LCD   \n",
              "3  Samsung     55\" QN55QN700B Widescreen LCD Ultra HDTV   QN55QN700B     LCD   \n",
              "4  Samsung     58\" UN58TU690T Widescreen LCD Ultra HDTV   UN58TU690T     LCD   \n",
              "\n",
              "  Screen Size (Diag Inches) Standby Passive Power Watts On Mode Power Watts  \\\n",
              "0                        32                         0.5                  42   \n",
              "1                        50                         0.5                  54   \n",
              "2                        55                         0.5                 100   \n",
              "3                        55                         0.5                 115   \n",
              "4                        58                         0.5                  70   \n",
              "\n",
              "   Native Verticle Resolution  Screen area Energy Star Version Cluster  \\\n",
              "0                      1080.0        425.0      All Other (Suppressed)   \n",
              "1                      2160.0       1047.0      All Other (Suppressed)   \n",
              "2                      2160.0       1276.0      All Other (Suppressed)   \n",
              "3                      4320.0       1276.0      All Other (Suppressed)   \n",
              "4                      2160.0       1420.0      All Other (Suppressed)   \n",
              "\n",
              "  Energy Star Qualified (V8.0) ES flag       P.on       P.hr   P.on_max  \\\n",
              "0                        False   False  28.017350   0.000000  28.017350   \n",
              "1                         True   False  74.624074  24.874691  49.749383   \n",
              "2                        False   False  84.738695  28.246232  56.492464   \n",
              "3                        False   False  84.738695  28.246232  56.492464   \n",
              "4                         True   False  90.498128  30.166043  60.332085   \n",
              "\n",
              "   Annual power consumption (kWh)  \n",
              "0                        77.39095  \n",
              "1                        98.50255  \n",
              "2                       179.43035  \n",
              "3                       205.81985  \n",
              "4                       126.65135  "
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              "      <th>Item Description</th>\n",
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              "      <th>0</th>\n",
              "      <td>Samsung</td>\n",
              "      <td>32\" QN32LS03T Widescreen LCD Ultra HDTV Ref</td>\n",
              "      <td>QN32LS03T</td>\n",
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              "      <td>Samsung</td>\n",
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              "      <td>HG50Q60AAN</td>\n",
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              "    <tr>\n",
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              "      <td>Samsung</td>\n",
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              "      <td>Samsung</td>\n",
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              "      <td>QN55QN700B</td>\n",
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              "      <td>UN58TU690T</td>\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "\n",
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              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
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              "      quickchartButtonEl.style.display =\n",
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              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "TV",
              "summary": "{\n  \"name\": \"TV\",\n  \"rows\": 1509,\n  \"fields\": [\n    {\n      \"column\": \"Brand\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"Samsung\",\n          \"Haier\",\n          \"Proscan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Item Description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1413,\n        \"samples\": [\n          \"55\\\" QN55Q80TA Widescreen LCD Ultra HDTV\",\n          \"65\\\" OLED65C6P Widescreen LCD Ultra HDTV w/Glasses\",\n          \"83\\\" XR83A90J Widescreen LCD Ultra HDTV\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Model Number\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1385,\n        \"samples\": [\n          \"RLDED3258A\",\n          \"KD75X85J\",\n          \"32S325\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"TV type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Supressed\",\n          \"Other\",\n          \"LCD\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Screen Size (Diag Inches)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 43,\n        \"samples\": [\n          \"13\",\n          \"31\",\n          \"33\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Standby Passive Power Watts\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"0.5\",\n          \"Supressed\",\n          \"0.1\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"On Mode Power Watts\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 675,\n        \"samples\": [\n          \"152.5\",\n          \"120.1\",\n          \"24.1\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Native Verticle Resolution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 654.8498296018266,\n        \"min\": 720.0,\n        \"max\": 4320.0,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          2161.0,\n          769.0,\n          1080.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Screen area\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 737.7693161070246,\n        \"min\": 146.0,\n        \"max\": 4232.0,\n        \"num_unique_values\": 107,\n        \"samples\": [\n          1304.0,\n          772.0,\n          1544.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Energy Star Version Cluster\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 8,\n        \"samples\": [\n          \"Not Specified\",\n          \"Version 8.0\",\n          \"All Other (Suppressed)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Energy Star Qualified (V8.0)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ES flag\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"P.on\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 29.43958306788925,\n        \"min\": 17.21669778,\n        \"max\": 135.1593029,\n        \"num_unique_values\": 120,\n        \"samples\": [\n          128.2727974,\n          40.64885516\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"P.hr\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 13.246305367858424,\n        \"min\": 0.0,\n        \"max\": 45.05310097,\n        \"num_unique_values\": 77,\n        \"samples\": [\n          31.69394759,\n          31.64646005\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"P.on_max\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.930639690270645,\n        \"min\": 17.21669778,\n        \"max\": 90.10620194,\n        \"num_unique_values\": 107,\n        \"samples\": [\n          57.26355024,\n          40.68357594\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Annual power consumption (kWh)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 112.5289535758957,\n        \"min\": 0.0,\n        \"max\": 1036.92777,\n        \"num_unique_values\": 835,\n        \"samples\": [\n          165.71146,\n          189.82117\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Create new Dataframe that sorts by LCD and OLED Screen types"
      ],
      "metadata": {
        "id": "besj32YNKUX7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Sort by LCD and OLED Screen Types\n",
        "TV_Screen_Options = ['LCD', 'OLED']\n",
        "TV_df = TV.loc[TV['TV type'].isin(TV_Screen_Options)]\n",
        "TV_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "bjreFr9uIll5",
        "outputId": "fa776203-8bca-468c-f14c-7ab9ca9c0560"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Brand                             Item Description Model Number TV type  \\\n",
              "0  Samsung  32\" QN32LS03T Widescreen LCD Ultra HDTV Ref    QN32LS03T     LCD   \n",
              "1  Samsung     50\" HG50Q60AAN Widescreen LCD Ultra HDTV   HG50Q60AAN     LCD   \n",
              "2  Samsung      55\" QN55Q90TD Widescreen LCD Ultra HDTV    QN55Q90TD     LCD   \n",
              "3  Samsung     55\" QN55QN700B Widescreen LCD Ultra HDTV   QN55QN700B     LCD   \n",
              "4  Samsung     58\" UN58TU690T Widescreen LCD Ultra HDTV   UN58TU690T     LCD   \n",
              "\n",
              "  Screen Size (Diag Inches) Standby Passive Power Watts On Mode Power Watts  \\\n",
              "0                        32                         0.5                  42   \n",
              "1                        50                         0.5                  54   \n",
              "2                        55                         0.5                 100   \n",
              "3                        55                         0.5                 115   \n",
              "4                        58                         0.5                  70   \n",
              "\n",
              "   Native Verticle Resolution  Screen area Energy Star Version Cluster  \\\n",
              "0                      1080.0        425.0      All Other (Suppressed)   \n",
              "1                      2160.0       1047.0      All Other (Suppressed)   \n",
              "2                      2160.0       1276.0      All Other (Suppressed)   \n",
              "3                      4320.0       1276.0      All Other (Suppressed)   \n",
              "4                      2160.0       1420.0      All Other (Suppressed)   \n",
              "\n",
              "  Energy Star Qualified (V8.0) ES flag       P.on       P.hr   P.on_max  \\\n",
              "0                        False   False  28.017350   0.000000  28.017350   \n",
              "1                         True   False  74.624074  24.874691  49.749383   \n",
              "2                        False   False  84.738695  28.246232  56.492464   \n",
              "3                        False   False  84.738695  28.246232  56.492464   \n",
              "4                         True   False  90.498128  30.166043  60.332085   \n",
              "\n",
              "   Annual power consumption (kWh)  \n",
              "0                        77.39095  \n",
              "1                        98.50255  \n",
              "2                       179.43035  \n",
              "3                       205.81985  \n",
              "4                       126.65135  "
            ],
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              "      <th>Brand</th>\n",
              "      <th>Item Description</th>\n",
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              "      <th>Annual power consumption (kWh)</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Samsung</td>\n",
              "      <td>32\" QN32LS03T Widescreen LCD Ultra HDTV Ref</td>\n",
              "      <td>QN32LS03T</td>\n",
              "      <td>LCD</td>\n",
              "      <td>32</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Samsung</td>\n",
              "      <td>50\" HG50Q60AAN Widescreen LCD Ultra HDTV</td>\n",
              "      <td>HG50Q60AAN</td>\n",
              "      <td>LCD</td>\n",
              "      <td>50</td>\n",
              "      <td>0.5</td>\n",
              "      <td>54</td>\n",
              "      <td>2160.0</td>\n",
              "      <td>1047.0</td>\n",
              "      <td>All Other (Suppressed)</td>\n",
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              "      <td>74.624074</td>\n",
              "      <td>24.874691</td>\n",
              "      <td>49.749383</td>\n",
              "      <td>98.50255</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Samsung</td>\n",
              "      <td>55\" QN55Q90TD Widescreen LCD Ultra HDTV</td>\n",
              "      <td>QN55Q90TD</td>\n",
              "      <td>LCD</td>\n",
              "      <td>55</td>\n",
              "      <td>0.5</td>\n",
              "      <td>100</td>\n",
              "      <td>2160.0</td>\n",
              "      <td>1276.0</td>\n",
              "      <td>All Other (Suppressed)</td>\n",
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              "      <td>84.738695</td>\n",
              "      <td>28.246232</td>\n",
              "      <td>56.492464</td>\n",
              "      <td>179.43035</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Samsung</td>\n",
              "      <td>55\" QN55QN700B Widescreen LCD Ultra HDTV</td>\n",
              "      <td>QN55QN700B</td>\n",
              "      <td>LCD</td>\n",
              "      <td>55</td>\n",
              "      <td>0.5</td>\n",
              "      <td>115</td>\n",
              "      <td>4320.0</td>\n",
              "      <td>1276.0</td>\n",
              "      <td>All Other (Suppressed)</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>84.738695</td>\n",
              "      <td>28.246232</td>\n",
              "      <td>56.492464</td>\n",
              "      <td>205.81985</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Samsung</td>\n",
              "      <td>58\" UN58TU690T Widescreen LCD Ultra HDTV</td>\n",
              "      <td>UN58TU690T</td>\n",
              "      <td>LCD</td>\n",
              "      <td>58</td>\n",
              "      <td>0.5</td>\n",
              "      <td>70</td>\n",
              "      <td>2160.0</td>\n",
              "      <td>1420.0</td>\n",
              "      <td>All Other (Suppressed)</td>\n",
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              "      <td>90.498128</td>\n",
              "      <td>30.166043</td>\n",
              "      <td>60.332085</td>\n",
              "      <td>126.65135</td>\n",
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              "                                                    [key], {});\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "  </div>\n",
              "\n",
              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-79ab2290-a7d0-4c4c-80a8-04726851e984')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "     width=\"24px\">\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-79ab2290-a7d0-4c4c-80a8-04726851e984 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "TV_df",
              "summary": "{\n  \"name\": \"TV_df\",\n  \"rows\": 1335,\n  \"fields\": [\n    {\n      \"column\": \"Brand\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 17,\n        \"samples\": [\n          \"Samsung\",\n          \"LG\",\n          \"VIZIO\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Item Description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1289,\n        \"samples\": [\n          \"50\\\" D50-E1 Widescreen LCD Ultra HDTV\",\n          \"58\\\" UN58NU7100 Widescreen LCD Ultra HDTV\",\n          \"42\\\" WR42FX2002 Widescreen LCD HDTV\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Model Number\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1252,\n        \"samples\": [\n          \"UN50TU8000\",\n          \"65UJ7700\",\n          \"D55UN-E1\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"TV type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"OLED\",\n          \"LCD\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Screen Size (Diag Inches)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 36,\n        \"samples\": [\n          \"19\",\n          \"24\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Standby Passive Power Watts\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"0.5\",\n          \"0.3\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"On Mode Power Watts\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 674,\n        \"samples\": [\n          \"167\",\n          \"72.2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Native Verticle Resolution\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 654.6154007876873,\n        \"min\": 720.0,\n        \"max\": 4320.0,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          2161.0,\n          769.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Screen area\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 737.811772930954,\n        \"min\": 146.0,\n        \"max\": 4232.0,\n        \"num_unique_values\": 107,\n        \"samples\": [\n          1304.0,\n          660.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Energy Star Version Cluster\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 7,\n        \"samples\": [\n          \"All Other (Suppressed)\",\n          \"Not Specified\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Energy Star Qualified (V8.0)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ES flag\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"P.on\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 29.42059541027684,\n        \"min\": 17.21669778,\n        \"max\": 135.1593029,\n        \"num_unique_values\": 120,\n        \"samples\": [\n          117.677446,\n          94.93938015\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"P.hr\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 13.239269870274796,\n        \"min\": 0.0,\n        \"max\": 45.05310097,\n        \"num_unique_values\": 77,\n        \"samples\": [\n          31.69394759,\n          31.64646005\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"P.on_max\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16.920592386793565,\n        \"min\": 17.21669778,\n        \"max\": 90.10620194,\n        \"num_unique_values\": 107,\n        \"samples\": [\n          57.26355024,\n          36.72428001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Annual power consumption (kWh)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.95109617180299,\n        \"min\": 21.97665,\n        \"max\": 1036.92777,\n        \"num_unique_values\": 833,\n        \"samples\": [\n          164.83546,\n          189.82117\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## OLS Regression Calculations\n",
        "### Show OLS Regression Parameters"
      ],
      "metadata": {
        "id": "HEhqBlix6pin"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Creating x and y variables\n",
        "y = TV_df['Annual power consumption (kWh)']\n",
        "x = TV_df['Screen Size (Diag Inches)']\n",
        "\n",
        "#Convert x variable to a Float\n",
        "x = np.asarray(x, dtype='float64')\n",
        "\n",
        "#Fitting Linear Regression Model and printing out the parameters\n",
        "TV_LinReg = sm.OLS(y, sm.add_constant(x))\n",
        "TV_results = TV_LinReg.fit()\n",
        "print(TV_results.params)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LmOH1AbQEGHB",
        "outputId": "cf7a1c09-9665-481f-de97-d57d59ade04e"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "const   -120.090473\n",
            "x1         5.129827\n",
            "dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Show OLS Regression Summary"
      ],
      "metadata": {
        "id": "0OsmUU3YK_8Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Displaying OLS Regression Summary\n",
        "print(TV_results.summary())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c2fSigUcKB7x",
        "outputId": "b268c081-9a35-4a1b-85b5-cf66ad9c544d"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                                  OLS Regression Results                                  \n",
            "==========================================================================================\n",
            "Dep. Variable:     Annual power consumption (kWh)   R-squared:                       0.525\n",
            "Model:                                        OLS   Adj. R-squared:                  0.524\n",
            "Method:                             Least Squares   F-statistic:                     1471.\n",
            "Date:                            Sat, 09 Nov 2024   Prob (F-statistic):          1.53e-217\n",
            "Time:                                    01:04:46   Log-Likelihood:                -7634.9\n",
            "No. Observations:                            1335   AIC:                         1.527e+04\n",
            "Df Residuals:                                1333   BIC:                         1.528e+04\n",
            "Df Model:                                       1                                         \n",
            "Covariance Type:                        nonrobust                                         \n",
            "==============================================================================\n",
            "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "const       -120.0905      8.032    -14.951      0.000    -135.848    -104.333\n",
            "x1             5.1298      0.134     38.360      0.000       4.867       5.392\n",
            "==============================================================================\n",
            "Omnibus:                      737.009   Durbin-Watson:                   1.647\n",
            "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             9382.282\n",
            "Skew:                           2.290   Prob(JB):                         0.00\n",
            "Kurtosis:                      15.153   Cond. No.                         239.\n",
            "==============================================================================\n",
            "\n",
            "Notes:\n",
            "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Crete Linear Regression Plot"
      ],
      "metadata": {
        "id": "GdwzDsz3LI6x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Plotting the Linear Regression model\n",
        "sns.regplot(x= x, y= y, data=TV_df).set(title='Regression Plot between TV Screen Size & Annual Power Consumption', xlabel='TV Screen Size (Inches)', ylabel='Annual Power Consumption (kwh)')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 532
        },
        "id": "CqkYzAPhLPdb",
        "outputId": "f881dfd0-45d3-49e8-cd2b-0f1ea64de8e5"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0.5, 1.0, 'Regression Plot between TV Screen Size & Annual Power Consumption'),\n",
              " Text(0.5, 0, 'TV Screen Size (Inches)'),\n",
              " Text(0, 0.5, 'Annual Power Consumption (kwh)')]"
            ]
          },
          "metadata": {},
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Box Plot Between TV Screen Type and Annual Power Consumption\n"
      ],
      "metadata": {
        "id": "H-PrKnrDSqY8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Plotting box plot between TV Screen Type and Annual Power Consumption\n",
        "ns.boxplot(x='TV type', y='Annual power consumption (kWh)', data=TV_df)\n",
        "plt.title(\"Boxplot between TV Screen Type & Annual Power Consumption\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 480
        },
        "id": "mzU0WtYjVgDV",
        "outputId": "e1fa016c-756c-4215-8b6c-f69e14759b17"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}