Apache_JMeter.ipynb

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      "source": [
        "import pandas as pd\n",
        "import matplotlib as plt\n",
        "import seaborn as sns"
      ]
    },
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      "source": [
        "faceModcs = pd.read_csv('/content/drive/MyDrive/MESTRADO ADS/facebookModcs.csv',sep=',')\n",
        "faceModcsConn = pd.read_csv('/content/drive/MyDrive/MESTRADO ADS/facemodcsconnection.csv',sep=',')\n"
      ],
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      "outputs": []
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        "faceModcs.head()"
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              "   MoDCS  Facebook\n",
              "0   1102       338\n",
              "1   1145       239\n",
              "2   1105       258\n",
              "3   1121       255\n",
              "4   1088       250"
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              "   MoDCS  Facebook\n",
              "0     22        91\n",
              "1     17        31\n",
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              "4     18        31"
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              "<Figure size 432x288 with 1 Axes>"
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "faceModcsConn.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "Iti-Ubv36Hg4",
        "outputId": "062bf915-e0ff-47ed-d2e2-e7ef3187f03a"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   MoDCS  Facebook\n",
              "0     22        91\n",
              "1     17        31\n",
              "2     17        31\n",
              "3     17        31\n",
              "4     18        31"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1a1acf30-9adb-4041-a12c-a2f6731b4255\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>MoDCS</th>\n",
              "      <th>Facebook</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>22</td>\n",
              "      <td>91</td>\n",
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              "      <th>1</th>\n",
              "      <td>17</td>\n",
              "      <td>31</td>\n",
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              "      <th>2</th>\n",
              "      <td>17</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>17</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>18</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1a1acf30-9adb-4041-a12c-a2f6731b4255')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "  </svg>\n",
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              "      \n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-1a1acf30-9adb-4041-a12c-a2f6731b4255 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-1a1acf30-9adb-4041-a12c-a2f6731b4255');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "faceModcsConn.plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "K7Pv-r0s6L4X",
        "outputId": "4bd50308-bd8b-4e3c-e013-5faf27e6acdc"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f7af802b0d0>"
            ]
          },
          "metadata": {},
          "execution_count": 20
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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AHAL+iAn+C5RS9wNHgDs9U0Q7yYELIYQTtwK41nobEOHiq2G1W5wKyAsdhBDCiXXuxLR5AUpq4EIIYWedAA6mFi45cCGEAKwWwG0+0gpFCCHsrBXAvbylBi6EEHbWCuA2H8mBCyGEnbUCuOTAhRDCwVoBXHLgQgjhYK0ALjlwIYRwsFYAlxy4EEI4WCuAe/nInZhCCGFnrQBu85YauBBC2FkrgEsrFCGEcLBWAJdWKEII4WCtAC6tUIQQwsFiAbyB5MCFEMLOWgHcJjlwIYQoYq0ALikUIYRwcOuNPEqpOCAdKADytdYRSqnmwHwgFIgD7tRan/FMMe3kRh4hhHCoSg18iNY6XGtd9Gq1Z4BlWusuwDJ7t2dJM0IhhHCoSQplJDDb/v9sYFTNi1MJaUYohBAO7gZwDfyilIpWSk2y9wvWWp+0/38KCHY1olJqklIqSikVlZiYWLPSSg5cCCEc3MqBA5drrY8rpVoBS5VSe0t+qbXWSintakSt9QxgBkBERITLYdwmOXAhhHBwqwautT5u/zwNfAMMBBKUUm0A7J+nPVVIB3mYlRBCOFQawJVS/kqpJkX/A9cCu4DvgPH2wcYDizxVSAd5mJUQQji4k0IJBr5RShUN/7nWeolSajOwQCl1P3AEuNNzxbSTVihCCOFQaQDXWh8C+rronwwM80ShymXzAV0AWoM5oAghxEXLendigtTChRACqwVwm4/5lDy4EEJYLIB72QO41MCFEMJiAdxRA5emhEIIYa0ALjlwIYRwsFYAlxy4EEI4WCuASw5cCCEcrBXAbfYUiuTAhRDCYgFcauBCCOFgrQAuOXAhhHCwVgB31MAlhSKEENYM4FIDF0IIiwVwm+TAhRCiiLUCuNTAhRDCwVoB3CZ3YgohRBFrBXBpRiiEEA7WCuDSjFAIIRzcDuBKKS+l1Fal1GJ7d5hSaqNSKlYpNV8p1cBzxbSTZoRCCOFQlRr4o0BMie7XgDe11p2BM8D9tVkwlxy30ksNXAgh3ArgSqkQ4EbgI3u3AoYCX9kHmQ2M8kQBnUgOXAghHNytgf8P+AtQaO9uAaRqrYtyGfFAO1cjKqUmKaWilFJRiYmJNSqsvNBBCCGKVRrAlVI3Aae11tHVmYHWeobWOkJrHREUFFSdSRSTFzoIIYSDtxvDDAZGKKWGA75AAPAW0FQp5W2vhYcAxz1XTDtphSKEEA6V1sC11s9qrUO01qHAGGC51vpuYAVwu32w8cAij5WyiOTAhRDCoSbtwJ8GpiilYjE58Zm1U6QKSA5cVCT9FPz6IuTn1nVJhDgv3EmhOGitVwIr7f8fAgbWfpEqYLOBskkNXLi2+1tY8yZ0+D1ccm1dl0YIj7PWnZhgauGSAxeuJMeaz/1L6rYcQpwn1gvgXj5yJ6ZwzRHAfwat67YsQpwH1gvgNm+pgQvXkg+Ctx+kxcPpPXVdGiE8znoB3MtHcuCirLxsOHsM+o4x3ZJGERcB6wVwyYELV84cBjR0HAxtwk0aRYh6znoB3MtbcuCirKL8d4vfwSXXw7FNkJlct2USwsOsF8ClBi5ccQrg1wIaYn+t0yIJ4WnWC+BeDSQHLspKjgX/VuAbCG36mf8lDy7qOQsGcG+5E1OUlXwQWnQ2/9ts0OVaiF0mB3tRr1kvgNukFYpwITnWpE+KdL0ecs7C4VV1VyYhPMx6AdxLcuCilOyzkJnoHMC7XAt+zWDLnLorlxAeZr0AfqHUwLd8CjsWnJ955WXBipfhbPz5mZ/VJB80n0UpFADvhtB3LOz9ETJq+CIRUSw7DZb/CzJO13VJBFYM4F7edR/AT+6A7/8MCx+AJc9CYYFn57fmTVj1Gnz/qNwi7oqrAA7Qf7w5W9s+7/yXqb5a8TKs/g8seaauSyKwYgCv62aEWsOPT5nT88iJsOF9mDcWctI9M7+Uw7Dmf9CkjWkWt+8n5+8LC12PVx6tqzdObSjIN+up6K+2ppscCyhoFubcv1U3aH+pSaPU1ry0rtm08rKc10HRX1626+Gruq0KC11Pv/RfefdSVDS/hD2waYbZF3d9DYd/q1rZqqu8MlV13VR1+hZQpcfJXhDq+mFWOxbAsQ0w4h3ofy+06mEC+szr4K750LR97c7v5+fM818m/Ayf3wk/Pwu/Gwo+vhC3BhaMh87D4Oa3Tb+KpCfA/HvMD3js59C8U+Xz3/a5OcsY+S50v7n6y3FsE8wfBxmnivv9bijc/rE5GNZEcqxZ766Wv/94WPQwHFkHoYNrNp/Uo2b9NWkLY+eBUlUbf/t8UxZXrahs3nDNP+CyycXTjVkM3z4M4WPh2n8Xv1KwPCmHYN5dkBhTeVkC2sHoz6Bdf9NdkGdq1Tu/hFumQ9cbnIfXGn76C/gGwMRl8PH1pvvB3yovV3XlnoNvH4Kj6+HOT6HDpaZ/YQEs/bs5MI94B3rW4H3q8dFmm7brb5a7YePaKft5ovR5PCWPiIjQUVFRNZvI/HGQtB8mb6ydQlVFTjq8EwEBbc1ObLOfwBxcDgvuM3nXsfMgJKJ25nfgV5h7G1zzIlz+OBxaCXNGwpDnIaANfP8Y+AdB+gkIGQhj5kLjVq6ndWoXfD4aslJMW3plMz/gioLauRR4p79Z7sICU47Bj1Y9cO34EhZNNustYoIZP+sMrH0bmoeZA587B5PyTL8KGjWHcd+U/S43E/7bzQSkW2dUfx7HNsMXY025C/PhjtlVCxznUuCdAdCsI/S6rez3cWth/08w4D4YPhXWv2deThHQzjycq/MfzMHON8D19OPWmkCEht8/YrZxeXQhbP7IXBu4dTqEXQVf3geHVtjndwKu+zcMerh4W+9aCF/9EW58AyLvh5jvzfyufw0G/Z/768FdaSdh3hg4uR2atDbrb+R7Zjt+PdGsq4AQs26G/g2ueKLq++WuheYA4dsUMk9DcE8YOx8CXb6fvU4ppaK11mUCi/UC+FcTTCC7/HH3x/ENhD5jwLvETp2fA9u/gJw0023zgd63g3/L4mG0hr2L4Uyc6T620ey4E5eVDdKn95oackYC/P7P5f/QijQOhl63Fx8EwFwg2jEf8u2n01EfAwoeXm8ODgAL7oW9P5gg0mkI3DHLNJVb+KAJ5gMnmuBcUl4WrH0LGjaBsV+Yz8/vhDNHTA0mfKzrMi5+HKJnw8RfYd07sHshhN8DN71Z8bos6UycCRYdB5sDRqPmxd/FrYX5d5tlrOxgknTA/nwT+/4a2B56jDT/v9LeLMPw/5SzHFNg21yYEuM8/4rsWwLJB8z/2Wlm/QW0gTHzYOEkE8j/tAka+JthTu+F2KXF4zcLg243FgeVH54w2/PB36B1r7LzKyyE5S/BmjeKA1PPW2HU+yaH/8OTENTVXJgtHaiKDobNOsJdC5xb45QnIxG+uAviN5mgnZEAN/3PHFy+mWT28953Qps+ZvgN06BRC5i0Emxe5rfx6S1wfAtc+WTVg2dFdCFs+MC0Lrp9pkmDzR8HR9aYdZN+Em54DfqNg+8egZ0LoMco1xUnr4bQ5w7nszytYfVUWPEvaD/IVHxObDMHsQb+5uy03QDn6RyPNmdxRYJ7mjPIklKPwYkt0H2E8/o4lwIbP4CrnjbrrhqqHcCVUr7AaqAhJuXyldb6BaVUGPAF5nVq0cA4rXWF77KqlQC+/N+w+vWqjxd6Bdw5x/yAM5NN4Di63nmYph3MD6BVd3NK+eOTED3LeZhBD8P1r7ieR2aSSWkcWeNembqPMKdtDRqZYDpvjPNjUL39zM5UckdJPQYfDoUeI+D6V4vfE3p8i6kRpZXzbum2/c2OGtDWdGedMQeDw6tN7WXI884Hk5PbTc320gfNj6WwEFa9ai6mdrwcRn9aYl3eA0fXuZ4v2IP+G8UHoZKSD5ozgzNx5R9M9v9ian+5GWWnO+RZeLNnxTXBhN3wwRUQ1K3yNFdhAfzyvLm2UVLHy83+49/C/JA/uQGufAqGPm9SHQsfgLxzzuNETIAbXofEvTD9SnPNpLyDTJFtn5uU3KCH4epnS5zlrTCVl6wU1+N1GgJ3fFK1dFRetrkYH7vMVATCrrCvA/vBZO3/TDAFaNAExi2E9iVewpW4Hz6+rvwy1URgB7Pvt+5tuvNz4ccnzIHlto+g8zWmv9bmourKV0GX05igRefiA1t+jgn6O+ZDn9FmnyvaLxP2wLzR5uB2ywfFZ1jRs+GHKWVTX1f+pXgbHd1gDojnkk1lccTbZrpJsaaydPYY/HEJhJQ6MLipJgFcAf5a6wyllA+wBngUmAIs1Fp/oZT6ANiutZ5W0bRqJYBD1S8Y7v3BbLTA9nDdy7DkaXOKNvI9c8MHwOkYE4jysszKj/rE1Gwvn2Jq+0oBqvIcmdZlA40r0bPgl79B23ATCL5/1Oykd3xsahxgzgpc5XULC52DbZGCfMjPcj2/Bo3L1pIK8kzNcMtsU5sd9YE5mGhtcpzJsfBINPg1LR5nxwKTDgkMgeteMXnTtBMmR146bwrmbKCollqerDPmwHd4lfPBRGvYON3k/YN72QNoS9N//XvmgNIs1AT/u7+GLteUP4/YZaaG5e1rzkJc/ZBy0u2n50vg0ofMwaHobKb0+vt6Iuz5zhzg1r1jcqi3f2IOalrDb/81AbDT1WafcqxLNwJsuds3r/jsrDRX29dd5c0vL6s4aHk1cH0Azs+FgpzqzbciPo1c11bdKWtJJ7aafQttrhOtf89cwxryvOszh5JnJkP/BtmpZvv+bhiMmmZ+H4UF8MtzsPUz6HmL+e6HKeY30XU4rH8XOlxmDsLfPWKWY/Rc6HhZtVdHraRQlFKNMAH8IeAHoLXWOl8pdRnwotb6uorGr7UAXh1H1pta97lkk2oYMw/aRzoPczYePh8DCTtN8BzxNoTf5bky7f3RBIK8TBOI7voSgi7x3PxcKQqGvzxvgqNvoAkUqUeKL9SWdnSjvbaRZF+XnzvXzKqj5BlPYHsTLArzTXDudpPJX5c+EOz40lwULMiFP28z+fSKFKW50k+as63SslLNwWT466a2XJG0E+Z6SF6m+RGPmgY+fs7DbP3MHJgL8+Hmt0x+W5x/KYfMWV7SfnMAHzUNet1a/vB52aaSsusr0x35gP1st8TFWq1NWu3XFzGPMS5xVrrzK3PxuSAHWna1X+OpZN+sRI0CuFLKC5Mm6Qy8B/wH2KC17mz/vj3wk9a6THJPKTUJmATQoUOHAUeOHKnJctRMymFTo7vsYdc/YDC1sNVTzSNJa3DEdNupnSZ/fPkUc3peVw4sNeUoyjG36GLP2ZXT0vRMnMlTDnrI5F5rg9bmbODw6uJ+rfuYawrllSM+ygzvOEuqRGYSrHzFBOrSlA363WNqze7Y+4M56Ec+UH75jqwz5bvyqWrnP0UtyEqF36aag23p/LYrRWd/DRubfaI8+382tfzLpzhfF4qPhj3fwBVPOp/BVlNt1cCbAt8AfwNmuRPAS6rTGrgQQlhUeQG8SjfyaK1TgRXAZUBTpVTROUUIUM7VMyGEEJ5QaQBXSgXZa94opfyAPwAxmEB+u32w8cAiTxVSCCFEWe7UwNsAK5RSO4DNwFKt9WLgaWCKUioW05RwpueKKUTd+So6nrWxSXVdDCHKqPQeWK31DqCfi/6HgBo2PRDiwpadV8Dz3+4kMrQ5gzu3rHwEIc4j6z3MSojzaP2hZLLzCjmclFnXRRGiDAngQlRgeYx57vXx1Cyy8zz82GAhqkgCuBDl0FqzfO9pGnrb0BqOppyrfCQhziMJ4EKUY19COsdTs7htQAgAhxIljSIuLBLAhSjH8r0mfTJhsLkNWvLg4kIjAVyIciyPOU2vdgF0btWYoCYNOZzkxkPKhDiPJIAL4cKZzFy2HD3D0G7BAIS19JcauLjgSAAXwoVV+xMp1DC0m3nDUVgLfw4nyUVMcWGRAC6EC8v2nqZl4wb0aRcIQFiQP0kZOaRl1+ELtYUoRQK4EKV8u/U4P+86xTXdg7HZzCNqw1qaZ5HHSRpFXEAkgAthp7XmjaX7eWz+NsI7NOXp67s5vutkD+CSBxcXkkqfhSLExeIvX+3gy+h4bh8Qwsu39KaBd3H9pn3zRiglbcHFhUUCuBDA2XN5fBkdzz2DOvDSyF6oUm/38fXxol1TP19+fO4AABdjSURBVKmBiwuKJVIohYWalMwKX3gvRI3sP21elD2sW3CZ4F1EmhKKC40lAvj4TzYxaY68ik14zr5TJoB3CW5c7jCdWvoTl5RJVV5DKIQnWSKAd28TwI74s/I0OOExBxLS8W9g0iTlCWvpT3pOPkkZcjYoLgyWCOARHZuRW1DIjvizdV0UUUUr950m9dyFH/D2J2TQJbhJuekTgNBSLVFiTqax/VhqmeES03OYtfYwM9eYvyW7Tnmm0OKiV+lFTPsb5+cAwYAGZmit31JKNQfmA6FAHHCn1vqMJwoZEdocgM1xKQwMa+6JWQgPOJ2WzX2fbGbC4DD+fnOPui5OhQ6cTnfcdVmeTi1NeuVwUgbHU8/x9Fc78fFSrHjyaloF+ALmes2Dn0ax5ahzYN/412EE24cRora4UwPPB57QWvcABgGTlVI9gGeAZVrrLsAye7dHNPdvQOdWjdkcl+KpWQgP2BxnjufL9ybUcUkqlpyRQ1JGLpcEN6lwuHbN/PDxUry/8iCPz99O75BA8go0r/601zHMwq3H2XI0lX/f0ovtL1zLvAcGARAV55G6jbjIVRrAtdYntdZb7P+nY95I3w4YCcy2DzYbGOWpQgJEhjYn+sgZCgrlApJVFB1w45LPcSjxwn2S3/4EU7bKAriXTdGxhT9Hks9xZ0QI8x4YxANXhrFw63Gij6SQlp3Hqz/tJbx9U8ZGdiDQz4eI0Gb4+Xi5XflIyczlno82sj8hvcbLJeq/KuXAlVKhmBccbwSCtdYn7V+dwqRYXI0zSSkVpZSKSkxMrHZBI0ObkZ6d72gtIC58m+NS6BRk8sZFz9a+EB2wNyGsLIADPHltV16/rQ+v3daHBt42Jg/pTJtAX/6+aDdvLt1PcmYO/xzZ03ELvo+Xjf4dm7odwBdEHWNNbBIfrj5U/QUSFw23A7hSqjHwNfCY1jqt5HfatKtyWTXWWs/QWkdorSOCgoKqXdBIex486oikUWoiK7eAs1mefyBTenYeMSfTuLlPWy4JbsyymAs3gO9PSKeJrzfBAQ0rHfb6Xq25M7K942Jnowbe/HV4d3afSOOTtXGMjmhPn5CmTuNEdGxOzMk00it5EJbWmvmbjwGweMfJSocXtePU2Wyycmu3hVt+QSHHzsMr+NwK4EopH0zwnqu1XmjvnaCUamP/vg3g0V9oSDM/Wgf4sumwBPDqKijUjJ6xnpve+a3Wd9jSthxNpVDDwLDmDO0WzOa4lAv2SX77EzLoWkkLlIrc1KcNv/9dCwL9fHjquq5lvh8Y1pxCTZkLm6VtOJTC4aRM7vt9KFl5BSzadqJa5RHuO3U2m2veWMU/F++p1enOXHOYq/6zgh3xFW/zmqo0gCuzV88EYrTWb5T46jtgvP3/8cCi2i+eUzmIDGvO5rgUuZGimuZtOsqO+LMcS8li2qqDHp3X5sMpeNkU4e2bMqx7K/ILNb/tT/LoPKtDa83+hHS6uJE+KY9Sio/vi2TplCtp0bhsLT68fVO8bIrNlVQ+5m8+ShNfb56+vhvd2wTwxeaj1S6TcM8rP8WQkZPPom3HycjJr5VpFhZq5m48SqGGvy/aTaEHr9u5UwMfDIwDhiqlttn/hgOvAn9QSh0ArrF3e1RkaDMS0nKIP5NV4XA748/y6k973a7xnT2Xxz+/38Pj87fx+PxtPLFgO9FHarfVwLqDSbyxdH+Zm5H2nkrjlR9jOFONRwVk5xXwxi/72HAoudJhz2TmMvWXfQzq1Jyb+7blg1UHOZrsuVO8zXEp9GobgH9Db/q1b0qgn88FmQdPzMgh9Vwel1RwB6Y7fH28aNXEdTNB/4be9GobUGEePPVcLj/uOsUt/drh18CLMZHt2XU8jV3Hy977kJtfyNvLDrBqf/WvKVnFjvhUpq086JFK28ZDySzadoJh3VpxLreA76pxxrPtWCqz18U59Vt/KJmjKecY1q0V246l8vWW+FoqcVnutEJZo7VWWus+Wutw+9+PWutkrfUwrXUXrfU1WmuP5zYiS7QHL89PO09yx/R1fLDqILe9v67SIBWXlMkt769lzvo4oo+cIfrIGX6NSWDsjA0srKUV/+mGI4ybuYm3lx3grg83kJSRA5jmdbe9v47pqw9xy/trq9RSIzE9hzEzNvD28lju+Wgj8zZVXFv779J9pGfn848RvXhueHe8bYqXfqjd08YiOfkFbDuW6mi/7+1l4+quQazcd/qCa0V0wM0WKDUVEdqcbcdSycl3nbr6ZutxcvMLGRPZAYBR4e1o6G0rUws/k5nLuJkbeWPpfv74ySZmrjlcr89IX/4xhteW7OXn3bXbFDW/oJAXvttNu6Z+vHtXf7q1blLlM56s3AIe/iyaF77bzcp9xZWTeZuOEujnw3t392dAx2a8tsT9ymRVWeJOzCKXBDehia83Gw4lk51X4PSXlVvA+ytjeWjuFrq3CeC9u/qTkJbNqPfXsulwSpnhs/MKWHcwiVHvr+XMuVw+f2AQq/8yhNV/GcKqp66mf8emTFmwnak/73N5CqS1dvnD0Vo7pn8uN59/fL+bv327iyu7tGTqHX3ZfSKNUe+tZerP+5g4O4qwIH+m3d2ftOx8bnl/HesOuk4z5BcUOqa7+8RZRr23lr2n0njjzr4M7tySZxfu5N8/7OFcbn6Z5dx2LJW5G48yblBHurZuQutAX/40tDNL9ySwLCbBMVxVg2teiTLl5hc6+u86nkZOfqHjgAvm1WTJmblExRVvi8qUXJcV/eUXFLo1LVeKmut5OoBHhjYnJ7+QXcfTynynteaLTcfoGxJIj7YBAAQ28uHG3m1YtPUEqedyyc4r4EBCOre8v5atR1N57bbe/KFHMC8t3sPz3+4iz8U6KG8fBWq0LksquV+Wd3Aqrwylt2/p4Q4nZbLhkEnFvbR4T60+SuPzTUfZeyqd52/s7jjj2RF/lt0nXN/t7Wpdvr8ylhNnswlq0pB/fL+HnPwCUjJz+WV3Arf0a4evjxf/GNGT5Mxc/rf0QK2VvSRLPU7Wy6aIDG3Ogqh4FkS5rh2P6NuW12/vg6+PF93bNGHCrM3cOX19udP8XZA/H98XSccW/o5+TRs1YM6ES3n+2528uyKWw8mZ/PeOvvj6eAFwJDmTSXOiCWzkw7S7+zvynmcyc5n8+RbWHXROaUwYHMZzN3bHy6bo0qoxE+dE8e6KWK7rGcybo8Np1MCbnm0DuX/2Zu6duYmvH/o9fdsXt2SIPZ3OndM3OD2RMTigIV8++Ht6hwQyom9bXlq8hw9/O8yHvx12uZwt/Bvw+B8ucXTff3kYX0bFc//s4oeEtQn0Zdo9Awhv39TVJBy01sxaF8crP+4l1/6D97YpHh3WhT8N7ew4Q4oIbeYY56pLgvCyKUbP2ODoN6RrEG+N7UeAr0+ZeZzJzOVP87awNrby9FCgnw9vjQnn6q6u76Sct+koL/8Qw5+GdmbSlZ2cLlbuT0inWSMfWjZuUOl8aqJoXWyOS2FAx2ZO381aF8e+hHReubW3U/8xAzuwcOtxwv+51NGvhX8DPn/gUiJCm3PHgPa8/vM+Plh1kCPJ53jv7v4E+pl1eTotm//7LJqc/EKmjxtASLNGAGTm5PPEgu0s2e369v4AX2/eGtOPIZXclQrw486TPPXldjLtF8SVgnsu7cjfb+6Bj5epG+45kcakT6Po1jqA/40Jp3FDE3JOns3iwU+jnR6PcVmnFnw28VK87E0w528+hpdN8cadfXn0i21MW3nQaR+urg2HkvnPkn0M7tyC63u1BmBUv3a8/NNevth0jJdGBToNfzo9m4c+20JWbgEz7jXr8khyJtNXH2JUeFtu6R/C+I838fGaOHy8FLkFhYwZ2B6AXu0CGTuwA7PXxzFmYPtaryio83n6FRERoaOiavZUwdjTGSzd4/p0qm1TX0b0bev0A009l8vCLcfJyS9bs/D1sXFr/xDHTl+a1poZqw/x6pK99Alpyof3DiAu6RwPfhpFoTa1mFYBDfl4fCQ2m2LCrM2cPJvNA1eE0bihmWbnVo35Qw/nJvKnzmaz8XAyN/dp62gvDCYXf82bq2gb6Ms3Dw/GZlNorbln5kZ2xp/l/67+HQqFt00xIrxtmVuzf959qtwXDgzpFkS31gFO/Y4mn+PHXSfRGjSazzceJTE9hzdHhzO8dxuX08kvKOQf3+/h0w1HuLprEJeGtQBg+7FUluw+xajwtiRn5nI8NYvlT1ztNO4vu09x0F6+1KxcZv52mLCW5gDavnkjx3CHEjOYMGszJ1KzmXhFGE1cBPiSvtt+gn2n0njh5p6M/32oo39BoebVn2L48LfDtA7w5VRaNqMj2vPSqF6OlzXcNm0dXjbFggcvq3AetWHof1fSqaU/H42PBMy6fGnxHmavP8I13YN57+5+NPT2cgyvtear6HjHw7O8bDC8dxtHMC6yYPMx/vrNTjq2aMTH90WSmVPAxNmbSc3Kw8umaOjtxYf3DqB1oC/3z4pi76k0JgwOc3nBdfGOE8ScTOPvN/XgvsFhLpdDa837Kw/yn5/30a9DU67tYYJgXFIm86OOcUWXlrx7V382H07hz19spVEDL86cy6NLq8bMvC+S5IwcJs6O4lxuAROvCKOhtxenzmYxe/0R/n1LL+6+tCN5BYVc9spy+nVoyof3RvCnz7ewdE8Cv065ymlfqaoFUcd47puddGzhz6w/Rjqty8e+2MqyvafZ9Ndr8GtgtkPMyTQmzo4iJTMXby9FQ28bM+6N4P0Vsaw/mMzyJ68mOMCXB+ZEsTY2iRaNG9DCvyHfTh7smO6ZzFw+WXuYB6/6Hf4Nq1dnVkpFa60jyvS3WgCvCz/vPsVjX2yjia83Z87l0r6Z+aGkZuUxcXYUOXkFKGVu2phx7wAGdKz+81oWbolnyoLtvH5bH+6MbM9PO0/y0Nwt/HNkT+69LLT2FsqFpIwcHvw0mugjZ/jj4FDaNyv7Q1m+9zRrYpN48KpOPH1dN8cBSGvNu8tj+e/S/QCMjmjPa7f3qXB+6w4m8dBnW/CyKR68shM+XjZy8gv5YNVBvG2K6eMGOPLoFcnMyefRL7bxa0wCtw8IoUcbc6BaE5vE8r2nGX9ZR56/qQdvLzvAO8tjGdSpuSPovLF0P6P6teVfo3pXNIta8fRXO/hp10keu8bUIlfsO81vB5J44Iownrmhu6PmWR3rDybz0NxoFJCTX0iArw8z74ugobeNP87azOm0HJr4+pCdV8C7d/Ur92wlMyefx+ZvY+meBG7rH0LPtgFlhtly9AyLd5xkVHhbXr2tj+PMFIoPJq2aNORkWja92wXy0b0R7EtI5+G5W2jobSMjJ5+WjRsyc3wkXVubGqnWmjEzNrAvIZ0VT1zNxsPJ/N9nW/j4vgiGdgvm5Nkshk5dRd/2gY5tVx6/Bl6MDG9LowbFwbKwUDvOVooOMKUrbhsOJTNmxgbGDuxAl1aNycor4P0VsTTx9eGj8RH4+njZK2lZ5BVonrmhG/931e8AUxm65s1V5OYX8tptvRltv5ZRWySA19Cu42eZNCeKTkGNee+u/gQ2Mhv/eGoWD8yOolBrPrw3oka1AzA78h0frOdwUiY/PnoFt76/jia+3ix+5HK8vTx/ySI7r4C/LtzJwq3HXX7fwNvGSyN7lruDLt5xgr8u3On2afihxAwmzolyOnPoGtyEj8ZXbV0WFGpeW7KXD387RNEu7eOleP7GHk618m+2xvPM1zudzsjeHtuPEX3buj2v6vp59yke/DTa0d3Ay8Y/RvZk7MDa+bEfTspk4uzNNPb1Yca4AY4ztOSMHB6au4VTZ7P58N4IR9AsT2Gh5rWf9zJjdfG6LMmm4LFrLuGRoZ1dtp1ffzCZyZ9v4bJOLZh6R19HbfZAQjoPzImiZeOGfDBuAC1LnQHsPZXGjW+vYezA9hxLyWLfqXTWPjPUcWD7ZO1h/rl4j8sylda7XSAfjY8gOMCXc7n5PD5/Gz/vTuDuSzvw4oiejhRPSVprbnx7DXtOFl+n6BsSyPRxEbQONOsyJTOXyXO3cDYrj28nD3Z67d57K2KZtS6OlU9eXe2adnkkgNeCgkKNTVFmpy26yGmrQQ2qpF3Hz3Lzu2toHeDLybPZzJ80iEs7taiVabsrPTuPQhfXsxr62JxqXK5orat0U0xBoSYju7gNbhNf72qvy8ycfPILzPZo4G1zBI+SsvMKyMkzC2ezUWmKpjZl5ORTYC+fO+uyqsrbR7XWFGqqVMsvuS5L8vFWTrVbV/ILCl1WOMorX5EXv9vNnPVxaOCRIZ2Zcq3zjVHl7ZclbTiczOPztxHg68Mrt/bmv0v3sedEGs/f2IM/Dg6tcN/MLygkM6f4YmmAn7fL4QsLtct9tKBQ1+hMqjwSwC3m+W938tmGo4wMb8tbY/rVdXGEOC/OZuUxdOpKUs7l8ttfhpTJ97trz4k0Js7ezImz2fg38OKdu/oxtJvLxzVZQnkB3FKtUC4mT13bjQBfH/5YzoUkIeqjQD8f3hwdzoHTGdUO3gA92gbw7eTBvL/yIKMj29O9Tdlcfn0gNXAhhLjAlVcDt9SNPEIIIYpJABdCCIuSAC6EEBYlAVwIISxKArgQQliUBHAhhLAoCeBCCGFREsCFEMKizuuNPEqpROBINUdvCVx4L1X0vItxuS/GZYaLc7llmd3TUWsdVLrneQ3gNaGUinJ1J1J9dzEu98W4zHBxLrcsc81ICkUIISxKArgQQliUlQL4jLouQB25GJf7YlxmuDiXW5a5BiyTAxdCCOHMSjVwIYQQJUgAF0IIi7JEAFdKXa+U2qeUilVKPVPX5fEEpVR7pdQKpdQepdRupdSj9v7NlVJLlVIH7J/N6rqstU0p5aWU2qqUWmzvDlNKbbRv7/lKqQZ1XcbappRqqpT6Sim1VykVo5S6rL5va6XU4/Z9e5dSap5Syrc+bmul1MdKqdNKqV0l+rnctsp42778O5RS/asyrws+gCulvID3gBuAHsBYpVSPui2VR+QDT2itewCDgMn25XwGWKa17gIss3fXN48CMSW6XwPe1Fp3Bs4A99dJqTzrLWCJ1rob0Bez/PV2Wyul2gF/BiK01r0AL2AM9XNbzwKuL9WvvG17A9DF/jcJmFaVGV3wARwYCMRqrQ9prXOBL4CRdVymWqe1Pqm13mL/Px3zg26HWdbZ9sFmA6PqpoSeoZQKAW4EPrJ3K2Ao8JV9kPq4zIHAlcBMAK11rtY6lXq+rTHv4PVTSnkDjYCT1MNtrbVeDaSU6l3eth0JzNHGBqCpUqqNu/OyQgBvBxwr0R1v71dvKaVCgX7ARiBYa33S/tUpwLqv1nbtf8BfgEJ7dwsgVWudb++uj9s7DEgEPrGnjj5SSvlTj7e11vo4MBU4igncZ4Fo6v+2LlLetq1RfLNCAL+oKKUaA18Dj2mt00p+p02bz3rT7lMpdRNwWmsdXddlOc+8gf7ANK11PyCTUumSeritm2Fqm2FAW8CfsmmGi0JtblsrBPDjQPsS3SH2fvWOUsoHE7znaq0X2nsnFJ1S2T9P11X5PGAwMEIpFYdJjQ3F5Iab2k+zoX5u73ggXmu90d79FSag1+dtfQ1wWGudqLXOAxZitn9939ZFytu2NYpvVgjgm4Eu9qvVDTAXPr6r4zLVOnvudyYQo7V+o8RX3wHj7f+PBxad77J5itb6Wa11iNY6FLNdl2ut7wZWALfbB6tXywygtT4FHFNKdbX3GgbsoR5va0zqZJBSqpF9Xy9a5nq9rUsob9t+B9xrb40yCDhbItVSOa31Bf8HDAf2AweB5+q6PB5axssxp1U7gG32v+GYnPAy4ADwK9C8rsvqoeW/Glhs/78TsAmIBb4EGtZ1+TywvOFAlH17fws0q+/bGvgHsBfYBXwKNKyP2xqYh8nz52HOtu4vb9sCCtPK7iCwE9NKx+15ya30QghhUVZIoQghhHBBArgQQliUBHAhhLAoCeBCCGFREsCFEMKiJIALIYRFSQAXQgiL+n/Fz/Qn/EonNwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mean_modcs_sample = (faceModcs ['MoDCS'])"
      ],
      "metadata": {
        "id": "AiGhebVY7KYh"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_modcs_sample.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-cwwAA3Y7pcA",
        "outputId": "f2dd48c2-5ccf-4e89-9d5a-41ea5d0b91e4"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1128.74"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mean_facebook_sample = (faceModcs ['Facebook'])"
      ],
      "metadata": {
        "id": "hN90qKG59Eqw"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_facebook_sample.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fA4uFVxi9N0Y",
        "outputId": "6329b69d-2530-4a7e-f12d-99b98b23d330"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "260.21"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mean_modcs_connection = (faceModcsConn ['MoDCS'])"
      ],
      "metadata": {
        "id": "CIxNUQyo9Pug"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_modcs_connection.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OJgzBFFh9Zx4",
        "outputId": "88a8b34b-979e-400f-8213-85184f67763a"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "17.32"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mean_facebook_connection = (faceModcsConn ['Facebook'])"
      ],
      "metadata": {
        "id": "WKiZQivz9dZC"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mean_facebook_connection.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ewnZqnxU9jeX",
        "outputId": "975cdd8f-e095-4c09-8b0e-f928755c1561"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "31.77"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    }
  ]
}