1 - Observando distribuição dos atributos de entrada e da saída.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importando pacotes úteis\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt_2apli = pd.read_excel('Dataset.xlsx', sheet_name='Dataset AM 2 aplicações')\n",
    "dt_3apli = pd.read_excel('Dataset.xlsx', sheet_name='Dataset AM 3 aplicações')\n",
    "dt_aplicacoes = pd.read_excel('Dataset.xlsx', sheet_name='Score Acumulado Aplicações')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Aplicação 1 - SLLC</th>\n",
       "      <th>Aplicação 1 - DRAM</th>\n",
       "      <th>Aplicação 1 - NET</th>\n",
       "      <th>Aplicação 2 - SLLC</th>\n",
       "      <th>Aplicação 2 - DRAM</th>\n",
       "      <th>Aplicação 2 - NET</th>\n",
       "      <th>SlowDown</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.423619</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.777113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.340972</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.717028</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.314561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>222</td>\n",
       "      <td>0.030208</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.007904</td>\n",
       "      <td>0.010135</td>\n",
       "      <td>0.023649</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.091409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>223</td>\n",
       "      <td>0.030208</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.007904</td>\n",
       "      <td>0.016550</td>\n",
       "      <td>0.021351</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.076593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>224</td>\n",
       "      <td>0.030208</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.007904</td>\n",
       "      <td>0.068000</td>\n",
       "      <td>0.169369</td>\n",
       "      <td>0.493127</td>\n",
       "      <td>0.100670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>225</td>\n",
       "      <td>0.030208</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.007904</td>\n",
       "      <td>0.070336</td>\n",
       "      <td>0.164347</td>\n",
       "      <td>0.516838</td>\n",
       "      <td>0.097879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>226</td>\n",
       "      <td>0.030208</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.007904</td>\n",
       "      <td>0.053058</td>\n",
       "      <td>0.127207</td>\n",
       "      <td>0.003780</td>\n",
       "      <td>0.088420</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>226 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Id  Aplicação 1 - SLLC  Aplicação 1 - DRAM  Aplicação 1 - NET  \\\n",
       "0      1            1.000000            0.000000           0.100000   \n",
       "1      2            1.000000            0.000000           0.100000   \n",
       "2      3            1.000000            0.000000           0.100000   \n",
       "3      4            1.000000            0.000000           0.100000   \n",
       "4      5            1.000000            0.000000           0.100000   \n",
       "..   ...                 ...                 ...                ...   \n",
       "221  222            0.030208            0.000405           0.007904   \n",
       "222  223            0.030208            0.000405           0.007904   \n",
       "223  224            0.030208            0.000405           0.007904   \n",
       "224  225            0.030208            0.000405           0.007904   \n",
       "225  226            0.030208            0.000405           0.007904   \n",
       "\n",
       "     Aplicação 2 - SLLC  Aplicação 2 - DRAM  Aplicação 2 - NET  SlowDown  \n",
       "0              1.000000            0.000000           0.100000  1.423619  \n",
       "1              0.500000            0.100000           0.100000  0.777113  \n",
       "2              0.100000            0.100000           0.100000  0.340972  \n",
       "3              0.300000            1.000000           0.100000  0.717028  \n",
       "4              0.100000            0.500000           0.100000  0.314561  \n",
       "..                  ...                 ...                ...       ...  \n",
       "221            0.010135            0.023649           0.000000  0.091409  \n",
       "222            0.016550            0.021351           0.000000  0.076593  \n",
       "223            0.068000            0.169369           0.493127  0.100670  \n",
       "224            0.070336            0.164347           0.516838  0.097879  \n",
       "225            0.053058            0.127207           0.003780  0.088420  \n",
       "\n",
       "[226 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt_2apli"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>Aplicação 1 - SLLC</th>\n",
       "      <th>Aplicação 1 - DRAM</th>\n",
       "      <th>Aplicação 1 - NET</th>\n",
       "      <th>Aplicação 2 - SLLC</th>\n",
       "      <th>Aplicação 2 - DRAM</th>\n",
       "      <th>Aplicação 2 - NET</th>\n",
       "      <th>Aplicação 3 - SLLC</th>\n",
       "      <th>Aplicação 3 - DRAM</th>\n",
       "      <th>Aplicação 3 - NET</th>\n",
       "      <th>SlowDown</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>217</td>\n",
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       "      <td>0.000045</td>\n",
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       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "      <td>-0.030370</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>337</td>\n",
       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "      <td>0.024465</td>\n",
       "      <td>0.000428</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>0.008548</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>208</td>\n",
       "      <td>0.006728</td>\n",
       "      <td>0.015766</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "      <td>0.020808</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>305</td>\n",
       "      <td>0.006728</td>\n",
       "      <td>0.015766</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "      <td>0.024465</td>\n",
       "      <td>0.000428</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>0.032593</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>349</td>\n",
       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "      <td>0.024465</td>\n",
       "      <td>0.000428</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>0.024465</td>\n",
       "      <td>0.000428</td>\n",
       "      <td>0.005842</td>\n",
       "      <td>0.033900</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>380</th>\n",
       "      <td>86</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>2.393990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>31</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>2.585841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>382</th>\n",
       "      <td>120</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>2.624066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>383</th>\n",
       "      <td>111</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>2.647916</td>\n",
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       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>2.947923</td>\n",
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       "  </tbody>\n",
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       "<p>385 rows × 11 columns</p>\n",
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       "      Id  Aplicação 1 - SLLC  Aplicação 1 - DRAM  Aplicação 1 - NET  \\\n",
       "0    217            0.015291            0.000045           0.037801   \n",
       "1    337            0.015291            0.000045           0.037801   \n",
       "2    208            0.006728            0.015766           0.000000   \n",
       "3    305            0.006728            0.015766           0.000000   \n",
       "4    349            0.015291            0.000045           0.037801   \n",
       "..   ...                 ...                 ...                ...   \n",
       "380   86            0.900000            0.000000           0.500000   \n",
       "381   31            1.000000            0.000000           0.100000   \n",
       "382  120            0.700000            0.100000           0.400000   \n",
       "383  111            1.000000            0.000000           0.300000   \n",
       "384    1            1.000000            0.000000           0.100000   \n",
       "\n",
       "     Aplicação 2 - SLLC  Aplicação 2 - DRAM  Aplicação 2 - NET  \\\n",
       "0              0.015291            0.000045           0.037801   \n",
       "1              0.015291            0.000045           0.037801   \n",
       "2              0.015291            0.000045           0.037801   \n",
       "3              0.015291            0.000045           0.037801   \n",
       "4              0.024465            0.000428           0.005842   \n",
       "..                  ...                 ...                ...   \n",
       "380            0.900000            0.000000           0.500000   \n",
       "381            1.000000            0.000000           0.300000   \n",
       "382            0.700000            0.100000           0.400000   \n",
       "383            1.000000            0.000000           0.300000   \n",
       "384            1.000000            0.000000           0.100000   \n",
       "\n",
       "     Aplicação 3 - SLLC  Aplicação 3 - DRAM  Aplicação 3 - NET  SlowDown  \n",
       "0              0.015291            0.000045           0.037801 -0.030370  \n",
       "1              0.024465            0.000428           0.005842  0.008548  \n",
       "2              0.015291            0.000045           0.037801  0.020808  \n",
       "3              0.024465            0.000428           0.005842  0.032593  \n",
       "4              0.024465            0.000428           0.005842  0.033900  \n",
       "..                  ...                 ...                ...       ...  \n",
       "380            0.900000            0.000000           0.500000  2.393990  \n",
       "381            1.000000            0.000000           0.300000  2.585841  \n",
       "382            0.700000            0.100000           0.400000  2.624066  \n",
       "383            1.000000            0.000000           0.300000  2.647916  \n",
       "384            1.000000            0.000000           0.100000  2.947923  \n",
       "\n",
       "[385 rows x 11 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt_3apli"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Application</th>\n",
       "      <th>Score - SLLC</th>\n",
       "      <th>Score - DRAM</th>\n",
       "      <th>Score - NET</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S1.6</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S2.6</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S3.6</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S4.6</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S5.6</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S6.6</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>S7.6</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S8.6</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>S9.6</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>S10.6</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>S11.6</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>S12.6</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>S13.6</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>S14.6</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>S15.6</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>S16.6</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>S17.6</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>S18.6</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>S1.4</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>S3.4</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>S4.4</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>S7.4</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>S10.4</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>S12.4</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>S13.4</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>S16.4</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>S18.4</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>S3.2</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>S7.2</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>S10.2</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>S18.2</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>S3.1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>S7.1</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>HPL.I1.6</td>\n",
       "      <td>0.027731</td>\n",
       "      <td>0.056554</td>\n",
       "      <td>0.019210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>HPL.I9.6</td>\n",
       "      <td>0.025823</td>\n",
       "      <td>0.062432</td>\n",
       "      <td>0.015464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>DGEMM.I1.6</td>\n",
       "      <td>0.010135</td>\n",
       "      <td>0.023649</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>DGEMM.I3.6</td>\n",
       "      <td>0.016550</td>\n",
       "      <td>0.021351</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>PTRANS.I5.6</td>\n",
       "      <td>0.182826</td>\n",
       "      <td>0.213514</td>\n",
       "      <td>0.321649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>PTRANS.I9.6</td>\n",
       "      <td>0.017737</td>\n",
       "      <td>0.000158</td>\n",
       "      <td>0.111340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>FFT.I3.4</td>\n",
       "      <td>0.068000</td>\n",
       "      <td>0.169369</td>\n",
       "      <td>0.493127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>FFT.I4.4</td>\n",
       "      <td>0.070336</td>\n",
       "      <td>0.164347</td>\n",
       "      <td>0.516838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>MUFITS.A.6</td>\n",
       "      <td>0.030208</td>\n",
       "      <td>0.000405</td>\n",
       "      <td>0.007904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>MUFITS.B.6</td>\n",
       "      <td>0.053058</td>\n",
       "      <td>0.127207</td>\n",
       "      <td>0.003780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>HPL.I9.4</td>\n",
       "      <td>0.018006</td>\n",
       "      <td>0.041396</td>\n",
       "      <td>0.013746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>DGEMM.I3.4</td>\n",
       "      <td>0.010966</td>\n",
       "      <td>0.023468</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>PTRANS.I5.4</td>\n",
       "      <td>0.136165</td>\n",
       "      <td>0.090788</td>\n",
       "      <td>0.193814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>MUFITS.B.4</td>\n",
       "      <td>0.048954</td>\n",
       "      <td>0.075203</td>\n",
       "      <td>0.003093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>PTRANS.I9.4</td>\n",
       "      <td>0.015291</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.037801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>DGEMM.I1.4</td>\n",
       "      <td>0.006728</td>\n",
       "      <td>0.015766</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>HPL.I1.4</td>\n",
       "      <td>0.012232</td>\n",
       "      <td>0.038288</td>\n",
       "      <td>0.010997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>PTRANS.I5.2</td>\n",
       "      <td>0.054434</td>\n",
       "      <td>0.040541</td>\n",
       "      <td>0.189003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>DGEMM.I3.2</td>\n",
       "      <td>0.004281</td>\n",
       "      <td>0.009009</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>HPL.I9.2</td>\n",
       "      <td>0.007951</td>\n",
       "      <td>0.011261</td>\n",
       "      <td>0.005498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>FFT.I4.2</td>\n",
       "      <td>0.040979</td>\n",
       "      <td>0.085586</td>\n",
       "      <td>0.305842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>PTRANS.I12.1</td>\n",
       "      <td>0.049541</td>\n",
       "      <td>0.029279</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>DGEMM.I12.1</td>\n",
       "      <td>0.003058</td>\n",
       "      <td>0.004505</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>MUFITS.A.4</td>\n",
       "      <td>0.024465</td>\n",
       "      <td>0.000428</td>\n",
       "      <td>0.005842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>MUFITS.B.2</td>\n",
       "      <td>0.015902</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.000271</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Application  Score - SLLC  Score - DRAM  Score - NET\n",
       "0           S1.6      1.000000      0.000000     0.100000\n",
       "1           S2.6      0.500000      0.100000     0.100000\n",
       "2           S3.6      0.100000      0.100000     0.100000\n",
       "3           S4.6      0.300000      1.000000     0.100000\n",
       "4           S5.6      0.100000      0.500000     0.100000\n",
       "5           S6.6      0.500000      0.500000     0.100000\n",
       "6           S7.6      1.000000      0.000000     1.000000\n",
       "7           S8.6      0.500000      0.100000     1.000000\n",
       "8           S9.6      0.100000      0.100000     1.000000\n",
       "9          S10.6      0.300000      1.000000     1.000000\n",
       "10         S11.6      0.100000      0.500000     1.000000\n",
       "11         S12.6      0.500000      0.500000     1.000000\n",
       "12         S13.6      1.000000      0.000000     0.500000\n",
       "13         S14.6      0.500000      0.100000     0.500000\n",
       "14         S15.6      0.100000      0.100000     0.500000\n",
       "15         S16.6      0.300000      1.000000     0.500000\n",
       "16         S17.6      0.100000      0.500000     0.500000\n",
       "17         S18.6      0.500000      0.500000     0.500000\n",
       "18          S1.4      1.000000      0.000000     0.100000\n",
       "19          S3.4      0.100000      0.000000     0.100000\n",
       "20          S4.4      0.300000      0.900000     0.100000\n",
       "21          S7.4      0.900000      0.000000     0.500000\n",
       "22         S10.4      0.300000      0.900000     0.500000\n",
       "23         S12.4      0.700000      0.100000     0.500000\n",
       "24         S13.4      1.000000      0.000000     0.300000\n",
       "25         S16.4      0.300000      0.900000     0.300000\n",
       "26         S18.4      0.700000      0.100000     0.400000\n",
       "27          S3.2      0.100000      0.000000     0.000000\n",
       "28          S7.2      0.600000      0.000000     0.300000\n",
       "29         S10.2      0.500000      0.100000     0.300000\n",
       "30         S18.2      0.500000      0.000000     0.200000\n",
       "31          S3.1      0.000000      0.000000     0.000000\n",
       "32          S7.1      0.300000      0.000000     0.000000\n",
       "33      HPL.I1.6      0.027731      0.056554     0.019210\n",
       "34      HPL.I9.6      0.025823      0.062432     0.015464\n",
       "35    DGEMM.I1.6      0.010135      0.023649     0.000000\n",
       "36    DGEMM.I3.6      0.016550      0.021351     0.000000\n",
       "37   PTRANS.I5.6      0.182826      0.213514     0.321649\n",
       "38   PTRANS.I9.6      0.017737      0.000158     0.111340\n",
       "39      FFT.I3.4      0.068000      0.169369     0.493127\n",
       "40      FFT.I4.4      0.070336      0.164347     0.516838\n",
       "41    MUFITS.A.6      0.030208      0.000405     0.007904\n",
       "42    MUFITS.B.6      0.053058      0.127207     0.003780\n",
       "43      HPL.I9.4      0.018006      0.041396     0.013746\n",
       "44    DGEMM.I3.4      0.010966      0.023468     0.000000\n",
       "45   PTRANS.I5.4      0.136165      0.090788     0.193814\n",
       "46    MUFITS.B.4      0.048954      0.075203     0.003093\n",
       "47   PTRANS.I9.4      0.015291      0.000045     0.037801\n",
       "48    DGEMM.I1.4      0.006728      0.015766     0.000000\n",
       "49      HPL.I1.4      0.012232      0.038288     0.010997\n",
       "50   PTRANS.I5.2      0.054434      0.040541     0.189003\n",
       "51    DGEMM.I3.2      0.004281      0.009009     0.000000\n",
       "52      HPL.I9.2      0.007951      0.011261     0.005498\n",
       "53      FFT.I4.2      0.040979      0.085586     0.305842\n",
       "54  PTRANS.I12.1      0.049541      0.029279     0.000000\n",
       "55   DGEMM.I12.1      0.003058      0.004505     0.000000\n",
       "56    MUFITS.A.4      0.024465      0.000428     0.005842\n",
       "57    MUFITS.B.2      0.015902      0.027027     0.000271"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt_aplicacoes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([34.,  7.,  8.,  3.,  6.]),\n",
       " array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]),\n",
       " <a list of 5 Patch objects>)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dt_aplicacoes['Score - SLLC'], bins=[0, 0.2, 0.4, 0.6, 0.8, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([45.,  1.,  6.,  0.,  6.]),\n",
       " array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]),\n",
       " <a list of 5 Patch objects>)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAAD4CAYAAAD1jb0+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAMNklEQVR4nO3dbYyl9VnH8e+vbBGNrdDu0BAWnTbZGjZNLM0GMU18gNYgGOAFGojVNdm4aX1ITU10tW98egEmFmNCohshXY22IBrZgMYghaBNoQ5CeQxCEesGwk5TQBtjLfbyxbmL6+zMzs3MOWfmYr+fZDPn3Oc+e67/ntkvZ+9z7iFVhSSpnzdt9QCSpI0x4JLUlAGXpKYMuCQ1ZcAlqakd83ywnTt31uLi4jwfUpLae/DBB79cVQsrt8814IuLiywtLc3zISWpvST/utp2D6FIUlMGXJKaMuCS1JQBl6SmDLgkNWXAJakpAy5JTRlwSWrKgEtSU3M9E3MzFg/eudUjzN1z112+1SNI2sZ8BS5JTRlwSWrKgEtSUwZckpoy4JLUlAGXpKYMuCQ1ZcAlqSkDLklNGXBJasqAS1JTBlySmjLgktSUAZekpgy4JDVlwCWpKQMuSU0ZcElqyoBLUlOjA57ktCQPJbljuP7OJA8keTrJLUlOn92YkqSVXs8r8I8CTx53/XrghqraDbwE7J/mYJKkkxsV8CS7gMuBPxquB7gYuG3Y5TBw1SwGlCStbuwr8N8Dfhn4xnD97cDLVfXqcP0ocO5qd0xyIMlSkqXl5eVNDStJ+j/rBjzJjwLHqurB4zevsmutdv+qOlRVe6tq78LCwgbHlCSttGPEPu8HrkhyGXAG8FYmr8jPTLJjeBW+C3h+dmNKklZa9xV4Vf1qVe2qqkXgGuAzVfUTwD3A1cNu+4DbZzalJOkEm/kc+K8AH0vyDJNj4jdNZyRJ0hhjDqG8pqruBe4dLj8LXDj9kSRJY3gmpiQ1ZcAlqSkDLklNGXBJasqAS1JTBlySmjLgktSUAZekpgy4JDVlwCWpKQMuSU0ZcElqyoBLUlMGXJKaMuCS1JQBl6SmDLgkNWXAJakpAy5JTRlwSWrKgEtSUwZckpoy4JLUlAGXpKYMuCQ1ZcAlqSkDLklNGXBJasqAS1JTBlySmjLgktSUAZekpgy4JDVlwCWpKQMuSU0ZcElqyoBLUlPrBjzJGUk+n+QLSR5P8hvD9ncmeSDJ00luSXL67MeVJH3TmFfgXwMurqrvAd4LXJrkIuB64Iaq2g28BOyf3ZiSpJXWDXhNfHW4+ubhVwEXA7cN2w8DV81kQknSqkYdA09yWpKHgWPAXcAXgZer6tVhl6PAuWvc90CSpSRLy8vL05hZksTIgFfV/1TVe4FdwIXA+avttsZ9D1XV3qrau7CwsPFJJUn/z+v6FEpVvQzcC1wEnJlkx3DTLuD56Y4mSTqZMZ9CWUhy5nD5W4EPAE8C9wBXD7vtA26f1ZCSpBPtWH8XzgEOJzmNSfBvrao7kjwBfDrJbwMPATfNcE5J0grrBryqHgEuWGX7s0yOh0uStoBnYkpSUwZckpoy4JLUlAGXpKYMuCQ1ZcAlqSkDLklNGXBJasqAS1JTBlySmjLgktSUAZekpgy4JDVlwCWpKQMuSU0ZcElqyoBLUlMGXJKaMuCS1JQBl6SmDLgkNWXAJakpAy5JTRlwSWrKgEtSUwZckpoy4JLUlAGXpKYMuCQ1ZcAlqSkDLklNGXBJasqAS1JTBlySmjLgktSUAZekpgy4JDW1bsCTnJfkniRPJnk8yUeH7W9LcleSp4evZ81+XEnSN415Bf4q8EtVdT5wEfBzSfYAB4G7q2o3cPdwXZI0J+sGvKpeqKp/Gi7/B/AkcC5wJXB42O0wcNWshpQkneh1HQNPsghcADwAvKOqXoBJ5IGz17jPgSRLSZaWl5c3N60k6TWjA57k24G/AH6xqv597P2q6lBV7a2qvQsLCxuZUZK0ilEBT/JmJvH+06r6y2Hzi0nOGW4/Bzg2mxElSasZ8ymUADcBT1bVJ4676Qiwb7i8D7h9+uNJktayY8Q+7wd+Eng0ycPDtl8DrgNuTbIf+BLwY7MZUZK0mnUDXlX/AGSNmy+Z7jiSpLE8E1OSmjLgktSUAZekpgy4JDVlwCWpKQMuSU0ZcElqyoBLUlMGXJKaMuCS1JQBl6SmDLgkNWXAJakpAy5JTRlwSWrKgEtSUwZckpoy4JLUlAGXpKYMuCQ1ZcAlqSkDLklNGXBJasqAS1JTBlySmjLgktSUAZekpgy4JDVlwCWpKQMuSU0ZcElqyoBLUlMGXJKaMuCS1JQBl6SmDLgkNWXAJampdQOe5OYkx5I8dty2tyW5K8nTw9ezZjumJGmlMa/APwlcumLbQeDuqtoN3D1clyTN0boBr6r7gK+s2HwlcHi4fBi4aspzSZLWsdFj4O+oqhcAhq9nr7VjkgNJlpIsLS8vb/DhJEkrzfxNzKo6VFV7q2rvwsLCrB9Okk4ZGw34i0nOARi+HpveSJKkMTYa8CPAvuHyPuD26YwjSRprzMcIPwV8DvjuJEeT7AeuAz6Y5Gngg8N1SdIc7Vhvh6q6do2bLpnyLJKk18EzMSWpKQMuSU0ZcElqyoBLUlMGXJKaMuCS1JQBl6SmDLgkNWXAJakpAy5JTRlwSWrKgEtSU+v+MCtpnhYP3rnVI8zdc9ddvtUjzN2p9jzP6jn2FbgkNWXAJakpAy5JTRlwSWrKgEtSUwZckpoy4JLUlAGXpKYMuCQ1ZcAlqSkDLklNGXBJasqAS1JTBlySmjLgktSUAZekpgy4JDVlwCWpKQMuSU0ZcElqyoBLUlMGXJKa2rHVA2htiwfv3OoRJG1jvgKXpKY2FfAklyZ5KskzSQ5OayhJ0vo2HPAkpwE3Aj8C7AGuTbJnWoNJkk5uM6/ALwSeqapnq+q/gU8DV05nLEnSejbzJua5wL8dd/0o8L0rd0pyADgwXP1qkqc2+Hg7gS9v8L5dueZTQK4/9dbMKfY8T+E5/q7VNm4m4FllW52woeoQcGgTjzN5sGSpqvZu9vfpxDWfGlzzG9+s1ruZQyhHgfOOu74LeH5z40iSxtpMwP8R2J3knUlOB64BjkxnLEnSejZ8CKWqXk3y88DfAqcBN1fV41Ob7ESbPgzTkGs+NbjmN76ZrDdVJxy2liQ14JmYktSUAZekprZdwNc7PT/JtyS5Zbj9gSSL859yukas+WNJnkjySJK7k6z6mdBOxv4YhiRXJ6kkrT9yNma9SX58eJ4fT/Jn855x2kZ8X39nknuSPDR8b1+2FXNOU5KbkxxL8tgatyfJ7w9/Jo8ked+mHrCqts0vJm+GfhF4F3A68AVgz4p9fhb4g+HyNcAtWz33HNb8Q8C3DZc/ciqsedjvLcB9wP3A3q2ee8bP8W7gIeCs4frZWz33HNZ8CPjIcHkP8NxWzz2FdX8/8D7gsTVuvwz4Gybn0VwEPLCZx9tur8DHnJ5/JXB4uHwbcEmS1U4q6mLdNVfVPVX1n8PV+5l85r6zsT+G4beA3wH+a57DzcCY9f4McGNVvQRQVcfmPOO0jVlzAW8dLn8Hb4DzSKrqPuArJ9nlSuCPa+J+4Mwk52z08bZbwFc7Pf/ctfapqleBV4C3z2W62Riz5uPtZ/Jf8M7WXXOSC4DzquqOeQ42I2Oe43cD707y2ST3J7l0btPNxpg1/zrwoSRHgb8GfmE+o22p1/v3/aS22//QYczp+aNO4W9k9HqSfAjYC/zATCeavZOuOcmbgBuAn57XQDM25jneweQwyg8y+RfW3yd5T1W9POPZZmXMmq8FPllVv5vk+4A/Gdb8jdmPt2Wm2q/t9gp8zOn5r+2TZAeTf3qd7J8s292oH0mQ5APAx4Erquprc5ptVtZb81uA9wD3JnmOybHCI43fyBz7fX17VX29qv4FeIpJ0Lsas+b9wK0AVfU54AwmP+TqjWyqP4JkuwV8zOn5R4B9w+Wrgc/U8O5AU+uueTic8IdM4t392Ciss+aqeqWqdlbVYlUtMjnuf0VVLW3NuJs25vv6r5i8WU2SnUwOqTw71ymna8yavwRcApDkfCYBX57rlPN3BPip4dMoFwGvVNULG/7dtvpd2zXepf1nJu9gf3zY9ptM/gLD5En+c+AZ4PPAu7Z65jms+e+AF4GHh19HtnrmWa95xb730vhTKCOf4wCfAJ4AHgWu2eqZ57DmPcBnmXxC5WHgh7d65ims+VPAC8DXmbza3g98GPjwcc/zjcOfyaOb/b72VHpJamq7HUKRJI1kwCWpKQMuSU0ZcElqyoBLUlMGXJKaMuCS1NT/Aj4u+wkjK2xuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dt_aplicacoes['Score - DRAM'], bins=[0, 0.2, 0.4, 0.6, 0.8, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([33.,  7., 12.,  0.,  6.]),\n",
       " array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]),\n",
       " <a list of 5 Patch objects>)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dt_aplicacoes['Score - NET'], bins=[0, 0.2, 0.4, 0.6, 0.8, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt_2apli['SlowDown'] = (dt_2apli['SlowDown'] - dt_2apli['SlowDown'].min())/(dt_2apli['SlowDown'].max()-dt_2apli['SlowDown'].min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([120.,  68.,  28.,   6.,   4.]),\n",
       " array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]),\n",
       " <a list of 5 Patch objects>)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dt_2apli['SlowDown'], bins=[0, 0.2, 0.4, 0.6, 0.8, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt_3apli['SlowDown'] = (dt_3apli['SlowDown'] - dt_3apli['SlowDown'].min())/(dt_3apli['SlowDown'].max()-dt_3apli['SlowDown'].min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([226.,  73.,  63.,  17.,   6.]),\n",
       " array([0. , 0.2, 0.4, 0.6, 0.8, 1. ]),\n",
       " <a list of 5 Patch objects>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dt_3apli['SlowDown'], bins=[0, 0.2, 0.4, 0.6, 0.8, 1])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}