Merging the signal with its feature row.ipynb

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      "       data_ID         0         1         2         3         4         5  \\\n",
      "0   A_01_06_06 -0.116201 -0.120952 -0.125470 -0.129755 -0.133807 -0.137628   \n",
      "1       A_01_1 -0.110777 -0.119968 -0.128788 -0.137072 -0.144673 -0.151463   \n",
      "2   A_01_17_07 -0.061985 -0.065903 -0.069614 -0.073117 -0.076413 -0.079501   \n",
      "3       A_01_2 -0.071215 -0.067523 -0.063781 -0.060007 -0.056219 -0.052437   \n",
      "4       A_01_3 -0.119150 -0.120002 -0.120831 -0.121598 -0.122282 -0.122872   \n",
      "..         ...       ...       ...       ...       ...       ...       ...   \n",
      "63      A_07_4 -0.042867 -0.040006 -0.037546 -0.035554 -0.034082 -0.033164   \n",
      "64      A_08_1  0.004036  0.017585  0.030874  0.043721  0.055952  0.067408   \n",
      "65      A_08_2 -0.087354 -0.086402 -0.085131 -0.083613 -0.081923 -0.080136   \n",
      "66      A_08_3 -0.007330 -0.009214 -0.011009 -0.012670 -0.014156 -0.015427   \n",
      "67      A_08_4 -0.014677 -0.015100 -0.015465 -0.015775 -0.016033 -0.016245   \n",
      "\n",
      "           6         7         8  ...     16373     16374     16375     16376  \\\n",
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      "2  -0.082381 -0.085054 -0.087520  ... -0.042598 -0.041292 -0.040163 -0.039244   \n",
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      "4  -0.123371 -0.123792 -0.124154  ... -0.415537 -0.394111 -0.370438 -0.345248   \n",
      "..       ...       ...       ...  ...       ...       ...       ...       ...   \n",
      "63 -0.032819 -0.033047 -0.033831  ... -0.026688 -0.026522 -0.026546 -0.026751   \n",
      "64  0.077946  0.087443  0.095800  ... -0.047111 -0.046589 -0.045931 -0.045112   \n",
      "65 -0.078319 -0.076532 -0.074827  ...  0.028132  0.026087  0.024014  0.021915   \n",
      "66 -0.016451 -0.017198 -0.017648  ... -0.041657 -0.040411 -0.038846 -0.036959   \n",
      "67 -0.016417 -0.016556 -0.016672  ... -0.061674 -0.064179 -0.066817 -0.069398   \n",
      "\n",
      "       16377     16378     16379     16380     16381     16382  \n",
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      "2  -0.038572 -0.038178 -0.038093 -0.038341 -0.038940 -0.039903  \n",
      "3  -0.048634 -0.048705 -0.048821 -0.049004 -0.049278 -0.049663  \n",
      "4  -0.319237 -0.293054 -0.267288 -0.242461 -0.219016 -0.197320  \n",
      "..       ...       ...       ...       ...       ...       ...  \n",
      "63 -0.027120 -0.027628 -0.028243 -0.028929 -0.029646 -0.030352  \n",
      "64 -0.044118 -0.042945 -0.041599 -0.040095 -0.038454 -0.036707  \n",
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      "\n",
      "[68 rows x 16384 columns]\n",
      "       data_ID         0         1         2         3         4         5  \\\n",
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      "2       C_01_2 -0.044535 -0.053890 -0.064269 -0.075458 -0.087177 -0.099078   \n",
      "3       C_01_3 -0.039560 -0.039457 -0.039018 -0.038201 -0.036967 -0.035283   \n",
      "4       C_02_1  0.327384  0.285837  0.242924  0.199535  0.156541  0.114777   \n",
      "..         ...       ...       ...       ...       ...       ...       ...   \n",
      "73  C_09_26_07  0.072516  0.084666  0.096211  0.107152  0.117489  0.127221   \n",
      "74      C_09_3 -0.093928 -0.093802 -0.093489 -0.092975 -0.092251 -0.091314   \n",
      "75      C_09_4 -0.008243 -0.007125 -0.005950 -0.004734 -0.003496 -0.002253   \n",
      "76      C_09_5  0.013856  0.013657  0.013206  0.012521  0.011624  0.010543   \n",
      "77  C_10_17_07 -0.110495 -0.107921 -0.105409 -0.102958 -0.100570 -0.098244   \n",
      "\n",
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      "77 -0.095979 -0.093777 -0.091637  ...       NaN       NaN       NaN       NaN   \n",
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      "..       ...       ...       ...       ...       ...       ...  \n",
      "73       NaN       NaN       NaN       NaN       NaN       NaN  \n",
      "74 -0.012663 -0.012284 -0.011742 -0.011050 -0.010224 -0.009282  \n",
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      "[78 rows x 60001 columns]\n",
      "       data_ID         0         1         2         3         4         5  \\\n",
      "0   A_01_06_06 -0.116201 -0.120952 -0.125470 -0.129755 -0.133807 -0.137628   \n",
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      "4       A_01_3 -0.119150 -0.120002 -0.120831 -0.121598 -0.122282 -0.122872   \n",
      "..         ...       ...       ...       ...       ...       ...       ...   \n",
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      "76      C_09_5  0.013856  0.013657  0.013206  0.012521  0.011624  0.010543   \n",
      "77  C_10_17_07 -0.110495 -0.107921 -0.105409 -0.102958 -0.100570 -0.098244   \n",
      "\n",
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      "2  -0.082381 -0.085054 -0.087520  ...       NaN       NaN       NaN       NaN   \n",
      "3  -0.048684 -0.044979 -0.041344  ...       NaN       NaN       NaN       NaN   \n",
      "4  -0.123371 -0.123792 -0.124154  ...       NaN       NaN       NaN       NaN   \n",
      "..       ...       ...       ...  ...       ...       ...       ...       ...   \n",
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      "[146 rows x 60001 columns]\n"
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       "      <td>-0.128788</td>\n",
       "      <td>-0.137072</td>\n",
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       "      <th>3</th>\n",
       "      <td>A_01_2</td>\n",
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       "      <td>-0.067523</td>\n",
       "      <td>-0.063781</td>\n",
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       "      <th>73</th>\n",
       "      <td>C_09_26_07</td>\n",
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       "      <th>74</th>\n",
       "      <td>C_09_3</td>\n",
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       "      <th>75</th>\n",
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       "      <td>-0.003496</td>\n",
       "      <td>-0.002253</td>\n",
       "      <td>-0.001018</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>0.001381</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002396</td>\n",
       "      <td>0.004371</td>\n",
       "      <td>0.006242</td>\n",
       "      <td>0.007971</td>\n",
       "      <td>0.009523</td>\n",
       "      <td>0.010870</td>\n",
       "      <td>0.011986</td>\n",
       "      <td>0.012853</td>\n",
       "      <td>0.013457</td>\n",
       "      <td>0.013792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>C_09_5</td>\n",
       "      <td>0.013856</td>\n",
       "      <td>0.013657</td>\n",
       "      <td>0.013206</td>\n",
       "      <td>0.012521</td>\n",
       "      <td>0.011624</td>\n",
       "      <td>0.010543</td>\n",
       "      <td>0.009310</td>\n",
       "      <td>0.007958</td>\n",
       "      <td>0.006523</td>\n",
       "      <td>...</td>\n",
       "      <td>0.126180</td>\n",
       "      <td>0.127804</td>\n",
       "      <td>0.129277</td>\n",
       "      <td>0.130603</td>\n",
       "      <td>0.131788</td>\n",
       "      <td>0.132841</td>\n",
       "      <td>0.133772</td>\n",
       "      <td>0.134593</td>\n",
       "      <td>0.135319</td>\n",
       "      <td>0.135964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>C_10_17_07</td>\n",
       "      <td>-0.110495</td>\n",
       "      <td>-0.107921</td>\n",
       "      <td>-0.105409</td>\n",
       "      <td>-0.102958</td>\n",
       "      <td>-0.100570</td>\n",
       "      <td>-0.098244</td>\n",
       "      <td>-0.095979</td>\n",
       "      <td>-0.093777</td>\n",
       "      <td>-0.091637</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>146 rows × 60001 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       data_ID         0         1         2         3         4         5  \\\n",
       "0   A_01_06_06 -0.116201 -0.120952 -0.125470 -0.129755 -0.133807 -0.137628   \n",
       "1       A_01_1 -0.110777 -0.119968 -0.128788 -0.137072 -0.144673 -0.151463   \n",
       "2   A_01_17_07 -0.061985 -0.065903 -0.069614 -0.073117 -0.076413 -0.079501   \n",
       "3       A_01_2 -0.071215 -0.067523 -0.063781 -0.060007 -0.056219 -0.052437   \n",
       "4       A_01_3 -0.119150 -0.120002 -0.120831 -0.121598 -0.122282 -0.122872   \n",
       "..         ...       ...       ...       ...       ...       ...       ...   \n",
       "73  C_09_26_07  0.072516  0.084666  0.096211  0.107152  0.117489  0.127221   \n",
       "74      C_09_3 -0.093928 -0.093802 -0.093489 -0.092975 -0.092251 -0.091314   \n",
       "75      C_09_4 -0.008243 -0.007125 -0.005950 -0.004734 -0.003496 -0.002253   \n",
       "76      C_09_5  0.013856  0.013657  0.013206  0.012521  0.011624  0.010543   \n",
       "77  C_10_17_07 -0.110495 -0.107921 -0.105409 -0.102958 -0.100570 -0.098244   \n",
       "\n",
       "           6         7         8  ...     59990     59991     59992     59993  \\\n",
       "0  -0.141215 -0.144570 -0.147692  ...       NaN       NaN       NaN       NaN   \n",
       "1  -0.157344 -0.162247 -0.166136  ...       NaN       NaN       NaN       NaN   \n",
       "2  -0.082381 -0.085054 -0.087520  ...       NaN       NaN       NaN       NaN   \n",
       "3  -0.048684 -0.044979 -0.041344  ...       NaN       NaN       NaN       NaN   \n",
       "4  -0.123371 -0.123792 -0.124154  ...       NaN       NaN       NaN       NaN   \n",
       "..       ...       ...       ...  ...       ...       ...       ...       ...   \n",
       "73  0.136348  0.144871  0.152790  ...       NaN       NaN       NaN       NaN   \n",
       "74 -0.090167 -0.088818 -0.087279  ... -0.012376 -0.012726 -0.012890 -0.012867   \n",
       "75 -0.001018  0.000197  0.001381  ...  0.002396  0.004371  0.006242  0.007971   \n",
       "76  0.009310  0.007958  0.006523  ...  0.126180  0.127804  0.129277  0.130603   \n",
       "77 -0.095979 -0.093777 -0.091637  ...       NaN       NaN       NaN       NaN   \n",
       "\n",
       "       59994     59995     59996     59997     59998     59999  \n",
       "0        NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "1        NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "2        NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "3        NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "4        NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "..       ...       ...       ...       ...       ...       ...  \n",
       "73       NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "74 -0.012663 -0.012284 -0.011742 -0.011050 -0.010224 -0.009282  \n",
       "75  0.009523  0.010870  0.011986  0.012853  0.013457  0.013792  \n",
       "76  0.131788  0.132841  0.133772  0.134593  0.135319  0.135964  \n",
       "77       NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "\n",
       "[146 rows x 60001 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "\n",
    "folder_path1 = 'C:/Users/Ewunetie/OneDrive - University of Gondar,/2022-2023 files/Courses/Project/CTRL/Chewing.csv'\n",
    "folder_path2 = 'C:/Users/Ewunetie/OneDrive - University of Gondar,/2022-2023 files/Courses/Project/CTRL/Control.csv'\n",
    "folder_path = 'C:/Users/Ewunetie/OneDrive - University of Gondar,/2022-2023 files/Courses/Project/CTRL'\n",
    "df1 = pd.read_csv(folder_path1)\n",
    "print(df1)\n",
    "df2 = pd.read_csv(folder_path2)\n",
    "print(df2)\n",
    "\n",
    "dfs=pd.concat([df1, df2],axis=0)\n",
    "df=pd.DataFrame(dfs)\n",
    "print(df)\n",
    "\n",
    "output_file_path = os.path.join(folder_path,\"CTRL.csv\")\n",
    "df.to_csv(output_file_path, index=False)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a3391d3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7449b36e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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