test_pd_methods.ipynb

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       "<div>\n",
       "<style scoped>\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INOUT_ID</th>\n",
       "      <th>AD_CLIENT_ID</th>\n",
       "      <th>AD_ORG_ID</th>\n",
       "      <th>ISACTIVE</th>\n",
       "      <th>CREATED</th>\n",
       "      <th>CREATEDBY</th>\n",
       "      <th>UPDATED</th>\n",
       "      <th>UPDATEDBY</th>\n",
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       "      <th>DESCRIPTION</th>\n",
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       "      <th>M_INOUT_AMVAL_ID</th>\n",
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       "      <th>LOCATIONS_ID</th>\n",
       "      <th>ACCT_AC_HOLDING_ID</th>\n",
       "      <th>VAHED_MALI</th>\n",
       "      <th>ACCT_AC_JOURNAL_ID</th>\n",
       "      <th>BASEINFO_RECORDID</th>\n",
       "      <th>C_YEAR_ID</th>\n",
       "      <th>Unnamed: 43</th>\n",
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       "      <td>210619032</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>206</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>206.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>469637758</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9405</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>469637759</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>346</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>346.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>469637760</td>\n",
       "      <td>104000002</td>\n",
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       "      <td>Y</td>\n",
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       "      <td>210619032</td>\n",
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       "      <td>382</td>\n",
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       "      <td>382.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
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       "      <td>104000002</td>\n",
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       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>142</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>142.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>469637762</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>244</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>244.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>469637763</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>469637764</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>1/29/2017 14:02</td>\n",
       "      <td>210033614</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>469637765</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1050</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1050.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>469637766</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>469637767</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>202</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>202.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>469637768</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>235</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>235.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>469637769</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>469637770</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>469637772</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>590</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>590.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>469637773</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>576</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>576.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>469637774</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>6/28/2015 7:50</td>\n",
       "      <td>210619032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>433</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>433.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470900574.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>210032665</td>\n",
       "      <td>104000002</td>\n",
       "      <td>0</td>\n",
       "      <td>Y</td>\n",
       "      <td>12/26/2013 9:49</td>\n",
       "      <td>210035294</td>\n",
       "      <td>12/26/2013 9:50</td>\n",
       "      <td>210035294</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</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>20 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     INOUT_ID  AD_CLIENT_ID  AD_ORG_ID ISACTIVE          CREATED  CREATEDBY  \\\n",
       "0   469637755     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "1   469637756     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "2   469637757     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "3   469637758     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "4   469637759     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "5   469637760     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "6   469637761     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "7   469637762     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "8   469637763     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "9   469637764     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "10  469637765     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "11  469637766     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "12  469637767     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "13  469637768     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "14  469637769     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "15  469637770     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "16  469637772     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "17  469637773     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "18  469637774     104000002          0        Y   6/28/2015 7:50  210619032   \n",
       "19  210032665     104000002          0        Y  12/26/2013 9:49  210035294   \n",
       "\n",
       "            UPDATED  UPDATEDBY  NAME DESCRIPTION  ... STRING3  \\\n",
       "0   11/8/2017 11:15  210033614   NaN          69  ...     NaN   \n",
       "1    6/28/2015 7:50  210619032   NaN          73  ...     NaN   \n",
       "2    6/28/2015 7:50  210619032   NaN         206  ...     NaN   \n",
       "3    6/28/2015 7:50  210619032   NaN        9405  ...     NaN   \n",
       "4    6/28/2015 7:50  210619032   NaN         346  ...     NaN   \n",
       "5    6/28/2015 7:50  210619032   NaN         382  ...     NaN   \n",
       "6    6/28/2015 7:50  210619032   NaN         142  ...     NaN   \n",
       "7    6/28/2015 7:50  210619032   NaN         244  ...     NaN   \n",
       "8    6/28/2015 7:50  210619032   NaN          92  ...     NaN   \n",
       "9   1/29/2017 14:02  210033614   NaN         150  ...     NaN   \n",
       "10   6/28/2015 7:50  210619032   NaN        1050  ...     NaN   \n",
       "11   6/28/2015 7:50  210619032   NaN          21  ...     NaN   \n",
       "12   6/28/2015 7:50  210619032   NaN         202  ...     NaN   \n",
       "13   6/28/2015 7:50  210619032   NaN         235  ...     NaN   \n",
       "14   6/28/2015 7:50  210619032   NaN          88  ...     NaN   \n",
       "15   6/28/2015 7:50  210619032   NaN          29  ...     NaN   \n",
       "16   6/28/2015 7:50  210619032   NaN         590  ...     NaN   \n",
       "17   6/28/2015 7:50  210619032   NaN         576  ...     NaN   \n",
       "18   6/28/2015 7:50  210619032   NaN         433  ...     NaN   \n",
       "19  12/26/2013 9:50  210035294   NaN         NaN  ...     NaN   \n",
       "\n",
       "    M_INOUT_AMVAL_ID  DOCUMENTNO1 LOCATIONS_ID ACCT_AC_HOLDING_ID  \\\n",
       "0                NaN         69.0          NaN                1.0   \n",
       "1                NaN         73.0          NaN                1.0   \n",
       "2                NaN        206.0          NaN                1.0   \n",
       "3                NaN       9405.0          NaN                1.0   \n",
       "4                NaN        346.0          NaN                1.0   \n",
       "5                NaN        382.0          NaN                1.0   \n",
       "6                NaN        142.0          NaN                1.0   \n",
       "7                NaN        244.0          NaN                1.0   \n",
       "8                NaN         92.0          NaN                1.0   \n",
       "9                NaN        150.0          NaN                1.0   \n",
       "10               NaN       1050.0          NaN                1.0   \n",
       "11               NaN         21.0          NaN                1.0   \n",
       "12               NaN        202.0          NaN                1.0   \n",
       "13               NaN        235.0          NaN                1.0   \n",
       "14               NaN         88.0          NaN                1.0   \n",
       "15               NaN         29.0          NaN                1.0   \n",
       "16               NaN        590.0          NaN                1.0   \n",
       "17               NaN        576.0          NaN                1.0   \n",
       "18               NaN        433.0          NaN                1.0   \n",
       "19               NaN          NaN          NaN                1.0   \n",
       "\n",
       "     VAHED_MALI  ACCT_AC_JOURNAL_ID  BASEINFO_RECORDID  C_YEAR_ID  Unnamed: 43  \n",
       "0   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "1   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "2   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "3   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "4   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "5   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "6   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "7   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "8   200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "9           NaN                 NaN                NaN        NaN          NaN  \n",
       "10          NaN                 NaN                NaN        NaN          NaN  \n",
       "11  200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "12          NaN                 NaN                NaN        NaN          NaN  \n",
       "13  200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "14  200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "15  200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "16  200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "17  200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "18  200000138.0         470900574.0                NaN        NaN          NaN  \n",
       "19          NaN                 NaN                NaN        NaN          NaN  \n",
       "\n",
       "[20 rows x 44 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "INOUT = pd.read_csv('DataSets/INOUT.csv')\n",
    "\n",
    "# shows first 10 records\n",
    "INOUT[0:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7600, 44)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Index(['INOUT_ID', 'AD_CLIENT_ID', 'AD_ORG_ID', 'ISACTIVE', 'CREATED',\n",
       "       'CREATEDBY', 'UPDATED', 'UPDATEDBY', 'NAME', 'DESCRIPTION', 'HELP',\n",
       "       'DOCUMENTNO', 'C_DOCSTATUS_ID', 'DOCUMENTDATE', 'C_DOCTYPE_ID',\n",
       "       'REF_ORG', 'C_COSTCENTER_ID', 'COM_BPARTNER_ID', 'M_PRODUCT_ID',\n",
       "       'REQUESTNO', 'REQUESTDATE', 'PITYPE', 'ADDRESS_ID', 'ABVIOUSTYPE',\n",
       "       'PC_ACTIVITIES_ID', 'M_PIINOUT_REQUEST_ID', 'ACCEPTANCETYPE',\n",
       "       'RESPONSIBLEBPARTNER', 'RESPONSIBLEMANAGER', 'FROMUSERMANAGERID',\n",
       "       'COM_BPARTNER_ID_F', 'LETTERNO', 'LETTERDATE', 'SUB_REF_ORG', 'STRING3',\n",
       "       'M_INOUT_AMVAL_ID', 'DOCUMENTNO1', 'LOCATIONS_ID', 'ACCT_AC_HOLDING_ID',\n",
       "       'VAHED_MALI', 'ACCT_AC_JOURNAL_ID', 'BASEINFO_RECORDID', 'C_YEAR_ID',\n",
       "       'Unnamed: 43'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(INOUT.shape)\n",
    "\n",
    "# columns\n",
    "INOUT.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "INOUT_ID                  int64\n",
       "AD_CLIENT_ID              int64\n",
       "AD_ORG_ID                 int64\n",
       "ISACTIVE                 object\n",
       "CREATED                  object\n",
       "CREATEDBY                 int64\n",
       "UPDATED                  object\n",
       "UPDATEDBY                 int64\n",
       "NAME                    float64\n",
       "DESCRIPTION              object\n",
       "HELP                     object\n",
       "DOCUMENTNO              float64\n",
       "C_DOCSTATUS_ID            int64\n",
       "DOCUMENTDATE             object\n",
       "C_DOCTYPE_ID             object\n",
       "REF_ORG                 float64\n",
       "C_COSTCENTER_ID         float64\n",
       "COM_BPARTNER_ID         float64\n",
       "M_PRODUCT_ID            float64\n",
       "REQUESTNO               float64\n",
       "REQUESTDATE              object\n",
       "PITYPE                   object\n",
       "ADDRESS_ID               object\n",
       "ABVIOUSTYPE             float64\n",
       "PC_ACTIVITIES_ID        float64\n",
       "M_PIINOUT_REQUEST_ID    float64\n",
       "ACCEPTANCETYPE           object\n",
       "RESPONSIBLEBPARTNER      object\n",
       "RESPONSIBLEMANAGER      float64\n",
       "FROMUSERMANAGERID       float64\n",
       "COM_BPARTNER_ID_F       float64\n",
       "LETTERNO                 object\n",
       "LETTERDATE               object\n",
       "SUB_REF_ORG              object\n",
       "STRING3                  object\n",
       "M_INOUT_AMVAL_ID        float64\n",
       "DOCUMENTNO1             float64\n",
       "LOCATIONS_ID            float64\n",
       "ACCT_AC_HOLDING_ID      float64\n",
       "VAHED_MALI              float64\n",
       "ACCT_AC_JOURNAL_ID      float64\n",
       "BASEINFO_RECORDID       float64\n",
       "C_YEAR_ID               float64\n",
       "Unnamed: 43             float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# each column's dtype\n",
    "INOUT.dtypes\n",
    "\n",
    "# i = INOUT['INOUT_ID'].dtype\n",
    "# print(type(i))\n",
    "# if i == 'int64':\n",
    "#     print('heloo')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7592    470737412.0\n",
       "7593    470737412.0\n",
       "7594    470737412.0\n",
       "7595    470737412.0\n",
       "7596            NaN\n",
       "7597    470737412.0\n",
       "7598    470737412.0\n",
       "7599            NaN\n",
       "Name: C_YEAR_ID, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# INOUT.INOUT_ID.head(9)\n",
    "INOUT.C_YEAR_ID.tail(8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "183\n"
     ]
    }
   ],
   "source": [
    "# unique values in the 'VAHED_MALI' column\n",
    "\n",
    "# pd.unique(INOUT[\"VAHED_MALI\"])\n",
    "\n",
    "b = INOUT[\"DOCUMENTNO1\"].nunique()\n",
    "\n",
    "# print(a)\n",
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      232.000000\n",
       "mean       465.038793\n",
       "std       1515.408117\n",
       "min          1.000000\n",
       "25%         45.750000\n",
       "50%        138.500000\n",
       "75%        441.750000\n",
       "max      13877.000000\n",
       "Name: DOCUMENTNO1, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# statistics summery\n",
    "\n",
    "# INOUT.describe()\n",
    "\n",
    "INOUT['DOCUMENTNO1'].describe()\n",
    "\n",
    "# INOUT['DOCUMENTNO1'].median()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "ufunc 'true_divide' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32me:\\taha\\code\\DM\\ph1\\src\\test_pd_methods.ipynb Cell 7\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/e%3A/taha/code/DM/ph1/src/test_pd_methods.ipynb#X12sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m INOUT\u001b[39m.\u001b[39;49mboxplot(by\u001b[39m=\u001b[39;49m\u001b[39m'\u001b[39;49m\u001b[39mLETTERNO\u001b[39;49m\u001b[39m'\u001b[39;49m,column\u001b[39m=\u001b[39;49m[\u001b[39m'\u001b[39;49m\u001b[39mDESCRIPTION\u001b[39;49m\u001b[39m'\u001b[39;49m],grid\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m)\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\pandas\\plotting\\_core.py:511\u001b[0m, in \u001b[0;36mboxplot_frame\u001b[1;34m(self, column, by, ax, fontsize, rot, grid, figsize, layout, return_type, backend, **kwargs)\u001b[0m\n\u001b[0;32m    494\u001b[0m \u001b[39m@Substitution\u001b[39m(backend\u001b[39m=\u001b[39m_backend_doc)\n\u001b[0;32m    495\u001b[0m \u001b[39m@Appender\u001b[39m(_boxplot_doc)\n\u001b[0;32m    496\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mboxplot_frame\u001b[39m(\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    508\u001b[0m     \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs,\n\u001b[0;32m    509\u001b[0m ):\n\u001b[0;32m    510\u001b[0m     plot_backend \u001b[39m=\u001b[39m _get_plot_backend(backend)\n\u001b[1;32m--> 511\u001b[0m     \u001b[39mreturn\u001b[39;00m plot_backend\u001b[39m.\u001b[39mboxplot_frame(\n\u001b[0;32m    512\u001b[0m         \u001b[39mself\u001b[39m,\n\u001b[0;32m    513\u001b[0m         column\u001b[39m=\u001b[39mcolumn,\n\u001b[0;32m    514\u001b[0m         by\u001b[39m=\u001b[39mby,\n\u001b[0;32m    515\u001b[0m         ax\u001b[39m=\u001b[39max,\n\u001b[0;32m    516\u001b[0m         fontsize\u001b[39m=\u001b[39mfontsize,\n\u001b[0;32m    517\u001b[0m         rot\u001b[39m=\u001b[39mrot,\n\u001b[0;32m    518\u001b[0m         grid\u001b[39m=\u001b[39mgrid,\n\u001b[0;32m    519\u001b[0m         figsize\u001b[39m=\u001b[39mfigsize,\n\u001b[0;32m    520\u001b[0m         layout\u001b[39m=\u001b[39mlayout,\n\u001b[0;32m    521\u001b[0m         return_type\u001b[39m=\u001b[39mreturn_type,\n\u001b[0;32m    522\u001b[0m         \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs,\n\u001b[0;32m    523\u001b[0m     )\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\pandas\\plotting\\_matplotlib\\boxplot.py:425\u001b[0m, in \u001b[0;36mboxplot_frame\u001b[1;34m(self, column, by, ax, fontsize, rot, grid, figsize, layout, return_type, **kwds)\u001b[0m\n\u001b[0;32m    410\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mboxplot_frame\u001b[39m(\n\u001b[0;32m    411\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[0;32m    412\u001b[0m     column\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    421\u001b[0m     \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwds,\n\u001b[0;32m    422\u001b[0m ):\n\u001b[0;32m    423\u001b[0m     \u001b[39mimport\u001b[39;00m \u001b[39mmatplotlib\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mpyplot\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mplt\u001b[39;00m\n\u001b[1;32m--> 425\u001b[0m     ax \u001b[39m=\u001b[39m boxplot(\n\u001b[0;32m    426\u001b[0m         \u001b[39mself\u001b[39m,\n\u001b[0;32m    427\u001b[0m         column\u001b[39m=\u001b[39mcolumn,\n\u001b[0;32m    428\u001b[0m         by\u001b[39m=\u001b[39mby,\n\u001b[0;32m    429\u001b[0m         ax\u001b[39m=\u001b[39max,\n\u001b[0;32m    430\u001b[0m         fontsize\u001b[39m=\u001b[39mfontsize,\n\u001b[0;32m    431\u001b[0m         grid\u001b[39m=\u001b[39mgrid,\n\u001b[0;32m    432\u001b[0m         rot\u001b[39m=\u001b[39mrot,\n\u001b[0;32m    433\u001b[0m         figsize\u001b[39m=\u001b[39mfigsize,\n\u001b[0;32m    434\u001b[0m         layout\u001b[39m=\u001b[39mlayout,\n\u001b[0;32m    435\u001b[0m         return_type\u001b[39m=\u001b[39mreturn_type,\n\u001b[0;32m    436\u001b[0m         \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwds,\n\u001b[0;32m    437\u001b[0m     )\n\u001b[0;32m    438\u001b[0m     plt\u001b[39m.\u001b[39mdraw_if_interactive()\n\u001b[0;32m    439\u001b[0m     \u001b[39mreturn\u001b[39;00m ax\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\pandas\\plotting\\_matplotlib\\boxplot.py:372\u001b[0m, in \u001b[0;36mboxplot\u001b[1;34m(data, column, by, ax, fontsize, rot, grid, figsize, layout, return_type, **kwds)\u001b[0m\n\u001b[0;32m    367\u001b[0m         columns \u001b[39m=\u001b[39m [column]\n\u001b[0;32m    369\u001b[0m \u001b[39mif\u001b[39;00m by \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m    370\u001b[0m     \u001b[39m# Prefer array return type for 2-D plots to match the subplot layout\u001b[39;00m\n\u001b[0;32m    371\u001b[0m     \u001b[39m# https://github.com/pandas-dev/pandas/pull/12216#issuecomment-241175580\u001b[39;00m\n\u001b[1;32m--> 372\u001b[0m     result \u001b[39m=\u001b[39m _grouped_plot_by_column(\n\u001b[0;32m    373\u001b[0m         plot_group,\n\u001b[0;32m    374\u001b[0m         data,\n\u001b[0;32m    375\u001b[0m         columns\u001b[39m=\u001b[39;49mcolumns,\n\u001b[0;32m    376\u001b[0m         by\u001b[39m=\u001b[39;49mby,\n\u001b[0;32m    377\u001b[0m         grid\u001b[39m=\u001b[39;49mgrid,\n\u001b[0;32m    378\u001b[0m         figsize\u001b[39m=\u001b[39;49mfigsize,\n\u001b[0;32m    379\u001b[0m         ax\u001b[39m=\u001b[39;49max,\n\u001b[0;32m    380\u001b[0m         layout\u001b[39m=\u001b[39;49mlayout,\n\u001b[0;32m    381\u001b[0m         return_type\u001b[39m=\u001b[39;49mreturn_type,\n\u001b[0;32m    382\u001b[0m     )\n\u001b[0;32m    383\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m    384\u001b[0m     \u001b[39mif\u001b[39;00m return_type \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\pandas\\plotting\\_matplotlib\\boxplot.py:251\u001b[0m, in \u001b[0;36m_grouped_plot_by_column\u001b[1;34m(plotf, data, columns, by, numeric_only, grid, figsize, ax, layout, return_type, **kwargs)\u001b[0m\n\u001b[0;32m    249\u001b[0m gp_col \u001b[39m=\u001b[39m grouped[col]\n\u001b[0;32m    250\u001b[0m keys, values \u001b[39m=\u001b[39m \u001b[39mzip\u001b[39m(\u001b[39m*\u001b[39mgp_col)\n\u001b[1;32m--> 251\u001b[0m re_plotf \u001b[39m=\u001b[39m plotf(keys, values, ax, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m    252\u001b[0m ax\u001b[39m.\u001b[39mset_title(col)\n\u001b[0;32m    253\u001b[0m ax\u001b[39m.\u001b[39mset_xlabel(pprint_thing(by))\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\pandas\\plotting\\_matplotlib\\boxplot.py:338\u001b[0m, in \u001b[0;36mboxplot.<locals>.plot_group\u001b[1;34m(keys, values, ax)\u001b[0m\n\u001b[0;32m    336\u001b[0m keys \u001b[39m=\u001b[39m [pprint_thing(x) \u001b[39mfor\u001b[39;00m x \u001b[39min\u001b[39;00m keys]\n\u001b[0;32m    337\u001b[0m values \u001b[39m=\u001b[39m [np\u001b[39m.\u001b[39masarray(remove_na_arraylike(v), dtype\u001b[39m=\u001b[39m\u001b[39mobject\u001b[39m) \u001b[39mfor\u001b[39;00m v \u001b[39min\u001b[39;00m values]\n\u001b[1;32m--> 338\u001b[0m bp \u001b[39m=\u001b[39m ax\u001b[39m.\u001b[39mboxplot(values, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwds)\n\u001b[0;32m    339\u001b[0m \u001b[39mif\u001b[39;00m fontsize \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m    340\u001b[0m     ax\u001b[39m.\u001b[39mtick_params(axis\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mboth\u001b[39m\u001b[39m\"\u001b[39m, labelsize\u001b[39m=\u001b[39mfontsize)\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\__init__.py:1412\u001b[0m, in \u001b[0;36m_preprocess_data.<locals>.inner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1409\u001b[0m \u001b[39m@functools\u001b[39m\u001b[39m.\u001b[39mwraps(func)\n\u001b[0;32m   1410\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39minner\u001b[39m(ax, \u001b[39m*\u001b[39margs, data\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs):\n\u001b[0;32m   1411\u001b[0m     \u001b[39mif\u001b[39;00m data \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m-> 1412\u001b[0m         \u001b[39mreturn\u001b[39;00m func(ax, \u001b[39m*\u001b[39m\u001b[39mmap\u001b[39m(sanitize_sequence, args), \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m   1414\u001b[0m     bound \u001b[39m=\u001b[39m new_sig\u001b[39m.\u001b[39mbind(ax, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[0;32m   1415\u001b[0m     auto_label \u001b[39m=\u001b[39m (bound\u001b[39m.\u001b[39marguments\u001b[39m.\u001b[39mget(label_namer)\n\u001b[0;32m   1416\u001b[0m                   \u001b[39mor\u001b[39;00m bound\u001b[39m.\u001b[39mkwargs\u001b[39m.\u001b[39mget(label_namer))\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\axes\\_axes.py:3711\u001b[0m, in \u001b[0;36mAxes.boxplot\u001b[1;34m(self, x, notch, sym, vert, whis, positions, widths, patch_artist, bootstrap, usermedians, conf_intervals, meanline, showmeans, showcaps, showbox, showfliers, boxprops, labels, flierprops, medianprops, meanprops, capprops, whiskerprops, manage_ticks, autorange, zorder)\u001b[0m\n\u001b[0;32m   3708\u001b[0m \u001b[39mif\u001b[39;00m bootstrap \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m   3709\u001b[0m     bootstrap \u001b[39m=\u001b[39m rcParams[\u001b[39m'\u001b[39m\u001b[39mboxplot.bootstrap\u001b[39m\u001b[39m'\u001b[39m]\n\u001b[1;32m-> 3711\u001b[0m bxpstats \u001b[39m=\u001b[39m cbook\u001b[39m.\u001b[39;49mboxplot_stats(x, whis\u001b[39m=\u001b[39;49mwhis, bootstrap\u001b[39m=\u001b[39;49mbootstrap,\n\u001b[0;32m   3712\u001b[0m                                labels\u001b[39m=\u001b[39;49mlabels, autorange\u001b[39m=\u001b[39;49mautorange)\n\u001b[0;32m   3713\u001b[0m \u001b[39mif\u001b[39;00m notch \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[0;32m   3714\u001b[0m     notch \u001b[39m=\u001b[39m rcParams[\u001b[39m'\u001b[39m\u001b[39mboxplot.notch\u001b[39m\u001b[39m'\u001b[39m]\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1195\u001b[0m, in \u001b[0;36mboxplot_stats\u001b[1;34m(X, whis, bootstrap, labels, autorange)\u001b[0m\n\u001b[0;32m   1192\u001b[0m x \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39masarray(x)\n\u001b[0;32m   1194\u001b[0m \u001b[39m# arithmetic mean\u001b[39;00m\n\u001b[1;32m-> 1195\u001b[0m stats[\u001b[39m'\u001b[39m\u001b[39mmean\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39;49mmean(x)\n\u001b[0;32m   1197\u001b[0m \u001b[39m# medians and quartiles\u001b[39;00m\n\u001b[0;32m   1198\u001b[0m q1, med, q3 \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mpercentile(x, [\u001b[39m25\u001b[39m, \u001b[39m50\u001b[39m, \u001b[39m75\u001b[39m])\n",
      "File \u001b[1;32m<__array_function__ internals>:180\u001b[0m, in \u001b[0;36mmean\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\numpy\\core\\fromnumeric.py:3474\u001b[0m, in \u001b[0;36mmean\u001b[1;34m(a, axis, dtype, out, keepdims, where)\u001b[0m\n\u001b[0;32m   3471\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[0;32m   3472\u001b[0m         \u001b[39mreturn\u001b[39;00m mean(axis\u001b[39m=\u001b[39maxis, dtype\u001b[39m=\u001b[39mdtype, out\u001b[39m=\u001b[39mout, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[1;32m-> 3474\u001b[0m \u001b[39mreturn\u001b[39;00m _methods\u001b[39m.\u001b[39m_mean(a, axis\u001b[39m=\u001b[39maxis, dtype\u001b[39m=\u001b[39mdtype,\n\u001b[0;32m   3475\u001b[0m                       out\u001b[39m=\u001b[39mout, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n",
      "File \u001b[1;32mc:\\Users\\siedt\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\numpy\\core\\_methods.py:191\u001b[0m, in \u001b[0;36m_mean\u001b[1;34m(a, axis, dtype, out, keepdims, where)\u001b[0m\n\u001b[0;32m    189\u001b[0m         ret \u001b[39m=\u001b[39m ret\u001b[39m.\u001b[39mdtype\u001b[39m.\u001b[39mtype(ret \u001b[39m/\u001b[39m rcount)\n\u001b[0;32m    190\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m--> 191\u001b[0m     ret \u001b[39m=\u001b[39m ret \u001b[39m/\u001b[39;49m rcount\n\u001b[0;32m    193\u001b[0m \u001b[39mreturn\u001b[39;00m ret\n",
      "\u001b[1;31mTypeError\u001b[0m: ufunc 'true_divide' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "INOUT.boxplot(by='LETTERNO',column=['DESCRIPTION'],grid=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AD_CLIENT_ID</th>\n",
       "      <th>AD_ORG_ID</th>\n",
       "      <th>CREATEDBY</th>\n",
       "      <th>UPDATEDBY</th>\n",
       "      <th>NAME</th>\n",
       "      <th>DOCUMENTNO</th>\n",
       "      <th>C_DOCSTATUS_ID</th>\n",
       "      <th>REF_ORG</th>\n",
       "      <th>C_COSTCENTER_ID</th>\n",
       "      <th>COM_BPARTNER_ID</th>\n",
       "      <th>...</th>\n",
       "      <th>COM_BPARTNER_ID_F</th>\n",
       "      <th>M_INOUT_AMVAL_ID</th>\n",
       "      <th>DOCUMENTNO1</th>\n",
       "      <th>LOCATIONS_ID</th>\n",
       "      <th>ACCT_AC_HOLDING_ID</th>\n",
       "      <th>VAHED_MALI</th>\n",
       "      <th>ACCT_AC_JOURNAL_ID</th>\n",
       "      <th>BASEINFO_RECORDID</th>\n",
       "      <th>C_YEAR_ID</th>\n",
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       "      <td>0.0</td>\n",
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       "      <td>14.0</td>\n",
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       "      <td>469638776.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "      <td>1000876.0</td>\n",
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       "      <td>470903280.0</td>\n",
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       "      <td>3000025.0</td>\n",
       "      <td>200000538.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>105003577.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000876.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>470744640</th>\n",
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       "      <td>7064.0</td>\n",
       "      <td>3000025.0</td>\n",
       "      <td>210000080.0</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>300001364.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000147.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>210000001.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>469638739.0</td>\n",
       "      <td>469637411.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470744641</th>\n",
       "      <td>104000002.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>469637406.0</td>\n",
       "      <td>469637406.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7066.0</td>\n",
       "      <td>3000025.0</td>\n",
       "      <td>200000647.0</td>\n",
       "      <td>469638214.0</td>\n",
       "      <td>300171539.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000199.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>200000138.0</td>\n",
       "      <td>470916937.0</td>\n",
       "      <td>469638686.0</td>\n",
       "      <td>469637411.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7600 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           AD_CLIENT_ID  AD_ORG_ID    CREATEDBY    UPDATEDBY  NAME  \\\n",
       "INOUT_ID                                                             \n",
       "210032665   104000002.0        0.0  210035294.0  210035294.0   NaN   \n",
       "469637407   104000002.0        0.0  210619039.0  210032662.0   NaN   \n",
       "469637409   104000002.0        0.0  210032662.0  210032662.0   NaN   \n",
       "469637410   104000002.0        0.0  210032662.0  210032662.0   NaN   \n",
       "469637411   104000002.0        0.0  210032662.0  210032662.0   NaN   \n",
       "...                 ...        ...          ...          ...   ...   \n",
       "470644637   104000002.0        0.0  469637406.0  469637406.0   NaN   \n",
       "470644638   104000002.0        0.0  469637406.0  469637406.0   NaN   \n",
       "470644639   104000002.0        0.0  469637406.0  469637406.0   NaN   \n",
       "470744640   104000002.0        0.0  469637406.0  469637406.0   NaN   \n",
       "470744641   104000002.0        0.0  469637406.0  469637406.0   NaN   \n",
       "\n",
       "           DOCUMENTNO  C_DOCSTATUS_ID      REF_ORG  C_COSTCENTER_ID  \\\n",
       "INOUT_ID                                                              \n",
       "210032665         NaN       3000018.0  200000142.0      210000013.0   \n",
       "469637407        29.0       3000025.0  200000407.0      210000022.0   \n",
       "469637409        31.0       3000025.0  200000471.0      210032656.0   \n",
       "469637410        32.0       3000025.0  200000119.0      200000106.0   \n",
       "469637411        33.0       3000025.0  210619769.0      210032638.0   \n",
       "...               ...             ...          ...              ...   \n",
       "470644637      7025.0       3000025.0  200000538.0             14.0   \n",
       "470644638      7026.0       3000025.0  200000538.0             14.0   \n",
       "470644639      7027.0       3000025.0  200000538.0             14.0   \n",
       "470744640      7064.0       3000025.0  210000080.0           1117.0   \n",
       "470744641      7066.0       3000025.0  200000647.0      469638214.0   \n",
       "\n",
       "           COM_BPARTNER_ID  ...  COM_BPARTNER_ID_F  M_INOUT_AMVAL_ID  \\\n",
       "INOUT_ID                    ...                                        \n",
       "210032665      105001250.0  ...                NaN               NaN   \n",
       "469637407      210619283.0  ...                NaN               NaN   \n",
       "469637409      300001360.0  ...                NaN               NaN   \n",
       "469637410      105001127.0  ...                NaN               NaN   \n",
       "469637411      210619283.0  ...                NaN               NaN   \n",
       "...                    ...  ...                ...               ...   \n",
       "470644637      105003577.0  ...                NaN               NaN   \n",
       "470644638      105003577.0  ...                NaN               NaN   \n",
       "470644639      105003577.0  ...                NaN               NaN   \n",
       "470744640      300001364.0  ...                NaN               NaN   \n",
       "470744641      300171539.0  ...                NaN               NaN   \n",
       "\n",
       "           DOCUMENTNO1  LOCATIONS_ID  ACCT_AC_HOLDING_ID   VAHED_MALI  \\\n",
       "INOUT_ID                                                                \n",
       "210032665          NaN           NaN                 1.0          NaN   \n",
       "469637407          NaN           NaN                 1.0  200000138.0   \n",
       "469637409          NaN           NaN                 1.0  200000138.0   \n",
       "469637410          NaN           NaN                 1.0  200000138.0   \n",
       "469637411          NaN           NaN                 1.0  200000138.0   \n",
       "...                ...           ...                 ...          ...   \n",
       "470644637          NaN     1000876.0                 4.0  200000538.0   \n",
       "470644638          NaN     1000876.0                 4.0  200000538.0   \n",
       "470644639          NaN     1000876.0                 4.0  200000538.0   \n",
       "470744640          NaN     1000147.0                 1.0  210000001.0   \n",
       "470744641          NaN     1000199.0                 1.0  200000138.0   \n",
       "\n",
       "           ACCT_AC_JOURNAL_ID  BASEINFO_RECORDID    C_YEAR_ID  Unnamed: 43  \n",
       "INOUT_ID                                                                    \n",
       "210032665                 NaN                NaN          NaN          NaN  \n",
       "469637407         470900574.0                NaN          NaN          NaN  \n",
       "469637409         470900574.0                NaN          NaN          NaN  \n",
       "469637410         470900574.0                NaN          NaN          NaN  \n",
       "469637411         470900574.0                NaN          NaN          NaN  \n",
       "...                       ...                ...          ...          ...  \n",
       "470644637         470903280.0        469638776.0  469637411.0          NaN  \n",
       "470644638         470903280.0        469638776.0  469637411.0          NaN  \n",
       "470644639         470903280.0        469638449.0  469637411.0          NaN  \n",
       "470744640                 NaN        469638739.0  469637411.0          NaN  \n",
       "470744641         470916937.0        469638686.0  469637411.0          NaN  \n",
       "\n",
       "[7600 rows x 27 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group data\n",
    "\n",
    "grouped_data = INOUT.groupby('INOUT_ID')\n",
    "\n",
    "grouped_data.median()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "UPDATEDBY\n",
       "210032662      3\n",
       "210032977      0\n",
       "210033167      0\n",
       "210033614      2\n",
       "210035294      0\n",
       "210618973      0\n",
       "210619032    227\n",
       "210619039      0\n",
       "469637406      0\n",
       "469637484      0\n",
       "469638254      0\n",
       "469640523      0\n",
       "470766401      0\n",
       "Name: DOCUMENTNO1, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count the number of samples\n",
    "INOUT.groupby('UPDATEDBY')['DOCUMENTNO1'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas\n",
    "import pandas as pd\n",
    "from prettytable import PrettyTable\n",
    "\n",
    "dataSet = pd.read_csv('Data set/INOUT.csv')\n",
    "title = [\"name\", \"type\",\"min\", \"max\", \"mean\", \"median\"]\n",
    "\n",
    "table = PrettyTable()\n",
    "maxList = []\n",
    "minList = []\n",
    "typeList = []\n",
    "meanList = []\n",
    "nameList = []\n",
    "medianList = []\n",
    "modeList = []\n",
    "\n",
    "for attribute in dataSet.columns:\n",
    "    if dataSet[attribute].dtype == 'object':\n",
    "        continue\n",
    "    nameList.append(attribute)\n",
    "    typeList.append(dataSet[attribute].dtype)\n",
    "    minList.append(dataSet[attribute].min())\n",
    "    maxList.append(dataSet[attribute].max())\n",
    "    meanList.append(dataSet[attribute].mean())\n",
    "    medianList.append(dataSet[attribute].median())\n",
    "\n",
    "\n",
    "table.add_column(title[0], nameList)\n",
    "table.add_column(title[1], typeList)\n",
    "table.add_column(title[2], minList)\n",
    "table.add_column(title[3], maxList)\n",
    "table.add_column(title[4], meanList)\n",
    "table.add_column(title[5], medianList)\n",
    "\n",
    "print(table)\n"
   ]
  }
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