testing scraping total_impressions

.gitignore

@@ -0,0 +1 @@
+demo.xlsx

.idea/jupyter-settings.xml

@@ -0,0 +1,17 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="JupyterPersistentConnectionParameters">
+    <option name="moduleParameters">
+      <map>
+        <entry key="$PROJECT_DIR$/.idea/slide-demo.iml">
+          <value>
+            <JupyterConnectionParameters>
+              <option name="managed" value="true" />
+              <option name="sdkName" value="/opt/anaconda3" />
+            </JupyterConnectionParameters>
+          </value>
+        </entry>
+      </map>
+    </option>
+  </component>
+</project>

app.py

@@ -11,9 +11,17 @@ if uploaded_file is not None:
     processor = Processor()
     processor.load_data(uploaded_file)
 
-    slide_url = slide.create_presentation("Carching Presentation Testing")
+    # slide_url = slide.create_presentation("Carching Presentation Testing")
+    # st.write(f"Here's the new slide url {slide_url}")
 
-    st.write(f"Here's the new slide url {slide_url}")
+    st.write(f"Total Impressions: {processor.total_impressions}")
+    st.write(f"Actual Impressions Percentage: {processor.actual_impressions_percentage}")
+    st.write(f"Target Impressions Percentage: {processor.target_impressions_percentage}")
+    st.write(f"Distance Travelled: {processor.distance_travelled}")
+    st.write(f"Target Travelled: {processor.target_travelled}")
+    st.write(f"Actual Travelled: {processor.actual_travelled}")
+    st.write(f"Total On Road: {processor.total_on_road}")
+    st.write(f"High Traffic Percentage: {processor.high_traffic_percentage}")
+    st.write(f"Normal Traffic Percentage: {processor.normal_traffic_percentage}")
 
-    st.write(processor.df)
 

notebook.ipynb

@@ -2,15 +2,346 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "initial_id",
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2024-11-18T17:27:45.765230Z",
+     "start_time": "2024-11-18T17:27:43.764041Z"
+    }
    },
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_excel('demo.xlsx')"
+   ],
    "outputs": [],
+   "execution_count": 2
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-11-18T18:29:32.919196Z",
+     "start_time": "2024-11-18T18:29:32.841076Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "df",
+   "id": "3fc9b282a2a5215d",
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "'impression'",
+     "output_type": "error",
+     "traceback": [
+      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
+      "\u001B[0;31mKeyError\u001B[0m                                  Traceback (most recent call last)",
+      "File \u001B[0;32m/opt/anaconda3/lib/python3.11/site-packages/pandas/core/indexes/base.py:3805\u001B[0m, in \u001B[0;36mIndex.get_loc\u001B[0;34m(self, key)\u001B[0m\n\u001B[1;32m   3804\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m-> 3805\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_engine\u001B[38;5;241m.\u001B[39mget_loc(casted_key)\n\u001B[1;32m   3806\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mKeyError\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m err:\n",
+      "File \u001B[0;32mindex.pyx:167\u001B[0m, in \u001B[0;36mpandas._libs.index.IndexEngine.get_loc\u001B[0;34m()\u001B[0m\n",
+      "File \u001B[0;32mindex.pyx:196\u001B[0m, in \u001B[0;36mpandas._libs.index.IndexEngine.get_loc\u001B[0;34m()\u001B[0m\n",
+      "File \u001B[0;32mpandas/_libs/hashtable_class_helper.pxi:7081\u001B[0m, in \u001B[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001B[0;34m()\u001B[0m\n",
+      "File \u001B[0;32mpandas/_libs/hashtable_class_helper.pxi:7089\u001B[0m, in \u001B[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001B[0;34m()\u001B[0m\n",
+      "\u001B[0;31mKeyError\u001B[0m: 'impression'",
+      "\nThe above exception was the direct cause of the following exception:\n",
+      "\u001B[0;31mKeyError\u001B[0m                                  Traceback (most recent call last)",
+      "Cell \u001B[0;32mIn[21], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m df[\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mimpression\u001B[39m\u001B[38;5;124m'\u001B[39m] \u001B[38;5;241m=\u001B[39m df[\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mimpression\u001B[39m\u001B[38;5;124m'\u001B[39m]\u001B[38;5;241m.\u001B[39mstr\u001B[38;5;241m.\u001B[39mreplace(\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m,\u001B[39m\u001B[38;5;124m'\u001B[39m, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124m'\u001B[39m)\u001B[38;5;241m.\u001B[39mastype(\u001B[38;5;28mint\u001B[39m)\n",
+      "File \u001B[0;32m/opt/anaconda3/lib/python3.11/site-packages/pandas/core/frame.py:4102\u001B[0m, in \u001B[0;36mDataFrame.__getitem__\u001B[0;34m(self, key)\u001B[0m\n\u001B[1;32m   4100\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mcolumns\u001B[38;5;241m.\u001B[39mnlevels \u001B[38;5;241m>\u001B[39m \u001B[38;5;241m1\u001B[39m:\n\u001B[1;32m   4101\u001B[0m     \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_getitem_multilevel(key)\n\u001B[0;32m-> 4102\u001B[0m indexer \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mcolumns\u001B[38;5;241m.\u001B[39mget_loc(key)\n\u001B[1;32m   4103\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m is_integer(indexer):\n\u001B[1;32m   4104\u001B[0m     indexer \u001B[38;5;241m=\u001B[39m [indexer]\n",
+      "File \u001B[0;32m/opt/anaconda3/lib/python3.11/site-packages/pandas/core/indexes/base.py:3812\u001B[0m, in \u001B[0;36mIndex.get_loc\u001B[0;34m(self, key)\u001B[0m\n\u001B[1;32m   3807\u001B[0m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(casted_key, \u001B[38;5;28mslice\u001B[39m) \u001B[38;5;129;01mor\u001B[39;00m (\n\u001B[1;32m   3808\u001B[0m         \u001B[38;5;28misinstance\u001B[39m(casted_key, abc\u001B[38;5;241m.\u001B[39mIterable)\n\u001B[1;32m   3809\u001B[0m         \u001B[38;5;129;01mand\u001B[39;00m \u001B[38;5;28many\u001B[39m(\u001B[38;5;28misinstance\u001B[39m(x, \u001B[38;5;28mslice\u001B[39m) \u001B[38;5;28;01mfor\u001B[39;00m x \u001B[38;5;129;01min\u001B[39;00m casted_key)\n\u001B[1;32m   3810\u001B[0m     ):\n\u001B[1;32m   3811\u001B[0m         \u001B[38;5;28;01mraise\u001B[39;00m InvalidIndexError(key)\n\u001B[0;32m-> 3812\u001B[0m     \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mKeyError\u001B[39;00m(key) \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01merr\u001B[39;00m\n\u001B[1;32m   3813\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mTypeError\u001B[39;00m:\n\u001B[1;32m   3814\u001B[0m     \u001B[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001B[39;00m\n\u001B[1;32m   3815\u001B[0m     \u001B[38;5;66;03m#  InvalidIndexError. Otherwise we fall through and re-raise\u001B[39;00m\n\u001B[1;32m   3816\u001B[0m     \u001B[38;5;66;03m#  the TypeError.\u001B[39;00m\n\u001B[1;32m   3817\u001B[0m     \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_check_indexing_error(key)\n",
+      "\u001B[0;31mKeyError\u001B[0m: 'impression'"
+     ]
+    }
+   ],
+   "execution_count": 21
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-11-18T18:30:20.773902Z",
+     "start_time": "2024-11-18T18:30:20.766806Z"
+    }
+   },
+   "cell_type": "code",
    "source": [
-    ""
-   ]
+    "# Grab the Column E\n",
+    "impression_column = df.iloc[:, 4]\n",
+    "total_impressions = impression_column[impression_column.shift(-1).isna()].iloc[0]\n",
+    "\n",
+    "total_impressions\n"
+   ],
+   "id": "76eb4775dda9b64c",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "71796.3"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 23
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-11-18T17:35:53.956689Z",
+     "start_time": "2024-11-18T17:35:53.939722Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "",
+   "id": "388149da2aba2a39",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "                   Addresses Sum of New Road Duration (Mins)  \\\n",
+       "27                     Total                         16041.4   \n",
+       "30  Target (Total Campaigns)                          144000   \n",
+       "34  Target (Total Campaigns)                            2400   \n",
+       "45                     Total                         16041.4   \n",
+       "52                     Total                         16041.4   \n",
+       "59                     Total                         16041.4   \n",
+       "65                     Total                         16041.4   \n",
+       "73                     Total                         16041.4   \n",
+       "80                     Total                           15180   \n",
+       "88                     Total                         16041.4   \n",
+       "93                     Total                         16041.4   \n",
+       "\n",
+       "   Sum of New Road Duration (Hours)       % Impression     %.1 Unnamed: 6  \\\n",
+       "27                            267.4  100.0%    71796.3  100.0%        NaN   \n",
+       "30                             100%     NaN        NaN     NaN        NaN   \n",
+       "34                              100     NaN        NaN     NaN        NaN   \n",
+       "45                            267.4  100.0%    71796.3  100.0%        NaN   \n",
+       "52                            267.4  100.0%    71796.3  100.0%        NaN   \n",
+       "59                          21915.9  115628       400%     NaN      Total   \n",
+       "65                            267.4  100.0%    71796.3  100.0%        NaN   \n",
+       "73                            267.4  100.0%    71796.3  100.0%        NaN   \n",
+       "80                              253  100.0%    67497.1  100.0%        NaN   \n",
+       "88                            267.4  100.0%    71796.3  100.0%        NaN   \n",
+       "93                            267.4  100.0%    71796.3  100.0%        NaN   \n",
+       "\n",
+       "   Addresses.1 Sum of Idle Final (Mins) Sum of Idle Final (Hours)     %.2  \n",
+       "27       Total                  21915.9                     365.3  100.0%  \n",
+       "30   Idle Time             21915.866667                       NaN     NaN  \n",
+       "34         NaN                      NaN                       NaN     NaN  \n",
+       "45       Total                  21915.9                     365.3  100.0%  \n",
+       "52       Total                  21915.9                     365.3  100.0%  \n",
+       "59     16041.4                  21915.9                    115628    400%  \n",
+       "65       Total                  21915.9                     365.3  100.0%  \n",
+       "73       Total                  21915.9                     365.3  100.0%  \n",
+       "80       Total                  21228.8                     353.8  100.0%  \n",
+       "88       Total                  21915.9                     365.3  100.0%  \n",
+       "93       Total                  21915.9                     365.3  100.0%  "
+      ],
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Addresses</th>\n",
+       "      <th>Sum of New Road Duration (Mins)</th>\n",
+       "      <th>Sum of New Road Duration (Hours)</th>\n",
+       "      <th>%</th>\n",
+       "      <th>Impression</th>\n",
+       "      <th>%.1</th>\n",
+       "      <th>Unnamed: 6</th>\n",
+       "      <th>Addresses.1</th>\n",
+       "      <th>Sum of Idle Final (Mins)</th>\n",
+       "      <th>Sum of Idle Final (Hours)</th>\n",
+       "      <th>%.2</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>267.4</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>71796.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>365.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>Target (Total Campaigns)</td>\n",
+       "      <td>144000</td>\n",
+       "      <td>100%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Idle Time</td>\n",
+       "      <td>21915.866667</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>Target (Total Campaigns)</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>100</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",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>267.4</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>71796.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>365.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>267.4</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>71796.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>365.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>115628</td>\n",
+       "      <td>400%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>115628</td>\n",
+       "      <td>400%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>65</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>267.4</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>71796.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>365.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>73</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>267.4</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>71796.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>365.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>80</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>15180</td>\n",
+       "      <td>253</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>67497.1</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21228.8</td>\n",
+       "      <td>353.8</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>88</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>267.4</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>71796.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>365.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>93</th>\n",
+       "      <td>Total</td>\n",
+       "      <td>16041.4</td>\n",
+       "      <td>267.4</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>71796.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Total</td>\n",
+       "      <td>21915.9</td>\n",
+       "      <td>365.3</td>\n",
+       "      <td>100.0%</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 10
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": "",
+   "id": "7e4bdb4279ac698d"
   }
  ],
  "metadata": {

processor.py

@@ -18,6 +18,9 @@ class Processor:
     def load_data(self, file):
         self.df = pd.read_excel(file)
 
+        impression_column = self.df.iloc[:, 4]
+        self.total_impressions = impression_column[impression_column.shift(-1).isna()].iloc[0]
+
 
     def process(self):
         pass