applications_log.ipynb

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    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import plotly.graph_objects as go\n",
    "import plotly.offline as pyo"
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   "source": [
    "# Load the data from your XLSX file\n",
    "df = pd.read_excel('./applications_analytics_randomized.xlsx', engine='openpyxl')\n",
    "\n",
    "# Convert dates from string to datetime format\n",
    "df['Date'] = pd.to_datetime(df['Date'], format='%d.%m.%Y')\n",
    "\n",
    "# Set Date as the index of the dataframe\n",
    "df.set_index('Date', inplace=True)\n",
    "\n",
    "# Create a column for the week number of the year\n",
    "df['Week_Number'] = df.index.to_series().dt.isocalendar().week\n",
    "\n",
    "# Group by the week number and sum the number of applications\n",
    "df_weekly = df.groupby('Week_Number').sum()\n",
    "\n",
    "# Ensure all weeks are present\n",
    "latest_week = df['Week_Number'][df['Week_Number'].last_valid_index()]\n",
    "\n",
    "df_weekly = df_weekly.reindex(np.arange(1, latest_week+1), fill_value=0)\n",
    "\n",
    "# Reset index before creating the table\n",
    "df = df.reset_index()\n",
    "\n",
    "# Create a new dataframe for the table\n",
    "df_table = df.groupby('Week_Number').agg(\n",
    "    {'Date': [np.min, np.max]}) # Get the first and last date for each week\n",
    "df_table.columns = ['Start Date', 'End Date'] # Rename columns\n",
    "\n",
    "# Create a column for the month of the year\n",
    "df['Month'] = df['Date'].dt.month\n",
    "\n",
    "# Group by the month and sum the number of applications\n",
    "df_monthly = df.groupby('Month').sum(numeric_only=True)\n",
    "df_monthly = df_monthly.drop(['Week_Number'], axis=1)\n",
    "\n",
    "latest_month = df_monthly['Number of Applications'].last_valid_index()\n",
    "\n",
    "# Ensure all months are present\n",
    "df_monthly = df_monthly.reindex(np.arange(1, latest_month+1), fill_value=0)"
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Number of Applications</th>\n",
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       "      <th>Month</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-04-18</td>\n",
       "      <td>6</td>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
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       "      <th>1</th>\n",
       "      <td>2022-04-21</td>\n",
       "      <td>9</td>\n",
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       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-04-23</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
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       "      <th>3</th>\n",
       "      <td>2022-05-07</td>\n",
       "      <td>3</td>\n",
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       "      <td>2022-05-07</td>\n",
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       "        Date  Number of Applications  Week_Number  Month\n",
       "0 2022-04-18                       6           16      4\n",
       "1 2022-04-21                       9           16      4\n",
       "2 2022-04-23                       4           16      4\n",
       "3 2022-05-07                       3           18      5\n",
       "4 2022-05-07                       2           18      5"
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   "source": [
    "\n",
    "# Compute trendline (assuming you've already done this above)\n",
    "z = np.polyfit(df_monthly.index, df_monthly['Number of Applications'], 1)\n",
    "p = np.poly1d(z)\n",
    "\n",
    "# Create a line trace for \"Number of Applications\"\n",
    "trace1 = go.Scatter(x=df_monthly.index, \n",
    "                    y=df_monthly['Number of Applications'], \n",
    "                    mode='lines',\n",
    "                    name='Number of Applications',\n",
    "                    line=dict(color=convert_to_rgb_str(sns_palette[0])))\n",
    "\n",
    "# Create a line trace for the trendline\n",
    "trace2 = go.Scatter(x=df_monthly.index, \n",
    "                    y=p(df_monthly.index), \n",
    "                    mode='lines',\n",
    "                    name=f'Trend: y={z[0]:.2f}x + {z[1]:.2f}',\n",
    "                    line=dict(color=convert_to_rgb_str(sns_palette[1]), dash='dash'))\n",
    "\n",
    "# Layout configuration\n",
    "layout = go.Layout(title='Number of Applications by Month',\n",
    "                   xaxis=dict(title='Month Number'),\n",
    "                   yaxis=dict(title='Number of Applications'))\n",
    "\n",
    "# Combine traces and layout, and plot\n",
    "fig = go.Figure(data=[trace1, trace2], layout=layout)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Number of Applications</th>\n",
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       "      <td>32</td>\n",
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      ],
      "text/plain": [
       "       Number of Applications\n",
       "Month                        \n",
       "1                           0\n",
       "2                           0\n",
       "3                           0\n",
       "4                          19\n",
       "5                          15\n",
       "6                          20\n",
       "7                          19\n",
       "8                          35\n",
       "9                           4\n",
       "10                         32"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_monthly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Number of Applications</th>\n",
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       "    <tr>\n",
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       "      <td>14.40</td>\n",
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       "      <td>17.00</td>\n",
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       "      <td>19.75</td>\n",
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      ],
      "text/plain": [
       "       Number of Applications\n",
       "count                   10.00\n",
       "mean                    14.40\n",
       "std                     13.07\n",
       "min                      0.00\n",
       "25%                      1.00\n",
       "50%                     17.00\n",
       "75%                     19.75\n",
       "max                     35.00"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df_monthly.describe().round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
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       "144"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df_monthly['Number of Applications'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Month\n",
       "6     18.00\n",
       "7     18.00\n",
       "8     24.67\n",
       "9     19.33\n",
       "10    23.67\n",
       "Name: Number of Applications, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_monthly['Number of Applications'].rolling(window=3).mean().tail().round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
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     "metadata": {},
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   ],
   "source": [
    "# Compute trendline (assuming you've already done this above)\n",
    "z = np.polyfit(df_weekly.index, df_weekly['Number of Applications'], 1)\n",
    "p = np.poly1d(z)\n",
    "\n",
    "# Create a line trace for \"Number of Applications\"\n",
    "trace1 = go.Scatter(x=df_weekly.index, \n",
    "                    y=df_weekly['Number of Applications'], \n",
    "                    mode='lines',\n",
    "                    name='Number of Applications',\n",
    "                    line=dict(color=convert_to_rgb_str(sns_palette[0])))\n",
    "\n",
    "# Create a line trace for the trendline\n",
    "trace2 = go.Scatter(x=df_weekly.index, \n",
    "                    y=p(df_weekly.index), \n",
    "                    mode='lines',\n",
    "                    name=f'Trend: y={z[0]:.2f}x + {z[1]:.2f}',\n",
    "                    line=dict(color=convert_to_rgb_str(sns_palette[1]), dash='dash'))\n",
    "\n",
    "# Layout configuration\n",
    "layout = go.Layout(title='Number of Applications by Week',\n",
    "                   xaxis=dict(title='Week Number'),\n",
    "                   yaxis=dict(title='Number of Applications'))\n",
    "\n",
    "# Combine traces and layout, and plot\n",
    "fig = go.Figure(data=[trace1, trace2], layout=layout)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>Number of Applications</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Week_Number</th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "             Number of Applications\n",
       "Week_Number                        \n",
       "1                                 0\n",
       "2                                 0\n",
       "3                                 0\n",
       "4                                 0\n",
       "5                                 0\n",
       "6                                 0\n",
       "7                                 0\n",
       "8                                 0\n",
       "9                                 0\n",
       "10                                0\n",
       "11                                0\n",
       "12                                0\n",
       "13                                0\n",
       "14                                0\n",
       "15                                0\n",
       "16                               19\n",
       "17                                0\n",
       "18                                5\n",
       "19                               10\n",
       "20                                0\n",
       "21                                0\n",
       "22                                0\n",
       "23                                7\n",
       "24                                2\n",
       "25                               11\n",
       "26                                0\n",
       "27                                0\n",
       "28                                0\n",
       "29                                9\n",
       "30                               10\n",
       "31                               18\n",
       "32                                9\n",
       "33                                7\n",
       "34                                1\n",
       "35                                0\n",
       "36                                2\n",
       "37                                0\n",
       "38                                2\n",
       "39                                0\n",
       "40                               18\n",
       "41                               13\n",
       "42                                1"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weekly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>Number of Applications</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>42.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>19.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Number of Applications\n",
       "count                   42.00\n",
       "mean                     3.43\n",
       "std                      5.64\n",
       "min                      0.00\n",
       "25%                      0.00\n",
       "50%                      0.00\n",
       "75%                      6.50\n",
       "max                     19.00"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weekly.describe().round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Week_Number\n",
       "38    1.00\n",
       "39    1.00\n",
       "40    5.00\n",
       "41    8.25\n",
       "42    8.00\n",
       "Name: Number of Applications, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weekly['Number of Applications'].rolling(window=4).mean().tail().round(2)"
   ]
  }
 ],
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