diff --git "a/research_hod_lod.ipynb" "b/research_hod_lod.ipynb"
--- "a/research_hod_lod.ipynb"
+++ "b/research_hod_lod.ipynb"
@@ -10,10 +10,10 @@
      "output_type": "stream",
      "text": [
       "Found cached dataset text (C:/Users/WINSTON-ITX/.cache/huggingface/datasets/boomsss___text/boomsss--SPX_full_30min-37ae67efd8a1cc91/0.0.0/cb1e9bd71a82ad27976be3b12b407850fe2837d80c22c5e03a28949843a8ace2)\n",
-      "getting econ tickers: 100%|██████████| 3/3 [00:00<00:00,  4.75it/s]\n",
-      "Getting release dates: 100%|██████████| 8/8 [00:01<00:00,  4.10it/s]\n",
-      "Making indicators: 100%|██████████| 8/8 [00:00<00:00, 2664.11it/s]\n",
-      "Merging econ data: 100%|██████████| 8/8 [00:00<00:00, 999.03it/s]\n",
+      "getting econ tickers: 100%|██████████| 3/3 [00:00<00:00,  3.81it/s]\n",
+      "Getting release dates: 100%|██████████| 8/8 [00:01<00:00,  5.02it/s]\n",
+      "Making indicators: 100%|██████████| 8/8 [00:00<00:00, 7994.86it/s]\n",
+      "Merging econ data: 100%|██████████| 8/8 [00:00<00:00, 1141.77it/s]\n",
       "Found cached dataset text (C:/Users/WINSTON-ITX/.cache/huggingface/datasets/boomsss___text/boomsss--SPX_full_30min-37ae67efd8a1cc91/0.0.0/cb1e9bd71a82ad27976be3b12b407850fe2837d80c22c5e03a28949843a8ace2)\n"
      ]
     }
@@ -57,29 +57,127 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
-    "data = fr.loc['2018-07-01':]"
+    "data = fr.loc['2007-04-28':]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 22,
+   "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>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Datetime</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2007-04-30 09:00:00-04:00</th>\n",
+       "      <td>1494.07</td>\n",
+       "      <td>1494.07</td>\n",
+       "      <td>1494.07</td>\n",
+       "      <td>1494.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2007-04-30 09:30:00-04:00</th>\n",
+       "      <td>1494.07</td>\n",
+       "      <td>1495.36</td>\n",
+       "      <td>1491.92</td>\n",
+       "      <td>1493.42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2007-04-30 10:00:00-04:00</th>\n",
+       "      <td>1493.91</td>\n",
+       "      <td>1496.01</td>\n",
+       "      <td>1492.17</td>\n",
+       "      <td>1495.20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2007-04-30 10:30:00-04:00</th>\n",
+       "      <td>1495.23</td>\n",
+       "      <td>1497.16</td>\n",
+       "      <td>1494.82</td>\n",
+       "      <td>1497.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2007-04-30 11:00:00-04:00</th>\n",
+       "      <td>1496.89</td>\n",
+       "      <td>1496.93</td>\n",
+       "      <td>1495.71</td>\n",
+       "      <td>1496.05</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              Open     High      Low    Close\n",
+       "Datetime                                                     \n",
+       "2007-04-30 09:00:00-04:00  1494.07  1494.07  1494.07  1494.07\n",
+       "2007-04-30 09:30:00-04:00  1494.07  1495.36  1491.92  1493.42\n",
+       "2007-04-30 10:00:00-04:00  1493.91  1496.01  1492.17  1495.20\n",
+       "2007-04-30 10:30:00-04:00  1495.23  1497.16  1494.82  1497.00\n",
+       "2007-04-30 11:00:00-04:00  1496.89  1496.93  1495.71  1496.05"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1330294508.py:1: SettingWithCopyWarning: \n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\850442621.py:1: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
       "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
       "  data['Date'] = pd.to_datetime(data.index.date)\n",
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1330294508.py:2: SettingWithCopyWarning: \n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\850442621.py:2: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
@@ -91,28 +189,27 @@
    "source": [
     "data['Date'] = pd.to_datetime(data.index.date)\n",
     "data['HourMin'] = [f'{str(h).zfill(2)}{str(m).zfill(2)}' for h,m in zip(data.index.hour, data.index.minute)]\n",
-    "data = data.merge(gap_data, how = 'left', on ='Date')"
+    "# data = data.merge(gap_data, how = 'left', on ='Date')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Open                 float64\n",
-       "High                 float64\n",
-       "Low                  float64\n",
-       "Close                float64\n",
-       "Date          datetime64[ns]\n",
-       "HourMin               object\n",
-       "CurrentGap           float64\n",
+       "Open              float64\n",
+       "High              float64\n",
+       "Low               float64\n",
+       "Close             float64\n",
+       "Date       datetime64[ns]\n",
+       "HourMin            object\n",
        "dtype: object"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -123,26 +220,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\3315939868.py:4: SettingWithCopyWarning: \n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\3315939868.py:4: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
       "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
       "  data1['RowNumber'] = data1.groupby('Date').cumcount() + 1\n",
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\3315939868.py:7: SettingWithCopyWarning: \n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\3315939868.py:7: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
       "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
       "  data1['HighBar'] = data1['RowNumber'].where(data1.index.isin(high_idx)) > 0\n",
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\3315939868.py:10: SettingWithCopyWarning: \n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\3315939868.py:10: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
@@ -166,12 +263,866 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\1433357630.py:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
+      "  closes = data1.groupby('Date')['Date','Close'].tail(1)\n"
+     ]
+    }
+   ],
+   "source": [
+    "opens = data1.groupby('Date')[['Date','Open']].head(1)\n",
+    "closes = data1.groupby('Date')['Date','Close'].tail(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_gaps = closes.merge(opens, on = 'Date')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_gaps['PrevClose'] = df_gaps['Close'].shift(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_gaps['CurrentGap'] = ((df_gaps['Open'] - df_gaps['PrevClose']) / df_gaps['PrevClose'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>HourMin</th>\n",
+       "      <th>RowNumber</th>\n",
+       "      <th>HighBar</th>\n",
+       "      <th>LowBar</th>\n",
+       "      <th>CurrentGap</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1494.07</td>\n",
+       "      <td>1495.36</td>\n",
+       "      <td>1491.92</td>\n",
+       "      <td>1493.42</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>0930</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1493.91</td>\n",
+       "      <td>1496.01</td>\n",
+       "      <td>1492.17</td>\n",
+       "      <td>1495.20</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1495.23</td>\n",
+       "      <td>1497.16</td>\n",
+       "      <td>1494.82</td>\n",
+       "      <td>1497.00</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1496.89</td>\n",
+       "      <td>1496.93</td>\n",
+       "      <td>1495.71</td>\n",
+       "      <td>1496.05</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1100</td>\n",
+       "      <td>4</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1496.10</td>\n",
+       "      <td>1496.22</td>\n",
+       "      <td>1493.63</td>\n",
+       "      <td>1494.00</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>5</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>1493.99</td>\n",
+       "      <td>1495.33</td>\n",
+       "      <td>1493.73</td>\n",
+       "      <td>1495.33</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1200</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>1495.55</td>\n",
+       "      <td>1496.62</td>\n",
+       "      <td>1495.29</td>\n",
+       "      <td>1495.29</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>7</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1495.01</td>\n",
+       "      <td>1496.83</td>\n",
+       "      <td>1495.01</td>\n",
+       "      <td>1495.45</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>8</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1495.42</td>\n",
+       "      <td>1496.18</td>\n",
+       "      <td>1494.48</td>\n",
+       "      <td>1495.09</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1330</td>\n",
+       "      <td>9</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1495.22</td>\n",
+       "      <td>1495.68</td>\n",
+       "      <td>1492.81</td>\n",
+       "      <td>1493.08</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>1493.05</td>\n",
+       "      <td>1493.49</td>\n",
+       "      <td>1489.31</td>\n",
+       "      <td>1489.75</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1430</td>\n",
+       "      <td>11</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1490.17</td>\n",
+       "      <td>1490.65</td>\n",
+       "      <td>1487.55</td>\n",
+       "      <td>1487.92</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1500</td>\n",
+       "      <td>12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1487.87</td>\n",
+       "      <td>1488.08</td>\n",
+       "      <td>1482.31</td>\n",
+       "      <td>1482.31</td>\n",
+       "      <td>2007-04-30</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>13</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1483.00</td>\n",
+       "      <td>1486.14</td>\n",
+       "      <td>1482.26</td>\n",
+       "      <td>1482.52</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>0930</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1484.31</td>\n",
+       "      <td>1485.00</td>\n",
+       "      <td>1476.70</td>\n",
+       "      <td>1478.15</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>1477.86</td>\n",
+       "      <td>1482.04</td>\n",
+       "      <td>1477.41</td>\n",
+       "      <td>1481.93</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1482.07</td>\n",
+       "      <td>1482.72</td>\n",
+       "      <td>1480.42</td>\n",
+       "      <td>1481.94</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1100</td>\n",
+       "      <td>4</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>1481.77</td>\n",
+       "      <td>1483.99</td>\n",
+       "      <td>1480.61</td>\n",
+       "      <td>1480.61</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>5</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>1480.62</td>\n",
+       "      <td>1482.15</td>\n",
+       "      <td>1480.36</td>\n",
+       "      <td>1480.70</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1200</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>1480.72</td>\n",
+       "      <td>1482.13</td>\n",
+       "      <td>1480.33</td>\n",
+       "      <td>1480.44</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>7</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>1480.36</td>\n",
+       "      <td>1480.36</td>\n",
+       "      <td>1477.78</td>\n",
+       "      <td>1479.68</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>8</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>1479.61</td>\n",
+       "      <td>1483.42</td>\n",
+       "      <td>1479.55</td>\n",
+       "      <td>1482.70</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1330</td>\n",
+       "      <td>9</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1482.77</td>\n",
+       "      <td>1484.67</td>\n",
+       "      <td>1481.83</td>\n",
+       "      <td>1484.16</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>1484.10</td>\n",
+       "      <td>1487.27</td>\n",
+       "      <td>1483.97</td>\n",
+       "      <td>1486.15</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1430</td>\n",
+       "      <td>11</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>1486.11</td>\n",
+       "      <td>1486.81</td>\n",
+       "      <td>1484.27</td>\n",
+       "      <td>1484.27</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1500</td>\n",
+       "      <td>12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>1484.05</td>\n",
+       "      <td>1486.50</td>\n",
+       "      <td>1483.97</td>\n",
+       "      <td>1486.12</td>\n",
+       "      <td>2007-05-01</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>13</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>1486.45</td>\n",
+       "      <td>1491.90</td>\n",
+       "      <td>1486.45</td>\n",
+       "      <td>1491.47</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>0930</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>1491.76</td>\n",
+       "      <td>1494.48</td>\n",
+       "      <td>1491.76</td>\n",
+       "      <td>1493.76</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>1493.76</td>\n",
+       "      <td>1497.56</td>\n",
+       "      <td>1493.56</td>\n",
+       "      <td>1496.94</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>1496.92</td>\n",
+       "      <td>1497.01</td>\n",
+       "      <td>1495.68</td>\n",
+       "      <td>1495.98</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1100</td>\n",
+       "      <td>4</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>1495.87</td>\n",
+       "      <td>1496.08</td>\n",
+       "      <td>1495.11</td>\n",
+       "      <td>1495.58</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>5</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>1495.69</td>\n",
+       "      <td>1497.13</td>\n",
+       "      <td>1495.15</td>\n",
+       "      <td>1496.96</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1200</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>1497.00</td>\n",
+       "      <td>1497.32</td>\n",
+       "      <td>1495.72</td>\n",
+       "      <td>1496.26</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>7</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>1496.49</td>\n",
+       "      <td>1498.38</td>\n",
+       "      <td>1496.49</td>\n",
+       "      <td>1497.72</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>8</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>1497.52</td>\n",
+       "      <td>1498.37</td>\n",
+       "      <td>1497.32</td>\n",
+       "      <td>1497.88</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1330</td>\n",
+       "      <td>9</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>1497.82</td>\n",
+       "      <td>1499.10</td>\n",
+       "      <td>1497.11</td>\n",
+       "      <td>1498.97</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>10</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>1498.99</td>\n",
+       "      <td>1499.00</td>\n",
+       "      <td>1497.59</td>\n",
+       "      <td>1497.76</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1430</td>\n",
+       "      <td>11</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>1497.73</td>\n",
+       "      <td>1497.75</td>\n",
+       "      <td>1495.64</td>\n",
+       "      <td>1496.65</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1500</td>\n",
+       "      <td>12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>1496.86</td>\n",
+       "      <td>1496.97</td>\n",
+       "      <td>1494.75</td>\n",
+       "      <td>1495.77</td>\n",
+       "      <td>2007-05-02</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>13</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000222</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>1496.02</td>\n",
+       "      <td>1499.23</td>\n",
+       "      <td>1496.02</td>\n",
+       "      <td>1498.70</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>0930</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>1499.34</td>\n",
+       "      <td>1500.51</td>\n",
+       "      <td>1497.04</td>\n",
+       "      <td>1499.22</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>1498.84</td>\n",
+       "      <td>1502.91</td>\n",
+       "      <td>1498.31</td>\n",
+       "      <td>1502.63</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1030</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>1502.71</td>\n",
+       "      <td>1502.92</td>\n",
+       "      <td>1501.03</td>\n",
+       "      <td>1502.09</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1100</td>\n",
+       "      <td>4</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>1502.08</td>\n",
+       "      <td>1502.15</td>\n",
+       "      <td>1500.54</td>\n",
+       "      <td>1501.99</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1130</td>\n",
+       "      <td>5</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>1501.87</td>\n",
+       "      <td>1502.45</td>\n",
+       "      <td>1498.92</td>\n",
+       "      <td>1498.92</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1200</td>\n",
+       "      <td>6</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>1498.85</td>\n",
+       "      <td>1501.09</td>\n",
+       "      <td>1498.78</td>\n",
+       "      <td>1500.68</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>7</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>1500.67</td>\n",
+       "      <td>1501.42</td>\n",
+       "      <td>1499.22</td>\n",
+       "      <td>1499.83</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>8</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>1499.86</td>\n",
+       "      <td>1501.85</td>\n",
+       "      <td>1499.51</td>\n",
+       "      <td>1501.18</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1330</td>\n",
+       "      <td>9</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>1501.22</td>\n",
+       "      <td>1502.35</td>\n",
+       "      <td>1500.81</td>\n",
+       "      <td>1501.72</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>1502.21</td>\n",
+       "      <td>1502.71</td>\n",
+       "      <td>1500.55</td>\n",
+       "      <td>1502.71</td>\n",
+       "      <td>2007-05-03</td>\n",
+       "      <td>1430</td>\n",
+       "      <td>11</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>0.000167</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Open     High      Low    Close       Date HourMin  RowNumber  HighBar  \\\n",
+       "0   1494.07  1495.36  1491.92  1493.42 2007-04-30    0930          1    False   \n",
+       "1   1493.91  1496.01  1492.17  1495.20 2007-04-30    1000          2    False   \n",
+       "2   1495.23  1497.16  1494.82  1497.00 2007-04-30    1030          3     True   \n",
+       "3   1496.89  1496.93  1495.71  1496.05 2007-04-30    1100          4    False   \n",
+       "4   1496.10  1496.22  1493.63  1494.00 2007-04-30    1130          5    False   \n",
+       "5   1493.99  1495.33  1493.73  1495.33 2007-04-30    1200          6    False   \n",
+       "6   1495.55  1496.62  1495.29  1495.29 2007-04-30    1230          7    False   \n",
+       "7   1495.01  1496.83  1495.01  1495.45 2007-04-30    1300          8    False   \n",
+       "8   1495.42  1496.18  1494.48  1495.09 2007-04-30    1330          9    False   \n",
+       "9   1495.22  1495.68  1492.81  1493.08 2007-04-30    1400         10    False   \n",
+       "10  1493.05  1493.49  1489.31  1489.75 2007-04-30    1430         11    False   \n",
+       "11  1490.17  1490.65  1487.55  1487.92 2007-04-30    1500         12    False   \n",
+       "12  1487.87  1488.08  1482.31  1482.31 2007-04-30    1530         13    False   \n",
+       "13  1483.00  1486.14  1482.26  1482.52 2007-05-01    0930          1    False   \n",
+       "14  1484.31  1485.00  1476.70  1478.15 2007-05-01    1000          2    False   \n",
+       "15  1477.86  1482.04  1477.41  1481.93 2007-05-01    1030          3    False   \n",
+       "16  1482.07  1482.72  1480.42  1481.94 2007-05-01    1100          4    False   \n",
+       "17  1481.77  1483.99  1480.61  1480.61 2007-05-01    1130          5    False   \n",
+       "18  1480.62  1482.15  1480.36  1480.70 2007-05-01    1200          6    False   \n",
+       "19  1480.72  1482.13  1480.33  1480.44 2007-05-01    1230          7    False   \n",
+       "20  1480.36  1480.36  1477.78  1479.68 2007-05-01    1300          8    False   \n",
+       "21  1479.61  1483.42  1479.55  1482.70 2007-05-01    1330          9    False   \n",
+       "22  1482.77  1484.67  1481.83  1484.16 2007-05-01    1400         10    False   \n",
+       "23  1484.10  1487.27  1483.97  1486.15 2007-05-01    1430         11     True   \n",
+       "24  1486.11  1486.81  1484.27  1484.27 2007-05-01    1500         12    False   \n",
+       "25  1484.05  1486.50  1483.97  1486.12 2007-05-01    1530         13    False   \n",
+       "26  1486.45  1491.90  1486.45  1491.47 2007-05-02    0930          1    False   \n",
+       "27  1491.76  1494.48  1491.76  1493.76 2007-05-02    1000          2    False   \n",
+       "28  1493.76  1497.56  1493.56  1496.94 2007-05-02    1030          3    False   \n",
+       "29  1496.92  1497.01  1495.68  1495.98 2007-05-02    1100          4    False   \n",
+       "30  1495.87  1496.08  1495.11  1495.58 2007-05-02    1130          5    False   \n",
+       "31  1495.69  1497.13  1495.15  1496.96 2007-05-02    1200          6    False   \n",
+       "32  1497.00  1497.32  1495.72  1496.26 2007-05-02    1230          7    False   \n",
+       "33  1496.49  1498.38  1496.49  1497.72 2007-05-02    1300          8    False   \n",
+       "34  1497.52  1498.37  1497.32  1497.88 2007-05-02    1330          9    False   \n",
+       "35  1497.82  1499.10  1497.11  1498.97 2007-05-02    1400         10     True   \n",
+       "36  1498.99  1499.00  1497.59  1497.76 2007-05-02    1430         11    False   \n",
+       "37  1497.73  1497.75  1495.64  1496.65 2007-05-02    1500         12    False   \n",
+       "38  1496.86  1496.97  1494.75  1495.77 2007-05-02    1530         13    False   \n",
+       "39  1496.02  1499.23  1496.02  1498.70 2007-05-03    0930          1    False   \n",
+       "40  1499.34  1500.51  1497.04  1499.22 2007-05-03    1000          2    False   \n",
+       "41  1498.84  1502.91  1498.31  1502.63 2007-05-03    1030          3    False   \n",
+       "42  1502.71  1502.92  1501.03  1502.09 2007-05-03    1100          4    False   \n",
+       "43  1502.08  1502.15  1500.54  1501.99 2007-05-03    1130          5    False   \n",
+       "44  1501.87  1502.45  1498.92  1498.92 2007-05-03    1200          6    False   \n",
+       "45  1498.85  1501.09  1498.78  1500.68 2007-05-03    1230          7    False   \n",
+       "46  1500.67  1501.42  1499.22  1499.83 2007-05-03    1300          8    False   \n",
+       "47  1499.86  1501.85  1499.51  1501.18 2007-05-03    1330          9    False   \n",
+       "48  1501.22  1502.35  1500.81  1501.72 2007-05-03    1400         10    False   \n",
+       "49  1502.21  1502.71  1500.55  1502.71 2007-05-03    1430         11    False   \n",
+       "\n",
+       "    LowBar  CurrentGap  \n",
+       "0    False         NaN  \n",
+       "1    False         NaN  \n",
+       "2    False         NaN  \n",
+       "3    False         NaN  \n",
+       "4    False         NaN  \n",
+       "5    False         NaN  \n",
+       "6    False         NaN  \n",
+       "7    False         NaN  \n",
+       "8    False         NaN  \n",
+       "9    False         NaN  \n",
+       "10   False         NaN  \n",
+       "11   False         NaN  \n",
+       "12    True         NaN  \n",
+       "13   False    0.000465  \n",
+       "14   False    0.000465  \n",
+       "15   False    0.000465  \n",
+       "16   False    0.000465  \n",
+       "17   False    0.000465  \n",
+       "18   False    0.000465  \n",
+       "19   False    0.000465  \n",
+       "20    True    0.000465  \n",
+       "21   False    0.000465  \n",
+       "22   False    0.000465  \n",
+       "23   False    0.000465  \n",
+       "24   False    0.000465  \n",
+       "25   False    0.000465  \n",
+       "26    True    0.000222  \n",
+       "27   False    0.000222  \n",
+       "28   False    0.000222  \n",
+       "29   False    0.000222  \n",
+       "30   False    0.000222  \n",
+       "31   False    0.000222  \n",
+       "32   False    0.000222  \n",
+       "33   False    0.000222  \n",
+       "34   False    0.000222  \n",
+       "35   False    0.000222  \n",
+       "36   False    0.000222  \n",
+       "37   False    0.000222  \n",
+       "38   False    0.000222  \n",
+       "39    True    0.000167  \n",
+       "40   False    0.000167  \n",
+       "41   False    0.000167  \n",
+       "42   False    0.000167  \n",
+       "43   False    0.000167  \n",
+       "44   False    0.000167  \n",
+       "45   False    0.000167  \n",
+       "46   False    0.000167  \n",
+       "47   False    0.000167  \n",
+       "48   False    0.000167  \n",
+       "49   False    0.000167  "
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data1 = data1.merge(df_gaps[['Date','CurrentGap']], how = 'left', on = 'Date')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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TrPM8Bj/8MlxnS/V4/6Fp1Gi0zsS3gQa3Z1834z7/rAV9krcCn2LwkeZngV8DjmdwPOvfVtVf9lzvJQz951fVt/p8/n3UnNQbV/jejenm6nEj6DZYqurJ7m6nrwHu63t9prEuXZ2prE9Xa6rb2qS2s+65fd0srsZkt7O+TlpM68HgjPRrgbcwuDH/D3ftbwD+osc6JwE3AXcD1wB/AvxV1/aGHuu8tauxjcGPtVwD3MvgI9xbeqxzGoOfcryKwRvlp4CvdG2n9VTjPcC3gL9mcKnYV4FrGfyy2L+epXWZ8vpMfFub4nbm62YZbme9/GdM8wHcNjR898i0W3usczuDX9Iabf8h4Gs91pnWG9fdwJp52o8b/X9cyt8GeGn3nH8P/GDXfiyDW1rPzLpMeX0mvq1NcTvzdbMMt7OZOxnLM6/9//DItIN7rPOiqvrqaGNV3ZTkRT3WeX5V3QmQ5MGq+j9dnVuTvLDHOgcx2EMYtRt4fl9FqupvAJLcX1Xbu7ZvPvXRtCdTWReY2vpMY1ub1nbm62Y/THo7m8Wg/y9Jvq+qHqmqLz3VmOTlQG/figWuSnJl95xPnQk/BvhpBh/d+jKtN67LgC1JruCZ67OBwQ/H9CLJ86rqqfMnT7WtYAbXBaa2PtPY1qa1nfm62Q+T3s5m7mTsNCV5F/N/LXnzvpdadI31wJ9U1SMj7S8HfqKqPtFjrVcx//rc1dPzvwm4swY/RDPcvobBR+vP9FGne84TgfVMaF26GtNcnx9n/vXpZVub8nbm62Zxzz/x7Wzmgr77KHMO8BMM7nHzBINvlv1eVd1w4HomaT5JfqCqvt1KnVk0i/e6uZTBlwl+Hbge+HLX9itJfqGvIkkOS3JhkruT7EnyUDd8YZIXT6DOX02yzgJ9uGqWaiT5/iS/nuTTSc4amfa7E6rzvgnWeWmS/5HkoiRHJvlokjuSfD7JyyZY484+a3R1jhh9ADcnObwbnlSdIydUZ93Q8GFJPtX9bT7bXULad40XJ7m09xozuEd/R1W9bmj8pqr6oSSHALdX1at6qnM1cB1w+dCJkpcy+DTxo1V12oTrnA38WI913rCvScCXq2rJL/Zp1OjqfBG4h8Elez8LfAd4X1U9luTWqtpXP5Zrna8AVwIvAt4H/E/gswwuuzulqk6fhRpdnSf53q/yr2JwQrOq6vgZq/P03znJp4C/AT4J/Bvg7VX1nlmo0cslSNN8ALcAL6/vXkr1Z0PT7uqxzvb9mbaM6zzB4A3l+nkej85Kja7O7SPjHwH+AjiSni+xnVKd24aG73+2PiznGt1z/UcGJ11fO9T2jb6e/wDUuXVoeHR76OtvM/Eas3jVzX8Grk/yGIOrhjYAJFnJ4DBOX76Z5EMM9rS/1dV4CYM9+geebcFlWudu4N9X1T2jE5L0VWcaNQAOGbpKgar6eJLdwJ8Bh85gneFDqKNXjq2YoRpU1X9L8jngt7q/+fnMf/OxmagD/ECSDzL4VPr9SVJdAtPfoe+J15i5Y/RVdR2D+1tczuCj6E9mcD/no6rqQz2Wei+DPbc/7Y6d72Fw87QjgDNnsM5H2fffu69zG9OoAfC/gR8dbqiq32ewl/f4DNb5X0kO7Z7/6d9USPIKBrfjnZUadM+/q6rOZLAdX8PgXvG9m1KdTwL/jMEb++XAUfD04dXbZ6ZG3x91Jv0APsTgm2S/DLy/e2zq/kM2TakPP2Od5VfDOsuvBvBC4DWt1JnVv80snoz9OvDqqvrOSPvBwLaqOmEKfbi/qlZbZ3nVsM7yrWGdA1tjFo/RT+XHIJLcsa9JQC+XPLVWp6V1aa1OS+vSWp1p1JjFoP8lpvNjEC9hcC7g4ZH2ADda54DVsM7yrWGdZVpj5oK+qr6S5JVM/scgvgwcWlW3j05IcoN1DlgN6yzfGtZZpjVm7hi9JGlxZu7ySknS4hj0ktQ4g15NS/IPI+PnJPmdHp+/knxmaPygJA8m+XI3vj7Jpr7qSftj5k7GSstBkoOqai/wj8Brkrywqh4FTmVwcQAAVTUHzB2gbkqAe/R6DkuyJsl13S1hr02yumv//SRnDM33D92/70jy50nmgOEfndgMvLsbPgv4w6Fln/4E0T3vbye5McnO4RrSJBn0at0Lk9z+1AO4YGjaf2dwM7nXMbht72+P8XxvAH6xql451HYFsCHJC4DXAd/zm6lDXgb8MPCvgAvHXw1p/3noRq17tKpOemokyTnA2m70LQzu+Q3waWCcn5+7uaq+MdxQVXdk8LNvZzHYu382X6rB3TDvSk8/KiEtxKCXvtdeuk+7Gfx05fAPNP/jPpaZA/4r8A4GdyPdl8eGhrP/XZTG56EbPZfdSPd7BsBPAn/eDd8HvLEbXg88f4znugz41aq6s88OSn0w6PVc9gvAz3Q3lfop4Be79k8Cb0/yNQaHd/a1F/+0GtwbfZxj/NLUeQsESWqce/SS1DiDXpIaZ9BLUuMMeklqnEEvSY0z6CWpcQa9JDXOoJekxv1/Yhd40bzY07AAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -188,12 +1139,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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jjKki/rtgC9sOZPGXUb0pnAcw0uwalDHGmB/Iyy/g+fS19GndgKFdm0UtH3YNyhhjzA9MWLyNTRlHuPe8lKjVnsBfAXVO2HNhjDEmJuQXKM9OW0P3E+pxVo/kqObFTxOflvAwxhgTZz5Zup11uw8zbnhnqlWLXu0J/NWgPsYVSALUAjrgpmc/MYz5MsYYE2EFBcqzU9fQqVldRvZqEe3slF5AFe3BJyL9gJvCliNjjDFRMWXFTr7fcYgnL+1LQpRrT1COiQdVdQGu40SpRGSEiKwUkTUi8vtitrcTkS9F5DsRSReR1mXNjzHGmIpTVZ6ZuoZ2TepwYd+W0c4O4KMGJSK3ByxWA/oB23y8LgF4Djgb2ALMFZEJqro8YLfHgTdV9Z8iMhx4BBhThvwbY4wJgemrdrNk6wEeu6Q31RNiY9J0P7moF/CoibsmdZGP1w0A1qjqOlXNAdKKeV1PYKr3fJrPdI0xxoRQYe2pVcPaXHxy7DRkiZuLMAwJi4wGRqjqdd7yGGCgqo4L2OddYLaqPiUio4D/AE1VdW+RtMbihlwiOTk5JS0trUJ5y8zMJCkpMlMWRyNeNGLGe7xoxLR4lT9mZYm3fG8+f52bxZieNTizbWJEYgZKTU2dr6r9f7RBVYM+cNNsNAxYbgR85uN1o4FXA5bHAM8W2acl8F9gIfAUrimwYbB0U1JStKKmTZtW4TRiOV40YsZ7vGjEtHiVP2ZliXfZS7P0lIe/0KM5eRGLGQiYp8V83/vpZt5MVfcHFGj7RKS5j9dtBdoELLf21gUWjtuAUQAikgRcEhjLGGNMeM3bkMGsdXu597we1EpMiHZ2fsDPNah8EWlbuCAi7fB3o+5coIuIdBCRGsBlwITAHUSkqYgU5uFuYLy/bBtjjAmFZ6auoXHdGlwxsG3pO0eYnxrUPcBMEZmOu1n3DLzrQcGoap6IjAM+AxKA8aq6TEQewlXnJgDDgEdERIEZwM3lOwxjjDFltXjzfqav2s2dI7pRp4af4iCy/Nyo+6l3c+4gb9X/qeoeP4mr6mRgcpF19wU8/zfwb//ZNcYYEyrPTltDg9qJjBnULtpZKVapTXwicjGQq6qTVHUSkCciPw17zowxxoTNiu0H+WL5Tq49rT31apWt516k+LkGdb+qHihc8Dox3B+2HBljjAm7Z6etIalmda49tUO0s1IiPwVUcfvEXmOlMcYYX9bsOsTkJdu5enA7GtSJzdoT+Cug5onIkyLSyXs8CcwPd8aMMcaEx/PT1lKregK/Oj12a0/gr4C6BcgB3vce2VhvO2OMqZQ27j3M/xZv48qBbWmSVDPa2QnKTy++wyLyMPCwqmZGIE/GGGPC5IX0tSRUE8YO6RjtrJQqaA1KRG4SkU3ARmCjiGwUEZsLyhhjKqGt+4/ynwVbuOyUNjSvXyva2SlViQWUiNwLnA8MU9UmqtoESAVGetuMMcZUIi9NXwvADUM7RTkn/gSrQY0BRqnqusIV3vNLgavDnTFjjDGhs+tgFmlzN3NJv9a0alg72tnxJVgBpaqaVczKo0BB+LJkjDEm1F6esY78AuWmYZ2jnRXfghVQW0XkzKIrvZlvt4cvS8YYY0Jpb2Y278zexEV9W9K2SZ1oZ8e3YL34fgP8T0Rmcvy+p/7AadjMt8YYU2m8NnM9WXn53JRaeWpPEKQGparLgF64Ucbbe48ZQC9vmzHGmBi3/0gOb87ayLm9W9C5eWRnMK6ooPdBedegbI4mY4yppN74ZgOZ2XmMq2S1J/A3koQxxphK6FBWLuNnrufsnsn0aFE/2tkpMyugjDEmTr317UYOZuVxy/DKV3sCnwWUiDQTkWbhzowxxpjQOJKTx6tfrWdo12b0ad0w2tkpl2AjSYiIPCAie4CVwCoR2S0i95X0mmLSGCEiK0VkjYj8vpjtbUVkmogsFJHvROTc8h2GMcaYQO/O3kTG4Rx+c2blrD1B8BrUbbgu5aeoamNVbQQMBE4TkdtKS1hEEoDngJFAT+ByEelZZLd7gQ9U9WTgMuD5chyDMcaYAFm5+bw0Yx2DOzYhpV3jaGen3Eob6uhyVV1fuMIb6ugq/A11NABYo6rrVDUHSOPH908pUHjlrgGwzW/GjTHGFO+DeZvZfSibWypx7QlAVLX4DSJLVbVXWbcF7DMaGKGq13nLY4CBqjouYJ8WwOdAI6AucJaq/mgyRBEZC4wFSE5OTklLS/NzbCXKzMwkKSly9wNEOl40YsZ7vGjEtHiVP2Y04tWqU5c7ZxylcS3hnoG1EJGwx6zoMaamps5X1f4/2qCqxT6ABeXZFrDPaODVgOUxwLNF9rkd+K33fDCwHKgWLN2UlBStqGnTplU4jViOF42Y8R4vGjEtXuWPGY14783eqO3umqTTvt8ZsZgVBczTYr7vg92o21dEDgKBxa96y34mEtkKtAlYbu2tC/QrYIRXUM4SkVpAU2CXj/SNMcYEyC9Qnk9fS5/WDRjatfJ3vA421FGCqtZX1XoBj8LlRB9pzwW6iEgHEamB6wQxocg+m4AzAUSkB67g212+QzHGmKrt2+15bMo4wrjUzmFv2ouEUqd8F5FU4ERvcamqpvtJWFXzRGQc8BmQAIxX1WUi8hCuOjcB+C3witcrUIFrvOqeMcaYMsgvUCaty6X7CfU4q0dytLMTEiUWUCLSCvgvkMXx0cx/JiK1gYtVtWhz3Y+o6mRgcpF19wU8X47rym6MMaacsnLzeeLzlWw/rNxzUWeqVav8tScIXoN6FnhBVd8IXCkiV+PuV7IpN4wxJsq+Wr2bez9aysa9RzijVXVG9moR7SyFTLACqqeqXlx0paq+KSL3hDFPxhhjSrHrUBYPT1rBhMXb6NC0Lu9cN5DcLUtJiJPaEwQvoIrtQCEi1XDXlIwxxkRYQYHy3txNPPrJ92TnFnDrmV349bBO1EpMIH1LtHMXWsEKqEki8grwf6p6GEBE6gJ/p8h1JWOMMeG3YvtB7vlwCQs27WdwxyY8fHEvOjWrXJMQlkWwAupO4BFgo4hsxN3/1Ab4J/CHCOTNGGMMbmTyp6as5tWZ62lQO5EnL+3LxSe3iouu5MGUWECpai7wOxH5I1A4oNNaVT0SkZwZY4zhyxU7ue9/y9i6/yiXndKG34/sTsM6NaKdrYgI1s18VDGruxSW2Kr633BlyhhjqrodB7J4cOIyPlm6gy7Nk/jXjYM5pX3lHZm8PII18V1Q5PnEgGXF3SNljDEmhPILlDdnbeCJz1eRm1/AHed04/ozOlKjetWbAD1YE9+1hc9FZGHgsjHGmNBbsuUAf/hwCUu2HmBo12b86aJetG1SJ9rZippShzry2PBDxhgTJoeycnni81W8OWsDTZJq8uwVJ3Ne7xZx3wmiNH4LKGOMMSGmqny6dAcPTFzGrkPZjBnUjt+d0436tfyMxx3/gnWSmMjxmlNHEfnBSOSqemE4M2aMMfFsc8YR7p+wjKnf76Jni/q8NKY/J7VpGO1sxZRgNajHA54/Ee6MGGNMVZCbX8D4mev5x5TViMC95/XgmlPbUz2h6nWCKE2wThLTI5kRY4yJd/M37uOeD5fw/Y5DnN0zmQcuPJFWDWtHO1sxy65BGWNMmB04kstjn33Pe3M2cUL9Wrw0JoVzTjwh2tmKeVZAGWNMmKgq/1u0lT9NWk7G4Rx+eVoHbju7K0k17avXjxIbPUXkLe/vreVNXERGiMhKEVkjIr8vZvvfRWSR91glIvvLG8sYY2LJut2ZPD4vi1vTFtGqYW0mjDudP57f0wqnMgj2TqWISEvglyLyJm6w2GNUNSNYwiKSADwHnA1sAeaKyARvFt3CNG4L2P8W4OSyH4IxxsSO5dsO8nz6GiYv2U7NBHjoohO5cmC7uJqnKVKCFVAvAl8CHXFTvge+u+qtD2YAsEZV1wGISBpuFt7lJex/OXC/jzwbY0zMmbchg+fT1zL1+10k1azO2CGd6FFtOxcNbh/trFVaohp8kAgReUFVf13mhEVGAyNU9TpveQwwUFXHFbNvO+BboLWq5hezfSwwFiA5OTklLS2trNn5gczMTJKSIjeHSqTjRSNmvMeLRkyLF/sxVZWle/KZtC6XlfsKqJcIZ7dP5My2idRNFHtPfUpNTZ2vqv1/tEFVS30AfYFx3qOPz9eMBl4NWB4DPFvCvncBz/hJNyUlRStq2rRpFU4jluNFI2a8x4tGTIsXuzHz8gv04++26XlPz9B2d03SQX+ZouNnrtPD2blhiedXZX1PgXlazPd9qVfrROQ3uNpL4ejl74jIy6r6TCkv3Yqb4LBQa29dcS4Dbi4tL8YYE025+QV8tHArL0xfy7rdh+nQtC5/vaQPPz25VZUcbTzc/HQnuQ7XNFc47ftjwCygtAJqLm7+qA64guky4IqiO4lId6CRl6YxxsScozn5vD93Ey/PWMe2A1n0bFGfZ684mZG9WljnhzDyU0AJEHhdKJ8iPfqKo6p5IjIO+AxIAMar6jIReQhXnSsc2+8yIM2r5hljTMw4mJXLW7M2Mn7mevYezuGU9o3486jeDOvarMqPNB4Jfgqo14HZIvKht/xT4DU/iavqZGBykXX3FVl+wE9axhgTKXsysxk/cz1vzdrIoew8hnVrxk3DOjOgQ9Wa0TbaSi2gVPVJEUkHTvdWXauqC8OaK2OMiYIt+47wyox1pM3dTE5+Aef2asGvh3WiV6sG0c5aleTrlmZVXQAsCHNejDEmKtbsyuTF6Wv5aKHrxzWqXytuGNqJTs0i22Xb/JCNuWGMqbKWbDnA8+lr+HTZDmpWr8ZVg9px/ZCONsJ4jLACyhhTpagqc9Zn8Fz6Wmas2k29WtW5eVhnrj2tPU2SakY7eyaAn/ugbgHeVtV9EciPMcaEhaqyaFcez7w4i/kb99E0qQZ3jujGVYPa2RTrMcpPDSoZN9DrAmA88Jl1CTfGVBabM44w8bttfLRwK6t2ZtOqYTUeuuhELu3fhlqJCdHOngnCTy++e0Xkj8BPgGuBZ0XkA+A1VV0b7gwaY0xZ7TiQxcdLtjNx8TYWbd4PwEltGvKrXjX4/eXDSLTp1SsFv734VER2ADuAPNzID/8WkS9U9c5wZtAYY/zYm5nN5KU7mLR4G3M2ZKAKPVvU564R3Tm/TwvaNK5Denq6FU6ViJ9rULcCVwN7gFeBO1Q1V0SqAasBK6CMMVFx4Gguny3bwcTF2/hm7V7yC5ROzeryf2d25fy+LaybeCXnpwbVGBilqhsDV6pqgYicH55sGWNM8Q5n5zFlxU4mLt7OjFW7yckvoE3j2twwpCMX9G1J9xPq2TBEccJPAdWxaOEkIm+p6hhVXRGmfBljzDFZufmkr9zFxMXb+fL7nWTlFnBC/VpcPbgdF/RtSZ/WDaxQikN+CqgTAxe8qdxTwpMdY4xxcvIK+HrNHiYu3sbny3eSmZ1Hk7o1+FlKGy7o25L+7RpRzUYSj2slFlAicjfwB6C2iBwsXA3kAC9HIG/GmComv0D5dt1eJi7exidLd3DgaC71a1XnvN4tOL9vCwZ3bEJ16+RQZZRYQKnqI8AjIvKIqt4dwTwZY6qQggJlwaZ9TFy8jY+X7GBPZjZ1ayRwds9kLujbkjO6NLPJAKuoYDWo7qr6PfAvEelXdLs3gKwxxpSZqrL+QD5ff7ycj7/bzrYDWdSsXo0zezTngj4tSe3e3G6iNUGvQf0WuB54ophtCgwPS46MMXEpKzefWWv3MmXFTqZ+v4vtB7JITNjAkC7NuHNEd87qmUxSTRse1BwXrInveu9vauSyY4yJJ7sOZTHt+11MWbGLmav3cDQ3nzo1EjijS1PObVPALaOG0rBOjWhn08SoYE18o4K9UFX/W1riIjICeAo35furqvpoMftcCjyAq5UtVtUrSkvXGBObVJXl2w8ydcUupny/i8XeMEMtG9RidEprzuzRnEEdm1ArMYH09HQrnExQwerTFwTZpkDQAsrrjv4ccDawBTfg7ARVXR6wTxfgbuA0Vd0nIs1959wYExOycvOZtW4vX67YydQVu9h2IAuAvm0a8tuzu3Jmj2R6tLCbZ03ZBWviu7aCaQ8A1qjqOgARSQMuApYH7HM98FzhVB6ququCMY0xEbD7ULbXdLeTmWv2cCQnn9qJCZzepSm3ntWF1O7NaV6vVrSzaSo5KWnmDBG5SlXfFpHbi9uuqk8GTVhkNDBCVa/zlscAA1V1XMA+HwGrgNNwzYAPqOqnxaQ1FhgLkJycnJKWlubj0EqWmZlJUlLkxuiKdLxoxIz3eNGIGUvxVJUtmcrCXXks2pXP+gMFKNC4lnBSswT6Nk+gR+MEaiT4ryXZZ1j544UqZmpq6nxV7V90fbAmvrre33oVihxcdaALMAxoDcwQkd6quj9wJ1V9Ge/m4P79++uwYcMqFDQ9PZ2KphHL8aIRM97jRSNmtONl5+Xz7boMvlyxky9X7GLr/qMA9G3dgNsGJHNmj+b0bFG/3E139hlW/njhjhmsie8l7++D5Ux7K9AmYLm1ty7QFmC2quYC60VkFa7AmlvOmMaYCtiT6Zruvlyxi69W7+ZwTj61Eqtxeudm3DK8M8O7N6d5fWu6M5HhZ7qNjrieeINwnSNmAbcVXlsKYi7QRUQ64Aqmy4CiPfQ+Ai4HXheRpkBXoLR0jTEhcjQnn4Wb9zFnfQaT5h1l7WdTUIUT6tfiopNbcVaP5pzaqandNGuiws9dce/ieuNd7C1fBrwHDAz2IlXNE5FxwGe460vjVXWZiDwEzFPVCd62n4jIciAfN9fU3vIdijGmNJnZeczfuI/Z6/YyZ30Gi7fsJzdfEYH29apx65ldOKtHMie2LH/TnTGh4qeAqqOqbwUsvy0id/hJXFUnA5OLrLsv4LkCt3sPY0yIHTiSy5wNGcxZ7wqkpdsOkl+gJFQTerdqwC9P78DADo1JadeYhbO/ZtiwrtHOsjHHBLtRt7H39BMR+T2Qhmvi+zlFCh1jTGzYk5nNnPUZzFmfwbfr9rJy5yFUoUZCNU5q05CbhnViQIfG9GvbiLo2rJCJccHO0Pm4Aqmwnn9DwDbF3WBrjImi7QeOMmd9BrPXZzB73V7W7j4MQO3EBFLaNeLc3i0Y0KExJ7VpaNeRTKUTrBdfh0hmxBgTnKqyOeMos9fvZbZXS9qUcQSAejWr0799I0antGFgx8b0atnApqgwlZ6vOr6I9AJ6Asf6l6rqm+HKlDHGFUhrdmV6NSR3DWm7N4xQwzqJDGjfmKsHt2NQxyb0aFGfBJtd1sQZP93M78fdSNsTd+1pJDATsALKmBBSVdbuzmTW2r18uy6Dr1Ye4eBn0wFomlSTgR0bM6hDYwZ0aEKX5kk23bmJe35qUKOBvsBCVb1WRJKBt8ObLWPin6qybs9hvl2391ihtCczG4AWDWpxYtMELhrUkwEdGtOhaV3r9m2qHD8F1FFVLRCRPBGpD+zihyNEGGN8UFU27j3iCqR1e/l23V52HnQFUnL9mpzeuQmDOjZhcKcmtG1ch+nTpzNsQNso59qY6PFTQM0TkYbAK7iefZm40SSMMaXYnHHEFUZrXaFUeA2paVJNBndqwuCOTRjU0WpIxhSn1AJKVW/ynr4oIp8C9VX1u/Bmy5jKadv+o8zyCqNZa/ceG2C1Sd0aDOrYhEGdmjC4Y2M6NUuyAsmYUvjtxTcKOB13/9NMwAooY4AdB7KOXUOatW7vsW7fjeokMrBDE8YO6cjgTq5TgxVIxpSNn158zwOdcePvAdwgImep6s1hzZkxMWjXoSy+XZfhdWrYy/o97sbYBrUTGdihMdec2p7BnZrQLbme9bIzpoL81KCGAz28cfMQkX8Cy8KaK2NixOHsPL5Zu5cZq3YzZckRtn/6JeBujB3YsTFXDmxr9yEZEyZ+Cqg1QFtgo7fcxltnTNwpvBcpfeVupq3cxdz1+8jJL6BujQQ6NajGNUO6MLhTE05s2cAKJGPCLNhgsRNx15zqAStEZI63aQAwp6TXGVPZFNaS0lfuIn3l7mMdG7omJ3Htae0Z2q0Z/ds15puZMxg2tFOUc2tM1RGsBvV4xHJhTAQF1pLSV+5mzvqMY7Wk0zo35ebUzgzt1oxWDWtHO6vGVGnBBoudXvjcGz3iFG9xjqruCnfGjAmlIzl5fLNmL+mrXC1py77jtaRrTmvPsK7N6N++sQ2wakwM8dOL71Lgb0A6buqNZ0TkDlX9t4/XjsBNF58AvKqqjxbZfo2X9lZv1bOq+mpZDsCY4rha0uFjzXaFtaQ6Xi3p18M6Maxbc6slGRPD/HSSuAc4pbDWJCLNgClA0AJKRBJwU8WfDWwB5orIBFVdXmTX91V1XJlzbkwRR3LymLV2L9NW/rCW1KV5Er84tR3DujWnf/tG1Kxu8yIZUxn4KaCqFWnS2wv4aQcZAKxR1XUAIpIGXAQULaCMKZfAWtL0VbuZve54LenUTk25cWgnhnVrRutGdaKdVWNMOfgpoD4Vkc84fqOu3ynfWwGbA5a3AAOL2e8SERkCrAJuU9XNxexjDABHc/KZtW4Pby/P5o9zprE5w9WSOjdP4urB7UjtbrUkY+KFePffFr/Rjc3SGtdB4nRv9Veq+mGpCYuMBkao6nXe8hhgYGBznog0ATJVNVtEbgB+rqrDi0lrLDAWIDk5OSUtLc3v8RUrMzOTpKSkCqURy/GiETOc8XYdKeC73fl8tzufFRn55BZAjWpKzybV6dMsgd5NE2hWJ/ydG+LpPa2K8aIRM97jhSpmamrqfFXt/6MNqhr0ASwpbZ8SXjcY+Cxg+W7g7iD7JwAHSks3JSVFK2ratGkVTiOW40UjZijjZefm69erd+ufJi7T4Y9P03Z3TdJ2d03SYX+bpg9MWKozVu3Sz7+cGrJ4flXm99TiRSdmvMcLVUxgnhbzfe+niW+BiJyiqnPLWCjOBbqISAdcL73LgCsCdxCRFqq63Vu8EFhRxhgmTuw8mEX6yl1M/X4XM1fv4XBOPjUSqnnDCbmmuw5N6x7bP32rjeJgTLzzU0ANBK4SkQ3AYVxXc1XVPsFepKp5IjIO+AxXOxqvqstE5CFcaTkB+I2IXAjkARnANeU+ElOp5BcoizbvY9r3bkihZdsOAm4m2QtPasXw7s05tVMT6tb0NeC+MSYO+fnvP6e8iavqZIp0qFDV+wKe341r+jNVwL7DOcxYvZup37ted/uP5JJQTUhp24g7R3RjePfmdEuuZ9NSGGOA4GPxNQf+gJtqYwnwiKoejFTGTOWnqizbdvBY092izfspUDd53/DuzUnt1pwhXZrRoE5itLNqjIlBwWpQb+KmeH8GOB94GmuCM6U4lJXL12v2HGu623UoG4A+rRtwy/AupHZvTp9WDWyuJGNMqYIVUC1U9R7v+WcisiASGTKVz6a9R/hkfS4vr/6WuRsyyM1X6tWszpCuzRjWrRnDujWnWb2a0c6mMaaSCXoNSkQa4TpFACQELqtqRpjzZmKYqjJzzR7e+HoDU1fuQhW6Jmfzy9M7kNqtOSntGpGYYAOvGmPKL1gB1QDXxBfYFlNYi1KgY7gyZWLX4ew8/rtwK//8ZgNrdmXSpG4NbkntTJu8rfzs3KHRzp4xJo4Em26jfQTzYWLc5owjvDlrA2lzN3MoK49ererzxM/6cn7fFtSsnkB6+vbSEzHGmDKwm0xMiVSVWWv38vo3G5iyYifVRBjZ6wSuPa09/do2su7gxpiwsgLK/MjRnHw+WrSVN77ewMqdh2hUJ5GbhnXiqkHtaNHA5k8yxkSGFVDmmC37jvDWtxtJm7OZA0dz6dGiPn8d3YcL+7akVqKNDm6MiSxfBZSInA50UdXXvQkLk1R1fXizZiJBVZm9PoM3vt7A58t3ADCi1wlcc2oHTmlvzXjGmOjxM+X7/UB/oBvwOpAIvA2cFt6smXDKys1nwqJtvP7NBlZsP0jDOomMHdKJMYPb2TToxpiY4KcGdTFwMl4Xc1XdJiL1wporEzbbDxzlrVkbeW/OJvYdyaX7CfV4dFRvLjqpFbVrWDOeMSZ2+CmgclRVRUQBRKRuaS8wsUVVmb9xH69/s4FPl+5AVTm7ZzLXnNqBQR0bWzOeMSYm+SmgPhCRl4CGInI98EvglfBmy4RCVm4+k77bzhvfrGfp1oPUr1WdX53egTGD2tGmcZ1oZ88YY4IqtYBS1cdF5GzgIO461H2q+kXYc2bKbefBLP67OofffjWVvYdz6NI8iT9f3IuLT25FnRrWcdMYUzn46SRxO/C+FUqxb/ehbJ6btoZ3Zm8kL185s0cy157WnlM7NbFmPGNMpePn53Q94HMRyQDeB/6lqjvDmy1TFgezcnllxjpem7me7LwCLu3fmpNr7eHSc/tHO2vGGFNupQ43raoPquqJwM1AC2C6iEzxk7iIjBCRlSKyRkR+H2S/S0RERcS+UcsgKzefl6avZchfp/HM1DUM796cL24bwiOj+tC8jo0kboyp3MpyQWIXsAPYCzQvbWcRSQCeA84GtgBzRWSCqi4vsl894FZgdhnyUqXl5hfwwbzNPP3lanYezGZYt2b87ifd6NWqQbSzZowxIePnGtRNwKVAM+BfwPVFC5kSDADWqOo6L5004CKg6Gv/BDwG3FGGfFdJBQXKxO+28fcvVrFh7xH6t2vEM5f3Y0CHxtHOmjHGhJyoavAdRB7BdZJYVKaERUYDI1T1Om95DDBQVccF7NMPuEdVLxGRdOB3qjqvmLTGAmMBkpOTU9LS0sqSlR/JzMwkKSmpQmlEMp6q8t2efP69KpfNhwpoU68al3RJpG+zhBI7P1S2Y4z1eNGIafEqf8x4jxeqmKmpqfNV9ceXeFS12AdQ3/vbuLhHSa8LeP1o4NWA5THAswHL1YB0oL23nA70Ly3dlJQUrahp06ZVOI1IxZuzfq+OfuFrbXfXJB3y16n60cItmp9fENaY5RHv8aIR0+JV/pjxHi9UMYF5Wsz3fbAmvneB83Gz6io/nFnXz4y6W4E2AcutvXWF6gG9gHSvFnACMEFELtRialFVzbJtB3j8s5VMW7mb5vVq8vBPe/HzU9rYNOrGmCoj2Iy653t/O5Qz7blAFxHpgCuYLgOuCEj/ANC0cDlYE19VsmHPYZ74YhUTF2+jQe1Efj+yO78Y3N7GyTPGVDl+Okl8qapnlrauKFXNE5FxwGdAAjBeVZeJyEO46tyEimQ83uw4kMXTU1fz/tzN1EioxrjUzlw/pCMNaidGO2vGGBMVJRZQIlILqAM0FZFGHG/iqw+08pO4qk4GJhdZd18J+w7zk2a82Xc4hxenr+WNbzZQoMpVA9ty8/DONK9XK9pZM8aYqApWg7oB+D+gJe46VGEBdRB4NrzZin+Hs/MYP3M9L89YR2ZOHhef3Irbzupqg7gaY4wn2DWop4CnROQWVX0mgnmKa9l5+bw3exPPTlvDnswczu6ZzO9+0o1uJ9gUW8YYE8jPaObPiEgvoCdQK2D9m+HMWLzJL1A+XLiVv3+xiq37jzK4YxNevrob/do2inbWjDEmJvmd8n0YroCaDIwEZgJWQPmgqszfmcef/zGD1bsy6d2qAY9e0pvTOze1EcaNMSYIP2PxjQb6AgtV9VoRSQbeDm+24sP+Izn87l/fMWVFNp2aVeeFK/sxotcJVjAZY4wPfgqoo6paICJ5IlIfN2hsm9JeVNXN25DBb95byO7MbC7vXoM/jRlCdbvJ1hhjfPNTQM0TkYa4ad7nA5nArHBmqjIrKFBemL6WJ79YRauGtfnPr08lY80iK5yMMaaM/HSSuMl7+qKIfIobo++78Garctp9KJvbP1jEV6v3cH6fFvxlVG/q10okfU20c2aMMZVPsBt1+wXbpqoLwpOlyumbNXu49f1FHDyayyOjenPZKW3sWpMxxlRAsBrUE0G2KTA8xHmplPLyC3j6y9U8M20NHZvW5a1fDaD7CfWjnS1jjKn0gt2omxrJjFRGOw5k8Zu0hcxZn8HPUlrz4EUnUqdGWSYpNsYYUxI/90FdXdz6qn6j7rTvd3H7B4vIzivgyUv7Mqpf62hnyRhj4oqfn/unBDyvBZwJLKCK3qibk1fA45+v5OUZ6+h+Qj2eu7IfnZpFdgZLY4ypCvz04rslcNnrcl6xOdcrqc0ZR7jlvYUs2ryfMYPacc95PaiVaPM0GWNMOJTngslhoLyTGFZanyzZzp3/+Q4Unr+yH+f2bhHtLBljTFzzcw1qIq7XHkA13Jh8H4QzU7EkKzefv0xewZuzNtK3dQOeubwfbZvYlBjGGBNufmpQjwc8zwM2quqWMOUnpqzbncm4dxeyfPtBrj+jA3ec050a1W1ECGOMiQQ/16CmA3jj8FX3njdW1YzSXisiI4CncFO+v6qqjxbZfiNwM5CPG0JprKouL+tBhMNHC7fyhw+XUKN6NV77RX/O7JEc7SwZY0yV4qeJbyzwEJAFFOBm1lWgYymvSwCeA84GtgBzRWRCkQLoXVV90dv/QuBJYEQ5jiNkjuTkcf//lvGv+VsY0L4xT11+Ei0a1I5mlowxpkry08R3B9BLVfeUMe0BwBpVXQcgImnARcCxAkpVDwbsX5fj17qiYuWOQ9z87gLW7s7kluGdufXMLjbIqzHGRImoBi8TvAFiR6nqkTIlLDIaGKGq13nLY4CBqjquyH43A7cDNYDhqrq6mLTGAmMBkpOTU9LSKtbLPTMzk6Sk4/cuqSrTt+TxzoocalcXbuhTkxObhq77eNF4kRDpmPEeLxoxLV7ljxnv8UIVMzU1db6q9v/RBlUN+gBOBhYBLwFPFz58vG407rpT4fIY4Nkg+18B/LO0dFNSUrSipk2bduz5waM5Ou7dBdrurkl65Svf6q6DWRVOP1i8SIl0zHiPF42YFq/yx4z3eKGKCczTYr7v/TTxvQRMBZbgrkH5tZUfTmzY2ltXkjTghTKkX2FLtx7g5ncXsGXfUe44pxu/HtqJatVsBHJjjIkFfgqoRFW9vRxpzwW6iEgHXMF0Ga6WdIyIdNHjTXrnAT9q3gsHVeX1r9fzyOTvaZJUg7SxgzilfeNIhDbGGOOTnwLqE+8a0EQgu3ClltLNXFXzRGQc8Bmum/l4VV0mIg/hqnMTgHEichaQC+wDflHO4/Bt/5EcnlmYzYJdyzmze3Me/1lfGtWtEe6wxhhjyshPAXW59/fugHWldjMHUNXJwOQi6+4LeH6rj/ghNfat+Szenc8fz+/JL09rb5MKGmNMjPJzo25cjbv3h3N7sGDBfH55elwdljHGxJ0qNx/USW0asn+tjUBujDGxzuaDMsYYE5NsPihjjDExqTzj+FTJ+aCMMcZEls0HZYwxJibZfFDGGGNiUokFlIh0BpLVmw8qYP1pIlJTVdeGPXfGGGOqrGDXoP4BHCxm/UFvmzHGGBM2JU63ISJzVfWUErYtUdXeYc1ZCURkN7Cxgsk0Bco6v1VliheNmPEeLxoxLV7ljxnv8UIVs52qNiu6Mtg1qIZBtkVtitniDqKsRGSeFjf3SJhEOl40YsZ7vGjEtHiVP2a8xwt3zGBNfPNE5PpiMnMdMD8cmTHGGGMKBatB/R/woYhcyfECqT9u5tuLw5wvY4wxVVyJBZSq7gROFZFUoJe3+mNVnRqRnIXXy3EeLxox4z1eNGJavMofM97jhTVmiZ0kjDHGmGgqz1BHxhhjTNhZAWWMMSYmWQFljDEmJlX5AkpE6ohIzSjFjuj7H+l4pvKLxjkT7/8X9n/oX5V+o0RkFPA28ImInC8iHSMQs52InAigqgXeOomjeN1F5AwRqSki1cMdLxoxq0C8iJ4z0YgZ7/G89Cv9eVple/GJSAfgM+BKoBswGNgFTFDVhWGKeQnwF2C793gfmKKqmSIiGuIPIwrxRgGPAuuBvcA84A1VzQhHvGjErALxInrORCNmvMfzYsbFeVqVa1D1gS2qOldV3wZex90XdoGItAt1MBGpC1wNXKmqw4BvgaHAlSKSFIYTJtLxqgOXAL9S1XNwc4Y1B+4UkcZh+ieMaMwqEC+i50w0YsZ7PC9m3JynVbaAUtXFwAERGectzwMmAG2A7mEIWYAb37CTF+8pYI4XayiEvG060vEEaAD09uJ9BEz0tl0R4ljRihnv8SJ9zkQjZrzHgzg6T6tUASUiw0TkFyJyo7fqdaCTiFwKoKpzgVnATSKSGKKYIiIJqnoUeAYYIiL9vM1pwDbcL6xjbdMVjJcgIjW8eM968U4OY7waIlJLVXOBvwLniMhZ3uZvgIXAGYTwXBOR2iJS14v5BDBSRM4MV8xIH2MUji+i56gXM9LnaVz/H3ox4+48rTIFlIiciztRagF3i8hY4Evge+A0Efmtt+tRIBP3q6CiMS8CxgOvishpwGzcda4LRSRFnb8BTSUEHTS8YxwPvCcig4HPccPg/1RE+oUh3iXAu8AEEbkA2ISrhV4qImd78d4HmgAnVTSeF/N8jndsOUdVpwGTgctF5KxQx4z0MUbh+CJ6jnoxI32exvX/oRczLs9TP1O+V3oi0gV4CLhFVaeJSCbuGlQbVX1JREYCN3gnVgtce3FOBWP2BR4DbgfaAS8CfwRm4H5V3CgiM4A84ARgfwXjnQc8DNwDdAUeUNVzRORdXEeQX4c4Xlcv3i+B9sD1wCfAKlyzxm0i0hM3wWUrYEtF4nkxzwP+BNwCdAb+IiJTgPcABW4X11MqJDEjfYxROL6InqNezEifp3H9f+jFjN/zVFXj9sHxXoptgRO958m4XzNvAl8Bfw/YvwvQJESxzwE+Clg+F/cL4yIvDxcCk7wP9eQKxmoMvAKkesspwMfAjbiBfht78T4ORTwvxgAgPWD5VNygkTfiCvnTgHe8fIUiXh3gb8DZ3nJHYDrwIDAEN2naYNyvulDFHBipY4zS8UXsHI3ieRrX/4denEERPE9rA49H6jyt8JsTyw8g2fub4P2tDvwEuNRbrgOsBa4JR2xcITgQqOatOxdYBgz2lmsCNUIQKwFo5j1viLuO9iJwM+5XVGoo4wXEfB24FKjurTsN98ttZMA+1UL4njby/tbH/QL+O+5X6ZfAZWGK+WakjhGoF8njw/W0isg56qVVDWga4fO0tXeeRuL/sDrQMlLHB9QJeF/D/r8I1C48tkidp3HbxOc12/1OROYB2SLymqpuFJGvVPWod8H0iIi8A+wLUcyBuGtch1V1nohsAH4O7BSRzao6WUQ6Az8TkW9VNTsE8eoAB1W1cM6uhsBtqvqtt0814HoRmRGCePVV9aC3qLh5wgYAu0Tka1X9WkTSgGtFZIq6i6cVEhhTVQs/pwLgJlVd6u2jwFUi8l+teNNsP9x7mquqs3G17EGE6Ri9eHWBLHWddAqF6/gG43pc5arqlyKyFddFOCznaEDMhkCOqn7prU4ifOfpSNwPtjeB3UAGYTxGL15zVf0nrvMDhPH4vPTOAfqIyLNANmH+X/Ti9RWRf6jqfm912P4PC8VlJwmv/fMZ4AFcVToReFNEOniFk6hqvohcDlyA+zVV0ZgjcdXaK4H7RORJVb0P92X3G1y1G9yHWlO9nxkhiHc5cK+IvAagqhuA2SLH7uDOA/aoan4F440CvhKRgV7hXgC8ARwBzgMu83ZVIAt3nBVSJOaxc1VVM1V1acAxVsc121Yopnfh9zVgLHCHuMk6/4nrNBPyYwyId70X7wYAVT0YpuM7F/eLfjjux9tQ3PWZZGAcIT5Hi8RMxV2buBBAVbeo6rdhOE9r4pq2XhKRi73C4GGgJXATrmYBofs/LIz3orjOGED4js+LORLXS2+uqh4N+F88hGu6DPV5WhhvTmDBo6qZwPJQn6c/UNEqWCw+gJOB1wKWLwRmAum4Kr/gvtjnA71CEC8B13V0jB6v+n4LvOIt/xFXmHyKKwz7hiHe18B/iux3FTAX7/pbBeK1996/L7y4/TnelJCE+0J/w3t/lxCaawfFxZRi9rvGO8YKfY7eOfNd4WcD/Ax42nteL9THWEK8v4fx+Prh7u4vbNZ6GDczdqL3COk5GiTmhXhN76E+TwPSu947Z9bjbh4F15vsIdwPjpAdYzHxfuGtqxawPWTHB/T04owNOK6eQPuAWG+H8DwtLl43oE84ztMfxQ9lYtF+eG/cKd6X2zbgOm/9X3C1mAc4fv2pP9A6hLHvwiswAtZ9A/zNe94I12soJDFLiPcV8JL3fAjwYShOGFwnk6He8/tw3Vf7436BHvtnxHUnbR6i4yspZmHBWA33Jf8W0DsE8U4FbgxY7oy7obK9t1zY4SYkxxgkXhvcDygJ8fENAAZ5zxt7/x8TcS0Mf/bWN/DOm1CdoyXFfAt4xlt/RgjP00Tv70W4Aj8FWI27R+dPuNaMZqE6xiDxHgOewhX8w0N1fF6sFOB54DpgBDAFN3TSVOCxgP16h+g8LSneFwGf4Um4H28VPk9/FD/UCUbrAYzC3dOU7p0gz+Panp/DXbyrDvwaeDSEMbsGPL8KWAq0DVjXFPgv0DOC8f7tfdnVxOtUEKJ4DQKe/9H7ojnFW+4bpvc0WMzu3t86IYxX2NEkwfsymwjUL7pfhOK1D8PxJeAK9ps5/ku/Fa4X1tAwfYYlxUzH9fYK6XnqLXcA3vOe/w7IAV4Ix/EFifect1zh4yvmPT0N1zFhLa55UXA/bL4EhoThMywp3hTc9dnqQFKo3t8f5CMciUb6gful8j5wmrf8c9x9D8/xwy/wG3BdeauHIOb5uOsvaQHr/gRsLhIzDRgQ4XiDQxjvvYB1NQKe/xF3Y+CjuKaqUPxaK0vMpXg9wkL8nhbWBqvhekHVB8bganAV/SItS7xJeL2lQvl+eutrFll+DTi1op9fOWKeEcJ47wasawQ8jevVthy4FzeA6c8jHO/yEL+ngefNAODiIvu9gVdjjWC8kJw3JeYlnIlH6oEroD7B6y6O+9WWiruwd6O3/CtgDaFpSqiLa8cuvC4R+IX6J2AxrjC8xzthO1TyeG8HbKsZ8Dwd12wTiiaoiMYsJV6Cd079C3gVdx2lQrXgGItXPeD5KNy1g3Zh/gxDHrOUeI/ierdd4i0PBTpXpnglxAwsGGsHPL8kTO9pWOOVmp9wJh7JB3A27lfuGd5yAnAFrr27LnAb0C2E8VriOggUNqsFFhoX45oTXyV0bc/Rjvd2ke1dcWNt9Q3jexrWmD7ifYQr8ENy3sRSPFyBeDMh6igUrZjFxHvXW18Nr5mKYjrXVJZ4JcR8p8j2XxDCDgqRjhfsETfzQYlILdyFvD64f4oZ3vp04HpVXR3G2E1wd27nqOrlXjf3TFXdGGfxjqrqVSJyEq4parmq7omHmMXE6wJcizuXlsdhvO64URY+VtU1oY4XjZglnDPZqroi1LGiEa+EmD1wrUWfquq6yh7vR/HjpYACEJFGuFrT+bieM9nAncBwVd0Z5thNcde3TsXV3oapaoXHn4vBeIO9eENVdVvwV1WumAHxCu+VOSOc500U452Ku9A9RFV3hCteNGIWc86kRvj/IqzxisQsfE+Hqur2eIkXKK5u1FU30sAruGtPw3El/VXhLpy82HtwnQUa4C4mhvUkjWK8hsCocBdO0YgZEK8+7lpCWM+bKMZr4MULa+EUjZjFnDOR/r8Ia7wiMQvf07AWFpGOFyjuhjpSd6fzNHEjBquGaK6V0ni1t3OBn6jqEotX+WJavMofM97jRSNmNI7xWOx4auKLNnGThWVZvMob0+JV/pjxHi8aMaNxjGAFlDHGmBgVV9egjDHGxA8roIwxxsQkK6CMMcbEJCugjDHGxCQroEyVJCKZRZav8WYnjTkissG7WbK49V8VWbdIRApnOO0vIk9XIO41ItKyvK83pqKsgDImhEQk0vcW1hORNl7sHoEbVHWeqv6mAmlfgxuXzZiosALKmCJEpL2ITBWR70TkSxFp661/Q0RGB+yX6f0dJiJficgE3GCvRdN7QUTmicgyEXkwYP0GEXlQRBaIyBJvrDpEpImIfO7t/ypueJmSfICbXgbcLNHvBaQ/TEQmec8fEJHxIpIuIutE5DcBx7o04DW/8/YdjZsg8h2vVlZbRFJEZLqIzBeRz0SkRdneWWPKxgooU1XV9r54F4nIItx04IWeAf6pqn2Ad3Bz/ZSmH3CrqnYtZts9qtofN5DxUBHpE7Btj6r2A17ATXYHcD8wU1VPxI0p2TZI3P/gpq8AuAA36WFJCgdrHQDcLyKJJe2oqv/GTftxpaqeBOTh3pfRqpoCjAf+HCSWMRUWd0MdGePTUe+LF3DXW3A1BnADfxZ+6b+FG9uxNHNUdX0J2y4VkbG4/7cWQE/c2GbgZlwGNwVFYcwhhc9V9WMR2Rck7l5gn4hcBqzATTRXko9VNRvIFpFdQHIpxxSoG9AL+EJEwA2MGrEx2UzVZAWUMf7l4bU6iEg1oEbAtsPFvUBEOuBqRqeo6j4ReQOoFbBLtvc3n/L/P76Pmz36mlL2yw54Xhjv2DF5alE8AZap6uBy5tGYMrMmPmN+7BvgMu/5lUBhT7kNQIr3/ELcBHylqY8rvA6ISDIw0sdrZuCmjUFERuKmFA/mQ1wt7zMfaRe1E2juXfeqiZuqptAhoJ73fCXQTEQGe/lKFDcPmTFhYzUoY37sFuB1EbkD2I2bSBDcVC7/E5HFuGmxi601BVLVxSKyEPge2Ax87SP+g8B7IrIMV1huKiXGIeAxAK/5zTdVzRWRh4A5wFYvn4XeAF4UkaO4Zs/RwNMi0gD33fEPYFmZAhpTBjZYrDHGmJhkTXzGGGNikhVQxhhjYpIVUMYYY2KSFVDGGGNikhVQxhhjYpIVUMYYY2KSFVDGGGNi0v8DHPcFh6VEMV8AAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -227,12 +1178,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -249,26 +1200,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1950565345.py:28: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\1950565345.py:28: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
       "  axs[0, 0].set_xticklabels(hod_prob.index, rotation=45)\n",
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1950565345.py:42: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\1950565345.py:42: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
       "  axs[0, 1].set_xticklabels(lod_prob.index, rotation=45)\n",
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1950565345.py:57: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\1950565345.py:57: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
       "  axs[1, 0].set_xticklabels(cumulative_hod.index, rotation=45)\n",
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1950565345.py:71: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\1950565345.py:71: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
       "  axs[1, 1].set_xticklabels(cumulative_lod.index, rotation=45)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1152x576 with 4 Axes>"
       ]
@@ -370,24 +1321,290 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Index(['Open', 'High', 'Low', 'Close', 'Date', 'HourMin', 'CurrentGap',\n",
-       "       'RowNumber', 'HighBar', 'LowBar'],\n",
-       "      dtype='object')"
+       "Index(['Open', 'High', 'Low', 'Close', 'Date', 'HourMin', 'CurrentGap',\n",
+       "       'RowNumber', 'HighBar', 'LowBar'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data1.columns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_24704\\2610222875.py:7: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  data1['CurrentGapCat'] = pd.qcut(data1['CurrentGap'], 4)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Assuming you have a DataFrame 'data1' with the 'HourMin', 'HighBar', and 'LowBar' columns\n",
+    "\n",
+    "# List of values to filter and plot\n",
+    "data1['CurrentGapCat'] = pd.qcut(data1['CurrentGap'], 4)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "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>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Date</th>\n",
+       "      <th>HourMin</th>\n",
+       "      <th>CurrentGap</th>\n",
+       "      <th>RowNumber</th>\n",
+       "      <th>HighBar</th>\n",
+       "      <th>LowBar</th>\n",
+       "      <th>CurrentGapCat</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1492.19</td>\n",
+       "      <td>1492.91</td>\n",
+       "      <td>1492.19</td>\n",
+       "      <td>1492.87</td>\n",
+       "      <td>2007-04-27</td>\n",
+       "      <td>1200</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1492.54</td>\n",
+       "      <td>1494.46</td>\n",
+       "      <td>1492.30</td>\n",
+       "      <td>1493.32</td>\n",
+       "      <td>2007-04-27</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1493.30</td>\n",
+       "      <td>1494.45</td>\n",
+       "      <td>1493.07</td>\n",
+       "      <td>1494.41</td>\n",
+       "      <td>2007-04-27</td>\n",
+       "      <td>1300</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1494.60</td>\n",
+       "      <td>1496.55</td>\n",
+       "      <td>1494.31</td>\n",
+       "      <td>1495.04</td>\n",
+       "      <td>2007-04-27</td>\n",
+       "      <td>1330</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1495.01</td>\n",
+       "      <td>1496.97</td>\n",
+       "      <td>1494.65</td>\n",
+       "      <td>1495.85</td>\n",
+       "      <td>2007-04-27</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57168</th>\n",
+       "      <td>4565.23</td>\n",
+       "      <td>4567.31</td>\n",
+       "      <td>4562.06</td>\n",
+       "      <td>4564.47</td>\n",
+       "      <td>2023-07-19</td>\n",
+       "      <td>1330</td>\n",
+       "      <td>-0.002484</td>\n",
+       "      <td>9</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>(-0.0757, -0.00219]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57169</th>\n",
+       "      <td>4564.45</td>\n",
+       "      <td>4565.74</td>\n",
+       "      <td>4557.48</td>\n",
+       "      <td>4560.63</td>\n",
+       "      <td>2023-07-19</td>\n",
+       "      <td>1400</td>\n",
+       "      <td>-0.002484</td>\n",
+       "      <td>10</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>(-0.0757, -0.00219]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57170</th>\n",
+       "      <td>4560.61</td>\n",
+       "      <td>4568.09</td>\n",
+       "      <td>4560.61</td>\n",
+       "      <td>4567.86</td>\n",
+       "      <td>2023-07-19</td>\n",
+       "      <td>1430</td>\n",
+       "      <td>-0.002484</td>\n",
+       "      <td>11</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>(-0.0757, -0.00219]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57171</th>\n",
+       "      <td>4567.82</td>\n",
+       "      <td>4574.66</td>\n",
+       "      <td>4567.61</td>\n",
+       "      <td>4572.09</td>\n",
+       "      <td>2023-07-19</td>\n",
+       "      <td>1500</td>\n",
+       "      <td>-0.002484</td>\n",
+       "      <td>12</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>(-0.0757, -0.00219]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>57172</th>\n",
+       "      <td>4572.04</td>\n",
+       "      <td>4572.04</td>\n",
+       "      <td>4565.59</td>\n",
+       "      <td>4565.65</td>\n",
+       "      <td>2023-07-19</td>\n",
+       "      <td>1530</td>\n",
+       "      <td>-0.002484</td>\n",
+       "      <td>13</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>(-0.0757, -0.00219]</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>52956 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          Open     High      Low    Close       Date HourMin  CurrentGap  \\\n",
+       "0      1492.19  1492.91  1492.19  1492.87 2007-04-27    1200         NaN   \n",
+       "1      1492.54  1494.46  1492.30  1493.32 2007-04-27    1230         NaN   \n",
+       "2      1493.30  1494.45  1493.07  1494.41 2007-04-27    1300         NaN   \n",
+       "3      1494.60  1496.55  1494.31  1495.04 2007-04-27    1330         NaN   \n",
+       "4      1495.01  1496.97  1494.65  1495.85 2007-04-27    1400         NaN   \n",
+       "...        ...      ...      ...      ...        ...     ...         ...   \n",
+       "57168  4565.23  4567.31  4562.06  4564.47 2023-07-19    1330   -0.002484   \n",
+       "57169  4564.45  4565.74  4557.48  4560.63 2023-07-19    1400   -0.002484   \n",
+       "57170  4560.61  4568.09  4560.61  4567.86 2023-07-19    1430   -0.002484   \n",
+       "57171  4567.82  4574.66  4567.61  4572.09 2023-07-19    1500   -0.002484   \n",
+       "57172  4572.04  4572.04  4565.59  4565.65 2023-07-19    1530   -0.002484   \n",
+       "\n",
+       "       RowNumber  HighBar  LowBar        CurrentGapCat  \n",
+       "0              1    False    True                  NaN  \n",
+       "1              2    False   False                  NaN  \n",
+       "2              3    False   False                  NaN  \n",
+       "3              4    False   False                  NaN  \n",
+       "4              5    False   False                  NaN  \n",
+       "...          ...      ...     ...                  ...  \n",
+       "57168          9    False   False  (-0.0757, -0.00219]  \n",
+       "57169         10    False    True  (-0.0757, -0.00219]  \n",
+       "57170         11    False   False  (-0.0757, -0.00219]  \n",
+       "57171         12    False   False  (-0.0757, -0.00219]  \n",
+       "57172         13    False   False  (-0.0757, -0.00219]  \n",
+       "\n",
+       "[52956 rows x 11 columns]"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data1.columns"
+    "data1"
    ]
   },
   {
@@ -398,7 +1615,7 @@
     {
      "data": {
       "text/plain": [
-       "CategoricalDtype(categories=[(-0.0757, -0.00306], (-0.00306, -0.000396], (-0.000396, 0.00136], (0.00136, 0.00364], (0.00364, 0.0478]], ordered=True)"
+       "52956"
       ]
      },
      "execution_count": 19,
@@ -407,83 +1624,67 @@
     }
    ],
    "source": [
-    "data1['CurrentGapCat'].dtypes"
+    "len(data1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
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+       "Open                 0\n",
+       "High                 0\n",
+       "Low                  0\n",
+       "Close                0\n",
+       "Date                 0\n",
+       "HourMin              0\n",
+       "CurrentGap       36490\n",
+       "RowNumber            0\n",
+       "HighBar              0\n",
+       "LowBar               0\n",
+       "CurrentGapCat    36490\n",
+       "dtype: int64"
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+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
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-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1885325193.py:58: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
-      "  axs[0].set_xticklabels(cumulative_hod.index, rotation=45)\n",
-      "C:\\Users\\WINSTON-ITX\\AppData\\Local\\Temp\\ipykernel_11332\\1885325193.py:68: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
-      "  axs[1].set_xticklabels(cumulative_lod.index, rotation=45)\n"
-     ]
-    },
     {
      "data": {
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",
       "text/plain": [
-       "<Figure size 1080x432 with 2 Axes>"
+       "[NaN, (0.000478, 0.00294], (0.00294, 0.0478], (-0.00219, 0.000478], (-0.0757, -0.00219]]\n",
+       "Categories (4, interval[float64, right]): [(-0.0757, -0.00219] < (-0.00219, 0.000478] < (0.000478, 0.00294] < (0.00294, 0.0478]]"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "# Assuming you have a DataFrame 'data1' with the 'HourMin', 'HighBar', and 'LowBar' columns\n",
-    "\n",
-    "# List of values to filter and plot\n",
-    "data1['CurrentGapCat'] = pd.qcut(data1['CurrentGap'], 5)\n",
+    "data1['CurrentGapCat'].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "\n",
     "# Function to convert a float to a percentage string with desired precision\n",
     "def float_to_percent(value, precision=2):\n",
@@ -500,10 +1701,10 @@
     "print(formatted_categories)\n",
     "data1['Labels'] = formatted_categories\n",
     "\n",
-    "tuples = list(set([s for s in zip(data1['CurrentGapCat'], data1['Labels'])]))\n",
+    "tuples = sorted(list(set([s for s in zip(data1['CurrentGapCat'], data1['Labels'])])))\n",
     "\n",
     "# Create a 1x2 grid of subplots with shared Y-axis\n",
-    "fig, axs = plt.subplots(1, 2, figsize=(15, 6), sharey=True)\n",
+    "fig, axs = plt.subplots(1, 2, figsize=(15, 4), sharey=True)\n",
     "\n",
     "# Loop through the specified values and plot the cumulative distributions\n",
     "for t in tuples:\n",
@@ -560,242 +1761,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "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>Open</th>\n",
-       "      <th>High</th>\n",
-       "      <th>Low</th>\n",
-       "      <th>Close</th>\n",
-       "      <th>Date</th>\n",
-       "      <th>HourMin</th>\n",
-       "      <th>CurrentGap</th>\n",
-       "      <th>RowNumber</th>\n",
-       "      <th>HighBar</th>\n",
-       "      <th>LowBar</th>\n",
-       "      <th>CurrentGapCat</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>2733.27</td>\n",
-       "      <td>2736.58</td>\n",
-       "      <td>2730.35</td>\n",
-       "      <td>2732.58</td>\n",
-       "      <td>2018-07-03</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>0.004043</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(0.00364, 0.0478]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>121</th>\n",
-       "      <td>2801.43</td>\n",
-       "      <td>2803.71</td>\n",
-       "      <td>2796.75</td>\n",
-       "      <td>2798.78</td>\n",
-       "      <td>2018-07-16</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>-0.003248</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(-0.0757, -0.00306]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>247</th>\n",
-       "      <td>2842.35</td>\n",
-       "      <td>2843.17</td>\n",
-       "      <td>2834.73</td>\n",
-       "      <td>2834.73</td>\n",
-       "      <td>2018-07-27</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>0.000064</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(-0.000396, 0.00136]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>261</th>\n",
-       "      <td>2819.00</td>\n",
-       "      <td>2821.74</td>\n",
-       "      <td>2812.14</td>\n",
-       "      <td>2813.36</td>\n",
-       "      <td>2018-07-30</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>0.002544</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(0.00136, 0.00364]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>429</th>\n",
-       "      <td>2827.95</td>\n",
-       "      <td>2827.95</td>\n",
-       "      <td>2814.59</td>\n",
-       "      <td>2814.66</td>\n",
-       "      <td>2018-08-15</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>0.004637</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(0.00364, 0.0478]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17254</th>\n",
-       "      <td>4226.71</td>\n",
-       "      <td>4231.10</td>\n",
-       "      <td>4215.56</td>\n",
-       "      <td>4217.66</td>\n",
-       "      <td>2023-05-30</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>-0.003514</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(-0.0757, -0.00306]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17268</th>\n",
-       "      <td>4190.74</td>\n",
-       "      <td>4195.44</td>\n",
-       "      <td>4184.54</td>\n",
-       "      <td>4185.02</td>\n",
-       "      <td>2023-05-31</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>0.000766</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(-0.000396, 0.00136]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17338</th>\n",
-       "      <td>4285.47</td>\n",
-       "      <td>4299.19</td>\n",
-       "      <td>4284.97</td>\n",
-       "      <td>4295.32</td>\n",
-       "      <td>2023-06-07</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>0.000274</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(-0.000396, 0.00136]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17436</th>\n",
-       "      <td>4440.95</td>\n",
-       "      <td>4448.47</td>\n",
-       "      <td>4425.67</td>\n",
-       "      <td>4429.61</td>\n",
-       "      <td>2023-06-16</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>-0.003057</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(-0.00306, -0.000396]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>17599</th>\n",
-       "      <td>4422.62</td>\n",
-       "      <td>4422.62</td>\n",
-       "      <td>4395.21</td>\n",
-       "      <td>4398.22</td>\n",
-       "      <td>2023-07-06</td>\n",
-       "      <td>0930</td>\n",
-       "      <td>-0.001598</td>\n",
-       "      <td>1</td>\n",
-       "      <td>True</td>\n",
-       "      <td>False</td>\n",
-       "      <td>(-0.00306, -0.000396]</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>310 rows × 11 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          Open     High      Low    Close       Date HourMin  CurrentGap  \\\n",
-       "14     2733.27  2736.58  2730.35  2732.58 2018-07-03    0930    0.004043   \n",
-       "121    2801.43  2803.71  2796.75  2798.78 2018-07-16    0930   -0.003248   \n",
-       "247    2842.35  2843.17  2834.73  2834.73 2018-07-27    0930    0.000064   \n",
-       "261    2819.00  2821.74  2812.14  2813.36 2018-07-30    0930    0.002544   \n",
-       "429    2827.95  2827.95  2814.59  2814.66 2018-08-15    0930    0.004637   \n",
-       "...        ...      ...      ...      ...        ...     ...         ...   \n",
-       "17254  4226.71  4231.10  4215.56  4217.66 2023-05-30    0930   -0.003514   \n",
-       "17268  4190.74  4195.44  4184.54  4185.02 2023-05-31    0930    0.000766   \n",
-       "17338  4285.47  4299.19  4284.97  4295.32 2023-06-07    0930    0.000274   \n",
-       "17436  4440.95  4448.47  4425.67  4429.61 2023-06-16    0930   -0.003057   \n",
-       "17599  4422.62  4422.62  4395.21  4398.22 2023-07-06    0930   -0.001598   \n",
-       "\n",
-       "       RowNumber  HighBar  LowBar          CurrentGapCat  \n",
-       "14             1     True   False      (0.00364, 0.0478]  \n",
-       "121            1     True   False    (-0.0757, -0.00306]  \n",
-       "247            1     True   False   (-0.000396, 0.00136]  \n",
-       "261            1     True   False     (0.00136, 0.00364]  \n",
-       "429            1     True   False      (0.00364, 0.0478]  \n",
-       "...          ...      ...     ...                    ...  \n",
-       "17254          1     True   False    (-0.0757, -0.00306]  \n",
-       "17268          1     True   False   (-0.000396, 0.00136]  \n",
-       "17338          1     True   False   (-0.000396, 0.00136]  \n",
-       "17436          1     True   False  (-0.00306, -0.000396]  \n",
-       "17599          1     True   False  (-0.00306, -0.000396]  \n",
-       "\n",
-       "[310 rows x 11 columns]"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "data1.query('HourMin == \"0930\" & HighBar == True')"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tuples"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,