diff --git a/notebook.ipynb b/notebook.ipynb
index d41fb3f..fc0fb8c 100644
--- a/notebook.ipynb
+++ b/notebook.ipynb
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": null,
    "id": "b0ee2af1",
    "metadata": {},
    "outputs": [
@@ -71,35 +71,12 @@
     "# Convert all columns to numeric where possible, coercing errors to NaN\n",
     "df = df.apply(pd.to_numeric, errors='ignore')\n",
     "\n",
-    "# Display column names and data types to verify conversion\n",
-    "print(\"Column names and data types after conversion:\")\n",
-    "print(df.dtypes)\n",
-    "print(\"\\nFirst few rows:\")"
+    "# Display column names and data types to verify conversion"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "id": "98da3827",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Phase transition times: [3.0, 54.0, 233.0, 1733.0]\n"
-     ]
-    }
-   ],
-   "source": [
-    "first_unique_phase = df.drop_duplicates(subset='PHASE')\n",
-    "phase_times = first_unique_phase['T(sec)'].tolist()\n",
-    "print(f\"Phase transition times: {phase_times}\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": null,
    "id": "ef8bc7ac",
    "metadata": {},
    "outputs": [
@@ -115,6 +92,9 @@
     }
    ],
    "source": [
+    "first_unique_phase = df.drop_duplicates(subset='PHASE')\n",
+    "phase_times = first_unique_phase['T(sec)'].tolist()\n",
+    "\n",
     "plt.figure(figsize=(18, 5))\n",
     "ax1 = plt.subplot()\n",
     "\n",
@@ -152,307 +132,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "id": "033cee9a",
+   "execution_count": 78,
+   "id": "06244aa2",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Data grouped by Speed (numeric columns only):\n"
-     ]
-    },
     {
      "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>T(sec)</th>\n",
-       "      <th>HR(bpm)</th>\n",
-       "      <th>VO2(ml/min)</th>\n",
-       "      <th>VCO2(ml/min)</th>\n",
-       "      <th>RER</th>\n",
-       "      <th>VE(l/min)</th>\n",
-       "      <th>FEO2</th>\n",
-       "      <th>FECO2</th>\n",
-       "      <th>FETO2</th>\n",
-       "      <th>FETCO2</th>\n",
-       "      <th>...</th>\n",
-       "      <th>EE(kcal/day)</th>\n",
-       "      <th>EE(kcal/min)</th>\n",
-       "      <th>CARBS(kcal)</th>\n",
-       "      <th>CARBS(%)</th>\n",
-       "      <th>FAT(kcal)</th>\n",
-       "      <th>FAT(%)</th>\n",
-       "      <th>MET</th>\n",
-       "      <th>CUMULATIVE EE(kcal)</th>\n",
-       "      <th>BP(kPa)</th>\n",
-       "      <th>Watts</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>Speed</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>3.5</th>\n",
-       "      <td>142.4</td>\n",
-       "      <td>96.1</td>\n",
-       "      <td>1046.2</td>\n",
-       "      <td>854.9</td>\n",
-       "      <td>0.8</td>\n",
-       "      <td>28.3</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>7230.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>39.4</td>\n",
-       "      <td>0.3</td>\n",
-       "      <td>60.6</td>\n",
-       "      <td>5.5</td>\n",
-       "      <td>8.8</td>\n",
-       "      <td>99.5</td>\n",
-       "      <td>95.7</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4.0</th>\n",
-       "      <td>320.8</td>\n",
-       "      <td>109.3</td>\n",
-       "      <td>1423.6</td>\n",
-       "      <td>1271.0</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>38.7</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>10008.1</td>\n",
-       "      <td>7.0</td>\n",
-       "      <td>0.4</td>\n",
-       "      <td>64.1</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>35.9</td>\n",
-       "      <td>7.5</td>\n",
-       "      <td>27.3</td>\n",
-       "      <td>99.5</td>\n",
-       "      <td>112.4</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4.5</th>\n",
-       "      <td>501.8</td>\n",
-       "      <td>139.4</td>\n",
-       "      <td>1991.2</td>\n",
-       "      <td>1862.2</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>56.0</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>14132.4</td>\n",
-       "      <td>9.8</td>\n",
-       "      <td>0.6</td>\n",
-       "      <td>78.0</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>22.0</td>\n",
-       "      <td>10.5</td>\n",
-       "      <td>52.3</td>\n",
-       "      <td>99.5</td>\n",
-       "      <td>123.8</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5.0</th>\n",
-       "      <td>685.6</td>\n",
-       "      <td>153.2</td>\n",
-       "      <td>2216.6</td>\n",
-       "      <td>2098.0</td>\n",
-       "      <td>0.9</td>\n",
-       "      <td>64.3</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>15771.4</td>\n",
-       "      <td>11.0</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>80.7</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>19.3</td>\n",
-       "      <td>11.7</td>\n",
-       "      <td>85.1</td>\n",
-       "      <td>99.5</td>\n",
-       "      <td>135.2</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5.5</th>\n",
-       "      <td>862.6</td>\n",
-       "      <td>163.1</td>\n",
-       "      <td>2303.3</td>\n",
-       "      <td>2198.3</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>69.9</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>...</td>\n",
-       "      <td>16579.3</td>\n",
-       "      <td>11.5</td>\n",
-       "      <td>0.7</td>\n",
-       "      <td>86.3</td>\n",
-       "      <td>0.1</td>\n",
-       "      <td>13.7</td>\n",
-       "      <td>12.2</td>\n",
-       "      <td>118.3</td>\n",
-       "      <td>99.5</td>\n",
-       "      <td>151.9</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 26 columns</p>\n",
-       "</div>"
-      ],
+      "image/png": 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       "text/plain": [
-       "       T(sec)  HR(bpm)  VO2(ml/min)  VCO2(ml/min)  RER  VE(l/min)  FEO2  \\\n",
-       "Speed                                                                     \n",
-       "3.5     142.4     96.1       1046.2         854.9  0.8       28.3   0.2   \n",
-       "4.0     320.8    109.3       1423.6        1271.0  0.9       38.7   0.2   \n",
-       "4.5     501.8    139.4       1991.2        1862.2  0.9       56.0   0.2   \n",
-       "5.0     685.6    153.2       2216.6        2098.0  0.9       64.3   0.2   \n",
-       "5.5     862.6    163.1       2303.3        2198.3  1.0       69.9   0.2   \n",
-       "\n",
-       "       FECO2  FETO2  FETCO2  ...  EE(kcal/day)  EE(kcal/min)  CARBS(kcal)  \\\n",
-       "Speed                        ...                                            \n",
-       "3.5      0.0    0.0     0.0  ...        7230.0           5.0          0.2   \n",
-       "4.0      0.0    0.0     0.0  ...       10008.1           7.0          0.4   \n",
-       "4.5      0.0    0.0     0.0  ...       14132.4           9.8          0.6   \n",
-       "5.0      0.0    0.0     0.0  ...       15771.4          11.0          0.7   \n",
-       "5.5      0.0    0.0     0.0  ...       16579.3          11.5          0.7   \n",
-       "\n",
-       "       CARBS(%)  FAT(kcal)  FAT(%)   MET  CUMULATIVE EE(kcal)  BP(kPa)  Watts  \n",
-       "Speed                                                                          \n",
-       "3.5        39.4        0.3    60.6   5.5                  8.8     99.5   95.7  \n",
-       "4.0        64.1        0.2    35.9   7.5                 27.3     99.5  112.4  \n",
-       "4.5        78.0        0.2    22.0  10.5                 52.3     99.5  123.8  \n",
-       "5.0        80.7        0.2    19.3  11.7                 85.1     99.5  135.2  \n",
-       "5.5        86.3        0.1    13.7  12.2                118.3     99.5  151.9  \n",
-       "\n",
-       "[5 rows x 26 columns]"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# Group by speed and calculate mean for numeric columns only\n",
-    "speed_groups = df.groupby('Speed').mean(numeric_only=True).round(1)\n",
-    "print(\"Data grouped by Speed (numeric columns only):\")\n",
-    "\n",
-    "speed_groups = speed_groups.iloc[1:-1]\n",
-    "speed_groups.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "id": "25f1a8ef",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "       T(sec)  HR(bpm)  VO2(ml/min)  VCO2(ml/min)  RER  VE(l/min)  FEO2  \\\n",
-      "Speed                                                                     \n",
-      "3.5     142.4     96.1       1046.2         854.9  0.8       28.3   0.2   \n",
-      "4.0     320.8    109.3       1423.6        1271.0  0.9       38.7   0.2   \n",
-      "4.5     501.8    139.4       1991.2        1862.2  0.9       56.0   0.2   \n",
-      "5.0     685.6    153.2       2216.6        2098.0  0.9       64.3   0.2   \n",
-      "5.5     862.6    163.1       2303.3        2198.3  1.0       69.9   0.2   \n",
-      "6.0    1042.3    170.8       2282.2        2229.4  1.0       72.0   0.2   \n",
-      "6.5    1225.8    179.6       2381.8        2345.0  1.0       81.2   0.2   \n",
-      "7.0    1412.0    187.2       2348.1        2409.4  1.1       88.5   0.2   \n",
-      "7.5    1596.7    194.0       2519.0        2734.9  1.1      107.0   0.2   \n",
-      "\n",
-      "       FECO2  FETO2  FETCO2  ...  EE(kcal/day)  EE(kcal/min)  CARBS(kcal)  \\\n",
-      "Speed                        ...                                            \n",
-      "3.5      0.0    0.0     0.0  ...        7230.0           5.0          0.2   \n",
-      "4.0      0.0    0.0     0.0  ...       10008.1           7.0          0.4   \n",
-      "4.5      0.0    0.0     0.0  ...       14132.4           9.8          0.6   \n",
-      "5.0      0.0    0.0     0.0  ...       15771.4          11.0          0.7   \n",
-      "5.5      0.0    0.0     0.0  ...       16579.3          11.5          0.7   \n",
-      "6.0      0.0    0.0     0.0  ...       16763.2          11.6          0.8   \n",
-      "6.5      0.0    0.0     0.0  ...       17690.0          12.3          0.8   \n",
-      "7.0      0.0    0.0     0.0  ...       17600.5          12.2          0.9   \n",
-      "7.5      0.0    0.0     0.0  ...       18976.5          13.2          0.9   \n",
-      "\n",
-      "       CARBS(%)  FAT(kcal)  FAT(%)   MET  CUMULATIVE EE(kcal)  BP(kPa)  Watts  \n",
-      "Speed                                                                          \n",
-      "3.5        39.4        0.3    60.6   5.5                  8.8     99.5   95.7  \n",
-      "4.0        64.1        0.2    35.9   7.5                 27.3     99.5  112.4  \n",
-      "4.5        78.0        0.2    22.0  10.5                 52.3     99.5  123.8  \n",
-      "5.0        80.7        0.2    19.3  11.7                 85.1     99.5  135.2  \n",
-      "5.5        86.3        0.1    13.7  12.2                118.3     99.5  151.9  \n",
-      "6.0        93.9        0.1     6.1  12.1                152.8     99.5  163.3  \n",
-      "6.5        93.8        0.1     6.2  12.6                189.8     99.5  180.0  \n",
-      "7.0        97.3        0.0     2.7  12.4                227.9     99.5  191.4  \n",
-      "7.5        99.7        0.0     0.3  13.3                267.2     99.5  208.1  \n",
-      "\n",
-      "[9 rows x 26 columns]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1200x800 with 2 Axes>"
+       "<Figure size 1500x800 with 2 Axes>"
       ]
      },
      "metadata": {},
@@ -460,62 +148,100 @@
     }
    ],
    "source": [
+    "\n",
+    "# Group by speed and calculate mean for numeric columns only\n",
     "speed_groups = df.groupby('Speed').mean(numeric_only=True).round(1)\n",
-    "# Plot Speed vs Heart Rate from the grouped data\n",
-    "plt.figure(figsize=(12, 8))\n",
     "\n",
     "# Drop the first and last row from speed_groups\n",
     "speed_groups = speed_groups.iloc[1:-1]\n",
-    "print(speed_groups)\n",
-    "\n",
-    "# Create speed bins from 3.5 to 7.5 mph\n",
-    "speed_bins = np.arange(3.5, 8.0, 0.5)\n",
-    "stage_labels = [f'Stage {i}' for i in range(1, len(speed_bins) + 1)]\n",
     "\n",
     "# Filter data to only include speeds in the desired range\n",
     "filtered_data = speed_groups[(speed_groups.index >= 3.5) & (speed_groups.index <= 7.5)]\n",
     "\n",
-    "# Create the main axis for heart rate line plot\n",
-    "ax1 = plt.gca()\n",
-    "line = ax1.plot(filtered_data.index, filtered_data['HR(bpm)'], marker='o', linewidth=2, markersize=6, color='red', label='Heart Rate')\n",
-    "ax1.set_xlabel('Speed (mph)', fontsize=12)\n",
-    "ax1.set_ylabel('Heart Rate (bpm)', fontsize=12, color='red')\n",
-    "ax1.tick_params(axis='y', labelcolor='red')\n",
+    "# Create figure with specific size\n",
+    "plt.figure(figsize=(15, 8))\n",
+    "plt.style.use('default')\n",
     "\n",
-    "# Add heart rate values as text labels on the points\n",
-    "for i, (speed, hr) in enumerate(zip(filtered_data.index, filtered_data['HR(bpm)'])):\n",
-    "    ax1.text(speed, hr + 2, f'{int(hr)}', ha='center', va='bottom', fontsize=9, fontweight='bold', color='red')\n",
-    "\n",
-    "# Create secondary y-axis for stacked bar chart (Fat and Carbs)\n",
-    "ax2 = ax1.twinx()\n",
+    "# Create stage labels and positions\n",
+    "stage_labels = [f'Stage {i}' for i in range(1, len(filtered_data) + 1)]\n",
+    "x_positions = np.arange(len(filtered_data))\n",
     "\n",
     "# Calculate fat and carbs energy expenditure from percentages\n",
     "fat_ee = filtered_data['EE(kcal/min)'] * filtered_data['FAT(%)'] / 100\n",
     "carbs_ee = filtered_data['EE(kcal/min)'] * filtered_data['CARBS(%)'] / 100\n",
     "\n",
-    "# Create stacked bar chart\n",
-    "bars_fat = ax2.bar(filtered_data.index, fat_ee, alpha=0.7, width=0.2, color='orange', label='Fat')\n",
-    "bars_carbs = ax2.bar(filtered_data.index, carbs_ee, bottom=fat_ee, alpha=0.7, width=0.2, color='blue', label='Carbs')\n",
+    "# Create the main axis for the stacked bars\n",
+    "ax1 = plt.gca()\n",
     "\n",
-    "ax2.set_ylabel('Energy Expenditure (kcal/min)', fontsize=12, color='black')\n",
-    "ax2.tick_params(axis='y', labelcolor='black')\n",
+    "# Create stacked bar chart with colors\n",
+    "bars_fat = ax1.bar(x_positions, fat_ee, color='#1f77b4', alpha=0.8, width=0.6, label='Fat')\n",
+    "bars_carbs = ax1.bar(x_positions, carbs_ee, bottom=fat_ee, color='#ff7f0e', alpha=0.8, width=0.6, label='Carbs')\n",
     "\n",
-    "# Add total EE values as text labels on top of bars\n",
-    "for i, (speed, total_ee) in enumerate(zip(filtered_data.index, filtered_data['EE(kcal/min)'])):\n",
-    "    ax2.text(speed, total_ee + 0.3, f'{total_ee:.1f}', ha='center', va='bottom', fontsize=9, fontweight='bold', color='black')\n",
+    "# Set labels and formatting for primary axis\n",
+    "ax1.set_xlabel('', fontsize=12)\n",
+    "ax1.set_ylabel('Fuel (kcal/min)', fontsize=12)\n",
+    "ax1.set_ylim(0, 20)\n",
     "\n",
-    "# Update x-axis with stage labels\n",
-    "plt.xticks(filtered_data.index, stage_labels)\n",
-    "plt.title('Heart Rate vs Speed with Fat/Carbs Energy Expenditure', fontsize=14, fontweight='bold')\n",
+    "# Add individual values on each bar segment\n",
+    "for i, (fat_val, carb_val, total_val) in enumerate(zip(fat_ee, carbs_ee, filtered_data['EE(kcal/min)'])):\n",
+    "    if fat_val > 0.3:  # Fat value\n",
+    "        ax1.text(i, fat_val/2, f'{fat_val:.1f}', ha='center', va='center',\n",
+    "                 fontsize=9, fontweight='bold', color='white')\n",
+    "    if carb_val > 0.3:  # Carbs value\n",
+    "        ax1.text(i, fat_val + carb_val/2, f'{carb_val:.1f}', ha='center', va='center',\n",
+    "                 fontsize=9, fontweight='bold', color='white')\n",
+    "    # Total EE\n",
+    "    ax1.text(i, total_val + 0.5, f'{total_val:.1f} kcal', ha='center', va='bottom',\n",
+    "             fontsize=10, fontweight='bold', color='black')\n",
     "\n",
-    "# Combine legends\n",
+    "# Add speed labels below x-axis\n",
+    "for i, speed in enumerate(filtered_data.index):\n",
+    "    ax1.text(i, -1.5, f'{speed:.1f} mph', ha='center', va='top', fontsize=9)\n",
+    "    ax1.text(i, -2.8, f'{speed*1.609:.1f} min/km', ha='center', va='top', fontsize=8, color='gray')\n",
+    "\n",
+    "# Create secondary y-axis for heart rate\n",
+    "ax2 = ax1.twinx()\n",
+    "\n",
+    "# Plot heart rate line (no manual offset)\n",
+    "hr_line = ax2.plot(x_positions, filtered_data['HR(bpm)'],\n",
+    "                   marker='o', linewidth=3, markersize=8, color='red', label='Heart Rate')\n",
+    "\n",
+    "# Set heart rate axis formatting\n",
+    "ax2.set_ylabel('Heart Rate (bpm)', fontsize=12, color='red')\n",
+    "ax2.tick_params(axis='y', labelcolor='red')\n",
+    "\n",
+    "# Dynamically adjust HR axis to float above bars\n",
+    "max_bar_height = max(filtered_data['EE(kcal/min)'])\n",
+    "ax2.set_ylim(0, 220)  # ensures HR line is above bars\n",
+    "\n",
+    "\n",
+    "# Add HR values above the points\n",
+    "for i, hr in enumerate(filtered_data['HR(bpm)']):\n",
+    "    ax2.text(i, hr + 10, f'{int(hr)}bpm', ha='center', va='bottom',\n",
+    "             fontsize=10, fontweight='bold', color='red')\n",
+    "\n",
+    "# Set x-axis formatting\n",
+    "ax1.set_xticks(x_positions)\n",
+    "ax1.set_xticklabels(stage_labels, fontsize=11)\n",
+    "\n",
+    "# Add title\n",
+    "plt.suptitle('Fuel Utilization Report - Institute of Science, Health and Performance',\n",
+    "             fontsize=14, fontweight='bold', y=0.95)\n",
+    "\n",
+    "# Create legend\n",
     "lines1, labels1 = ax1.get_legend_handles_labels()\n",
     "lines2, labels2 = ax2.get_legend_handles_labels()\n",
-    "ax1.legend(lines1 + lines2, labels1 + labels2, loc='upper left')\n",
+    "ax1.legend(lines1 + lines2, labels1 + labels2, loc='upper left',\n",
+    "           frameon=True, fancybox=True, shadow=True)\n",
     "\n",
-    "plt.grid(True, alpha=0.3)\n",
+    "# Add grid\n",
+    "ax1.grid(True, alpha=0.3, linestyle='-', linewidth=0.5)\n",
+    "ax1.set_axisbelow(True)\n",
+    "\n",
+    "# Adjust layout\n",
     "plt.tight_layout()\n",
-    "plt.show()"
+    "plt.subplots_adjust(bottom=0.1, top=0.9)\n",
+    "plt.show()\n"
    ]
   },
   {