diff --git a/examples/scratch_pad/dev_ext_axes_nightclouds_issue.ipynb b/examples/scratch_pad/dev_ext_axes_nightclouds_issue.ipynb
new file mode 100644
index 00000000..a985786b
--- /dev/null
+++ b/examples/scratch_pad/dev_ext_axes_nightclouds_issue.ipynb
@@ -0,0 +1,633 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# This allows multiple outputs from a single jupyter notebook cell:\n",
+    "from IPython.core.interactiveshell import InteractiveShell\n",
+    "InteractiveShell.ast_node_interactivity = \"all\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(252, 9)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2011-07-01</th>\n",
+       "      <td>132.089996</td>\n",
+       "      <td>134.100006</td>\n",
+       "      <td>131.779999</td>\n",
+       "      <td>133.919998</td>\n",
+       "      <td>117.161659</td>\n",
+       "      <td>202385700</td>\n",
+       "      <td>132.373927</td>\n",
+       "      <td>125.316073</td>\n",
+       "      <td>1.219057</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-07-05</th>\n",
+       "      <td>133.779999</td>\n",
+       "      <td>134.080002</td>\n",
+       "      <td>133.389999</td>\n",
+       "      <td>133.809998</td>\n",
+       "      <td>117.065437</td>\n",
+       "      <td>165936000</td>\n",
+       "      <td>133.254297</td>\n",
+       "      <td>124.912703</td>\n",
+       "      <td>1.066618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-07-06</th>\n",
+       "      <td>133.490005</td>\n",
+       "      <td>134.139999</td>\n",
+       "      <td>133.110001</td>\n",
+       "      <td>133.970001</td>\n",
+       "      <td>117.205429</td>\n",
+       "      <td>143331600</td>\n",
+       "      <td>134.040915</td>\n",
+       "      <td>124.627085</td>\n",
+       "      <td>0.992467</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2011-07-01  132.089996  134.100006  131.779999  133.919998  117.161659   \n",
+       "2011-07-05  133.779999  134.080002  133.389999  133.809998  117.065437   \n",
+       "2011-07-06  133.490005  134.139999  133.110001  133.970001  117.205429   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2011-07-01  202385700  132.373927  125.316073  1.219057  \n",
+       "2011-07-05  165936000  133.254297  124.912703  1.066618  \n",
+       "2011-07-06  143331600  134.040915  124.627085  0.992467  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2012-06-27</th>\n",
+       "      <td>132.419998</td>\n",
+       "      <td>133.429993</td>\n",
+       "      <td>131.970001</td>\n",
+       "      <td>133.169998</td>\n",
+       "      <td>118.980804</td>\n",
+       "      <td>108088000</td>\n",
+       "      <td>136.447962</td>\n",
+       "      <td>128.140042</td>\n",
+       "      <td>0.605441</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-06-28</th>\n",
+       "      <td>132.289993</td>\n",
+       "      <td>132.990005</td>\n",
+       "      <td>131.279999</td>\n",
+       "      <td>132.789993</td>\n",
+       "      <td>118.641281</td>\n",
+       "      <td>169242100</td>\n",
+       "      <td>136.500761</td>\n",
+       "      <td>128.219241</td>\n",
+       "      <td>0.551922</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-06-29</th>\n",
+       "      <td>135.199997</td>\n",
+       "      <td>136.270004</td>\n",
+       "      <td>134.850006</td>\n",
+       "      <td>136.100006</td>\n",
+       "      <td>121.598610</td>\n",
+       "      <td>212250900</td>\n",
+       "      <td>136.721010</td>\n",
+       "      <td>128.792993</td>\n",
+       "      <td>0.921670</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2012-06-27  132.419998  133.429993  131.970001  133.169998  118.980804   \n",
+       "2012-06-28  132.289993  132.990005  131.279999  132.789993  118.641281   \n",
+       "2012-06-29  135.199997  136.270004  134.850006  136.100006  121.598610   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2012-06-27  108088000  136.447962  128.140042  0.605441  \n",
+       "2012-06-28  169242100  136.500761  128.219241  0.551922  \n",
+       "2012-06-29  212250900  136.721010  128.792993  0.921670  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idf = pd.read_csv('../data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)\n",
+    "idf.shape\n",
+    "idf.head(3)\n",
+    "idf.tail(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "#### Let's grab 5 months of data from the input data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = idf.loc['2011-07-01':'2011-12-30',:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "#### We can, of course, plot a basic ohlc or candlestick plot:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.12.6a4'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import mplfinance as mpf\n",
+    "mpf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import copy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mplfinance._mplrcputils import rcParams_to_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (<ipython-input-8-a6774c8535dd>, line 1)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-8-a6774c8535dd>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    STOP HERE\u001b[0m\n\u001b[0m            ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
+   "source": [
+    "STOP HERE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {'axes.edgecolor': 'white',\n",
+    " 'axes.facecolor': '#0b0b0b',\n",
+    " 'axes.grid': True,\n",
+    " 'axes.labelcolor': 'white',\n",
+    " 'figure.dpi': 100.0,\n",
+    " 'figure.edgecolor': 'black',\n",
+    " 'figure.facecolor': 'black',\n",
+    " 'figure.figsize': [6.4, 4.8],\n",
+    " 'figure.subplot.bottom': 0.11,\n",
+    " 'grid.color': '#999999',\n",
+    " 'grid.linestyle': '--',\n",
+    " 'lines.color': 'white',\n",
+    " 'lines.linewidth': 1.0,\n",
+    " 'patch.edgecolor': 'white',\n",
+    " 'savefig.edgecolor': 'black',\n",
+    " 'savefig.facecolor': 'black',\n",
+    " 'text.color': 'white',\n",
+    " 'xtick.color': 'white',\n",
+    " 'ytick.color': 'white'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {\n",
+    "    'figure.edgecolor': 'black',\n",
+    "    'figure.facecolor': 'black',\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {\n",
+    "    'figure.dpi': 100.0,\n",
+    "    'figure.edgecolor': 'black',\n",
+    "    'figure.facecolor': 'black',\n",
+    "    'figure.figsize': [6.4, 4.8],\n",
+    "    'figure.subplot.bottom': 0.11,\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.rcParams.update(d)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = True\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x575 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rc1 = copy.deepcopy(plt.rcParams)\n",
+    "fig = plt.figure()\n",
+    "s = mpf._styles._get_mpfstyle('nightclouds')\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "ax3 = fig.add_subplot(2,2,1)\n",
+    "rc2 = copy.deepcopy(plt.rcParams)\n",
+    "mpf.plot(df,figscale=1,fig=fig,ax=ax3,style='nightclouds',type='candle')\n",
+    "rc3 = copy.deepcopy(plt.rcParams)\n",
+    "#fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = True\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 680x488.75 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rc4 = copy.deepcopy(plt.rcParams)\n",
+    "fig = plt.figure()\n",
+    "s = mpf._styles._get_mpfstyle('nightclouds')\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "ax3 = fig.add_subplot(2,2,1)\n",
+    "rc5 = copy.deepcopy(plt.rcParams)\n",
+    "mpf.plot(df,figscale=0.85,fig=fig,ax=ax3,style='nightclouds',type='candle')\n",
+    "rc6 = copy.deepcopy(plt.rcParams)\n",
+    "#fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rc3 == rc1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df1 = rcParams_to_df(rc1,name='rc1')\n",
+    "df2 = rcParams_to_df(rc2,name='rc2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.concat([df1,df2],axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif = df[df['rc1'] != df['rc2']].dropna(how='all')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mplfinance._mplrcputils import compare_styles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tup = compare_styles('dark_background','fast')\n",
+    "tup[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif['rc2']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif['rc2'].to_dict()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {'axes.edgecolor': 'white',\n",
+    " 'axes.facecolor': '#0b0b0b',\n",
+    " 'axes.grid': True,\n",
+    " 'axes.labelcolor': 'white',\n",
+    " 'figure.dpi': 100.0,\n",
+    " 'figure.edgecolor': 'black',\n",
+    " 'figure.facecolor': 'black',\n",
+    " 'figure.figsize': [6.4, 4.8],\n",
+    " 'figure.subplot.bottom': 0.11,\n",
+    " 'grid.color': '#999999',\n",
+    " 'grid.linestyle': '--',\n",
+    " 'lines.color': 'white',\n",
+    " 'lines.linewidth': 1.0,\n",
+    " 'patch.edgecolor': 'white',\n",
+    " 'savefig.edgecolor': 'black',\n",
+    " 'savefig.facecolor': 'black',\n",
+    " 'text.color': 'white',\n",
+    " 'xtick.color': 'white',\n",
+    " 'ytick.color': 'white'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/scratch_pad/dev_ext_axes_subclass.ipynb b/examples/scratch_pad/dev_ext_axes_subclass.ipynb
new file mode 100644
index 00000000..a07650ab
--- /dev/null
+++ b/examples/scratch_pad/dev_ext_axes_subclass.ipynb
@@ -0,0 +1,755 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# This allows multiple outputs from a single jupyter notebook cell:\n",
+    "from IPython.core.interactiveshell import InteractiveShell\n",
+    "InteractiveShell.ast_node_interactivity = \"all\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(252, 9)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2011-07-01</th>\n",
+       "      <td>132.089996</td>\n",
+       "      <td>134.100006</td>\n",
+       "      <td>131.779999</td>\n",
+       "      <td>133.919998</td>\n",
+       "      <td>117.161659</td>\n",
+       "      <td>202385700</td>\n",
+       "      <td>132.373927</td>\n",
+       "      <td>125.316073</td>\n",
+       "      <td>1.219057</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-07-05</th>\n",
+       "      <td>133.779999</td>\n",
+       "      <td>134.080002</td>\n",
+       "      <td>133.389999</td>\n",
+       "      <td>133.809998</td>\n",
+       "      <td>117.065437</td>\n",
+       "      <td>165936000</td>\n",
+       "      <td>133.254297</td>\n",
+       "      <td>124.912703</td>\n",
+       "      <td>1.066618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-07-06</th>\n",
+       "      <td>133.490005</td>\n",
+       "      <td>134.139999</td>\n",
+       "      <td>133.110001</td>\n",
+       "      <td>133.970001</td>\n",
+       "      <td>117.205429</td>\n",
+       "      <td>143331600</td>\n",
+       "      <td>134.040915</td>\n",
+       "      <td>124.627085</td>\n",
+       "      <td>0.992467</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2011-07-01  132.089996  134.100006  131.779999  133.919998  117.161659   \n",
+       "2011-07-05  133.779999  134.080002  133.389999  133.809998  117.065437   \n",
+       "2011-07-06  133.490005  134.139999  133.110001  133.970001  117.205429   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2011-07-01  202385700  132.373927  125.316073  1.219057  \n",
+       "2011-07-05  165936000  133.254297  124.912703  1.066618  \n",
+       "2011-07-06  143331600  134.040915  124.627085  0.992467  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2012-06-27</th>\n",
+       "      <td>132.419998</td>\n",
+       "      <td>133.429993</td>\n",
+       "      <td>131.970001</td>\n",
+       "      <td>133.169998</td>\n",
+       "      <td>118.980804</td>\n",
+       "      <td>108088000</td>\n",
+       "      <td>136.447962</td>\n",
+       "      <td>128.140042</td>\n",
+       "      <td>0.605441</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-06-28</th>\n",
+       "      <td>132.289993</td>\n",
+       "      <td>132.990005</td>\n",
+       "      <td>131.279999</td>\n",
+       "      <td>132.789993</td>\n",
+       "      <td>118.641281</td>\n",
+       "      <td>169242100</td>\n",
+       "      <td>136.500761</td>\n",
+       "      <td>128.219241</td>\n",
+       "      <td>0.551922</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-06-29</th>\n",
+       "      <td>135.199997</td>\n",
+       "      <td>136.270004</td>\n",
+       "      <td>134.850006</td>\n",
+       "      <td>136.100006</td>\n",
+       "      <td>121.598610</td>\n",
+       "      <td>212250900</td>\n",
+       "      <td>136.721010</td>\n",
+       "      <td>128.792993</td>\n",
+       "      <td>0.921670</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2012-06-27  132.419998  133.429993  131.970001  133.169998  118.980804   \n",
+       "2012-06-28  132.289993  132.990005  131.279999  132.789993  118.641281   \n",
+       "2012-06-29  135.199997  136.270004  134.850006  136.100006  121.598610   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2012-06-27  108088000  136.447962  128.140042  0.605441  \n",
+       "2012-06-28  169242100  136.500761  128.219241  0.551922  \n",
+       "2012-06-29  212250900  136.721010  128.792993  0.921670  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idf = pd.read_csv('../data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)\n",
+    "idf.shape\n",
+    "idf.head(3)\n",
+    "idf.tail(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "#### Let's grab 5 months of data from the input data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = idf.loc['2011-07-01':'2011-12-30',:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.12.6a4'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import mplfinance as mpf\n",
+    "mpf.__version__"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import copy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hasattr(fig,'mpfstyle')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig.mpfstyle = 'default'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hasattr(fig,'mpfstyle')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax = fig.add_subplot(2,2,1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax.style = 'default'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax.style"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax.xxx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mplfinance._mplrcputils import rcParams_to_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "STOP HERE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {'axes.edgecolor': 'white',\n",
+    " 'axes.facecolor': '#0b0b0b',\n",
+    " 'axes.grid': True,\n",
+    " 'axes.labelcolor': 'white',\n",
+    " 'figure.dpi': 100.0,\n",
+    " 'figure.edgecolor': 'black',\n",
+    " 'figure.facecolor': 'black',\n",
+    " 'figure.figsize': [6.4, 4.8],\n",
+    " 'figure.subplot.bottom': 0.11,\n",
+    " 'grid.color': '#999999',\n",
+    " 'grid.linestyle': '--',\n",
+    " 'lines.color': 'white',\n",
+    " 'lines.linewidth': 1.0,\n",
+    " 'patch.edgecolor': 'white',\n",
+    " 'savefig.edgecolor': 'black',\n",
+    " 'savefig.facecolor': 'black',\n",
+    " 'text.color': 'white',\n",
+    " 'xtick.color': 'white',\n",
+    " 'ytick.color': 'white'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {\n",
+    "    'figure.edgecolor': 'black',\n",
+    "    'figure.facecolor': 'black',\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {\n",
+    "    'figure.dpi': 100.0,\n",
+    "    'figure.edgecolor': 'black',\n",
+    "    'figure.facecolor': 'black',\n",
+    "    'figure.figsize': [6.4, 4.8],\n",
+    "    'figure.subplot.bottom': 0.11,\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.rcParams.update(d)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = True\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x575 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "rc1 = copy.deepcopy(plt.rcParams)\n",
+    "s = mpf._styles._get_mpfstyle('nightclouds')\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "rc2 = copy.deepcopy(plt.rcParams)\n",
+    "fig = plt.figure()\n",
+    "ax3 = fig.add_subplot(2,2,1)\n",
+    "mpf.plot(df,figscale=1,fig=fig,ax=ax3,style='nightclouds',type='candle')\n",
+    "rc3 = copy.deepcopy(plt.rcParams)\n",
+    "#fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rc4 = copy.deepcopy(plt.rcParams)\n",
+    "fig = plt.figure()\n",
+    "s = mpf._styles._get_mpfstyle('nightclouds')\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "ax3 = fig.add_subplot(2,2,1)\n",
+    "rc5 = copy.deepcopy(plt.rcParams)\n",
+    "mpf.plot(df,figscale=0.85,fig=fig,ax=ax3,style='nightclouds',type='candle')\n",
+    "rc6 = copy.deepcopy(plt.rcParams)\n",
+    "#fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rc3 == rc1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df1 = rcParams_to_df(rc1,name='rc1')\n",
+    "df2 = rcParams_to_df(rc2,name='rc2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.concat([df1,df2],axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif = df[df['rc1'] != df['rc2']].dropna(how='all')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from mplfinance._mplrcputils import compare_styles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tup = compare_styles('dark_background','fast')\n",
+    "tup[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif['rc2']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dif['rc2'].to_dict()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d = {'axes.edgecolor': 'white',\n",
+    " 'axes.facecolor': '#0b0b0b',\n",
+    " 'axes.grid': True,\n",
+    " 'axes.labelcolor': 'white',\n",
+    " 'figure.dpi': 100.0,\n",
+    " 'figure.edgecolor': 'black',\n",
+    " 'figure.facecolor': 'black',\n",
+    " 'figure.figsize': [6.4, 4.8],\n",
+    " 'figure.subplot.bottom': 0.11,\n",
+    " 'grid.color': '#999999',\n",
+    " 'grid.linestyle': '--',\n",
+    " 'lines.color': 'white',\n",
+    " 'lines.linewidth': 1.0,\n",
+    " 'patch.edgecolor': 'white',\n",
+    " 'savefig.edgecolor': 'black',\n",
+    " 'savefig.facecolor': 'black',\n",
+    " 'text.color': 'white',\n",
+    " 'xtick.color': 'white',\n",
+    " 'ytick.color': 'white'}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/examples/scratch_pad/dev_external_axes.ipynb b/examples/scratch_pad/dev_external_axes.ipynb
new file mode 100644
index 00000000..74bb9b10
--- /dev/null
+++ b/examples/scratch_pad/dev_external_axes.ipynb
@@ -0,0 +1,1175 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# This allows multiple outputs from a single jupyter notebook cell:\n",
+    "from IPython.core.interactiveshell import InteractiveShell\n",
+    "InteractiveShell.ast_node_interactivity = \"all\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(252, 9)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2011-07-01</th>\n",
+       "      <td>132.089996</td>\n",
+       "      <td>134.100006</td>\n",
+       "      <td>131.779999</td>\n",
+       "      <td>133.919998</td>\n",
+       "      <td>117.161659</td>\n",
+       "      <td>202385700</td>\n",
+       "      <td>132.373927</td>\n",
+       "      <td>125.316073</td>\n",
+       "      <td>1.219057</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-07-05</th>\n",
+       "      <td>133.779999</td>\n",
+       "      <td>134.080002</td>\n",
+       "      <td>133.389999</td>\n",
+       "      <td>133.809998</td>\n",
+       "      <td>117.065437</td>\n",
+       "      <td>165936000</td>\n",
+       "      <td>133.254297</td>\n",
+       "      <td>124.912703</td>\n",
+       "      <td>1.066618</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-07-06</th>\n",
+       "      <td>133.490005</td>\n",
+       "      <td>134.139999</td>\n",
+       "      <td>133.110001</td>\n",
+       "      <td>133.970001</td>\n",
+       "      <td>117.205429</td>\n",
+       "      <td>143331600</td>\n",
+       "      <td>134.040915</td>\n",
+       "      <td>124.627085</td>\n",
+       "      <td>0.992467</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2011-07-01  132.089996  134.100006  131.779999  133.919998  117.161659   \n",
+       "2011-07-05  133.779999  134.080002  133.389999  133.809998  117.065437   \n",
+       "2011-07-06  133.490005  134.139999  133.110001  133.970001  117.205429   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2011-07-01  202385700  132.373927  125.316073  1.219057  \n",
+       "2011-07-05  165936000  133.254297  124.912703  1.066618  \n",
+       "2011-07-06  143331600  134.040915  124.627085  0.992467  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2012-06-27</th>\n",
+       "      <td>132.419998</td>\n",
+       "      <td>133.429993</td>\n",
+       "      <td>131.970001</td>\n",
+       "      <td>133.169998</td>\n",
+       "      <td>118.980804</td>\n",
+       "      <td>108088000</td>\n",
+       "      <td>136.447962</td>\n",
+       "      <td>128.140042</td>\n",
+       "      <td>0.605441</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-06-28</th>\n",
+       "      <td>132.289993</td>\n",
+       "      <td>132.990005</td>\n",
+       "      <td>131.279999</td>\n",
+       "      <td>132.789993</td>\n",
+       "      <td>118.641281</td>\n",
+       "      <td>169242100</td>\n",
+       "      <td>136.500761</td>\n",
+       "      <td>128.219241</td>\n",
+       "      <td>0.551922</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2012-06-29</th>\n",
+       "      <td>135.199997</td>\n",
+       "      <td>136.270004</td>\n",
+       "      <td>134.850006</td>\n",
+       "      <td>136.100006</td>\n",
+       "      <td>121.598610</td>\n",
+       "      <td>212250900</td>\n",
+       "      <td>136.721010</td>\n",
+       "      <td>128.792993</td>\n",
+       "      <td>0.921670</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2012-06-27  132.419998  133.429993  131.970001  133.169998  118.980804   \n",
+       "2012-06-28  132.289993  132.990005  131.279999  132.789993  118.641281   \n",
+       "2012-06-29  135.199997  136.270004  134.850006  136.100006  121.598610   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2012-06-27  108088000  136.447962  128.140042  0.605441  \n",
+       "2012-06-28  169242100  136.500761  128.219241  0.551922  \n",
+       "2012-06-29  212250900  136.721010  128.792993  0.921670  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "idf = pd.read_csv('../data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)\n",
+    "idf.shape\n",
+    "idf.head(3)\n",
+    "idf.tail(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "#### Let's grab 5 months of data from the input data frame:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = idf.loc['2011-07-01':'2011-12-30',:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "#### We can, of course, plot a basic ohlc or candlestick plot:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.12.6a5'"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = False\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x431.25 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import mplfinance as mpf\n",
+    "mpf.__version__\n",
+    "mpf.plot(df,volume=True,tight_layout=True,figscale=0.75)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "      <th>UpperB</th>\n",
+       "      <th>LowerB</th>\n",
+       "      <th>PercentB</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2011-12-23</th>\n",
+       "      <td>125.669998</td>\n",
+       "      <td>126.430000</td>\n",
+       "      <td>125.410004</td>\n",
+       "      <td>126.389999</td>\n",
+       "      <td>111.850945</td>\n",
+       "      <td>92187200</td>\n",
+       "      <td>128.281026</td>\n",
+       "      <td>119.379974</td>\n",
+       "      <td>0.787550</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-12-27</th>\n",
+       "      <td>126.169998</td>\n",
+       "      <td>126.820000</td>\n",
+       "      <td>126.059998</td>\n",
+       "      <td>126.489998</td>\n",
+       "      <td>111.939430</td>\n",
+       "      <td>86075700</td>\n",
+       "      <td>128.321357</td>\n",
+       "      <td>120.017643</td>\n",
+       "      <td>0.779453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-12-28</th>\n",
+       "      <td>126.510002</td>\n",
+       "      <td>126.529999</td>\n",
+       "      <td>124.730003</td>\n",
+       "      <td>124.830002</td>\n",
+       "      <td>110.470383</td>\n",
+       "      <td>119107100</td>\n",
+       "      <td>128.084988</td>\n",
+       "      <td>120.732011</td>\n",
+       "      <td>0.557324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-12-29</th>\n",
+       "      <td>125.239998</td>\n",
+       "      <td>126.250000</td>\n",
+       "      <td>124.860001</td>\n",
+       "      <td>126.120003</td>\n",
+       "      <td>111.611977</td>\n",
+       "      <td>123507200</td>\n",
+       "      <td>128.213149</td>\n",
+       "      <td>120.716851</td>\n",
+       "      <td>0.720776</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2011-12-30</th>\n",
+       "      <td>126.019997</td>\n",
+       "      <td>126.330002</td>\n",
+       "      <td>125.500000</td>\n",
+       "      <td>125.500000</td>\n",
+       "      <td>111.063309</td>\n",
+       "      <td>95599000</td>\n",
+       "      <td>128.262110</td>\n",
+       "      <td>120.720891</td>\n",
+       "      <td>0.633732</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2011-12-23  125.669998  126.430000  125.410004  126.389999  111.850945   \n",
+       "2011-12-27  126.169998  126.820000  126.059998  126.489998  111.939430   \n",
+       "2011-12-28  126.510002  126.529999  124.730003  124.830002  110.470383   \n",
+       "2011-12-29  125.239998  126.250000  124.860001  126.120003  111.611977   \n",
+       "2011-12-30  126.019997  126.330002  125.500000  125.500000  111.063309   \n",
+       "\n",
+       "               Volume      UpperB      LowerB  PercentB  \n",
+       "Date                                                     \n",
+       "2011-12-23   92187200  128.281026  119.379974  0.787550  \n",
+       "2011-12-27   86075700  128.321357  120.017643  0.779453  \n",
+       "2011-12-28  119107100  128.084988  120.732011  0.557324  \n",
+       "2011-12-29  123507200  128.213149  120.716851  0.720776  \n",
+       "2011-12-30   95599000  128.262110  120.720891  0.633732  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df2 = df.tail(9).copy()\n",
+    "df2.loc[:,:] = float('nan')\n",
+    "ndf = df.append(df2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = False\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x431.25 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = False\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x431.25 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "mpf.plot(df,volume=True,tight_layout=True,figscale=0.75)\n",
+    "mpf.plot(ndf,volume=True,tight_layout=True,figscale=0.75)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "fig, ax = plt.subplots()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#dir(mpf.plotting)\n",
+    "#mpf.plotting._valid_plot_kwargs()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = True\n"
+     ]
+    }
+   ],
+   "source": [
+    "mpf.plot(df,scale_padding=1.0,ax=ax,fig=fig,figscale=0.75)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x431.25 with 1 Axes>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['binance',\n",
+       " 'blueskies',\n",
+       " 'brasil',\n",
+       " 'charles',\n",
+       " 'checkers',\n",
+       " 'classic',\n",
+       " 'default',\n",
+       " 'mike',\n",
+       " 'nightclouds',\n",
+       " 'sas',\n",
+       " 'starsandstripes',\n",
+       " 'yahoo']"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mpf.available_styles()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "#s = mpf._styles._get_mpfstyle('nightclouds')\n",
+    "#mpf._styles._apply_mpfstyle(s)\n",
+    "\n",
+    "#fig, axes = plt.subplots(2,2)\n",
+    "fig = plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "s = mpf._styles._get_mpfstyle('blueskies')\n",
+    "#s\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "ax1 = fig.add_subplot(2,2,1)\n",
+    "\n",
+    "s = mpf._styles._get_mpfstyle('yahoo')\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "ax2 = fig.add_subplot(2,2,2)\n",
+    "\n",
+    "s = mpf.make_mpf_style(base_mpl_style='fast',base_mpf_style='nightclouds')\n",
+    "#s = mpf._styles._get_mpfstyle('nightclouds')\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "ax3 = fig.add_subplot(2,2,3)\n",
+    "\n",
+    "s = mpf._styles._get_mpfstyle('starsandstripes')\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "ax4 = fig.add_subplot(2,2,4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = True\n",
+      "external_axes_mode = True\n",
+      "external_axes_mode = True\n",
+      "external_axes_mode = True\n"
+     ]
+    }
+   ],
+   "source": [
+    "# mpf.plot(df,ax=axes[0,0],fig=fig,style='blueskies')\n",
+    "# mpf.plot(df,type='candle',ax=axes[1,1],figscale=1.5,fig=fig,style='yahoo')\n",
+    "mpf.plot(df,ax=ax1,fig=fig,style='blueskies')\n",
+    "mpf.plot(df,type='candle',ax=ax2,figscale=1.5,fig=fig,style='yahoo')\n",
+    "#mpf.plot(df,ax=ax3,fig=fig,style='nightclouds',type='candle')\n",
+    "mpf.plot(df,ax=ax3,fig=fig,style='blueskies',type='candle')\n",
+    "mpf.plot(df,type='candle',ax=ax4,figscale=1.5,fig=fig,style='sas')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x862.5 with 4 Axes>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2016-07-28</th>\n",
+       "      <td>102.830002</td>\n",
+       "      <td>104.449997</td>\n",
+       "      <td>102.82</td>\n",
+       "      <td>104.339996</td>\n",
+       "      <td>101.613663</td>\n",
+       "      <td>39869800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-07-29</th>\n",
+       "      <td>104.190002</td>\n",
+       "      <td>104.550003</td>\n",
+       "      <td>103.68</td>\n",
+       "      <td>104.209999</td>\n",
+       "      <td>101.487068</td>\n",
+       "      <td>27733700</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High     Low       Close   Adj Close    Volume\n",
+       "Date                                                                        \n",
+       "2016-07-28  102.830002  104.449997  102.82  104.339996  101.613663  39869800\n",
+       "2016-07-29  104.190002  104.550003  103.68  104.209999  101.487068  27733700"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2016-07-28</th>\n",
+       "      <td>747.039978</td>\n",
+       "      <td>748.650024</td>\n",
+       "      <td>739.299988</td>\n",
+       "      <td>745.909973</td>\n",
+       "      <td>745.909973</td>\n",
+       "      <td>3530200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-07-29</th>\n",
+       "      <td>772.710022</td>\n",
+       "      <td>778.549988</td>\n",
+       "      <td>766.770020</td>\n",
+       "      <td>768.789978</td>\n",
+       "      <td>768.789978</td>\n",
+       "      <td>3841500</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2016-07-28  747.039978  748.650024  739.299988  745.909973  745.909973   \n",
+       "2016-07-29  772.710022  778.549988  766.770020  768.789978  768.789978   \n",
+       "\n",
+       "             Volume  \n",
+       "Date                 \n",
+       "2016-07-28  3530200  \n",
+       "2016-07-29  3841500  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Adj Close</th>\n",
+       "      <th>Volume</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Date</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>2016-07-28</th>\n",
+       "      <td>216.289993</td>\n",
+       "      <td>217.110001</td>\n",
+       "      <td>215.750000</td>\n",
+       "      <td>216.770004</td>\n",
+       "      <td>210.327698</td>\n",
+       "      <td>65035700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2016-07-29</th>\n",
+       "      <td>216.460007</td>\n",
+       "      <td>217.539993</td>\n",
+       "      <td>216.130005</td>\n",
+       "      <td>217.119995</td>\n",
+       "      <td>210.667282</td>\n",
+       "      <td>79519400</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Open        High         Low       Close   Adj Close  \\\n",
+       "Date                                                                     \n",
+       "2016-07-28  216.289993  217.110001  215.750000  216.770004  210.327698   \n",
+       "2016-07-29  216.460007  217.539993  216.130005  217.119995  210.667282   \n",
+       "\n",
+       "              Volume  \n",
+       "Date                  \n",
+       "2016-07-28  65035700  \n",
+       "2016-07-29  79519400  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "prefix = '../../examples/data/'\n",
+    "aapl = pd.read_csv(prefix+'yahoofinance-AAPL-20040819-20180120.csv',index_col='Date',parse_dates=True)\n",
+    "goog = pd.read_csv(prefix+'yahoofinance-GOOG-20040819-20180120.csv',index_col='Date',parse_dates=True)\n",
+    "spy  = pd.read_csv(prefix+'yahoofinance-SPY-20080101-20180101.csv',index_col='Date',parse_dates=True)\n",
+    "aapl = aapl.loc['2016-05-01':'2016-07-31']\n",
+    "goog = goog.loc['2016-05-01':'2016-07-31']\n",
+    "spy = spy.loc['2016-05-01':'2016-07-31']\n",
+    "aapl.tail(2)\n",
+    "goog.tail(2)\n",
+    "spy.tail(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['binance',\n",
+       " 'blueskies',\n",
+       " 'brasil',\n",
+       " 'charles',\n",
+       " 'checkers',\n",
+       " 'classic',\n",
+       " 'default',\n",
+       " 'mike',\n",
+       " 'nightclouds',\n",
+       " 'sas',\n",
+       " 'starsandstripes',\n",
+       " 'yahoo']"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mpf.available_styles()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sname = 'yahoo'\n",
+    "s = mpf._styles._get_mpfstyle(sname)\n",
+    "mpf._styles._apply_mpfstyle(s)\n",
+    "fig = plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax1 = fig.add_subplot(2,3,1)\n",
+    "ax2 = fig.add_subplot(2,3,2)\n",
+    "ax3 = fig.add_subplot(2,3,3)\n",
+    "\n",
+    "av1 = fig.add_subplot(3,3,7,sharex=ax1)\n",
+    "av2 = fig.add_subplot(3,3,8,sharex=ax1)\n",
+    "av3 = fig.add_subplot(3,3,9,sharex=ax3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = True\n",
+      "external_axes_mode = True\n",
+      "external_axes_mode = True\n"
+     ]
+    }
+   ],
+   "source": [
+    "mpf.plot(aapl,type='candle',ax=ax1,fig=fig,figratio=(10,5),style=s,volume=av1,mav=(10,20))\n",
+    "mpf.plot(goog,type='candle',ax=ax2,fig=fig,figratio=(10,5),style=s,volume=av2,mav=(10,20))\n",
+    "mpf.plot(spy ,type='candle',ax=ax3,fig=fig,figratio=(10,5),style=s,volume=av3,mav=(10,20))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "ax1.set_title('AAPL')\n",
+    "ax2.set_title('GOOG')\n",
+    "ax3.set_title('SPY')\n",
+    "#fig.suptitle('This is the Figure Title for the Entire Figure')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1150x575 with 6 Axes>"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "external_axes_mode = False\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x575 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ap = mpf.make_addplot(spy,type='ohlc')\n",
+    "mpf.plot(aapl,type='candle',style='yahoo',addplot=ap)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "plt.style.use('seaborn')\n",
+    "fig, ax = plt.subplots()\n",
+    "plt.rcParams.update({'axes.grid':False})\n",
+    "ax2 = ax.twinx()\n",
+    "mpf.plot(spy,fig=fig,ax=ax,type='ohlc',style='default')\n",
+    "mpf.plot(aapl,fig=fig,ax=ax2,type='candle',style='yahoo')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x575 with 2 Axes>"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/src/mplfinance/_arg_validators.py b/src/mplfinance/_arg_validators.py
index fcfa1da5..393fb784 100644
--- a/src/mplfinance/_arg_validators.py
+++ b/src/mplfinance/_arg_validators.py
@@ -2,6 +2,8 @@
 import pandas   as pd
 import numpy    as np
 import datetime
+from   mplfinance._helpers import _list_of_dict
+import matplotlib as mpl
 
 def _check_and_prepare_data(data, config):
     '''
@@ -266,3 +268,53 @@ def _scale_padding_validator(value):
     else:
         raise ValueError('`scale_padding` kwarg must be a number, or dict of (left,right,top,bottom) numbers.')
     return False
+
+def _check_for_external_axes(config):
+    '''
+    Check that all `fig` and `ax` kwargs are either ALL None, 
+    or ALL are valid instances of Figures/Axes:
+ 
+    An external Axes object can be passed in three places:
+        - mpf.plot() `ax=` kwarg
+        - mpf.plot() `volume=` kwarg
+        - mpf.make_addplot() `ax=` kwarg
+    ALL three places MUST be an Axes object, OR
+    ALL three places MUST be None.  But it may not be mixed.
+    '''
+    ap_axlist = []
+    addplot = config['addplot']
+    if addplot is not None:
+        if isinstance(addplot,dict):
+            addplot = [addplot,]   # make list of dict to be consistent
+        elif not _list_of_dict(addplot):
+            raise TypeError('addplot must be `dict`, or `list of dict`, NOT '+str(type(addplot)))
+        for apd in addplot:
+            ap_axlist.append(apd['ax'])
+ 
+    if len(ap_axlist) > 0:
+        if config['ax'] is None:
+            if not all([ax is None for ax in ap_axlist]):
+                raise ValueError('make_addplot() `ax` kwarg NOT all None, while plot() `ax` kwarg IS None')
+        else: # config['ax'] is NOT None:
+            if not isinstance(config['ax'],mpl.axes.Axes):
+                raise ValueError('plot() ax kwarg must be of type `matplotlib.axis.Axes`')
+            if not all([isinstance(ax,mpl.axes.Axes) for ax in ap_axlist]):
+                raise ValueError('make_addplot() `ax` kwargs must all be of type `matplotlib.axis.Axes`')
+
+    # At this point, if we have not raised an exception, then plot(ax=) and make_addplot(ax=)
+    # are in sync: either they are all None, or they are all of type `matplotlib.axes.Axes`.
+    # Therefore we only need plot(ax=), i.e. config['ax'], as we check `volume` and `fig`:
+
+    if config['ax'] is None:
+        if isinstance(config['volume'],mpl.axes.Axes):
+            raise ValueError('`volume` set to external Axes requires all other Axes be external.')
+        if config['fig'] is not None:
+            raise ValueError('`fig` kwarg must be None if `ax` kwarg is None.')
+    else:
+        if not isinstance(config['volume'],mpl.axes.Axes) and config['volume'] != False:
+            raise ValueError('`volume` must be of type `matplotlib.axis.Axes`')
+        if not isinstance(config['fig'],mpl.figure.Figure):
+            raise ValueError('`fig` kwarg must be of type `matplotlib.figure.Figure`')
+    
+    external_axes_mode = True if isinstance(config['ax'],mpl.axes.Axes) else False
+    return external_axes_mode
diff --git a/src/mplfinance/_mplrcputils.py b/src/mplfinance/_mplrcputils.py
new file mode 100755
index 00000000..ec39a05c
--- /dev/null
+++ b/src/mplfinance/_mplrcputils.py
@@ -0,0 +1,87 @@
+#!/usr/bin/env python
+"""
+rcparams utilities 
+"""
+
+import pandas as pd
+import matplotlib.pyplot as plt
+import sys
+
+__author__ = "Daniel Goldfarb"
+__version__ = "0.1.0"
+__license__ = "MIT"
+
+def rcParams_to_df(rcp,name=None):
+    keys = []
+    vals = []
+    for item in rcp:
+        keys.append(item)
+        vals.append(rcp[item])
+    df = pd.DataFrame(vals,index=pd.Index(keys,name='rcParamsKey'))    
+    if name is not None:
+        df.columns = [name]
+    else:
+        df.columns = ['Value']
+    return df
+
+def compare_styles(s1,s2):
+    with plt.rc_context():
+         plt.style.use('default')
+         plt.style.use(s1)
+         df1 = rcParams_to_df(plt.rcParams,name=s1)
+
+    with plt.rc_context():
+         plt.style.use('default')
+         plt.style.use(s2)
+         df2 = rcParams_to_df(plt.rcParams,name=s2)
+    
+    df  = pd.concat([df1,df2],axis=1)
+    dif = df[df[s1] != df[s2]].dropna(how='all')
+    return (dif,df,df1,df2)
+
+def main():
+    """ Main entry point of the app """
+    def usage():
+        print('\n    Usage: rcparams <command> <arguments> \n')
+        print('    Available commands: ')
+        print('        rcparams find <findstring>')
+        print('        rcparams compare <style1> <style2>')
+        print('')
+        exit(1)
+    commands = ('find','compare')
+
+    if len(sys.argv) < 3 :
+        print('\n    Too few arguments!')
+        usage()
+
+    command  = sys.argv[1]
+    if command not in commands:
+        print('\n    Unrecognized command \"'+command+'\"')
+        usage()
+
+    if command == 'find':
+        findstr = sys.argv[2]
+        df = rcParams_to_df(plt.rcParams)
+        if findstr == '--all':
+            for key in df.index:
+                print(key+':',df.loc[key,'Value'])
+        else:
+            print(df[df.index.str.contains(findstr)])
+
+    elif command == 'compare':
+        if len(sys.argv) < 4 :
+            print('\n    Need two styles to compare!')
+            usage()
+        style1 = sys.argv[2]
+        style2 = sys.argv[3]
+        dif,df,df1,df2 = compare_styles(style1,style2)
+        print('\n==== dif ====\n',dif)
+
+    else:
+        print('\n    Unrecognized command \"'+command+'\"')
+        usage()
+
+
+if __name__ == "__main__":
+    """ This is executed when run from the command line """
+    main()
diff --git a/src/mplfinance/_panels.py b/src/mplfinance/_panels.py
index ea4f5e02..e94721e8 100644
--- a/src/mplfinance/_panels.py
+++ b/src/mplfinance/_panels.py
@@ -145,6 +145,13 @@ def _build_panels( figure, config ):
     #print('panels=')
     #print(panels)
 
+    # TODO:  Throughout this section, right_pad is intentionally *less* 
+    #        than left_pad.  This assumes that the y-axis labels are on
+    #        the left, which is true for many mpf_styles, but *not* all.
+    #        Ideally need to determine which side has the axis labels.
+    #        And keep in mind, if secondary_y is in effect, then both
+    #        sides can have axis labels.
+
     left_pad    = 0.18
     right_pad   = 0.10
     top_pad     = 0.12
diff --git a/src/mplfinance/_version.py b/src/mplfinance/_version.py
index 873e1d42..9ad83a00 100644
--- a/src/mplfinance/_version.py
+++ b/src/mplfinance/_version.py
@@ -1,5 +1,5 @@
 
-version_info = (0, 12, 6, 'alpha', 4)
+version_info = (0, 12, 6, 'alpha', 5)
 
 _specifier_ = {'alpha': 'a','beta': 'b','candidate': 'rc','final': ''}
 
diff --git a/src/mplfinance/plotting.py b/src/mplfinance/plotting.py
index a0da634e..f8630067 100644
--- a/src/mplfinance/plotting.py
+++ b/src/mplfinance/plotting.py
@@ -1,6 +1,8 @@
 import matplotlib.dates  as mdates
 import matplotlib.pyplot as plt
 import matplotlib.colors as mcolors
+import matplotlib.axes   as mpl_axes
+import matplotlib.figure as mpl_fig
 import pandas as pd
 import numpy  as np
 import copy
@@ -33,7 +35,7 @@
 from mplfinance._arg_validators import _hlines_validator, _vlines_validator
 from mplfinance._arg_validators import _alines_validator, _tlines_validator
 from mplfinance._arg_validators import _scale_padding_validator
-from mplfinance._arg_validators import _valid_panel_id
+from mplfinance._arg_validators import _valid_panel_id, _check_for_external_axes
 
 from mplfinance._panels import _build_panels
 from mplfinance._panels import _set_ticks_on_bottom_panel_only
@@ -104,7 +106,7 @@ def _valid_plot_kwargs():
                                         'Validator'   : lambda value: value in _styles.available_styles() or isinstance(value,dict) },
  
         'volume'                    : { 'Default'     : False,
-                                        'Validator'   : lambda value: isinstance(value,bool) },
+                                        'Validator'   : lambda value: isinstance(value,bool) or isinstance(value,mpl_axes.Axes) },
  
         'mav'                       : { 'Default'     : None,
                                         'Validator'   : _mav_validator },
@@ -241,6 +243,12 @@ def _valid_plot_kwargs():
         
         'scale_padding'             : { 'Default'     : 1.0,   # Issue#193 
                                         'Validator'   : lambda value: _scale_padding_validator(value) },
+
+        'ax'                        : { 'Default'     : None,
+                                        'Validator'   : lambda value: isinstance(value,mpl_axes.Axes) },
+        
+        'fig'                       : { 'Default'     : None,
+                                        'Validator'   : lambda value: isinstance(value,mpl_fig.Figure) },
     }
 
     _validate_vkwargs_dict(vkwargs)
@@ -266,14 +274,17 @@ def plot( data, **kwargs ):
         err = "`addplot` is not supported for `type='" + config['type'] +"'`"
         raise ValueError(err)
 
+    external_axes_mode = _check_for_external_axes(config)
+    print('external_axes_mode =',external_axes_mode)
+
     style = config['style']
     if isinstance(style,str):
         style = config['style'] = _styles._get_mpfstyle(style)
 
     if isinstance(style,dict):
-        _styles._apply_mpfstyle(style)
+        if not external_axes_mode: _styles._apply_mpfstyle(style)
     else:
-       raise TypeError('style should be a `dict`; why is it not?')
+        raise TypeError('style should be a `dict`; why is it not?')
     
     if config['figsize'] is None:
         w,h = config['figratio']
@@ -289,15 +300,22 @@ def plot( data, **kwargs ):
     else:
         fsize = config['figsize']
     
-    fig = plt.figure()
+    if external_axes_mode:
+        fig = config['fig']
+    else:
+        fig = plt.figure()
+
     fig.set_size_inches(fsize)
 
     if config['volume'] and volumes is None:
         raise ValueError('Request for volume, but NO volume data.')
 
-    panels = _build_panels(fig, config)
-
-    volumeAxes = panels.at[config['volume_panel'],'axes'][0] if config['volume'] is True else None
+    if external_axes_mode:
+        panels     = None
+        volumeAxes = config['volume']
+    else:
+        panels = _build_panels(fig, config)
+        volumeAxes = panels.at[config['volume_panel'],'axes'][0] if config['volume'] is True else None
 
     fmtstring = _determine_format_string( dates, config['datetime_format'] )
 
@@ -310,7 +328,10 @@ def plot( data, **kwargs ):
         formatter = IntegerIndexDateTimeFormatter(dates, fmtstring)
         xdates = np.arange(len(dates))
 
-    axA1 = panels.at[config['main_panel'],'axes'][0]
+    if external_axes_mode:
+        axA1 = config['ax']
+    else:
+        axA1 = panels.at[config['main_panel'],'axes'][0]
 
     # Will have to handle widths config separately for PMOVE types ??
     config['_width_config'] = _determine_width_config(xdates, config)
@@ -437,7 +458,11 @@ def plot( data, **kwargs ):
         volumeAxes.set_ylim( miny, maxy )
 
     xrotation = config['xrotation']
-    _set_ticks_on_bottom_panel_only(panels,formatter,rotation=xrotation)
+    if not external_axes_mode:
+        _set_ticks_on_bottom_panel_only(panels,formatter,rotation=xrotation)
+    else:
+        axA1.tick_params(axis='x',rotation=xrotation)
+        axA1.xaxis.set_major_formatter(formatter)
 
     addplot = config['addplot']
     if addplot is not None and ptype not in VALID_PMOVE_TYPES:
@@ -511,7 +536,7 @@ def plot( data, **kwargs ):
                    #    corners = (minx, miny), (maxx, maxy)
                    #    ax.update_datalim(corners)
 
-    if config['fill_between'] is not None:
+    if config['fill_between'] is not None and not external_axes_mode:
         fb    = config['fill_between']
         panid = config['main_panel']
         if isinstance(fb,dict):
@@ -528,10 +553,14 @@ def plot( data, **kwargs ):
             
     # put the primary axis on one side,
     # and the twinx() on the "other" side:
-    for panid,row in panels.iterrows():
-        ax = row['axes']
-        y_on_right = style['y_on_right'] if row['y_on_right'] is None else row['y_on_right']
-        _set_ylabels_side(ax[0],ax[1],y_on_right)
+    if not external_axes_mode:
+        for panid,row in panels.iterrows():
+            ax = row['axes']
+            y_on_right = style['y_on_right'] if row['y_on_right'] is None else row['y_on_right']
+            _set_ylabels_side(ax[0],ax[1],y_on_right)
+    else:
+        y_on_right = style['y_on_right']
+        _set_ylabels_side(axA1,None,y_on_right)
 
     # TODO: ================================================================
     # TODO:  Investigate:
@@ -584,9 +613,13 @@ def plot( data, **kwargs ):
         else:
             fig.suptitle(config['title'],size='x-large',weight='semibold', va='center')
 
-    for panid,row in panels.iterrows():
-        if not row['used2nd']:
-            row['axes'][1].set_visible(False)
+    if not external_axes_mode:
+        for panid,row in panels.iterrows():
+            if not row['used2nd']:
+                row['axes'][1].set_visible(False)
+
+    if external_axes_mode:
+        return None
 
     # Should we create a new kwarg to return a flattened axes list
     # versus a list of tuples of primary and secondary axes?
@@ -721,13 +754,15 @@ def _set_ylabels_side(ax_pri,ax_sec,primary_on_right):
     if primary_on_right == True:
         ax_pri.yaxis.set_label_position('right')
         ax_pri.yaxis.tick_right()
-        ax_sec.yaxis.set_label_position('left')
-        ax_sec.yaxis.tick_left()
+        if ax_sec is not None:
+            ax_sec.yaxis.set_label_position('left')
+            ax_sec.yaxis.tick_left()
     else:  # treat non-True as False, whether False, None, or anything else.
         ax_pri.yaxis.set_label_position('left')
         ax_pri.yaxis.tick_left()
-        ax_sec.yaxis.set_label_position('right')
-        ax_sec.yaxis.tick_right()
+        if ax_sec is not None:
+            ax_sec.yaxis.set_label_position('right')
+            ax_sec.yaxis.tick_right()
 
 def _plot_mav(ax,config,xdates,prices,apmav=None,apwidth=None):
     style = config['style']
@@ -827,6 +862,9 @@ def _valid_addplot_kwargs():
         'ylim'        : {'Default'      : None,
                          'Validator'    : lambda value: isinstance(value, (list,tuple)) and len(value) == 2 
                                                                       and all([isinstance(v,(int,float)) for v in value])},
+
+        'ax'          : {'Default'      : None,
+                         'Validator'    : lambda value: isinstance(value,mpl_axes.Axes) },
     }
 
     _validate_vkwargs_dict(vkwargs)