inside_bar_explore_spread.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.graph_objects as go\n",
    "import utils\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_cols = ['ENTRY', 'STOPLOSS', 'TAKEPROFIT']\n",
    "plot_colours = ['#043ef9', '#eb5334', '#34eb37']\n",
    "\n",
    "def plot_candles(df_plot):\n",
    "    fig = go.Figure()\n",
    "    fig.add_trace(go.Candlestick(\n",
    "        x=df_plot.time, open=df_plot.mid_o, high=df_plot.mid_h, low=df_plot.mid_l, close=df_plot.mid_c,\n",
    "        line=dict(width=1), opacity=1,\n",
    "        increasing_fillcolor='#24A06B',\n",
    "        decreasing_fillcolor=\"#CC2E3C\",\n",
    "        increasing_line_color='#2EC886',\n",
    "        decreasing_line_color='#FF3A4C'\n",
    "    ))\n",
    "    for i in range(0, 3):\n",
    "        fig.add_trace(go.Scatter(\n",
    "            x=df_buys.time,\n",
    "            y=df_buys[plot_cols[i]],\n",
    "            mode='markers',\n",
    "            marker=dict(color=plot_colours[i],size=12)\n",
    "        ))\n",
    "    for i in range(0, 3):\n",
    "        fig.add_trace(go.Scatter(\n",
    "            x=df_sells.time,\n",
    "            y=df_sells[plot_cols[i]],\n",
    "            mode='markers',\n",
    "            marker=dict(color=plot_colours[i],size=12)\n",
    "        ))\n",
    "    fig.update_layout(width=1000,height=400,\n",
    "        margin=dict(l=10,b=10,t=10),\n",
    "        font=dict(size=10,color=\"#e1e1e1\"),\n",
    "        paper_bgcolor=\"#1e1e1e\",\n",
    "        plot_bgcolor=\"#1e1e1e\")\n",
    "    fig.update_xaxes(\n",
    "        gridcolor=\"#1f292f\",\n",
    "        showgrid=True,fixedrange=True,rangeslider=dict(visible=False),\n",
    "        rangebreaks=[\n",
    "            dict(bounds=[\"sat\", \"mon\"])\n",
    "        ]\n",
    "    )\n",
    "    fig.update_yaxes(\n",
    "        gridcolor=\"#1f292f\",\n",
    "        showgrid=True,\n",
    "    )\n",
    "    fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pair = \"USD_JPY\"\n",
    "granularity = \"H4\"\n",
    "df_raw = pd.read_pickle(utils.get_his_data_filename(pair, granularity))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "non_cols = ['time', 'volume']\n",
    "mod_cols = [x for x in df_raw.columns if x not in non_cols]\n",
    "df_raw[mod_cols] = df_raw[mod_cols].apply(pd.to_numeric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['time', 'volume', 'mid_o', 'mid_h', 'mid_l', 'mid_c', 'bid_o', 'bid_h',\n",
       "       'bid_l', 'bid_c', 'ask_o', 'ask_h', 'ask_l', 'ask_c'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_raw.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df_raw[['time', 'mid_o', 'mid_h', 'mid_l', 'mid_c', 'bid_c', 'ask_c']].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>time</th>\n",
       "      <th>mid_o</th>\n",
       "      <th>mid_h</th>\n",
       "      <th>mid_l</th>\n",
       "      <th>mid_c</th>\n",
       "      <th>bid_c</th>\n",
       "      <th>ask_c</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01T22:00:00.000000000Z</td>\n",
       "      <td>108.651</td>\n",
       "      <td>108.761</td>\n",
       "      <td>108.607</td>\n",
       "      <td>108.673</td>\n",
       "      <td>108.667</td>\n",
       "      <td>108.679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02T02:00:00.000000000Z</td>\n",
       "      <td>108.671</td>\n",
       "      <td>108.758</td>\n",
       "      <td>108.658</td>\n",
       "      <td>108.742</td>\n",
       "      <td>108.736</td>\n",
       "      <td>108.747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-02T06:00:00.000000000Z</td>\n",
       "      <td>108.744</td>\n",
       "      <td>108.842</td>\n",
       "      <td>108.696</td>\n",
       "      <td>108.839</td>\n",
       "      <td>108.833</td>\n",
       "      <td>108.845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-02T10:00:00.000000000Z</td>\n",
       "      <td>108.836</td>\n",
       "      <td>108.866</td>\n",
       "      <td>108.658</td>\n",
       "      <td>108.694</td>\n",
       "      <td>108.688</td>\n",
       "      <td>108.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-02T14:00:00.000000000Z</td>\n",
       "      <td>108.697</td>\n",
       "      <td>108.748</td>\n",
       "      <td>108.212</td>\n",
       "      <td>108.529</td>\n",
       "      <td>108.523</td>\n",
       "      <td>108.535</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             time    mid_o    mid_h    mid_l    mid_c  \\\n",
       "0  2020-01-01T22:00:00.000000000Z  108.651  108.761  108.607  108.673   \n",
       "1  2020-01-02T02:00:00.000000000Z  108.671  108.758  108.658  108.742   \n",
       "2  2020-01-02T06:00:00.000000000Z  108.744  108.842  108.696  108.839   \n",
       "3  2020-01-02T10:00:00.000000000Z  108.836  108.866  108.658  108.694   \n",
       "4  2020-01-02T14:00:00.000000000Z  108.697  108.748  108.212  108.529   \n",
       "\n",
       "     bid_c    ask_c  \n",
       "0  108.667  108.679  \n",
       "1  108.736  108.747  \n",
       "2  108.833  108.845  \n",
       "3  108.688  108.700  \n",
       "4  108.523  108.535  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "SLOSS = 0.4\n",
    "TPROFIT = 0.8\n",
    "ENTRY_PRC = 0.1\n",
    "\n",
    "def direction(row):\n",
    "    if row.mid_c > row.mid_o:\n",
    "        return 1\n",
    "    return -1\n",
    "\n",
    "def get_signal(row):\n",
    "    if row.mid_h_prev > row.mid_h and row.mid_l_prev < row.mid_l:\n",
    "        return row.DIRECTION_prev\n",
    "    return 0\n",
    "\n",
    "def get_entry_stop(row):\n",
    "    if row.SIGNAL == 1:\n",
    "        return (row.RANGE_prev * ENTRY_PRC) + row.ask_h_prev\n",
    "    elif row.SIGNAL == -1:\n",
    "        return row.bid_l_prev - (row.RANGE_prev * ENTRY_PRC)\n",
    "    else:\n",
    "        return 0\n",
    "    \n",
    "def get_stop_loss(row):\n",
    "    if row.SIGNAL == 1:\n",
    "        return row.ENTRY - (row.RANGE_prev * SLOSS)\n",
    "    elif row.SIGNAL == -1:\n",
    "        return row.ENTRY + (row.RANGE_prev * SLOSS)\n",
    "    else:\n",
    "        return 0\n",
    "    \n",
    "def get_take_profit(row):\n",
    "    if row.SIGNAL == 1:\n",
    "        return row.ENTRY + (row.RANGE_prev * TPROFIT)\n",
    "    elif row.SIGNAL == -1:\n",
    "        return row.ENTRY - (row.RANGE_prev * TPROFIT)\n",
    "    else:\n",
    "        return 0   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df_raw.copy()\n",
    "df['RANGE'] = df.mid_h - df.mid_l\n",
    "df['mid_h_prev'] = df.mid_h.shift(1)\n",
    "df['mid_l_prev'] = df.mid_l.shift(1)\n",
    "df['ask_h_prev'] = df.ask_h.shift(1)\n",
    "df['bid_l_prev'] = df.bid_l.shift(1)\n",
    "df['RANGE_prev'] = df.RANGE.shift(1)\n",
    "df['DIRECTION'] = df.apply(direction, axis=1)\n",
    "df['DIRECTION_prev'] = df.DIRECTION.shift(1).fillna(0).astype(int)\n",
    "df.dropna(inplace=True)\n",
    "df['SIGNAL'] = df.apply(get_signal, axis=1)\n",
    "df.reset_index(drop=True, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['ENTRY'] = df.apply(get_entry_stop, axis=1)\n",
    "df['STOPLOSS'] = df.apply(get_stop_loss, axis=1)\n",
    "df['TAKEPROFIT'] = df.apply(get_take_profit, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>time</th>\n",
       "      <th>volume</th>\n",
       "      <th>mid_o</th>\n",
       "      <th>mid_h</th>\n",
       "      <th>mid_l</th>\n",
       "      <th>mid_c</th>\n",
       "      <th>bid_o</th>\n",
       "      <th>bid_h</th>\n",
       "      <th>bid_l</th>\n",
       "      <th>bid_c</th>\n",
       "      <th>...</th>\n",
       "      <th>mid_l_prev</th>\n",
       "      <th>ask_h_prev</th>\n",
       "      <th>bid_l_prev</th>\n",
       "      <th>RANGE_prev</th>\n",
       "      <th>DIRECTION</th>\n",
       "      <th>DIRECTION_prev</th>\n",
       "      <th>SIGNAL</th>\n",
       "      <th>ENTRY</th>\n",
       "      <th>STOPLOSS</th>\n",
       "      <th>TAKEPROFIT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-02T02:00:00.000000000Z</td>\n",
       "      <td>579</td>\n",
       "      <td>108.671</td>\n",
       "      <td>108.758</td>\n",
       "      <td>108.658</td>\n",
       "      <td>108.742</td>\n",
       "      <td>108.664</td>\n",
       "      <td>108.751</td>\n",
       "      <td>108.652</td>\n",
       "      <td>108.736</td>\n",
       "      <td>...</td>\n",
       "      <td>108.607</td>\n",
       "      <td>108.808</td>\n",
       "      <td>108.586</td>\n",
       "      <td>0.154</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>108.8234</td>\n",
       "      <td>108.7618</td>\n",
       "      <td>108.9466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-02T18:00:00.000000000Z</td>\n",
       "      <td>1029</td>\n",
       "      <td>108.526</td>\n",
       "      <td>108.572</td>\n",
       "      <td>108.494</td>\n",
       "      <td>108.561</td>\n",
       "      <td>108.520</td>\n",
       "      <td>108.566</td>\n",
       "      <td>108.488</td>\n",
       "      <td>108.511</td>\n",
       "      <td>...</td>\n",
       "      <td>108.212</td>\n",
       "      <td>108.754</td>\n",
       "      <td>108.206</td>\n",
       "      <td>0.536</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>108.1524</td>\n",
       "      <td>108.3668</td>\n",
       "      <td>107.7236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2020-01-06T02:00:00.000000000Z</td>\n",
       "      <td>1526</td>\n",
       "      <td>107.950</td>\n",
       "      <td>108.104</td>\n",
       "      <td>107.932</td>\n",
       "      <td>108.058</td>\n",
       "      <td>107.944</td>\n",
       "      <td>108.098</td>\n",
       "      <td>107.925</td>\n",
       "      <td>108.052</td>\n",
       "      <td>...</td>\n",
       "      <td>107.772</td>\n",
       "      <td>108.130</td>\n",
       "      <td>107.764</td>\n",
       "      <td>0.350</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>108.1650</td>\n",
       "      <td>108.0250</td>\n",
       "      <td>108.4450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2020-01-06T10:00:00.000000000Z</td>\n",
       "      <td>1785</td>\n",
       "      <td>107.988</td>\n",
       "      <td>108.164</td>\n",
       "      <td>107.982</td>\n",
       "      <td>108.120</td>\n",
       "      <td>107.982</td>\n",
       "      <td>108.158</td>\n",
       "      <td>107.975</td>\n",
       "      <td>108.114</td>\n",
       "      <td>...</td>\n",
       "      <td>107.926</td>\n",
       "      <td>108.185</td>\n",
       "      <td>107.920</td>\n",
       "      <td>0.253</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>107.8947</td>\n",
       "      <td>107.9959</td>\n",
       "      <td>107.6923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2020-01-07T10:00:00.000000000Z</td>\n",
       "      <td>2026</td>\n",
       "      <td>108.466</td>\n",
       "      <td>108.483</td>\n",
       "      <td>108.368</td>\n",
       "      <td>108.438</td>\n",
       "      <td>108.460</td>\n",
       "      <td>108.477</td>\n",
       "      <td>108.361</td>\n",
       "      <td>108.432</td>\n",
       "      <td>...</td>\n",
       "      <td>108.262</td>\n",
       "      <td>108.506</td>\n",
       "      <td>108.255</td>\n",
       "      <td>0.238</td>\n",
       "      <td>-1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>108.5298</td>\n",
       "      <td>108.4346</td>\n",
       "      <td>108.7202</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              time  volume    mid_o    mid_h    mid_l  \\\n",
       "0   2020-01-02T02:00:00.000000000Z     579  108.671  108.758  108.658   \n",
       "4   2020-01-02T18:00:00.000000000Z    1029  108.526  108.572  108.494   \n",
       "12  2020-01-06T02:00:00.000000000Z    1526  107.950  108.104  107.932   \n",
       "14  2020-01-06T10:00:00.000000000Z    1785  107.988  108.164  107.982   \n",
       "20  2020-01-07T10:00:00.000000000Z    2026  108.466  108.483  108.368   \n",
       "\n",
       "      mid_c    bid_o    bid_h    bid_l    bid_c  ...  mid_l_prev  ask_h_prev  \\\n",
       "0   108.742  108.664  108.751  108.652  108.736  ...     108.607     108.808   \n",
       "4   108.561  108.520  108.566  108.488  108.511  ...     108.212     108.754   \n",
       "12  108.058  107.944  108.098  107.925  108.052  ...     107.772     108.130   \n",
       "14  108.120  107.982  108.158  107.975  108.114  ...     107.926     108.185   \n",
       "20  108.438  108.460  108.477  108.361  108.432  ...     108.262     108.506   \n",
       "\n",
       "    bid_l_prev  RANGE_prev  DIRECTION  DIRECTION_prev  SIGNAL     ENTRY  \\\n",
       "0      108.586       0.154          1               1       1  108.8234   \n",
       "4      108.206       0.536          1              -1      -1  108.1524   \n",
       "12     107.764       0.350          1               1       1  108.1650   \n",
       "14     107.920       0.253          1              -1      -1  107.8947   \n",
       "20     108.255       0.238         -1               1       1  108.5298   \n",
       "\n",
       "    STOPLOSS  TAKEPROFIT  \n",
       "0   108.7618    108.9466  \n",
       "4   108.3668    107.7236  \n",
       "12  108.0250    108.4450  \n",
       "14  107.9959    107.6923  \n",
       "20  108.4346    108.7202  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SIGNAL!=0].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Trade():\n",
    "    def __init__(self, row):\n",
    "        self.candle_date = row.time\n",
    "        self.direction = row.SIGNAL\n",
    "        self.entry = row.ENTRY\n",
    "        self.TP = row.TAKEPROFIT\n",
    "        self.SL = row.STOPLOSS\n",
    "        self.running = False\n",
    "        self.result = None\n",
    "        self.stopped = None\n",
    "        \n",
    "    def update(self, row):\n",
    "        if self.running == True:\n",
    "            self.update_result(row)\n",
    "        else:\n",
    "            self.check_entry(row)\n",
    "            \n",
    "    def check_entry(self, row):\n",
    "        if self.direction == 1 and row.mid_c >= self.entry or self.direction == -1 and row.mid_c <= self.entry:\n",
    "            self.index = row.name\n",
    "            self.opened = row.time\n",
    "            self.running = True\n",
    "            \n",
    "    def update_result(self, row):\n",
    "        if self.direction == 1:\n",
    "            if row.mid_c >= self.TP:\n",
    "                self.result = 2.0\n",
    "            elif row.mid_c <= self.SL:\n",
    "                self.result = -1.0\n",
    "        else:\n",
    "            if row.mid_c <= self.TP:\n",
    "                self.result = 2.0\n",
    "            elif row.mid_c >= self.SL:\n",
    "                self.result = -1.0\n",
    "        \n",
    "        if self.result is not None:\n",
    "            self.running = False\n",
    "            self.stopped = row.time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "open_trades = []\n",
    "closed_trades = []\n",
    "\n",
    "for index, row in df.iterrows():\n",
    "    for ot in open_trades:\n",
    "        ot.update(row)\n",
    "        if ot.stopped is not None:\n",
    "            closed_trades.append(ot)\n",
    "    \n",
    "    open_trades = [x for x in open_trades if x.stopped is None]\n",
    "    \n",
    "    if row.SIGNAL != 0:\n",
    "        ope_trades = [x for x in open_trades if x.running == True]\n",
    "        open_trades.append(Trade(row))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "746"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(closed_trades)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_trades = pd.DataFrame.from_dict([vars(x) for x in closed_trades])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[df.SIGNAL!=0].to_pickle(\"USD_JPY_H4_trades.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_plot = df.iloc[0:60]\n",
    "df_buys = df_plot[df_plot.SIGNAL ==1]\n",
    "df_sells = df_plot[df_plot.SIGNAL == -1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
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       "                      candle_date  direction     entry        TP        SL  \\\n",
       "0  2020-01-02T02:00:00.000000000Z          1  108.8234  108.9466  108.7618   \n",
       "1  2020-01-02T18:00:00.000000000Z         -1  108.1524  107.7236  108.3668   \n",
       "2  2020-01-06T02:00:00.000000000Z          1  108.1650  108.4450  108.0250   \n",
       "3  2020-01-07T10:00:00.000000000Z          1  108.5298  108.7202  108.4346   \n",
       "4  2020-01-07T18:00:00.000000000Z          1  108.6670  108.9150  108.5430   \n",
       "\n",
       "   running  result                         stopped  index  \\\n",
       "0    False    -1.0  2020-01-02T10:00:00.000000000Z      1   \n",
       "1    False    -1.0  2020-01-06T18:00:00.000000000Z      6   \n",
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       "4    False     2.0  2020-01-08T14:00:00.000000000Z     26   \n",
       "\n",
       "                           opened  \n",
       "0  2020-01-02T06:00:00.000000000Z  \n",
       "1  2020-01-03T02:00:00.000000000Z  \n",
       "2  2020-01-06T14:00:00.000000000Z  \n",
       "3  2020-01-07T14:00:00.000000000Z  \n",
       "4  2020-01-08T10:00:00.000000000Z  "
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     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_trades.head()"
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  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
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   "cell_type": "code",
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