{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "aef8b826",
   "metadata": {},
   "source": [
    "# Aggregating"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "157bf535-0415-431d-a9d7-0375319e6bf1",
   "metadata": {},
   "source": [
    "Let's start with an unaggregated time series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "91d63514-8e66-4680-be77-252937bdd85d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        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>PRICE</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>COND</th>\n",
       "      <th>EXCHANGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-05-15 09:30:00.000178688</td>\n",
       "      <td>412.22</td>\n",
       "      <td>100</td>\n",
       "      <td>T</td>\n",
       "      <td>P</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-05-15 09:30:00.000776704</td>\n",
       "      <td>412.22</td>\n",
       "      <td>247</td>\n",
       "      <td></td>\n",
       "      <td>Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-05-15 09:30:00.003603456</td>\n",
       "      <td>412.22</td>\n",
       "      <td>100</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-05-15 09:30:00.006352128</td>\n",
       "      <td>412.24</td>\n",
       "      <td>1</td>\n",
       "      <td>I</td>\n",
       "      <td>K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-05-15 09:30:00.007128064</td>\n",
       "      <td>412.24</td>\n",
       "      <td>3</td>\n",
       "      <td>I</td>\n",
       "      <td>K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>2023-05-15 09:30:00.934032640</td>\n",
       "      <td>412.27</td>\n",
       "      <td>160</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>2023-05-15 09:30:00.975609344</td>\n",
       "      <td>412.24</td>\n",
       "      <td>2</td>\n",
       "      <td>I</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>2023-05-15 09:30:00.980264448</td>\n",
       "      <td>412.27</td>\n",
       "      <td>1</td>\n",
       "      <td>I</td>\n",
       "      <td>D</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>2023-05-15 09:30:00.985391616</td>\n",
       "      <td>412.28</td>\n",
       "      <td>100</td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>2023-05-15 09:30:00.985394944</td>\n",
       "      <td>412.28</td>\n",
       "      <td>100</td>\n",
       "      <td>Q</td>\n",
       "      <td>T</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>315 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Time   PRICE  SIZE  COND EXCHANGE\n",
       "0   2023-05-15 09:30:00.000178688  412.22   100    T         P\n",
       "1   2023-05-15 09:30:00.000776704  412.22   247              Z\n",
       "2   2023-05-15 09:30:00.003603456  412.22   100    T         T\n",
       "3   2023-05-15 09:30:00.006352128  412.24     1     I        K\n",
       "4   2023-05-15 09:30:00.007128064  412.24     3     I        K\n",
       "..                            ...     ...   ...   ...      ...\n",
       "310 2023-05-15 09:30:00.934032640  412.27   160    T         T\n",
       "311 2023-05-15 09:30:00.975609344  412.24     2     I        D\n",
       "312 2023-05-15 09:30:00.980264448  412.27     1     I        D\n",
       "313 2023-05-15 09:30:00.985391616  412.28   100              T\n",
       "314 2023-05-15 09:30:00.985394944  412.28   100     Q        T\n",
       "\n",
       "[315 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import onetick.py as otp\n",
    "\n",
    "s = otp.dt(2023, 5, 15, 9, 30)\n",
    "e = otp.dt(2023, 5, 15, 9, 30, 1)\n",
    "\n",
    "q = otp.DataSource('NYSE_TAQ', tick_type='TRD')\n",
    "q = q[['PRICE', 'SIZE', 'COND', 'EXCHANGE']]\n",
    "otp.run(q, start=s, end=e, symbols=['SPY'])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "56dbfa00-45b9-408c-bfc0-3ea78f601498",
   "metadata": {},
   "source": [
    "Let's make a note of the total number of trades.\n",
    "\n",
    "We can aggregate over the entire queried interval."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "34a94316-be74-4548-9f2f-0c7ea6781289",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</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>vwap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>324352</td>\n",
       "      <td>412.212012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Time  volume        vwap\n",
       "0 2023-05-15 09:30:01  324352  412.212012"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = otp.DataSource('NYSE_TAQ', tick_type='TRD')\n",
    "q = q[['PRICE', 'SIZE', 'COND', 'EXCHANGE']]\n",
    "q = q.agg({\n",
    "    'volume': otp.agg.sum('SIZE'),\n",
    "    'vwap': otp.agg.vwap('PRICE','SIZE')\n",
    "})\n",
    "otp.run(q, start=s, end=e, symbols=['SPY'])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "53f66ca3-1029-49d3-97c0-c1f4dd3ad842",
   "metadata": {},
   "source": [
    "Or over fixed buckets (aka bars or windows)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2d408201-90be-44e1-b8c5-0f4dc371e799",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>volume</th>\n",
       "      <th>vwap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-05-15 09:30:00.100</td>\n",
       "      <td>1498</td>\n",
       "      <td>412.235948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-05-15 09:30:00.200</td>\n",
       "      <td>7743</td>\n",
       "      <td>412.237833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-05-15 09:30:00.300</td>\n",
       "      <td>1815</td>\n",
       "      <td>412.243515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-05-15 09:30:00.400</td>\n",
       "      <td>307298</td>\n",
       "      <td>412.210324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-05-15 09:30:00.500</td>\n",
       "      <td>2205</td>\n",
       "      <td>412.250503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-05-15 09:30:00.600</td>\n",
       "      <td>416</td>\n",
       "      <td>412.258750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2023-05-15 09:30:00.700</td>\n",
       "      <td>276</td>\n",
       "      <td>412.244354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2023-05-15 09:30:00.800</td>\n",
       "      <td>1755</td>\n",
       "      <td>412.240875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2023-05-15 09:30:00.900</td>\n",
       "      <td>595</td>\n",
       "      <td>412.245782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2023-05-15 09:30:01.000</td>\n",
       "      <td>751</td>\n",
       "      <td>412.267643</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Time  volume        vwap\n",
       "0 2023-05-15 09:30:00.100    1498  412.235948\n",
       "1 2023-05-15 09:30:00.200    7743  412.237833\n",
       "2 2023-05-15 09:30:00.300    1815  412.243515\n",
       "3 2023-05-15 09:30:00.400  307298  412.210324\n",
       "4 2023-05-15 09:30:00.500    2205  412.250503\n",
       "5 2023-05-15 09:30:00.600     416  412.258750\n",
       "6 2023-05-15 09:30:00.700     276  412.244354\n",
       "7 2023-05-15 09:30:00.800    1755  412.240875\n",
       "8 2023-05-15 09:30:00.900     595  412.245782\n",
       "9 2023-05-15 09:30:01.000     751  412.267643"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = otp.DataSource('NYSE_TAQ', tick_type='TRD')\n",
    "q = q[['PRICE', 'SIZE', 'COND', 'EXCHANGE']]\n",
    "q = q.agg({\n",
    "    'volume': otp.agg.sum('SIZE'),\n",
    "    'vwap': otp.agg.vwap('PRICE','SIZE')\n",
    "}, bucket_interval=.1)\n",
    "otp.run(q, start=s, end=e, symbols=['SPY'])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "038be2be-08c2-432f-88c0-a021d3e6a737",
   "metadata": {},
   "source": [
    "Or over a sliding window."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "60d494a6-58ba-4b0a-9f5e-f6f01ecb9987",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>volume</th>\n",
       "      <th>vwap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-05-15 09:30:00.000178688</td>\n",
       "      <td>100</td>\n",
       "      <td>412.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-05-15 09:30:00.000776704</td>\n",
       "      <td>347</td>\n",
       "      <td>412.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-05-15 09:30:00.003603456</td>\n",
       "      <td>447</td>\n",
       "      <td>412.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-05-15 09:30:00.006352128</td>\n",
       "      <td>448</td>\n",
       "      <td>412.220045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-05-15 09:30:00.007128064</td>\n",
       "      <td>451</td>\n",
       "      <td>412.220177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>604</th>\n",
       "      <td>2023-05-15 09:30:00.980264448</td>\n",
       "      <td>553</td>\n",
       "      <td>412.263074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>605</th>\n",
       "      <td>2023-05-15 09:30:00.982660864</td>\n",
       "      <td>552</td>\n",
       "      <td>412.263062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>2023-05-15 09:30:00.985391616</td>\n",
       "      <td>652</td>\n",
       "      <td>412.265660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>607</th>\n",
       "      <td>2023-05-15 09:30:00.985394944</td>\n",
       "      <td>752</td>\n",
       "      <td>412.267566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>608</th>\n",
       "      <td>2023-05-15 09:30:00.993288704</td>\n",
       "      <td>751</td>\n",
       "      <td>412.267643</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>609 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Time  volume        vwap\n",
       "0   2023-05-15 09:30:00.000178688     100  412.220000\n",
       "1   2023-05-15 09:30:00.000776704     347  412.220000\n",
       "2   2023-05-15 09:30:00.003603456     447  412.220000\n",
       "3   2023-05-15 09:30:00.006352128     448  412.220045\n",
       "4   2023-05-15 09:30:00.007128064     451  412.220177\n",
       "..                            ...     ...         ...\n",
       "604 2023-05-15 09:30:00.980264448     553  412.263074\n",
       "605 2023-05-15 09:30:00.982660864     552  412.263062\n",
       "606 2023-05-15 09:30:00.985391616     652  412.265660\n",
       "607 2023-05-15 09:30:00.985394944     752  412.267566\n",
       "608 2023-05-15 09:30:00.993288704     751  412.267643\n",
       "\n",
       "[609 rows x 3 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = otp.DataSource('NYSE_TAQ', tick_type='TRD')\n",
    "q = q[['PRICE', 'SIZE', 'COND', 'EXCHANGE']]\n",
    "q = q.agg({\n",
    "    'volume': otp.agg.sum('SIZE'),\n",
    "    'vwap': otp.agg.vwap('PRICE','SIZE')\n",
    "}, bucket_interval=.1, running=True)\n",
    "otp.run(q, start=s, end=e, symbols=['SPY'])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "66ad92c4-2944-43c0-b950-7f6888f74867",
   "metadata": {},
   "source": [
    "Note that the number of output ticks is more than the number of  trades. This is due to the output tick being created not only when each input tick enters the window but also when it drops out."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8d28f734-8ffe-4525-9261-6f000944d27f",
   "metadata": {},
   "source": [
    "We can display all fields of the incoming tick along with the current values of the sliding window metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fad649b3-41c1-4dbb-b130-12f47eac85e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>PRICE</th>\n",
       "      <th>SIZE</th>\n",
       "      <th>COND</th>\n",
       "      <th>EXCHANGE</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-05-15 09:30:00.000178688</td>\n",
       "      <td>412.22</td>\n",
       "      <td>100</td>\n",
       "      <td>T</td>\n",
       "      <td>P</td>\n",
       "      <td>100</td>\n",
       "      <td>412.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-05-15 09:30:00.000776704</td>\n",
       "      <td>412.22</td>\n",
       "      <td>247</td>\n",
       "      <td></td>\n",
       "      <td>Z</td>\n",
       "      <td>347</td>\n",
       "      <td>412.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-05-15 09:30:00.003603456</td>\n",
       "      <td>412.22</td>\n",
       "      <td>100</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>447</td>\n",
       "      <td>412.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-05-15 09:30:00.006352128</td>\n",
       "      <td>412.24</td>\n",
       "      <td>1</td>\n",
       "      <td>I</td>\n",
       "      <td>K</td>\n",
       "      <td>448</td>\n",
       "      <td>412.220045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-05-15 09:30:00.007128064</td>\n",
       "      <td>412.24</td>\n",
       "      <td>3</td>\n",
       "      <td>I</td>\n",
       "      <td>K</td>\n",
       "      <td>451</td>\n",
       "      <td>412.220177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>310</th>\n",
       "      <td>2023-05-15 09:30:00.934032640</td>\n",
       "      <td>412.27</td>\n",
       "      <td>160</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>801</td>\n",
       "      <td>412.255893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>2023-05-15 09:30:00.975609344</td>\n",
       "      <td>412.24</td>\n",
       "      <td>2</td>\n",
       "      <td>I</td>\n",
       "      <td>D</td>\n",
       "      <td>552</td>\n",
       "      <td>412.263062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>2023-05-15 09:30:00.980264448</td>\n",
       "      <td>412.27</td>\n",
       "      <td>1</td>\n",
       "      <td>I</td>\n",
       "      <td>D</td>\n",
       "      <td>553</td>\n",
       "      <td>412.263074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>2023-05-15 09:30:00.985391616</td>\n",
       "      <td>412.28</td>\n",
       "      <td>100</td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td>652</td>\n",
       "      <td>412.265660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314</th>\n",
       "      <td>2023-05-15 09:30:00.985394944</td>\n",
       "      <td>412.28</td>\n",
       "      <td>100</td>\n",
       "      <td>Q</td>\n",
       "      <td>T</td>\n",
       "      <td>752</td>\n",
       "      <td>412.267566</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>315 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Time   PRICE  SIZE  COND EXCHANGE  volume        vwap\n",
       "0   2023-05-15 09:30:00.000178688  412.22   100    T         P     100  412.220000\n",
       "1   2023-05-15 09:30:00.000776704  412.22   247              Z     347  412.220000\n",
       "2   2023-05-15 09:30:00.003603456  412.22   100    T         T     447  412.220000\n",
       "3   2023-05-15 09:30:00.006352128  412.24     1     I        K     448  412.220045\n",
       "4   2023-05-15 09:30:00.007128064  412.24     3     I        K     451  412.220177\n",
       "..                            ...     ...   ...   ...      ...     ...         ...\n",
       "310 2023-05-15 09:30:00.934032640  412.27   160    T         T     801  412.255893\n",
       "311 2023-05-15 09:30:00.975609344  412.24     2     I        D     552  412.263062\n",
       "312 2023-05-15 09:30:00.980264448  412.27     1     I        D     553  412.263074\n",
       "313 2023-05-15 09:30:00.985391616  412.28   100              T     652  412.265660\n",
       "314 2023-05-15 09:30:00.985394944  412.28   100     Q        T     752  412.267566\n",
       "\n",
       "[315 rows x 7 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = otp.DataSource('NYSE_TAQ', tick_type='TRD')\n",
    "q = q[['PRICE', 'SIZE', 'COND', 'EXCHANGE']]\n",
    "q = q.agg({\n",
    "    'volume': otp.agg.sum('SIZE'),\n",
    "    'vwap': otp.agg.vwap('PRICE','SIZE')\n",
    "}, bucket_interval=.1, running=True, all_fields=True)\n",
    "otp.run(q, start=s, end=e, symbols=['SPY'])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "97d03ed4-cbf3-49e6-9989-8fee3b49b172",
   "metadata": {},
   "source": [
    "In this case, we are back to the same number of ticks as the number trades as an output tick is only created on arrival of an input tick."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "9e7454b1-deda-48dc-8a01-da63d48b4a5e",
   "metadata": {},
   "source": [
    "All of the aggregation operations support grouping."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b37e62f1-ff2c-4913-b9d7-bde925bfface",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>EXCHANGE</th>\n",
       "      <th>volume</th>\n",
       "      <th>vwap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>A</td>\n",
       "      <td>100</td>\n",
       "      <td>412.240000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>B</td>\n",
       "      <td>100</td>\n",
       "      <td>412.220000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>C</td>\n",
       "      <td>102</td>\n",
       "      <td>412.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>D</td>\n",
       "      <td>3269</td>\n",
       "      <td>412.231798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>H</td>\n",
       "      <td>8</td>\n",
       "      <td>412.260000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>K</td>\n",
       "      <td>2559</td>\n",
       "      <td>412.240684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>N</td>\n",
       "      <td>422</td>\n",
       "      <td>412.249976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>P</td>\n",
       "      <td>304988</td>\n",
       "      <td>412.210209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>T</td>\n",
       "      <td>8141</td>\n",
       "      <td>412.243563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>U</td>\n",
       "      <td>400</td>\n",
       "      <td>412.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>X</td>\n",
       "      <td>200</td>\n",
       "      <td>412.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2023-05-15 09:30:01</td>\n",
       "      <td>Z</td>\n",
       "      <td>4063</td>\n",
       "      <td>412.238673</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Time EXCHANGE  volume        vwap\n",
       "0  2023-05-15 09:30:01        A     100  412.240000\n",
       "1  2023-05-15 09:30:01        B     100  412.220000\n",
       "2  2023-05-15 09:30:01        C     102  412.250000\n",
       "3  2023-05-15 09:30:01        D    3269  412.231798\n",
       "4  2023-05-15 09:30:01        H       8  412.260000\n",
       "5  2023-05-15 09:30:01        K    2559  412.240684\n",
       "6  2023-05-15 09:30:01        N     422  412.249976\n",
       "7  2023-05-15 09:30:01        P  304988  412.210209\n",
       "8  2023-05-15 09:30:01        T    8141  412.243563\n",
       "9  2023-05-15 09:30:01        U     400  412.250000\n",
       "10 2023-05-15 09:30:01        X     200  412.250000\n",
       "11 2023-05-15 09:30:01        Z    4063  412.238673"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = otp.DataSource('NYSE_TAQ', tick_type='TRD')\n",
    "q = q[['PRICE', 'SIZE', 'COND', 'EXCHANGE']]\n",
    "q = q.agg({\n",
    "    'volume': otp.agg.sum('SIZE'),\n",
    "    'vwap': otp.agg.vwap('PRICE','SIZE')\n",
    "}, group_by=['EXCHANGE'])\n",
    "otp.run(q, start=s, end=e, symbols=['SPY'])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "4fefcfd9-3ed8-4341-968e-a9ea9fe81bf7",
   "metadata": {},
   "source": [
    "A list of all aggregations appears [here](../../api/aggregations/root.rst). It can also be retrieved with `dir(otp.agg)`."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "ccafbd04-38c1-4b7a-b4cf-5cda4bbc521f",
   "metadata": {},
   "source": [
    "**USE CASES**\n",
    "\n",
    "[Creating Bars](bars)\n",
    "\n",
    "[Golden Cross strategy](goldencross)"
   ]
  }
 ],
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