04 Import financial data.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "a465f2ae",
   "metadata": {},
   "source": [
    "# Chapter 04: Import financial data\n",
    "\n",
    "📈Join our community: https://discord.gg/wXjNPAc5BH\n",
    "\n",
    "📚Read our book: https://www.amazon.com/gp/product/B09HG18CYL \n",
    "\n",
    "🖥️Quantreo's YouTube channel: https://www.youtube.com/channel/UCp7jckfiEglNf_Gj62VR0pw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0ac39669",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "import MetaTrader5 as mt5\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d8361fa",
   "metadata": {},
   "source": [
    "### IMPORT TICKS DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78e9601a",
   "metadata": {},
   "source": [
    "##### Import ticks from"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4d3e100b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt5.initialize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f275acb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "array([(1647246650, 1.09201, 1.09201, 0., 0, 1647246650032, 6, 0.),\n",
       "       (1647246650, 1.09202, 1.09202, 0., 0, 1647246650242, 6, 0.),\n",
       "       (1647246650, 1.09201, 1.09201, 0., 0, 1647246650474, 6, 0.),\n",
       "       (1647246650, 1.09203, 1.09203, 0., 0, 1647246650905, 6, 0.),\n",
       "       (1647246651, 1.09205, 1.09205, 0., 0, 1647246651039, 6, 0.),\n",
       "       (1647246651, 1.09207, 1.09207, 0., 0, 1647246651137, 6, 0.),\n",
       "       (1647246651, 1.09208, 1.09208, 0., 0, 1647246651382, 6, 0.),\n",
       "       (1647246651, 1.09209, 1.09209, 0., 0, 1647246651761, 6, 0.),\n",
       "       (1647246651, 1.09208, 1.09208, 0., 0, 1647246651980, 6, 0.),\n",
       "       (1647246654, 1.09207, 1.09207, 0., 0, 1647246654451, 6, 0.)],\n",
       "      dtype=[('time', '<i8'), ('bid', '<f8'), ('ask', '<f8'), ('last', '<f8'), ('volume', '<u8'), ('time_msc', '<i8'), ('flags', '<u4'), ('volume_real', '<f8')])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import ticks from a date to \n",
    "\n",
    "# Compute now date\n",
    "from_date = datetime.now()\n",
    "\n",
    "# Extract n Ticks before now\n",
    "mt5.copy_ticks_from(\"EURUSD\", from_date, 10, mt5.COPY_TICKS_ALL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7e2d7e7b",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "      <th>last</th>\n",
       "      <th>volume</th>\n",
       "      <th>time_msc</th>\n",
       "      <th>flags</th>\n",
       "      <th>volume_real</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-03-14 08:33:29</td>\n",
       "      <td>1.09182</td>\n",
       "      <td>1.09184</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246809763</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-03-14 08:33:30</td>\n",
       "      <td>1.09183</td>\n",
       "      <td>1.09185</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246810974</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-03-14 08:33:31</td>\n",
       "      <td>1.09182</td>\n",
       "      <td>1.09184</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246811304</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-03-14 08:33:32</td>\n",
       "      <td>1.09181</td>\n",
       "      <td>1.09183</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246812942</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-03-14 08:33:33</td>\n",
       "      <td>1.09180</td>\n",
       "      <td>1.09182</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246813060</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-03-14 08:33:33</td>\n",
       "      <td>1.09181</td>\n",
       "      <td>1.09183</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246813178</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-03-14 08:33:33</td>\n",
       "      <td>1.09179</td>\n",
       "      <td>1.09181</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246813405</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-03-14 08:33:33</td>\n",
       "      <td>1.09180</td>\n",
       "      <td>1.09182</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246813927</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022-03-14 08:33:34</td>\n",
       "      <td>1.09179</td>\n",
       "      <td>1.09181</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246814273</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2022-03-14 08:33:34</td>\n",
       "      <td>1.09180</td>\n",
       "      <td>1.09182</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647246814982</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
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      "text/plain": [
       "                 time      bid      ask  last  volume       time_msc  flags  \\\n",
       "0 2022-03-14 08:33:29  1.09182  1.09184   0.0       0  1647246809763      6   \n",
       "1 2022-03-14 08:33:30  1.09183  1.09185   0.0       0  1647246810974      6   \n",
       "2 2022-03-14 08:33:31  1.09182  1.09184   0.0       0  1647246811304      6   \n",
       "3 2022-03-14 08:33:32  1.09181  1.09183   0.0       0  1647246812942      6   \n",
       "4 2022-03-14 08:33:33  1.09180  1.09182   0.0       0  1647246813060      6   \n",
       "5 2022-03-14 08:33:33  1.09181  1.09183   0.0       0  1647246813178      6   \n",
       "6 2022-03-14 08:33:33  1.09179  1.09181   0.0       0  1647246813405      6   \n",
       "7 2022-03-14 08:33:33  1.09180  1.09182   0.0       0  1647246813927      6   \n",
       "8 2022-03-14 08:33:34  1.09179  1.09181   0.0       0  1647246814273      6   \n",
       "9 2022-03-14 08:33:34  1.09180  1.09182   0.0       0  1647246814982      6   \n",
       "\n",
       "   volume_real  \n",
       "0          0.0  \n",
       "1          0.0  \n",
       "2          0.0  \n",
       "3          0.0  \n",
       "4          0.0  \n",
       "5          0.0  \n",
       "6          0.0  \n",
       "7          0.0  \n",
       "8          0.0  \n",
       "9          0.0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "# Compute now date\n",
    "\n",
    "\n",
    "# Compute now date\n",
    "from_date = datetime.now()\n",
    "\n",
    "# Extract n Ticks before now\n",
    "ticks = mt5.copy_ticks_from(\"EURUSD\", from_date, 10, mt5.COPY_TICKS_ALL)\n",
    "\n",
    "# Transfrom a tuple into a dataframe\n",
    "df_ticks = pd.DataFrame(ticks)\n",
    "\n",
    "# Convert number format of the date into date format\n",
    "df_ticks[\"time\"] = pd.to_datetime(df_ticks[\"time\"], unit=\"s\")\n",
    "\n",
    "\n",
    "df_ticks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a55e6cb0",
   "metadata": {},
   "source": [
    "##### Import ticks Range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "128e3558",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "      <th>last</th>\n",
       "      <th>volume</th>\n",
       "      <th>time_msc</th>\n",
       "      <th>flags</th>\n",
       "      <th>volume_real</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-01-04 23:00:00</td>\n",
       "      <td>1.12847</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-01-04 23:00:00</td>\n",
       "      <td>1.12845</td>\n",
       "      <td>1.12846</td>\n",
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       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-01-04 23:00:00</td>\n",
       "      <td>1.12842</td>\n",
       "      <td>1.12843</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641337200907</td>\n",
       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-01-04 23:00:01</td>\n",
       "      <td>1.12842</td>\n",
       "      <td>1.12847</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641337201109</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-01-04 23:00:01</td>\n",
       "      <td>1.12843</td>\n",
       "      <td>1.12848</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641337201733</td>\n",
       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>62585</th>\n",
       "      <td>2022-01-05 22:59:58</td>\n",
       "      <td>1.13108</td>\n",
       "      <td>1.13109</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641423598169</td>\n",
       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62586</th>\n",
       "      <td>2022-01-05 22:59:58</td>\n",
       "      <td>1.13109</td>\n",
       "      <td>1.13110</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641423598506</td>\n",
       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62587</th>\n",
       "      <td>2022-01-05 22:59:59</td>\n",
       "      <td>1.13108</td>\n",
       "      <td>1.13109</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641423599100</td>\n",
       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62588</th>\n",
       "      <td>2022-01-05 22:59:59</td>\n",
       "      <td>1.13109</td>\n",
       "      <td>1.13110</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641423599836</td>\n",
       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>62589</th>\n",
       "      <td>2022-01-05 22:59:59</td>\n",
       "      <td>1.13110</td>\n",
       "      <td>1.13111</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1641423599943</td>\n",
       "      <td>134</td>\n",
       "      <td>0.0</td>\n",
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      "text/plain": [
       "                     time      bid      ask  last  volume       time_msc  \\\n",
       "0     2022-01-04 23:00:00  1.12847  1.12848   0.0       0  1641337200067   \n",
       "1     2022-01-04 23:00:00  1.12845  1.12846   0.0       0  1641337200772   \n",
       "2     2022-01-04 23:00:00  1.12842  1.12843   0.0       0  1641337200907   \n",
       "3     2022-01-04 23:00:01  1.12842  1.12847   0.0       0  1641337201109   \n",
       "4     2022-01-04 23:00:01  1.12843  1.12848   0.0       0  1641337201733   \n",
       "...                   ...      ...      ...   ...     ...            ...   \n",
       "62585 2022-01-05 22:59:58  1.13108  1.13109   0.0       0  1641423598169   \n",
       "62586 2022-01-05 22:59:58  1.13109  1.13110   0.0       0  1641423598506   \n",
       "62587 2022-01-05 22:59:59  1.13108  1.13109   0.0       0  1641423599100   \n",
       "62588 2022-01-05 22:59:59  1.13109  1.13110   0.0       0  1641423599836   \n",
       "62589 2022-01-05 22:59:59  1.13110  1.13111   0.0       0  1641423599943   \n",
       "\n",
       "       flags  volume_real  \n",
       "0        130          0.0  \n",
       "1        134          0.0  \n",
       "2        134          0.0  \n",
       "3          4          0.0  \n",
       "4        134          0.0  \n",
       "...      ...          ...  \n",
       "62585    134          0.0  \n",
       "62586    134          0.0  \n",
       "62587    134          0.0  \n",
       "62588    134          0.0  \n",
       "62589    134          0.0  \n",
       "\n",
       "[62590 rows x 8 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute now date\n",
    "from_date = datetime(2022, 1, 5)\n",
    "to_date = datetime(2022, 1, 6)\n",
    "\n",
    "# Extract n Ticks before now\n",
    "ticks = mt5.copy_ticks_range(\"EURUSD\", from_date, to_date, mt5.COPY_TICKS_ALL)\n",
    "\n",
    "# Transform Tuple into a DataFrame\n",
    "df_ticks = pd.DataFrame(ticks)\n",
    "\n",
    "# Convert number format of the date into date format\n",
    "df_ticks[\"time\"] = pd.to_datetime(df_ticks[\"time\"], unit=\"s\")\n",
    "\n",
    "\n",
    "df_ticks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09702533",
   "metadata": {},
   "source": [
    "### IMPORT RATES DATA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2b7227c",
   "metadata": {},
   "source": [
    "##### Import rates from"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "db5864f0",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_volume</th>\n",
       "      <th>spread</th>\n",
       "      <th>real_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-02-22</td>\n",
       "      <td>1.13070</td>\n",
       "      <td>1.13670</td>\n",
       "      <td>1.12878</td>\n",
       "      <td>1.13241</td>\n",
       "      <td>102907</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-02-23</td>\n",
       "      <td>1.13246</td>\n",
       "      <td>1.13588</td>\n",
       "      <td>1.13012</td>\n",
       "      <td>1.13051</td>\n",
       "      <td>64439</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-02-24</td>\n",
       "      <td>1.13023</td>\n",
       "      <td>1.13086</td>\n",
       "      <td>1.11063</td>\n",
       "      <td>1.11919</td>\n",
       "      <td>171175</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-02-25</td>\n",
       "      <td>1.11908</td>\n",
       "      <td>1.12735</td>\n",
       "      <td>1.11659</td>\n",
       "      <td>1.12716</td>\n",
       "      <td>113512</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-02-28</td>\n",
       "      <td>1.11295</td>\n",
       "      <td>1.12464</td>\n",
       "      <td>1.11245</td>\n",
       "      <td>1.12178</td>\n",
       "      <td>138468</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-03-01</td>\n",
       "      <td>1.12177</td>\n",
       "      <td>1.12331</td>\n",
       "      <td>1.10897</td>\n",
       "      <td>1.11229</td>\n",
       "      <td>114181</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-03-02</td>\n",
       "      <td>1.11248</td>\n",
       "      <td>1.11434</td>\n",
       "      <td>1.10574</td>\n",
       "      <td>1.11184</td>\n",
       "      <td>129648</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-03-03</td>\n",
       "      <td>1.11160</td>\n",
       "      <td>1.11205</td>\n",
       "      <td>1.10332</td>\n",
       "      <td>1.10659</td>\n",
       "      <td>99725</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022-03-04</td>\n",
       "      <td>1.10651</td>\n",
       "      <td>1.10679</td>\n",
       "      <td>1.08852</td>\n",
       "      <td>1.09305</td>\n",
       "      <td>129366</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2022-03-07</td>\n",
       "      <td>1.09255</td>\n",
       "      <td>1.09324</td>\n",
       "      <td>1.08060</td>\n",
       "      <td>1.08533</td>\n",
       "      <td>166436</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2022-03-08</td>\n",
       "      <td>1.08511</td>\n",
       "      <td>1.09583</td>\n",
       "      <td>1.08471</td>\n",
       "      <td>1.09014</td>\n",
       "      <td>158841</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2022-03-09</td>\n",
       "      <td>1.08960</td>\n",
       "      <td>1.10961</td>\n",
       "      <td>1.08896</td>\n",
       "      <td>1.10750</td>\n",
       "      <td>116644</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022-03-10</td>\n",
       "      <td>1.10729</td>\n",
       "      <td>1.11213</td>\n",
       "      <td>1.09758</td>\n",
       "      <td>1.09859</td>\n",
       "      <td>125689</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2022-03-11</td>\n",
       "      <td>1.09845</td>\n",
       "      <td>1.10434</td>\n",
       "      <td>1.09021</td>\n",
       "      <td>1.09137</td>\n",
       "      <td>113278</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2022-03-14</td>\n",
       "      <td>1.09155</td>\n",
       "      <td>1.09547</td>\n",
       "      <td>1.09004</td>\n",
       "      <td>1.09528</td>\n",
       "      <td>35521</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         time     open     high      low    close  tick_volume  spread  \\\n",
       "0  2022-02-22  1.13070  1.13670  1.12878  1.13241       102907       0   \n",
       "1  2022-02-23  1.13246  1.13588  1.13012  1.13051        64439       0   \n",
       "2  2022-02-24  1.13023  1.13086  1.11063  1.11919       171175       0   \n",
       "3  2022-02-25  1.11908  1.12735  1.11659  1.12716       113512       0   \n",
       "4  2022-02-28  1.11295  1.12464  1.11245  1.12178       138468       0   \n",
       "5  2022-03-01  1.12177  1.12331  1.10897  1.11229       114181       0   \n",
       "6  2022-03-02  1.11248  1.11434  1.10574  1.11184       129648       0   \n",
       "7  2022-03-03  1.11160  1.11205  1.10332  1.10659        99725       0   \n",
       "8  2022-03-04  1.10651  1.10679  1.08852  1.09305       129366       0   \n",
       "9  2022-03-07  1.09255  1.09324  1.08060  1.08533       166436       0   \n",
       "10 2022-03-08  1.08511  1.09583  1.08471  1.09014       158841       0   \n",
       "11 2022-03-09  1.08960  1.10961  1.08896  1.10750       116644       0   \n",
       "12 2022-03-10  1.10729  1.11213  1.09758  1.09859       125689       0   \n",
       "13 2022-03-11  1.09845  1.10434  1.09021  1.09137       113278       0   \n",
       "14 2022-03-14  1.09155  1.09547  1.09004  1.09528        35521       0   \n",
       "\n",
       "    real_volume  \n",
       "0             0  \n",
       "1             0  \n",
       "2             0  \n",
       "3             0  \n",
       "4             0  \n",
       "5             0  \n",
       "6             0  \n",
       "7             0  \n",
       "8             0  \n",
       "9             0  \n",
       "10            0  \n",
       "11            0  \n",
       "12            0  \n",
       "13            0  \n",
       "14            0  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute now date\n",
    "from_date = datetime.now()\n",
    "\n",
    "# Extract n Ticks before now\n",
    "rates = mt5.copy_rates_from(\"EURUSD\", mt5.TIMEFRAME_D1, from_date, 15)\n",
    "\n",
    "# Transform Tuple into a DataFrame\n",
    "df_rates = pd.DataFrame(rates)\n",
    "\n",
    "# Convert number format of the date into date format\n",
    "df_rates[\"time\"] = pd.to_datetime(df_rates[\"time\"], unit=\"s\")\n",
    "\n",
    "df_rates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b90a0972",
   "metadata": {},
   "source": [
    "##### Import rates range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "516b4b18",
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_volume</th>\n",
       "      <th>spread</th>\n",
       "      <th>real_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-12-31 23:00:00</td>\n",
       "      <td>1.13755</td>\n",
       "      <td>1.13755</td>\n",
       "      <td>1.13755</td>\n",
       "      <td>1.13755</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-01-03 00:05:00</td>\n",
       "      <td>1.13693</td>\n",
       "      <td>1.13693</td>\n",
       "      <td>1.13688</td>\n",
       "      <td>1.13688</td>\n",
       "      <td>5</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-01-03 00:06:00</td>\n",
       "      <td>1.13689</td>\n",
       "      <td>1.13690</td>\n",
       "      <td>1.13652</td>\n",
       "      <td>1.13655</td>\n",
       "      <td>10</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-01-03 00:07:00</td>\n",
       "      <td>1.13655</td>\n",
       "      <td>1.13678</td>\n",
       "      <td>1.13645</td>\n",
       "      <td>1.13678</td>\n",
       "      <td>26</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-01-03 00:08:00</td>\n",
       "      <td>1.13678</td>\n",
       "      <td>1.13678</td>\n",
       "      <td>1.13673</td>\n",
       "      <td>1.13675</td>\n",
       "      <td>7</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7186</th>\n",
       "      <td>2022-01-07 23:50:00</td>\n",
       "      <td>1.13612</td>\n",
       "      <td>1.13612</td>\n",
       "      <td>1.13597</td>\n",
       "      <td>1.13598</td>\n",
       "      <td>29</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7187</th>\n",
       "      <td>2022-01-07 23:51:00</td>\n",
       "      <td>1.13597</td>\n",
       "      <td>1.13597</td>\n",
       "      <td>1.13584</td>\n",
       "      <td>1.13589</td>\n",
       "      <td>31</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7188</th>\n",
       "      <td>2022-01-07 23:52:00</td>\n",
       "      <td>1.13589</td>\n",
       "      <td>1.13590</td>\n",
       "      <td>1.13584</td>\n",
       "      <td>1.13586</td>\n",
       "      <td>20</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7189</th>\n",
       "      <td>2022-01-07 23:53:00</td>\n",
       "      <td>1.13585</td>\n",
       "      <td>1.13585</td>\n",
       "      <td>1.13580</td>\n",
       "      <td>1.13582</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7190</th>\n",
       "      <td>2022-01-07 23:54:00</td>\n",
       "      <td>1.13585</td>\n",
       "      <td>1.13591</td>\n",
       "      <td>1.13581</td>\n",
       "      <td>1.13590</td>\n",
       "      <td>22</td>\n",
       "      <td>14</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7191 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    time     open     high      low    close  tick_volume  \\\n",
       "0    2021-12-31 23:00:00  1.13755  1.13755  1.13755  1.13755            1   \n",
       "1    2022-01-03 00:05:00  1.13693  1.13693  1.13688  1.13688            5   \n",
       "2    2022-01-03 00:06:00  1.13689  1.13690  1.13652  1.13655           10   \n",
       "3    2022-01-03 00:07:00  1.13655  1.13678  1.13645  1.13678           26   \n",
       "4    2022-01-03 00:08:00  1.13678  1.13678  1.13673  1.13675            7   \n",
       "...                  ...      ...      ...      ...      ...          ...   \n",
       "7186 2022-01-07 23:50:00  1.13612  1.13612  1.13597  1.13598           29   \n",
       "7187 2022-01-07 23:51:00  1.13597  1.13597  1.13584  1.13589           31   \n",
       "7188 2022-01-07 23:52:00  1.13589  1.13590  1.13584  1.13586           20   \n",
       "7189 2022-01-07 23:53:00  1.13585  1.13585  1.13580  1.13582           10   \n",
       "7190 2022-01-07 23:54:00  1.13585  1.13591  1.13581  1.13590           22   \n",
       "\n",
       "      spread  real_volume  \n",
       "0         11            0  \n",
       "1         65            0  \n",
       "2         38            0  \n",
       "3         32            0  \n",
       "4         31            0  \n",
       "...      ...          ...  \n",
       "7186      14            0  \n",
       "7187      13            0  \n",
       "7188      13            0  \n",
       "7189      14            0  \n",
       "7190      14            0  \n",
       "\n",
       "[7191 rows x 8 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute now date\n",
    "from_date = datetime(2022,1,1)\n",
    "to_date = datetime(2022,1,10)\n",
    "\n",
    "# Extract n Ticks before now\n",
    "rates = mt5.copy_rates_range(\"EURUSD\", mt5.TIMEFRAME_M1, from_date, to_date)\n",
    "\n",
    "# Transform Tuple into a DataFrame\n",
    "df_rates = pd.DataFrame(rates)\n",
    "\n",
    "# Convert number format of the date into date format\n",
    "df_rates[\"time\"] = pd.to_datetime(df_rates[\"time\"], unit=\"s\")\n",
    "\n",
    "df_rates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc7b47ec",
   "metadata": {},
   "source": [
    "### AUTOMATIZATION"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "230bc023",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_ticks(symbol, number_of_data = 10000):\n",
    "    # Compute now date\n",
    "    from_date = datetime.now()\n",
    "\n",
    "    # Extract n Ticks before now\n",
    "    ticks = mt5.copy_ticks_from(symbol, from_date, number_of_data,  mt5.COPY_TICKS_ALL)\n",
    "\n",
    "    # Transform Tuple into a DataFrame\n",
    "    df_ticks = pd.DataFrame(ticks)\n",
    "\n",
    "    # Convert number format of the date into date format\n",
    "    df_ticks[\"time\"] = pd.to_datetime(df_ticks[\"time\"], unit=\"s\")\n",
    "    \n",
    "    df_ticks = df_ticks.set_index(\"time\")\n",
    "    \n",
    "    return df_ticks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "c36e3403",
   "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>bid</th>\n",
       "      <th>ask</th>\n",
       "      <th>last</th>\n",
       "      <th>volume</th>\n",
       "      <th>time_msc</th>\n",
       "      <th>flags</th>\n",
       "      <th>volume_real</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2022-03-14 08:48:18</th>\n",
       "      <td>1.09207</td>\n",
       "      <td>1.09207</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1647247698409</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-14 08:48:19</th>\n",
       "      <td>1.09206</td>\n",
       "      <td>1.09206</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647247699137</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 08:48:19</th>\n",
       "      <td>1.09203</td>\n",
       "      <td>1.09203</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647247699260</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 08:48:19</th>\n",
       "      <td>1.09201</td>\n",
       "      <td>1.09201</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647247699378</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 08:48:20</th>\n",
       "      <td>1.09199</td>\n",
       "      <td>1.09199</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647247700791</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</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>2022-03-14 10:28:49</th>\n",
       "      <td>1.09462</td>\n",
       "      <td>1.09462</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647253729343</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 10:28:49</th>\n",
       "      <td>1.09463</td>\n",
       "      <td>1.09463</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647253729540</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 10:28:51</th>\n",
       "      <td>1.09464</td>\n",
       "      <td>1.09464</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647253731384</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 10:28:51</th>\n",
       "      <td>1.09468</td>\n",
       "      <td>1.09468</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647253731756</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 10:28:51</th>\n",
       "      <td>1.09469</td>\n",
       "      <td>1.09469</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1647253731829</td>\n",
       "      <td>6</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         bid      ask  last  volume       time_msc  flags  \\\n",
       "time                                                                        \n",
       "2022-03-14 08:48:18  1.09207  1.09207   0.0       0  1647247698409      6   \n",
       "2022-03-14 08:48:19  1.09206  1.09206   0.0       0  1647247699137      6   \n",
       "2022-03-14 08:48:19  1.09203  1.09203   0.0       0  1647247699260      6   \n",
       "2022-03-14 08:48:19  1.09201  1.09201   0.0       0  1647247699378      6   \n",
       "2022-03-14 08:48:20  1.09199  1.09199   0.0       0  1647247700791      6   \n",
       "...                      ...      ...   ...     ...            ...    ...   \n",
       "2022-03-14 10:28:49  1.09462  1.09462   0.0       0  1647253729343      6   \n",
       "2022-03-14 10:28:49  1.09463  1.09463   0.0       0  1647253729540      6   \n",
       "2022-03-14 10:28:51  1.09464  1.09464   0.0       0  1647253731384      6   \n",
       "2022-03-14 10:28:51  1.09468  1.09468   0.0       0  1647253731756      6   \n",
       "2022-03-14 10:28:51  1.09469  1.09469   0.0       0  1647253731829      6   \n",
       "\n",
       "                     volume_real  \n",
       "time                              \n",
       "2022-03-14 08:48:18          0.0  \n",
       "2022-03-14 08:48:19          0.0  \n",
       "2022-03-14 08:48:19          0.0  \n",
       "2022-03-14 08:48:19          0.0  \n",
       "2022-03-14 08:48:20          0.0  \n",
       "...                          ...  \n",
       "2022-03-14 10:28:49          0.0  \n",
       "2022-03-14 10:28:49          0.0  \n",
       "2022-03-14 10:28:51          0.0  \n",
       "2022-03-14 10:28:51          0.0  \n",
       "2022-03-14 10:28:51          0.0  \n",
       "\n",
       "[10000 rows x 7 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_ticks(\"EURUSD\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "1a34ae95",
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>tick_volume</th>\n",
       "      <th>spread</th>\n",
       "      <th>real_volume</th>\n",
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       "    <tr>\n",
       "      <th>time</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-03-08 05:00:00</th>\n",
       "      <td>1.08745</td>\n",
       "      <td>1.08789</td>\n",
       "      <td>1.08673</td>\n",
       "      <td>1.08675</td>\n",
       "      <td>2787</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-08 06:00:00</th>\n",
       "      <td>1.08675</td>\n",
       "      <td>1.08728</td>\n",
       "      <td>1.08649</td>\n",
       "      <td>1.08698</td>\n",
       "      <td>2671</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-08 07:00:00</th>\n",
       "      <td>1.08697</td>\n",
       "      <td>1.08703</td>\n",
       "      <td>1.08558</td>\n",
       "      <td>1.08598</td>\n",
       "      <td>3569</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-08 08:00:00</th>\n",
       "      <td>1.08597</td>\n",
       "      <td>1.08664</td>\n",
       "      <td>1.08522</td>\n",
       "      <td>1.08604</td>\n",
       "      <td>4213</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-08 09:00:00</th>\n",
       "      <td>1.08605</td>\n",
       "      <td>1.08837</td>\n",
       "      <td>1.08509</td>\n",
       "      <td>1.08614</td>\n",
       "      <td>8196</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-14 04:00:00</th>\n",
       "      <td>1.09173</td>\n",
       "      <td>1.09182</td>\n",
       "      <td>1.09004</td>\n",
       "      <td>1.09095</td>\n",
       "      <td>3885</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 05:00:00</th>\n",
       "      <td>1.09095</td>\n",
       "      <td>1.09123</td>\n",
       "      <td>1.09044</td>\n",
       "      <td>1.09049</td>\n",
       "      <td>2324</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-14 06:00:00</th>\n",
       "      <td>1.09049</td>\n",
       "      <td>1.09174</td>\n",
       "      <td>1.09010</td>\n",
       "      <td>1.09170</td>\n",
       "      <td>1732</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-14 07:00:00</th>\n",
       "      <td>1.09168</td>\n",
       "      <td>1.09181</td>\n",
       "      <td>1.09086</td>\n",
       "      <td>1.09111</td>\n",
       "      <td>2106</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2022-03-14 08:00:00</th>\n",
       "      <td>1.09110</td>\n",
       "      <td>1.09231</td>\n",
       "      <td>1.09094</td>\n",
       "      <td>1.09176</td>\n",
       "      <td>2474</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        open     high      low    close  tick_volume  spread  \\\n",
       "time                                                                           \n",
       "2022-03-08 05:00:00  1.08745  1.08789  1.08673  1.08675         2787       0   \n",
       "2022-03-08 06:00:00  1.08675  1.08728  1.08649  1.08698         2671       0   \n",
       "2022-03-08 07:00:00  1.08697  1.08703  1.08558  1.08598         3569       0   \n",
       "2022-03-08 08:00:00  1.08597  1.08664  1.08522  1.08604         4213       0   \n",
       "2022-03-08 09:00:00  1.08605  1.08837  1.08509  1.08614         8196       0   \n",
       "...                      ...      ...      ...      ...          ...     ...   \n",
       "2022-03-14 04:00:00  1.09173  1.09182  1.09004  1.09095         3885       0   \n",
       "2022-03-14 05:00:00  1.09095  1.09123  1.09044  1.09049         2324       0   \n",
       "2022-03-14 06:00:00  1.09049  1.09174  1.09010  1.09170         1732       0   \n",
       "2022-03-14 07:00:00  1.09168  1.09181  1.09086  1.09111         2106       0   \n",
       "2022-03-14 08:00:00  1.09110  1.09231  1.09094  1.09176         2474       0   \n",
       "\n",
       "                     real_volume  \n",
       "time                              \n",
       "2022-03-08 05:00:00            0  \n",
       "2022-03-08 06:00:00            0  \n",
       "2022-03-08 07:00:00            0  \n",
       "2022-03-08 08:00:00            0  \n",
       "2022-03-08 09:00:00            0  \n",
       "...                          ...  \n",
       "2022-03-14 04:00:00            0  \n",
       "2022-03-14 05:00:00            0  \n",
       "2022-03-14 06:00:00            0  \n",
       "2022-03-14 07:00:00            0  \n",
       "2022-03-14 08:00:00            0  \n",
       "\n",
       "[100 rows x 7 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_rates(symbol, number_of_data = 10000, timeframe=mt5.TIMEFRAME_D1):\n",
    "    # Compute now date\n",
    "    from_date = datetime.now()\n",
    "\n",
    "    # Extract n Ticks before now\n",
    "    rates = mt5.copy_rates_from(symbol, timeframe, from_date, number_of_data)\n",
    "\n",
    "\n",
    "    # Transform Tuple into a DataFrame\n",
    "    df_rates = pd.DataFrame(rates)\n",
    "\n",
    "    # Convert number format of the date into date format\n",
    "    df_rates[\"time\"] = pd.to_datetime(df_rates[\"time\"], unit=\"s\")\n",
    "    \n",
    "    df_rates = df_rates.set_index(\"time\")\n",
    "    \n",
    "    return df_rates\n",
    "\n",
    "get_rates(\"EURUSD\", number_of_data = 100, timeframe=mt5.TIMEFRAME_H1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "91673865",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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