diff --git a/data.ipynb b/data.ipynb
new file mode 100644
index 0000000..9e0ca72
--- /dev/null
+++ b/data.ipynb
@@ -0,0 +1,496 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "2acce44b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "5ba70af7",
+   "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>Timestamp</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Volume</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>7317754</th>\n",
+       "      <td>2025-11-30 23:55:00+00:00</td>\n",
+       "      <td>90405.0</td>\n",
+       "      <td>90452.0</td>\n",
+       "      <td>90403.0</td>\n",
+       "      <td>90452.0</td>\n",
+       "      <td>0.531700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7317755</th>\n",
+       "      <td>2025-11-30 23:56:00+00:00</td>\n",
+       "      <td>90452.0</td>\n",
+       "      <td>90481.0</td>\n",
+       "      <td>90420.0</td>\n",
+       "      <td>90420.0</td>\n",
+       "      <td>0.055547</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7317756</th>\n",
+       "      <td>2025-11-30 23:57:00+00:00</td>\n",
+       "      <td>90412.0</td>\n",
+       "      <td>90458.0</td>\n",
+       "      <td>90396.0</td>\n",
+       "      <td>90435.0</td>\n",
+       "      <td>0.301931</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7317757</th>\n",
+       "      <td>2025-11-30 23:58:00+00:00</td>\n",
+       "      <td>90428.0</td>\n",
+       "      <td>90428.0</td>\n",
+       "      <td>90362.0</td>\n",
+       "      <td>90362.0</td>\n",
+       "      <td>4.591653</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7317758</th>\n",
+       "      <td>2025-11-30 23:59:00+00:00</td>\n",
+       "      <td>90363.0</td>\n",
+       "      <td>90386.0</td>\n",
+       "      <td>90362.0</td>\n",
+       "      <td>90382.0</td>\n",
+       "      <td>0.410369</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        Timestamp     Open     High      Low    Close  \\\n",
+       "7317754 2025-11-30 23:55:00+00:00  90405.0  90452.0  90403.0  90452.0   \n",
+       "7317755 2025-11-30 23:56:00+00:00  90452.0  90481.0  90420.0  90420.0   \n",
+       "7317756 2025-11-30 23:57:00+00:00  90412.0  90458.0  90396.0  90435.0   \n",
+       "7317757 2025-11-30 23:58:00+00:00  90428.0  90428.0  90362.0  90362.0   \n",
+       "7317758 2025-11-30 23:59:00+00:00  90363.0  90386.0  90362.0  90382.0   \n",
+       "\n",
+       "           Volume  \n",
+       "7317754  0.531700  \n",
+       "7317755  0.055547  \n",
+       "7317756  0.301931  \n",
+       "7317757  4.591653  \n",
+       "7317758  0.410369  "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(\"data.csv\")\n",
+    "df['Timestamp'] = pd.to_datetime(df['Timestamp'], unit='s', utc=True)\n",
+    "df.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "d4b22f3b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Timestamp</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>Close</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5078</th>\n",
+       "      <td>2025-11-26</td>\n",
+       "      <td>86304.0</td>\n",
+       "      <td>90646.0</td>\n",
+       "      <td>87331.0</td>\n",
+       "      <td>90477.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5079</th>\n",
+       "      <td>2025-11-27</td>\n",
+       "      <td>90091.0</td>\n",
+       "      <td>91926.0</td>\n",
+       "      <td>90476.0</td>\n",
+       "      <td>91325.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5080</th>\n",
+       "      <td>2025-11-28</td>\n",
+       "      <td>90233.0</td>\n",
+       "      <td>93091.0</td>\n",
+       "      <td>91326.0</td>\n",
+       "      <td>90913.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5081</th>\n",
+       "      <td>2025-11-29</td>\n",
+       "      <td>90216.0</td>\n",
+       "      <td>91179.0</td>\n",
+       "      <td>90913.0</td>\n",
+       "      <td>90832.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5082</th>\n",
+       "      <td>2025-11-30</td>\n",
+       "      <td>90362.0</td>\n",
+       "      <td>91969.0</td>\n",
+       "      <td>90832.0</td>\n",
+       "      <td>90382.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Timestamp      Low     High     Open    Close\n",
+       "5078  2025-11-26  86304.0  90646.0  87331.0  90477.0\n",
+       "5079  2025-11-27  90091.0  91926.0  90476.0  91325.0\n",
+       "5080  2025-11-28  90233.0  93091.0  91326.0  90913.0\n",
+       "5081  2025-11-29  90216.0  91179.0  90913.0  90832.0\n",
+       "5082  2025-11-30  90362.0  91969.0  90832.0  90382.0"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_days = (\n",
+    "    df.groupby(df[\"Timestamp\"].dt.date)\n",
+    "    .agg({\"Low\": \"min\", \"High\": \"max\", \"Open\": \"first\", \"Close\": \"last\"})\n",
+    "    .reset_index()\n",
+    ")\n",
+    "df_days.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "91823496",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "\n",
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+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Timestamp</th>\n",
+       "      <th>Low</th>\n",
+       "      <th>High</th>\n",
+       "      <th>Open</th>\n",
+       "      <th>Close</th>\n",
+       "      <th>Avg</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>5078</th>\n",
+       "      <td>2025-11-26</td>\n",
+       "      <td>86304.0</td>\n",
+       "      <td>90646.0</td>\n",
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+       "      <th>5079</th>\n",
+       "      <td>2025-11-27</td>\n",
+       "      <td>90091.0</td>\n",
+       "      <td>91926.0</td>\n",
+       "      <td>90476.0</td>\n",
+       "      <td>91325.0</td>\n",
+       "      <td>91008.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5080</th>\n",
+       "      <td>2025-11-28</td>\n",
+       "      <td>90233.0</td>\n",
+       "      <td>93091.0</td>\n",
+       "      <td>91326.0</td>\n",
+       "      <td>90913.0</td>\n",
+       "      <td>91662.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5081</th>\n",
+       "      <td>2025-11-29</td>\n",
+       "      <td>90216.0</td>\n",
+       "      <td>91179.0</td>\n",
+       "      <td>90913.0</td>\n",
+       "      <td>90832.0</td>\n",
+       "      <td>90697.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5082</th>\n",
+       "      <td>2025-11-30</td>\n",
+       "      <td>90362.0</td>\n",
+       "      <td>91969.0</td>\n",
+       "      <td>90832.0</td>\n",
+       "      <td>90382.0</td>\n",
+       "      <td>91165.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Timestamp      Low     High     Open    Close      Avg\n",
+       "5078  2025-11-26  86304.0  90646.0  87331.0  90477.0  88475.0\n",
+       "5079  2025-11-27  90091.0  91926.0  90476.0  91325.0  91008.5\n",
+       "5080  2025-11-28  90233.0  93091.0  91326.0  90913.0  91662.0\n",
+       "5081  2025-11-29  90216.0  91179.0  90913.0  90832.0  90697.5\n",
+       "5082  2025-11-30  90362.0  91969.0  90832.0  90382.0  91165.5"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_days[\"Avg\"] = (df_days[\"Low\"] + df_days[\"High\"]) / 2\n",
+    "df_days.tail()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "9a7b3310",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
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+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>start_date</th>\n",
+       "      <th>end_date</th>\n",
+       "      <th>min_open</th>\n",
+       "      <th>max_close</th>\n",
+       "      <th>start_avg</th>\n",
+       "      <th>end_avg</th>\n",
+       "      <th>change</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>335</th>\n",
+       "      <td>2025-02-27</td>\n",
+       "      <td>2025-04-23</td>\n",
+       "      <td>76252.0</td>\n",
+       "      <td>94273.0</td>\n",
+       "      <td>84801.5</td>\n",
+       "      <td>93335.0</td>\n",
+       "      <td>0.100629</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>336</th>\n",
+       "      <td>2025-04-24</td>\n",
+       "      <td>2025-05-09</td>\n",
+       "      <td>93730.0</td>\n",
+       "      <td>103261.0</td>\n",
+       "      <td>92867.5</td>\n",
+       "      <td>103341.0</td>\n",
+       "      <td>0.112779</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>337</th>\n",
+       "      <td>2025-05-10</td>\n",
+       "      <td>2025-07-11</td>\n",
+       "      <td>100990.0</td>\n",
+       "      <td>117579.0</td>\n",
+       "      <td>103915.0</td>\n",
+       "      <td>117032.5</td>\n",
+       "      <td>0.126233</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>338</th>\n",
+       "      <td>2025-07-12</td>\n",
+       "      <td>2025-11-04</td>\n",
+       "      <td>106470.0</td>\n",
+       "      <td>124728.0</td>\n",
+       "      <td>117599.0</td>\n",
+       "      <td>103079.0</td>\n",
+       "      <td>0.123470</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>339</th>\n",
+       "      <td>2025-11-05</td>\n",
+       "      <td>2025-11-18</td>\n",
+       "      <td>92112.0</td>\n",
+       "      <td>105972.0</td>\n",
+       "      <td>101737.5</td>\n",
+       "      <td>91471.0</td>\n",
+       "      <td>0.100912</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     start_date    end_date  min_open  max_close  start_avg   end_avg  \\\n",
+       "335  2025-02-27  2025-04-23   76252.0    94273.0    84801.5   93335.0   \n",
+       "336  2025-04-24  2025-05-09   93730.0   103261.0    92867.5  103341.0   \n",
+       "337  2025-05-10  2025-07-11  100990.0   117579.0   103915.0  117032.5   \n",
+       "338  2025-07-12  2025-11-04  106470.0   124728.0   117599.0  103079.0   \n",
+       "339  2025-11-05  2025-11-18   92112.0   105972.0   101737.5   91471.0   \n",
+       "\n",
+       "       change  \n",
+       "335  0.100629  \n",
+       "336  0.112779  \n",
+       "337  0.126233  \n",
+       "338  0.123470  \n",
+       "339  0.100912  "
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "intervals = []\n",
+    "start_idx = 0\n",
+    "price_base = df_days.loc[start_idx, \"Avg\"]\n",
+    "\n",
+    "for i in range(1, len(df_days)):\n",
+    "    price_now = df_days.loc[i, \"Avg\"]\n",
+    "    change = abs(price_now - price_base) / price_base\n",
+    "\n",
+    "    if change >= 0.10:\n",
+    "        interval = df_days.loc[start_idx:i]\n",
+    "        \n",
+    "        intervals.append({\n",
+    "            \"start_date\": df_days.loc[start_idx, \"Timestamp\"],\n",
+    "            \"end_date\": df_days.loc[i, \"Timestamp\"],\n",
+    "            \"min_open\": interval[\"Open\"].min(),\n",
+    "            \"max_close\": interval[\"Close\"].max(),\n",
+    "            \"start_avg\": price_base,\n",
+    "            \"end_avg\": price_now,\n",
+    "            \"change\": change,\n",
+    "        })\n",
+    "\n",
+    "        start_idx = i + 1\n",
+    "        if start_idx >= len(df_days):\n",
+    "            break\n",
+    "        price_base = df_days.loc[start_idx, \"Avg\"]\n",
+    "\n",
+    "df_intervals = pd.DataFrame(intervals)\n",
+    "df_intervals.tail()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}