Pandas L5.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "193e503e",
   "metadata": {},
   "source": [
    "# Dates & Time Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c421917e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "05b0cce5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ASUS\\AppData\\Local\\Temp\\ipykernel_3420\\4245813629.py:1: FutureWarning: The pandas.datetime class is deprecated and will be removed from pandas in a future version. Import from datetime module instead.\n",
      "  d_parser = lambda x: pd.datetime.strptime(x, '%Y-%m-%d %H:%M:%S')\n"
     ]
    }
   ],
   "source": [
    "d_parser = lambda x: pd.datetime.strptime(x, '%Y-%m-%d %H:%M:%S')\n",
    "df = pd.read_csv('ETH_1h.csv', parse_dates=['Date'], date_parser=d_parser)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2c40d309",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>Unix Timestamp</th>\n",
       "      <th>Date</th>\n",
       "      <th>Symbol</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>0</th>\n",
       "      <td>1586995200000</td>\n",
       "      <td>2020-04-16 00:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>152.94</td>\n",
       "      <td>152.94</td>\n",
       "      <td>150.39</td>\n",
       "      <td>150.39</td>\n",
       "      <td>650.188125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1586991600000</td>\n",
       "      <td>2020-04-15 23:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>155.81</td>\n",
       "      <td>155.81</td>\n",
       "      <td>151.39</td>\n",
       "      <td>152.94</td>\n",
       "      <td>4277.567299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1586988000000</td>\n",
       "      <td>2020-04-15 22:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.18</td>\n",
       "      <td>157.30</td>\n",
       "      <td>155.32</td>\n",
       "      <td>155.81</td>\n",
       "      <td>106.337279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1586984400000</td>\n",
       "      <td>2020-04-15 21:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>158.04</td>\n",
       "      <td>158.31</td>\n",
       "      <td>157.16</td>\n",
       "      <td>157.18</td>\n",
       "      <td>55.244131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1586980800000</td>\n",
       "      <td>2020-04-15 20:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.10</td>\n",
       "      <td>158.10</td>\n",
       "      <td>156.87</td>\n",
       "      <td>158.04</td>\n",
       "      <td>144.262622</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unix Timestamp                Date  Symbol    Open    High     Low   Close  \\\n",
       "0   1586995200000 2020-04-16 00:00:00  ETHUSD  152.94  152.94  150.39  150.39   \n",
       "1   1586991600000 2020-04-15 23:00:00  ETHUSD  155.81  155.81  151.39  152.94   \n",
       "2   1586988000000 2020-04-15 22:00:00  ETHUSD  157.18  157.30  155.32  155.81   \n",
       "3   1586984400000 2020-04-15 21:00:00  ETHUSD  158.04  158.31  157.16  157.18   \n",
       "4   1586980800000 2020-04-15 20:00:00  ETHUSD  157.10  158.10  156.87  158.04   \n",
       "\n",
       "        Volume  \n",
       "0   650.188125  \n",
       "1  4277.567299  \n",
       "2   106.337279  \n",
       "3    55.244131  \n",
       "4   144.262622  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5eaad8ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(34497, 8)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d450c212",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unix Timestamp             int64\n",
       "Date              datetime64[ns]\n",
       "Symbol                    object\n",
       "Open                     float64\n",
       "High                     float64\n",
       "Low                      float64\n",
       "Close                    float64\n",
       "Volume                   float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a5381742",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2020-04-16 00:00:00'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[0, 'Date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0e04fd06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Thursday'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[0, 'Date'].day_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2d9bc4c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Date'] = pd.to_datetime(df['Date'], format = '%Y-%m-%d %I-%p')\n",
    "\n",
    "#Datetime Formatting Codes - http://bit.ly/python-dt-fmt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8bc37d2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       2020-04-16 00:00:00\n",
       "1       2020-04-15 23:00:00\n",
       "2       2020-04-15 22:00:00\n",
       "3       2020-04-15 21:00:00\n",
       "4       2020-04-15 20:00:00\n",
       "                ...        \n",
       "34492   2016-05-09 17:00:00\n",
       "34493   2016-05-09 16:00:00\n",
       "34494   2016-05-09 15:00:00\n",
       "34495   2016-05-09 14:00:00\n",
       "34496   2016-05-09 13:00:00\n",
       "Name: Date, Length: 34497, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Date']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "2b3d5755",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Thursday'"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[0, 'Date'].day_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "f65e8173",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         Thursday\n",
       "1        Wednesday\n",
       "2        Wednesday\n",
       "3        Wednesday\n",
       "4        Wednesday\n",
       "           ...    \n",
       "34492       Monday\n",
       "34493       Monday\n",
       "34494       Monday\n",
       "34495       Monday\n",
       "34496       Monday\n",
       "Name: Date, Length: 34497, dtype: object"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Date'].dt.day_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "2acec267",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Dayofweek'] = df['Date'].dt.day_name()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "5991cc6c",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unix Timestamp</th>\n",
       "      <th>Date</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Dayofweek</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1586995200000</td>\n",
       "      <td>2020-04-16 00:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>152.94</td>\n",
       "      <td>152.94</td>\n",
       "      <td>150.39</td>\n",
       "      <td>150.39</td>\n",
       "      <td>650.188125</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1586991600000</td>\n",
       "      <td>2020-04-15 23:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>155.81</td>\n",
       "      <td>155.81</td>\n",
       "      <td>151.39</td>\n",
       "      <td>152.94</td>\n",
       "      <td>4277.567299</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1586988000000</td>\n",
       "      <td>2020-04-15 22:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.18</td>\n",
       "      <td>157.30</td>\n",
       "      <td>155.32</td>\n",
       "      <td>155.81</td>\n",
       "      <td>106.337279</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1586984400000</td>\n",
       "      <td>2020-04-15 21:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>158.04</td>\n",
       "      <td>158.31</td>\n",
       "      <td>157.16</td>\n",
       "      <td>157.18</td>\n",
       "      <td>55.244131</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1586980800000</td>\n",
       "      <td>2020-04-15 20:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.10</td>\n",
       "      <td>158.10</td>\n",
       "      <td>156.87</td>\n",
       "      <td>158.04</td>\n",
       "      <td>144.262622</td>\n",
       "      <td>Wednesday</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34492</th>\n",
       "      <td>1462813200</td>\n",
       "      <td>2016-05-09 17:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>9.83</td>\n",
       "      <td>9.83</td>\n",
       "      <td>9.48</td>\n",
       "      <td>9.49</td>\n",
       "      <td>329.553213</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34493</th>\n",
       "      <td>1462809600</td>\n",
       "      <td>2016-05-09 16:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>9.99</td>\n",
       "      <td>9.99</td>\n",
       "      <td>9.79</td>\n",
       "      <td>9.83</td>\n",
       "      <td>62.379450</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34494</th>\n",
       "      <td>1462806000</td>\n",
       "      <td>2016-05-09 15:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>10.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.99</td>\n",
       "      <td>9.99</td>\n",
       "      <td>10.973567</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34495</th>\n",
       "      <td>1462802400</td>\n",
       "      <td>2016-05-09 14:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>9.55</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.55</td>\n",
       "      <td>10.00</td>\n",
       "      <td>235.774075</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34496</th>\n",
       "      <td>1462798800</td>\n",
       "      <td>2016-05-09 13:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9.55</td>\n",
       "      <td>432.562115</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>34497 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unix Timestamp                Date  Symbol    Open    High     Low  \\\n",
       "0       1586995200000 2020-04-16 00:00:00  ETHUSD  152.94  152.94  150.39   \n",
       "1       1586991600000 2020-04-15 23:00:00  ETHUSD  155.81  155.81  151.39   \n",
       "2       1586988000000 2020-04-15 22:00:00  ETHUSD  157.18  157.30  155.32   \n",
       "3       1586984400000 2020-04-15 21:00:00  ETHUSD  158.04  158.31  157.16   \n",
       "4       1586980800000 2020-04-15 20:00:00  ETHUSD  157.10  158.10  156.87   \n",
       "...               ...                 ...     ...     ...     ...     ...   \n",
       "34492      1462813200 2016-05-09 17:00:00  ETHUSD    9.83    9.83    9.48   \n",
       "34493      1462809600 2016-05-09 16:00:00  ETHUSD    9.99    9.99    9.79   \n",
       "34494      1462806000 2016-05-09 15:00:00  ETHUSD   10.00   10.00    9.99   \n",
       "34495      1462802400 2016-05-09 14:00:00  ETHUSD    9.55   10.00    9.55   \n",
       "34496      1462798800 2016-05-09 13:00:00  ETHUSD    0.00   12.00    0.00   \n",
       "\n",
       "        Close       Volume  Dayofweek  \n",
       "0      150.39   650.188125   Thursday  \n",
       "1      152.94  4277.567299  Wednesday  \n",
       "2      155.81   106.337279  Wednesday  \n",
       "3      157.18    55.244131  Wednesday  \n",
       "4      158.04   144.262622  Wednesday  \n",
       "...       ...          ...        ...  \n",
       "34492    9.49   329.553213     Monday  \n",
       "34493    9.83    62.379450     Monday  \n",
       "34494    9.99    10.973567     Monday  \n",
       "34495   10.00   235.774075     Monday  \n",
       "34496    9.55   432.562115     Monday  \n",
       "\n",
       "[34497 rows x 9 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a4614ed2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2016-05-09 13:00:00')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Date'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c558f563",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2020-04-16 00:00:00')"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Date'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "2866038e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('1437 days 11:00:00')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Date'].max()-df['Date'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "7272c810",
   "metadata": {},
   "outputs": [],
   "source": [
    "filter1 = (df['Date']>= '2019')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "22194cbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unix Timestamp</th>\n",
       "      <th>Date</th>\n",
       "      <th>Symbol</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1586995200000</td>\n",
       "      <td>2020-04-16 00:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>152.94</td>\n",
       "      <td>152.94</td>\n",
       "      <td>150.39</td>\n",
       "      <td>150.39</td>\n",
       "      <td>650.188125</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1586991600000</td>\n",
       "      <td>2020-04-15 23:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>155.81</td>\n",
       "      <td>155.81</td>\n",
       "      <td>151.39</td>\n",
       "      <td>152.94</td>\n",
       "      <td>4277.567299</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1586988000000</td>\n",
       "      <td>2020-04-15 22:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.18</td>\n",
       "      <td>157.30</td>\n",
       "      <td>155.32</td>\n",
       "      <td>155.81</td>\n",
       "      <td>106.337279</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1586984400000</td>\n",
       "      <td>2020-04-15 21:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>158.04</td>\n",
       "      <td>158.31</td>\n",
       "      <td>157.16</td>\n",
       "      <td>157.18</td>\n",
       "      <td>55.244131</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1586980800000</td>\n",
       "      <td>2020-04-15 20:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.10</td>\n",
       "      <td>158.10</td>\n",
       "      <td>156.87</td>\n",
       "      <td>158.04</td>\n",
       "      <td>144.262622</td>\n",
       "      <td>Wednesday</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",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11297</th>\n",
       "      <td>1546315200000</td>\n",
       "      <td>2019-01-01 04:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.83</td>\n",
       "      <td>133.75</td>\n",
       "      <td>130.83</td>\n",
       "      <td>132.09</td>\n",
       "      <td>1035.840465</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11298</th>\n",
       "      <td>1546311600000</td>\n",
       "      <td>2019-01-01 03:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>129.79</td>\n",
       "      <td>131.00</td>\n",
       "      <td>129.79</td>\n",
       "      <td>130.83</td>\n",
       "      <td>1307.299291</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11299</th>\n",
       "      <td>1546308000000</td>\n",
       "      <td>2019-01-01 02:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.98</td>\n",
       "      <td>130.98</td>\n",
       "      <td>129.25</td>\n",
       "      <td>129.79</td>\n",
       "      <td>837.808380</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11300</th>\n",
       "      <td>1546304400000</td>\n",
       "      <td>2019-01-01 01:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>131.10</td>\n",
       "      <td>131.10</td>\n",
       "      <td>128.72</td>\n",
       "      <td>130.98</td>\n",
       "      <td>965.092541</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11301</th>\n",
       "      <td>1546300800000</td>\n",
       "      <td>2019-01-01 00:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.80</td>\n",
       "      <td>131.70</td>\n",
       "      <td>130.00</td>\n",
       "      <td>131.10</td>\n",
       "      <td>1288.434493</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11302 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unix Timestamp                Date  Symbol    Open    High     Low  \\\n",
       "0       1586995200000 2020-04-16 00:00:00  ETHUSD  152.94  152.94  150.39   \n",
       "1       1586991600000 2020-04-15 23:00:00  ETHUSD  155.81  155.81  151.39   \n",
       "2       1586988000000 2020-04-15 22:00:00  ETHUSD  157.18  157.30  155.32   \n",
       "3       1586984400000 2020-04-15 21:00:00  ETHUSD  158.04  158.31  157.16   \n",
       "4       1586980800000 2020-04-15 20:00:00  ETHUSD  157.10  158.10  156.87   \n",
       "...               ...                 ...     ...     ...     ...     ...   \n",
       "11297   1546315200000 2019-01-01 04:00:00  ETHUSD  130.83  133.75  130.83   \n",
       "11298   1546311600000 2019-01-01 03:00:00  ETHUSD  129.79  131.00  129.79   \n",
       "11299   1546308000000 2019-01-01 02:00:00  ETHUSD  130.98  130.98  129.25   \n",
       "11300   1546304400000 2019-01-01 01:00:00  ETHUSD  131.10  131.10  128.72   \n",
       "11301   1546300800000 2019-01-01 00:00:00  ETHUSD  130.80  131.70  130.00   \n",
       "\n",
       "        Close       Volume  Dayofweek  \n",
       "0      150.39   650.188125   Thursday  \n",
       "1      152.94  4277.567299  Wednesday  \n",
       "2      155.81   106.337279  Wednesday  \n",
       "3      157.18    55.244131  Wednesday  \n",
       "4      158.04   144.262622  Wednesday  \n",
       "...       ...          ...        ...  \n",
       "11297  132.09  1035.840465    Tuesday  \n",
       "11298  130.83  1307.299291    Tuesday  \n",
       "11299  129.79   837.808380    Tuesday  \n",
       "11300  130.98   965.092541    Tuesday  \n",
       "11301  131.10  1288.434493    Tuesday  \n",
       "\n",
       "[11302 rows x 9 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[filter1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "31d4cf1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unix Timestamp</th>\n",
       "      <th>Date</th>\n",
       "      <th>Symbol</th>\n",
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       "  <tbody>\n",
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       "      <th>2545</th>\n",
       "      <td>1577833200000</td>\n",
       "      <td>2019-12-31 23:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>128.68</td>\n",
       "      <td>128.85</td>\n",
       "      <td>127.82</td>\n",
       "      <td>128.84</td>\n",
       "      <td>857.650259</td>\n",
       "      <td>Tuesday</td>\n",
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       "      <th>2546</th>\n",
       "      <td>1577829600000</td>\n",
       "      <td>2019-12-31 22:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>128.40</td>\n",
       "      <td>128.93</td>\n",
       "      <td>127.77</td>\n",
       "      <td>128.68</td>\n",
       "      <td>3050.507350</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2547</th>\n",
       "      <td>1577826000000</td>\n",
       "      <td>2019-12-31 21:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>127.87</td>\n",
       "      <td>128.41</td>\n",
       "      <td>127.81</td>\n",
       "      <td>128.40</td>\n",
       "      <td>447.680372</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2548</th>\n",
       "      <td>1577822400000</td>\n",
       "      <td>2019-12-31 20:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>127.86</td>\n",
       "      <td>128.30</td>\n",
       "      <td>127.86</td>\n",
       "      <td>127.87</td>\n",
       "      <td>151.711128</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2549</th>\n",
       "      <td>1577818800000</td>\n",
       "      <td>2019-12-31 19:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>128.78</td>\n",
       "      <td>128.78</td>\n",
       "      <td>127.86</td>\n",
       "      <td>127.86</td>\n",
       "      <td>2450.933248</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>11297</th>\n",
       "      <td>1546315200000</td>\n",
       "      <td>2019-01-01 04:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.83</td>\n",
       "      <td>133.75</td>\n",
       "      <td>130.83</td>\n",
       "      <td>132.09</td>\n",
       "      <td>1035.840465</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11298</th>\n",
       "      <td>1546311600000</td>\n",
       "      <td>2019-01-01 03:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>129.79</td>\n",
       "      <td>131.00</td>\n",
       "      <td>129.79</td>\n",
       "      <td>130.83</td>\n",
       "      <td>1307.299291</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11299</th>\n",
       "      <td>1546308000000</td>\n",
       "      <td>2019-01-01 02:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.98</td>\n",
       "      <td>130.98</td>\n",
       "      <td>129.25</td>\n",
       "      <td>129.79</td>\n",
       "      <td>837.808380</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11300</th>\n",
       "      <td>1546304400000</td>\n",
       "      <td>2019-01-01 01:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>131.10</td>\n",
       "      <td>131.10</td>\n",
       "      <td>128.72</td>\n",
       "      <td>130.98</td>\n",
       "      <td>965.092541</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11301</th>\n",
       "      <td>1546300800000</td>\n",
       "      <td>2019-01-01 00:00:00</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.80</td>\n",
       "      <td>131.70</td>\n",
       "      <td>130.00</td>\n",
       "      <td>131.10</td>\n",
       "      <td>1288.434493</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8757 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unix Timestamp                Date  Symbol    Open    High     Low  \\\n",
       "2545    1577833200000 2019-12-31 23:00:00  ETHUSD  128.68  128.85  127.82   \n",
       "2546    1577829600000 2019-12-31 22:00:00  ETHUSD  128.40  128.93  127.77   \n",
       "2547    1577826000000 2019-12-31 21:00:00  ETHUSD  127.87  128.41  127.81   \n",
       "2548    1577822400000 2019-12-31 20:00:00  ETHUSD  127.86  128.30  127.86   \n",
       "2549    1577818800000 2019-12-31 19:00:00  ETHUSD  128.78  128.78  127.86   \n",
       "...               ...                 ...     ...     ...     ...     ...   \n",
       "11297   1546315200000 2019-01-01 04:00:00  ETHUSD  130.83  133.75  130.83   \n",
       "11298   1546311600000 2019-01-01 03:00:00  ETHUSD  129.79  131.00  129.79   \n",
       "11299   1546308000000 2019-01-01 02:00:00  ETHUSD  130.98  130.98  129.25   \n",
       "11300   1546304400000 2019-01-01 01:00:00  ETHUSD  131.10  131.10  128.72   \n",
       "11301   1546300800000 2019-01-01 00:00:00  ETHUSD  130.80  131.70  130.00   \n",
       "\n",
       "        Close       Volume Dayofweek  \n",
       "2545   128.84   857.650259   Tuesday  \n",
       "2546   128.68  3050.507350   Tuesday  \n",
       "2547   128.40   447.680372   Tuesday  \n",
       "2548   127.87   151.711128   Tuesday  \n",
       "2549   127.86  2450.933248   Tuesday  \n",
       "...       ...          ...       ...  \n",
       "11297  132.09  1035.840465   Tuesday  \n",
       "11298  130.83  1307.299291   Tuesday  \n",
       "11299  129.79   837.808380   Tuesday  \n",
       "11300  130.98   965.092541   Tuesday  \n",
       "11301  131.10  1288.434493   Tuesday  \n",
       "\n",
       "[8757 rows x 9 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filter2 = (df['Date'] >= pd.to_datetime('2019-01-01')) & (df['Date'] < pd.to_datetime('2020-01-01'))\n",
    "df.loc[filter2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b9e6d3a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('Date', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "bd5657f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2020-04-16 00:00:00</th>\n",
       "      <td>1586995200000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>152.94</td>\n",
       "      <td>152.94</td>\n",
       "      <td>150.39</td>\n",
       "      <td>150.39</td>\n",
       "      <td>650.188125</td>\n",
       "      <td>Thursday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-15 23:00:00</th>\n",
       "      <td>1586991600000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>155.81</td>\n",
       "      <td>155.81</td>\n",
       "      <td>151.39</td>\n",
       "      <td>152.94</td>\n",
       "      <td>4277.567299</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-15 22:00:00</th>\n",
       "      <td>1586988000000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.18</td>\n",
       "      <td>157.30</td>\n",
       "      <td>155.32</td>\n",
       "      <td>155.81</td>\n",
       "      <td>106.337279</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-15 21:00:00</th>\n",
       "      <td>1586984400000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>158.04</td>\n",
       "      <td>158.31</td>\n",
       "      <td>157.16</td>\n",
       "      <td>157.18</td>\n",
       "      <td>55.244131</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-15 20:00:00</th>\n",
       "      <td>1586980800000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>157.10</td>\n",
       "      <td>158.10</td>\n",
       "      <td>156.87</td>\n",
       "      <td>158.04</td>\n",
       "      <td>144.262622</td>\n",
       "      <td>Wednesday</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>2016-05-09 17:00:00</th>\n",
       "      <td>1462813200</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>9.83</td>\n",
       "      <td>9.83</td>\n",
       "      <td>9.48</td>\n",
       "      <td>9.49</td>\n",
       "      <td>329.553213</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-09 16:00:00</th>\n",
       "      <td>1462809600</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>9.99</td>\n",
       "      <td>9.99</td>\n",
       "      <td>9.79</td>\n",
       "      <td>9.83</td>\n",
       "      <td>62.379450</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-09 15:00:00</th>\n",
       "      <td>1462806000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>10.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.99</td>\n",
       "      <td>9.99</td>\n",
       "      <td>10.973567</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-09 14:00:00</th>\n",
       "      <td>1462802400</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>9.55</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.55</td>\n",
       "      <td>10.00</td>\n",
       "      <td>235.774075</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-09 13:00:00</th>\n",
       "      <td>1462798800</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>9.55</td>\n",
       "      <td>432.562115</td>\n",
       "      <td>Monday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>34497 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Unix Timestamp  Symbol    Open    High     Low   Close  \\\n",
       "Date                                                                          \n",
       "2020-04-16 00:00:00   1586995200000  ETHUSD  152.94  152.94  150.39  150.39   \n",
       "2020-04-15 23:00:00   1586991600000  ETHUSD  155.81  155.81  151.39  152.94   \n",
       "2020-04-15 22:00:00   1586988000000  ETHUSD  157.18  157.30  155.32  155.81   \n",
       "2020-04-15 21:00:00   1586984400000  ETHUSD  158.04  158.31  157.16  157.18   \n",
       "2020-04-15 20:00:00   1586980800000  ETHUSD  157.10  158.10  156.87  158.04   \n",
       "...                             ...     ...     ...     ...     ...     ...   \n",
       "2016-05-09 17:00:00      1462813200  ETHUSD    9.83    9.83    9.48    9.49   \n",
       "2016-05-09 16:00:00      1462809600  ETHUSD    9.99    9.99    9.79    9.83   \n",
       "2016-05-09 15:00:00      1462806000  ETHUSD   10.00   10.00    9.99    9.99   \n",
       "2016-05-09 14:00:00      1462802400  ETHUSD    9.55   10.00    9.55   10.00   \n",
       "2016-05-09 13:00:00      1462798800  ETHUSD    0.00   12.00    0.00    9.55   \n",
       "\n",
       "                          Volume  Dayofweek  \n",
       "Date                                         \n",
       "2020-04-16 00:00:00   650.188125   Thursday  \n",
       "2020-04-15 23:00:00  4277.567299  Wednesday  \n",
       "2020-04-15 22:00:00   106.337279  Wednesday  \n",
       "2020-04-15 21:00:00    55.244131  Wednesday  \n",
       "2020-04-15 20:00:00   144.262622  Wednesday  \n",
       "...                          ...        ...  \n",
       "2016-05-09 17:00:00   329.553213     Monday  \n",
       "2016-05-09 16:00:00    62.379450     Monday  \n",
       "2016-05-09 15:00:00    10.973567     Monday  \n",
       "2016-05-09 14:00:00   235.774075     Monday  \n",
       "2016-05-09 13:00:00   432.562115     Monday  \n",
       "\n",
       "[34497 rows x 8 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "5c060d27",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2019-12-31 23:00:00</th>\n",
       "      <td>1577833200000</td>\n",
       "      <td>ETHUSD</td>\n",
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       "      <td>128.85</td>\n",
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       "    <tr>\n",
       "      <th>2019-12-31 22:00:00</th>\n",
       "      <td>1577829600000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>128.40</td>\n",
       "      <td>128.93</td>\n",
       "      <td>127.77</td>\n",
       "      <td>128.68</td>\n",
       "      <td>3050.507350</td>\n",
       "      <td>Tuesday</td>\n",
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       "    <tr>\n",
       "      <th>2019-12-31 21:00:00</th>\n",
       "      <td>1577826000000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>127.87</td>\n",
       "      <td>128.41</td>\n",
       "      <td>127.81</td>\n",
       "      <td>128.40</td>\n",
       "      <td>447.680372</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31 20:00:00</th>\n",
       "      <td>1577822400000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>127.86</td>\n",
       "      <td>128.30</td>\n",
       "      <td>127.86</td>\n",
       "      <td>127.87</td>\n",
       "      <td>151.711128</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31 19:00:00</th>\n",
       "      <td>1577818800000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>128.78</td>\n",
       "      <td>128.78</td>\n",
       "      <td>127.86</td>\n",
       "      <td>127.86</td>\n",
       "      <td>2450.933248</td>\n",
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       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>2019-01-01 04:00:00</th>\n",
       "      <td>1546315200000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.83</td>\n",
       "      <td>133.75</td>\n",
       "      <td>130.83</td>\n",
       "      <td>132.09</td>\n",
       "      <td>1035.840465</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 03:00:00</th>\n",
       "      <td>1546311600000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>129.79</td>\n",
       "      <td>131.00</td>\n",
       "      <td>129.79</td>\n",
       "      <td>130.83</td>\n",
       "      <td>1307.299291</td>\n",
       "      <td>Tuesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-01 02:00:00</th>\n",
       "      <td>1546308000000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.98</td>\n",
       "      <td>130.98</td>\n",
       "      <td>129.25</td>\n",
       "      <td>129.79</td>\n",
       "      <td>837.808380</td>\n",
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       "    <tr>\n",
       "      <th>2019-01-01 01:00:00</th>\n",
       "      <td>1546304400000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>131.10</td>\n",
       "      <td>131.10</td>\n",
       "      <td>128.72</td>\n",
       "      <td>130.98</td>\n",
       "      <td>965.092541</td>\n",
       "      <td>Tuesday</td>\n",
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       "    <tr>\n",
       "      <th>2019-01-01 00:00:00</th>\n",
       "      <td>1546300800000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.80</td>\n",
       "      <td>131.70</td>\n",
       "      <td>130.00</td>\n",
       "      <td>131.10</td>\n",
       "      <td>1288.434493</td>\n",
       "      <td>Tuesday</td>\n",
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       "  </tbody>\n",
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       "<p>8757 rows × 8 columns</p>\n",
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       "                     Unix Timestamp  Symbol    Open    High     Low   Close  \\\n",
       "Date                                                                          \n",
       "2019-12-31 23:00:00   1577833200000  ETHUSD  128.68  128.85  127.82  128.84   \n",
       "2019-12-31 22:00:00   1577829600000  ETHUSD  128.40  128.93  127.77  128.68   \n",
       "2019-12-31 21:00:00   1577826000000  ETHUSD  127.87  128.41  127.81  128.40   \n",
       "2019-12-31 20:00:00   1577822400000  ETHUSD  127.86  128.30  127.86  127.87   \n",
       "2019-12-31 19:00:00   1577818800000  ETHUSD  128.78  128.78  127.86  127.86   \n",
       "...                             ...     ...     ...     ...     ...     ...   \n",
       "2019-01-01 04:00:00   1546315200000  ETHUSD  130.83  133.75  130.83  132.09   \n",
       "2019-01-01 03:00:00   1546311600000  ETHUSD  129.79  131.00  129.79  130.83   \n",
       "2019-01-01 02:00:00   1546308000000  ETHUSD  130.98  130.98  129.25  129.79   \n",
       "2019-01-01 01:00:00   1546304400000  ETHUSD  131.10  131.10  128.72  130.98   \n",
       "2019-01-01 00:00:00   1546300800000  ETHUSD  130.80  131.70  130.00  131.10   \n",
       "\n",
       "                          Volume Dayofweek  \n",
       "Date                                        \n",
       "2019-12-31 23:00:00   857.650259   Tuesday  \n",
       "2019-12-31 22:00:00  3050.507350   Tuesday  \n",
       "2019-12-31 21:00:00   447.680372   Tuesday  \n",
       "2019-12-31 20:00:00   151.711128   Tuesday  \n",
       "2019-12-31 19:00:00  2450.933248   Tuesday  \n",
       "...                          ...       ...  \n",
       "2019-01-01 04:00:00  1035.840465   Tuesday  \n",
       "2019-01-01 03:00:00  1307.299291   Tuesday  \n",
       "2019-01-01 02:00:00   837.808380   Tuesday  \n",
       "2019-01-01 01:00:00   965.092541   Tuesday  \n",
       "2019-01-01 00:00:00  1288.434493   Tuesday  \n",
       "\n",
       "[8757 rows x 8 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['2019']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6f832c65",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2020-02-29 23:00:00</th>\n",
       "      <td>1583017200000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>222.93</td>\n",
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       "      <th>2020-02-29 22:00:00</th>\n",
       "      <td>1583013600000</td>\n",
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       "      <td>223.76</td>\n",
       "      <td>222.32</td>\n",
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       "    <tr>\n",
       "      <th>2020-02-29 21:00:00</th>\n",
       "      <td>1583010000000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>224.81</td>\n",
       "      <td>225.08</td>\n",
       "      <td>223.05</td>\n",
       "      <td>223.59</td>\n",
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       "      <td>Saturday</td>\n",
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       "    <tr>\n",
       "      <th>2020-02-29 20:00:00</th>\n",
       "      <td>1583006400000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>225.56</td>\n",
       "      <td>225.56</td>\n",
       "      <td>223.55</td>\n",
       "      <td>224.81</td>\n",
       "      <td>158.232905</td>\n",
       "      <td>Saturday</td>\n",
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       "    <tr>\n",
       "      <th>2020-02-29 19:00:00</th>\n",
       "      <td>1583002800000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>225.05</td>\n",
       "      <td>225.92</td>\n",
       "      <td>224.06</td>\n",
       "      <td>225.56</td>\n",
       "      <td>174.783652</td>\n",
       "      <td>Saturday</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
       "      <th>2020-01-01 04:00:00</th>\n",
       "      <td>1577851200000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>129.83</td>\n",
       "      <td>129.96</td>\n",
       "      <td>129.13</td>\n",
       "      <td>129.54</td>\n",
       "      <td>2807.129465</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01 03:00:00</th>\n",
       "      <td>1577847600000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>130.25</td>\n",
       "      <td>130.30</td>\n",
       "      <td>129.42</td>\n",
       "      <td>129.83</td>\n",
       "      <td>883.017780</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01 02:00:00</th>\n",
       "      <td>1577844000000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>129.95</td>\n",
       "      <td>130.58</td>\n",
       "      <td>129.95</td>\n",
       "      <td>130.25</td>\n",
       "      <td>527.921168</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01 01:00:00</th>\n",
       "      <td>1577840400000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>128.11</td>\n",
       "      <td>130.01</td>\n",
       "      <td>128.11</td>\n",
       "      <td>129.95</td>\n",
       "      <td>220.239530</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-01 00:00:00</th>\n",
       "      <td>1577836800000</td>\n",
       "      <td>ETHUSD</td>\n",
       "      <td>128.84</td>\n",
       "      <td>128.84</td>\n",
       "      <td>128.07</td>\n",
       "      <td>128.11</td>\n",
       "      <td>526.980282</td>\n",
       "      <td>Wednesday</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1440 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Unix Timestamp  Symbol    Open    High     Low   Close  \\\n",
       "Date                                                                          \n",
       "2020-02-29 23:00:00   1583017200000  ETHUSD  222.93  223.96  217.26  217.35   \n",
       "2020-02-29 22:00:00   1583013600000  ETHUSD  223.59  223.76  222.32  222.93   \n",
       "2020-02-29 21:00:00   1583010000000  ETHUSD  224.81  225.08  223.05  223.59   \n",
       "2020-02-29 20:00:00   1583006400000  ETHUSD  225.56  225.56  223.55  224.81   \n",
       "2020-02-29 19:00:00   1583002800000  ETHUSD  225.05  225.92  224.06  225.56   \n",
       "...                             ...     ...     ...     ...     ...     ...   \n",
       "2020-01-01 04:00:00   1577851200000  ETHUSD  129.83  129.96  129.13  129.54   \n",
       "2020-01-01 03:00:00   1577847600000  ETHUSD  130.25  130.30  129.42  129.83   \n",
       "2020-01-01 02:00:00   1577844000000  ETHUSD  129.95  130.58  129.95  130.25   \n",
       "2020-01-01 01:00:00   1577840400000  ETHUSD  128.11  130.01  128.11  129.95   \n",
       "2020-01-01 00:00:00   1577836800000  ETHUSD  128.84  128.84  128.07  128.11   \n",
       "\n",
       "                          Volume  Dayofweek  \n",
       "Date                                         \n",
       "2020-02-29 23:00:00  1247.560462   Saturday  \n",
       "2020-02-29 22:00:00   118.446008   Saturday  \n",
       "2020-02-29 21:00:00   191.602533   Saturday  \n",
       "2020-02-29 20:00:00   158.232905   Saturday  \n",
       "2020-02-29 19:00:00   174.783652   Saturday  \n",
       "...                          ...        ...  \n",
       "2020-01-01 04:00:00  2807.129465  Wednesday  \n",
       "2020-01-01 03:00:00   883.017780  Wednesday  \n",
       "2020-01-01 02:00:00   527.921168  Wednesday  \n",
       "2020-01-01 01:00:00   220.239530  Wednesday  \n",
       "2020-01-01 00:00:00   526.980282  Wednesday  \n",
       "\n",
       "[1440 rows x 8 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['2020-01':'2020-02']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "ac1154f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date\n",
       "2020-02-29 23:00:00    217.35\n",
       "2020-02-29 22:00:00    222.93\n",
       "2020-02-29 21:00:00    223.59\n",
       "2020-02-29 20:00:00    224.81\n",
       "2020-02-29 19:00:00    225.56\n",
       "                        ...  \n",
       "2020-01-01 04:00:00    129.54\n",
       "2020-01-01 03:00:00    129.83\n",
       "2020-01-01 02:00:00    130.25\n",
       "2020-01-01 01:00:00    129.95\n",
       "2020-01-01 00:00:00    128.11\n",
       "Name: Close, Length: 1440, dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['2020-01':'2020-02']['Close']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "4f96a2af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "195.22266666666675"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['2020-01':'2020-02']['Close'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "becc7075",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ASUS\\AppData\\Local\\Temp\\ipykernel_3420\\3485283041.py:1: FutureWarning: Indexing a DataFrame with a datetimelike index using a single string to slice the rows, like `frame[string]`, is deprecated and will be removed in a future version. Use `frame.loc[string]` instead.\n",
      "  df['2020-01-01']['High'].max()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "132.57"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['2020-01-01']['High'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "1e4a06eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "132.57"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "highs = df['High'].resample('D').max()\n",
    "highs['2020-01-01']\n",
    "\n",
    "#https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#dateoffset-objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "9a4dc05e",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "88782d35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "highs.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "4f2f50e3",
   "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>Unix 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",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-05-15</th>\n",
       "      <td>1.463076e+09</td>\n",
       "      <td>10.140387</td>\n",
       "      <td>10.310516</td>\n",
       "      <td>10.052387</td>\n",
       "      <td>10.205290</td>\n",
       "      <td>70.896402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-22</th>\n",
       "      <td>1.463657e+09</td>\n",
       "      <td>13.042262</td>\n",
       "      <td>13.144048</td>\n",
       "      <td>12.965179</td>\n",
       "      <td>13.066964</td>\n",
       "      <td>242.104139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-29</th>\n",
       "      <td>1.464262e+09</td>\n",
       "      <td>12.481012</td>\n",
       "      <td>12.555536</td>\n",
       "      <td>12.385357</td>\n",
       "      <td>12.471012</td>\n",
       "      <td>345.546483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-05</th>\n",
       "      <td>1.464867e+09</td>\n",
       "      <td>13.586369</td>\n",
       "      <td>13.651667</td>\n",
       "      <td>13.542202</td>\n",
       "      <td>13.594583</td>\n",
       "      <td>281.854432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-12</th>\n",
       "      <td>1.465472e+09</td>\n",
       "      <td>14.287500</td>\n",
       "      <td>14.326190</td>\n",
       "      <td>14.260179</td>\n",
       "      <td>14.297798</td>\n",
       "      <td>309.536737</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-22</th>\n",
       "      <td>1.584617e+12</td>\n",
       "      <td>124.640952</td>\n",
       "      <td>126.387917</td>\n",
       "      <td>122.802262</td>\n",
       "      <td>124.636012</td>\n",
       "      <td>2618.930260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-29</th>\n",
       "      <td>1.585222e+12</td>\n",
       "      <td>133.274762</td>\n",
       "      <td>134.287857</td>\n",
       "      <td>132.255714</td>\n",
       "      <td>133.285893</td>\n",
       "      <td>1374.652289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-05</th>\n",
       "      <td>1.585827e+12</td>\n",
       "      <td>137.517083</td>\n",
       "      <td>138.314583</td>\n",
       "      <td>136.791310</td>\n",
       "      <td>137.627440</td>\n",
       "      <td>898.945625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-12</th>\n",
       "      <td>1.586432e+12</td>\n",
       "      <td>163.601548</td>\n",
       "      <td>164.731071</td>\n",
       "      <td>162.422560</td>\n",
       "      <td>163.693929</td>\n",
       "      <td>1218.547250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-19</th>\n",
       "      <td>1.586866e+12</td>\n",
       "      <td>156.890137</td>\n",
       "      <td>157.744384</td>\n",
       "      <td>155.952055</td>\n",
       "      <td>156.778219</td>\n",
       "      <td>695.573831</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>206 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Unix Timestamp        Open        High         Low       Close  \\\n",
       "Date                                                                         \n",
       "2016-05-15    1.463076e+09   10.140387   10.310516   10.052387   10.205290   \n",
       "2016-05-22    1.463657e+09   13.042262   13.144048   12.965179   13.066964   \n",
       "2016-05-29    1.464262e+09   12.481012   12.555536   12.385357   12.471012   \n",
       "2016-06-05    1.464867e+09   13.586369   13.651667   13.542202   13.594583   \n",
       "2016-06-12    1.465472e+09   14.287500   14.326190   14.260179   14.297798   \n",
       "...                    ...         ...         ...         ...         ...   \n",
       "2020-03-22    1.584617e+12  124.640952  126.387917  122.802262  124.636012   \n",
       "2020-03-29    1.585222e+12  133.274762  134.287857  132.255714  133.285893   \n",
       "2020-04-05    1.585827e+12  137.517083  138.314583  136.791310  137.627440   \n",
       "2020-04-12    1.586432e+12  163.601548  164.731071  162.422560  163.693929   \n",
       "2020-04-19    1.586866e+12  156.890137  157.744384  155.952055  156.778219   \n",
       "\n",
       "                 Volume  \n",
       "Date                     \n",
       "2016-05-15    70.896402  \n",
       "2016-05-22   242.104139  \n",
       "2016-05-29   345.546483  \n",
       "2016-06-05   281.854432  \n",
       "2016-06-12   309.536737  \n",
       "...                 ...  \n",
       "2020-03-22  2618.930260  \n",
       "2020-03-29  1374.652289  \n",
       "2020-04-05   898.945625  \n",
       "2020-04-12  1218.547250  \n",
       "2020-04-19   695.573831  \n",
       "\n",
       "[206 rows x 6 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('W').mean() #Resemable based on week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "ef097177",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-05-15</th>\n",
       "      <td>10.205290</td>\n",
       "      <td>12.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10988.942273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-22</th>\n",
       "      <td>13.066964</td>\n",
       "      <td>14.77</td>\n",
       "      <td>10.06</td>\n",
       "      <td>40673.495362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-29</th>\n",
       "      <td>12.471012</td>\n",
       "      <td>14.43</td>\n",
       "      <td>10.41</td>\n",
       "      <td>58051.809091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-05</th>\n",
       "      <td>13.594583</td>\n",
       "      <td>16.05</td>\n",
       "      <td>12.41</td>\n",
       "      <td>47351.544496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-12</th>\n",
       "      <td>14.297798</td>\n",
       "      <td>15.75</td>\n",
       "      <td>13.83</td>\n",
       "      <td>52002.171838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-22</th>\n",
       "      <td>124.636012</td>\n",
       "      <td>153.17</td>\n",
       "      <td>100.70</td>\n",
       "      <td>439980.283707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-29</th>\n",
       "      <td>133.285893</td>\n",
       "      <td>144.14</td>\n",
       "      <td>119.17</td>\n",
       "      <td>230941.584515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-05</th>\n",
       "      <td>137.627440</td>\n",
       "      <td>150.32</td>\n",
       "      <td>124.09</td>\n",
       "      <td>151022.864981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-12</th>\n",
       "      <td>163.693929</td>\n",
       "      <td>176.74</td>\n",
       "      <td>142.87</td>\n",
       "      <td>204715.937994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-19</th>\n",
       "      <td>156.778219</td>\n",
       "      <td>162.15</td>\n",
       "      <td>150.12</td>\n",
       "      <td>50776.889638</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>206 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Close    High     Low         Volume\n",
       "Date                                                 \n",
       "2016-05-15   10.205290   12.00    0.00   10988.942273\n",
       "2016-05-22   13.066964   14.77   10.06   40673.495362\n",
       "2016-05-29   12.471012   14.43   10.41   58051.809091\n",
       "2016-06-05   13.594583   16.05   12.41   47351.544496\n",
       "2016-06-12   14.297798   15.75   13.83   52002.171838\n",
       "...                ...     ...     ...            ...\n",
       "2020-03-22  124.636012  153.17  100.70  439980.283707\n",
       "2020-03-29  133.285893  144.14  119.17  230941.584515\n",
       "2020-04-05  137.627440  150.32  124.09  151022.864981\n",
       "2020-04-12  163.693929  176.74  142.87  204715.937994\n",
       "2020-04-19  156.778219  162.15  150.12   50776.889638\n",
       "\n",
       "[206 rows x 4 columns]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('W').agg({'Close':'mean', 'High':'max', 'Low': 'min', 'Volume': 'sum'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "57196b77",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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