test01.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ccxt version 2.4.18\n",
      "numero mercati: 2131\n"
     ]
    }
   ],
   "source": [
    "import ccxt\n",
    "import pandas as pd\n",
    "from sklearn import preprocessing\n",
    "import pprint\n",
    "import datetime\n",
    "import plotly.graph_objects as go\n",
    "import numpy as np\n",
    "\n",
    "print('ccxt version', ccxt.__version__)\n",
    "\n",
    "\n",
    "# From timestamp to Datetime\n",
    "def convert_from_ms(value):\n",
    "    return datetime.datetime.fromtimestamp(value)\n",
    "\n",
    "\n",
    "exchange = ccxt.binance()\n",
    "markets = exchange.load_markets()\n",
    "print(f\"numero mercati: {len(markets)}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "symbol = 'BTC/EUR'\n",
    "filtered = []\n",
    "for s in exchange.symbols:\n",
    "    if s.startswith('BTC'):\n",
    "        filtered.append(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "ohlcv = exchange.fetch_ohlcv(symbol, '4h', limit=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "         timestamp      open      high       low     close      volume  \\\n0    1656820800000  18473.64  18597.98  18011.50  18377.86   330.04671   \n1    1656835200000  18377.79  18391.12  18178.44  18319.21   201.72188   \n2    1656849600000  18320.37  18354.71  18205.44  18274.99   183.48512   \n3    1656864000000  18274.43  18763.76  18243.71  18712.49   236.91553   \n4    1656878400000  18714.88  18849.00  18408.16  18510.15   247.36362   \n..             ...       ...       ...       ...       ...         ...   \n995  1671148800000  16311.80  16371.78  16299.42  16355.38   335.18676   \n996  1671163200000  16355.27  16437.38  16286.90  16433.92   379.90982   \n997  1671177600000  16434.12  16443.77  15940.00  16013.39  1122.04752   \n998  1671192000000  16013.53  16063.96  15902.50  15991.63   721.07127   \n999  1671206400000  15991.92  15997.30  15783.62  15861.68   465.31701   \n\n            date_parsed       avg         sma       stdev          bbup  \\\n0   2022-07-03 06:00:00  9592.230         NaN         NaN           NaN   \n1   2022-07-03 10:00:00  9301.900         NaN         NaN           NaN   \n2   2022-07-03 14:00:00  9251.990         NaN         NaN           NaN   \n3   2022-07-03 18:00:00  9641.905         NaN         NaN           NaN   \n4   2022-07-03 22:00:00  9644.920         NaN         NaN           NaN   \n..                  ...       ...         ...         ...           ...   \n995 2022-12-16 01:00:00  8222.070  16573.2490  198.331627  17061.741567   \n996 2022-12-16 05:00:00  8293.930  16578.6950  192.567839  17054.668596   \n997 2022-12-16 09:00:00  8473.770  16565.5945  221.087563  17131.413908   \n998 2022-12-16 13:00:00  8112.710  16551.6175  247.891830  17185.324076   \n999 2022-12-16 17:00:00  8105.490  16516.7725  291.929933  17281.442332   \n\n           bbdown   sell    buy  position_sell  position_buy stato  \n0             NaN  False  False          False         False  None  \n1             NaN  False  False          False         False  None  \n2             NaN  False  False          False         False  None  \n3             NaN  False  False          False         False  None  \n4             NaN  False  False          False         False  None  \n..            ...    ...    ...            ...           ...   ...  \n995  15970.917619  False  False          False         False  None  \n996  15995.545484  False  False          False         False  None  \n997  15915.432311  False  False          False         False  None  \n998  15821.919009  False  False          False         False  None  \n999  15675.827702  False  False          False         False  None  \n\n[1000 rows x 17 columns]",
      "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      <th>date_parsed</th>\n      <th>avg</th>\n      <th>sma</th>\n      <th>stdev</th>\n      <th>bbup</th>\n      <th>bbdown</th>\n      <th>sell</th>\n      <th>buy</th>\n      <th>position_sell</th>\n      <th>position_buy</th>\n      <th>stato</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1656820800000</td>\n      <td>18473.64</td>\n      <td>18597.98</td>\n      <td>18011.50</td>\n      <td>18377.86</td>\n      <td>330.04671</td>\n      <td>2022-07-03 06:00:00</td>\n      <td>9592.230</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1656835200000</td>\n      <td>18377.79</td>\n      <td>18391.12</td>\n      <td>18178.44</td>\n      <td>18319.21</td>\n      <td>201.72188</td>\n      <td>2022-07-03 10:00:00</td>\n      <td>9301.900</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1656849600000</td>\n      <td>18320.37</td>\n      <td>18354.71</td>\n      <td>18205.44</td>\n      <td>18274.99</td>\n      <td>183.48512</td>\n      <td>2022-07-03 14:00:00</td>\n      <td>9251.990</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1656864000000</td>\n      <td>18274.43</td>\n      <td>18763.76</td>\n      <td>18243.71</td>\n      <td>18712.49</td>\n      <td>236.91553</td>\n      <td>2022-07-03 18:00:00</td>\n      <td>9641.905</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1656878400000</td>\n      <td>18714.88</td>\n      <td>18849.00</td>\n      <td>18408.16</td>\n      <td>18510.15</td>\n      <td>247.36362</td>\n      <td>2022-07-03 22:00:00</td>\n      <td>9644.920</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</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      <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>995</th>\n      <td>1671148800000</td>\n      <td>16311.80</td>\n      <td>16371.78</td>\n      <td>16299.42</td>\n      <td>16355.38</td>\n      <td>335.18676</td>\n      <td>2022-12-16 01:00:00</td>\n      <td>8222.070</td>\n      <td>16573.2490</td>\n      <td>198.331627</td>\n      <td>17061.741567</td>\n      <td>15970.917619</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>996</th>\n      <td>1671163200000</td>\n      <td>16355.27</td>\n      <td>16437.38</td>\n      <td>16286.90</td>\n      <td>16433.92</td>\n      <td>379.90982</td>\n      <td>2022-12-16 05:00:00</td>\n      <td>8293.930</td>\n      <td>16578.6950</td>\n      <td>192.567839</td>\n      <td>17054.668596</td>\n      <td>15995.545484</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>997</th>\n      <td>1671177600000</td>\n      <td>16434.12</td>\n      <td>16443.77</td>\n      <td>15940.00</td>\n      <td>16013.39</td>\n      <td>1122.04752</td>\n      <td>2022-12-16 09:00:00</td>\n      <td>8473.770</td>\n      <td>16565.5945</td>\n      <td>221.087563</td>\n      <td>17131.413908</td>\n      <td>15915.432311</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>998</th>\n      <td>1671192000000</td>\n      <td>16013.53</td>\n      <td>16063.96</td>\n      <td>15902.50</td>\n      <td>15991.63</td>\n      <td>721.07127</td>\n      <td>2022-12-16 13:00:00</td>\n      <td>8112.710</td>\n      <td>16551.6175</td>\n      <td>247.891830</td>\n      <td>17185.324076</td>\n      <td>15821.919009</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>999</th>\n      <td>1671206400000</td>\n      <td>15991.92</td>\n      <td>15997.30</td>\n      <td>15783.62</td>\n      <td>15861.68</td>\n      <td>465.31701</td>\n      <td>2022-12-16 17:00:00</td>\n      <td>8105.490</td>\n      <td>16516.7725</td>\n      <td>291.929933</td>\n      <td>17281.442332</td>\n      <td>15675.827702</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 17 columns</p>\n</div>"
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])\n",
    "# df['datetime']=pd.to_datetime(df['timestamp'],unit='ms')\n",
    "df['date_parsed'] = (df['timestamp'] / 1000).apply(convert_from_ms)\n",
    "df['avg'] = df['high'] - df['low'] / 2\n",
    "\n",
    "#bollinger\n",
    "param_up=2.5\n",
    "param_down=3\n",
    "df['sma']=df.close.rolling(20).mean()\n",
    "df['stdev']=df.close.rolling(20).std()\n",
    "df['bbup']=df.sma.shift(1) + param_up*df.stdev\n",
    "df['bbdown']=df.sma.shift(1) - param_down*df.stdev\n",
    "\n",
    "df['avg'] = df['high'] - df['low'] / 2\n",
    "\n",
    "df['sell'] = (df.high>df.bbup)\n",
    "df['buy'] = (df.low<df.bbdown)\n",
    "df['position_sell'] = False\n",
    "df['position_buy'] = False\n",
    "df['stato']=None\n",
    "#df['position'] = np.where( (df.buy==True), 1,0)\n",
    "#df.position.fillna(method='ffill' , inplace=True)\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "        timestamp      open      high       low     close      volume  \\\n45  1657468800000  20507.36  20675.06  20275.97  20553.28   319.08563   \n46  1657483200000  20555.95  20812.17  20325.62  20514.69   232.58279   \n47  1657497600000  20520.05  20520.05  20165.07  20236.33   205.54144   \n48  1657512000000  20226.50  20291.91  20078.76  20211.54   183.83038   \n49  1657526400000  20211.42  20394.42  20185.00  20290.86   272.45973   \n50  1657540800000  20291.44  20618.18  20144.30  20261.78   423.81371   \n51  1657555200000  20263.79  20580.00  20243.99  20414.83   351.10818   \n52  1657569600000  20419.03  20466.74  19789.47  19864.33   351.96108   \n53  1657584000000  19863.77  19930.50  19698.46  19879.51   291.03943   \n54  1657598400000  19880.40  20025.48  19579.81  19700.16   371.97960   \n55  1657612800000  19702.37  19788.18  19540.05  19692.60   460.45565   \n56  1657627200000  19692.60  19900.00  19593.68  19747.44   611.02470   \n57  1657641600000  19752.45  19863.33  19210.00  19341.82   497.03727   \n58  1657656000000  19335.89  19483.86  19180.00  19264.35   308.76933   \n59  1657670400000  19269.46  19490.98  19194.99  19387.86   197.61018   \n60  1657684800000  19387.60  19826.82  19346.84  19635.00   303.94573   \n61  1657699200000  19637.33  19849.00  19591.88  19709.72   354.27250   \n62  1657713600000  19709.03  19949.11  18900.00  19307.32  1484.33594   \n63  1657728000000  19309.24  19847.79  19062.30  19532.32   515.64755   \n64  1657742400000  19546.03  20223.49  19479.56  20170.50   260.18959   \n65  1657756800000  20168.33  20381.57  20102.00  20144.87   241.58975   \n66  1657771200000  20147.75  20196.43  19834.99  19921.30   268.96704   \n67  1657785600000  19921.92  19977.74  19617.67  19720.98   419.68195   \n68  1657800000000  19728.41  20380.00  19620.00  20331.35   607.69229   \n69  1657814400000  20340.51  20833.24  20175.04  20564.01   479.79370   \n70  1657828800000  20568.16  20662.00  20375.50  20512.39   150.12464   \n71  1657843200000  20514.86  20744.73  20321.14  20544.46   263.46616   \n72  1657857600000  20549.86  20868.00  20426.76  20780.82   217.55220   \n73  1657872000000  20779.78  20977.27  20639.60  20656.75   416.18591   \n74  1657886400000  20656.75  20920.00  20589.64  20609.10   433.58248   \n75  1657900800000  20613.83  21008.95  20480.00  20993.00   293.10815   \n76  1657915200000  20994.66  21020.85  20579.71  20656.76   138.16319   \n77  1657929600000  20648.49  20687.35  20440.00  20569.58    95.83572   \n78  1657944000000  20569.44  20591.44  20307.92  20393.73   129.11403   \n79  1657958400000  20383.49  20522.53  20379.62  20455.96   102.39892   \n80  1657972800000  20456.78  20790.48  20426.22  20768.94   164.80414   \n81  1657987200000  20769.99  21400.00  20756.11  20999.98   572.62042   \n82  1658001600000  21005.46  21140.04  20732.07  21000.57   161.33142   \n83  1658016000000  20996.17  21252.00  20892.60  21123.65   128.20199   \n84  1658030400000  21124.67  21479.30  21034.31  21276.55   145.08238   \n85  1658044800000  21276.88  21354.24  21037.01  21261.94   164.56054   \n86  1658059200000  21261.82  21303.24  20903.66  20988.20   181.59892   \n87  1658073600000  20992.49  21166.08  20644.14  20836.32   244.42499   \n88  1658088000000  20840.42  20872.01  20543.89  20584.47   125.47296   \n89  1658102400000  20581.98  21136.00  20554.48  21055.32   173.82943   \n90  1658116800000  21053.35  22119.00  20952.36  21910.00   573.51422   \n91  1658131200000  21919.00  22197.00  21656.09  21828.48   450.41436   \n92  1658145600000  21832.43  22410.11  21624.97  22313.67   652.80635   \n93  1658160000000  22323.89  22362.03  21102.61  21326.40   513.45580   \n94  1658174400000  21335.30  22307.00  21152.72  22109.72   280.90632   \n95  1658188800000  22124.02  22624.89  21519.02  21623.42   561.46137   \n96  1658203200000  21626.69  21809.41  21207.68  21269.86   598.70724   \n97  1658217600000  21270.48  21635.08  21185.40  21372.78   597.87930   \n98  1658232000000  21372.11  22661.00  21369.48  22613.43  1022.52249   \n99  1658246400000  22589.52  23169.62  22417.49  22923.80   852.82144   \n\n           date_parsed        avg         sma       stdev          bbup  \\\n45 2022-07-10 18:00:00  10537.075  21156.0630  346.675915  22000.301789   \n46 2022-07-10 22:00:00  10649.360  21155.0480  348.614300  22027.598749   \n47 2022-07-11 02:00:00  10437.515  21093.8870  396.405866  22146.062665   \n48 2022-07-11 06:00:00  10252.530  21042.0975  440.511845  22195.166613   \n49 2022-07-11 10:00:00  10301.920  20967.7405  435.236720  22130.189301   \n50 2022-07-11 14:00:00  10546.030  20902.5955  438.679543  22064.439359   \n51 2022-07-11 18:00:00  10458.005  20860.2620  443.052529  22010.226824   \n52 2022-07-11 22:00:00  10572.005  20774.2020  461.539514  22014.110785   \n53 2022-07-12 02:00:00  10081.270  20696.1135  474.667761  21960.871402   \n54 2022-07-12 06:00:00  10235.575  20621.0685  508.102639  21966.370098   \n55 2022-07-12 10:00:00  10018.155  20545.0410  528.208849  21941.590623   \n56 2022-07-12 14:00:00  10103.160  20468.8090  527.777987  21864.485968   \n57 2022-07-12 18:00:00  10258.330  20382.1135  564.002211  21878.814527   \n58 2022-07-12 22:00:00   9893.860  20286.8560  584.529019  21843.436047   \n59 2022-07-13 02:00:00   9893.485  20194.4345  572.517226  21718.149066   \n60 2022-07-13 06:00:00  10153.400  20115.4810  531.946813  21524.301532   \n61 2022-07-13 10:00:00  10053.060  20054.5885  503.010742  21373.007856   \n62 2022-07-13 14:00:00  10499.110  19971.8765  481.574378  21258.524444   \n63 2022-07-13 18:00:00  10316.640  19902.6550  435.947571  21061.745427   \n64 2022-07-13 22:00:00  10483.710  19885.8120  417.470735  20946.331838   \n65 2022-07-14 02:00:00  10330.570  19865.3915  392.335253  20866.650132   \n66 2022-07-14 06:00:00  10278.935  19835.7220  361.906043  20770.156607   \n67 2022-07-14 10:00:00  10168.905  19809.9545  350.033335  20710.805336   \n68 2022-07-14 14:00:00  10570.000  19815.9450  358.197828  20705.449071   \n69 2022-07-14 18:00:00  10745.720  19829.6025  381.695280  20770.183199   \n70 2022-07-14 22:00:00  10474.250  19842.1330  400.290392  20830.328479   \n71 2022-07-15 02:00:00  10584.160  19848.6145  410.958873  20869.530184   \n72 2022-07-15 06:00:00  10654.620  19894.4390  460.869838  21000.789094   \n73 2022-07-15 10:00:00  10657.470  19933.3010  491.309165  21122.711913   \n74 2022-07-15 14:00:00  10625.180  19978.7480  510.281150  21209.003875   \n75 2022-07-15 18:00:00  10768.950  20043.7680  552.964481  21361.159202   \n76 2022-07-15 22:00:00  10730.995  20089.2340  564.578575  21455.214439   \n77 2022-07-16 02:00:00  10467.350  20150.6220  545.458052  21452.879131   \n78 2022-07-16 06:00:00  10437.480  20207.0910  505.902723  21415.378807   \n79 2022-07-16 10:00:00  10332.720  20260.4960  469.970223  21382.016558   \n80 2022-07-16 14:00:00  10577.370  20317.1930  458.805501  21407.509751   \n81 2022-07-16 18:00:00  11021.945  20381.7060  459.604141  21466.203352   \n82 2022-07-16 22:00:00  10774.005  20466.3685  403.850933  21391.333334   \n83 2022-07-17 02:00:00  10805.700  20545.9350  365.035814  21378.958035   \n84 2022-07-17 06:00:00  10962.145  20601.2375  388.211233  21516.463083   \n85 2022-07-17 10:00:00  10835.735  20657.0910  399.296454  21599.478634   \n86 2022-07-17 14:00:00  10851.410  20710.4360  365.675042  21571.278606   \n87 2022-07-17 18:00:00  10844.010  20766.2030  282.402376  21416.441940   \n88 2022-07-17 22:00:00  10600.065  20778.8590  267.148411  21434.074028   \n89 2022-07-18 02:00:00  10858.760  20803.4245  268.935378  21451.197446   \n90 2022-07-18 06:00:00  11642.820  20873.3050  356.617227  21694.967568   \n91 2022-07-18 10:00:00  11368.955  20937.5060  406.404385  21889.315964   \n92 2022-07-18 14:00:00  11597.625  21014.1485  507.310834  22205.783085   \n93 2022-07-18 18:00:00  11810.725  21047.6310  504.572102  22275.578755   \n94 2022-07-18 22:00:00  11730.640  21122.6620  545.816516  22412.172289   \n95 2022-07-19 02:00:00  11865.380  21154.1830  556.042055  22512.767138   \n96 2022-07-19 06:00:00  11205.570  21184.8380  543.944150  22514.043374   \n97 2022-07-19 10:00:00  11042.380  21224.9980  525.464847  22498.500117   \n98 2022-07-19 14:00:00  11976.260  21335.9830  572.921246  22657.301115   \n99 2022-07-19 18:00:00  11960.875  21459.3750  635.723664  22925.292160   \n\n          bbdown   sell    buy  position_sell  position_buy stato  \n45  20093.584254  False  False          False         False  None  \n46  20110.220101  False  False          False         False  None  \n47  19965.830402  False  False          False         False  None  \n48  19772.351464  False  False          False         False  None  \n49  19736.387339  False  False          False         False  None  \n50  19651.701870  False  False          False         False  None  \n51  19573.437912  False  False          False         False  None  \n52  19475.643458  False  False          False         False  None  \n53  19350.198718  False  False          False         False  None  \n54  19171.805583  False  False          False         False  None  \n55  19036.441952  False  False          False         False  None  \n56  18961.707038  False  False          False         False  None  \n57  18776.802367  False  False          False         False  None  \n58  18628.526444  False  False          False         False  None  \n59  18569.304321  False  False          False         False  None  \n60  18598.594062  False  False          False         False  None  \n61  18606.448773  False  False          False         False  None  \n62  18609.865367  False  False          False         False  None  \n63  18664.033787  False  False          False         False  None  \n64  18650.242794  False  False          False         False  None  \n65  18708.806242  False  False          False         False  None  \n66  18779.673371  False  False          False         False  None  \n67  18785.621996  False  False          False         False  None  \n68  18735.361015  False  False          False         False  None  \n69  18670.859161   True  False          False         False  None  \n70  18628.731325  False  False          False         False  None  \n71  18609.256380  False  False          False         False  None  \n72  18466.004987  False  False          False         False  None  \n73  18420.511504  False  False          False         False  None  \n74  18402.457550  False  False          False         False  None  \n75  18319.854558  False  False          False         False  None  \n76  18350.032274  False  False          False         False  None  \n77  18452.859843  False  False          False         False  None  \n78  18632.913832  False  False          False         False  None  \n79  18797.180331  False  False          False         False  None  \n80  18884.079498  False  False          False         False  None  \n81  18938.380578  False  False          False         False  None  \n82  19170.153200  False  False          False         False  None  \n83  19371.261058  False  False          False         False  None  \n84  19381.301300  False  False          False         False  None  \n85  19403.348139  False  False          False         False  None  \n86  19560.065873  False  False          False         False  None  \n87  19863.228873  False  False          False         False  None  \n88  19964.757766  False  False          False         False  None  \n89  19972.052865  False  False          False         False  None  \n90  19733.572818   True  False          False         False  None  \n91  19654.091844   True  False          False         False  None  \n92  19415.573498   True  False          False         False  None  \n93  19500.432194   True  False          False         False  None  \n94  19410.181453  False  False          False         False  None  \n95  19454.535834   True  False          False         False  None  \n96  19522.350551  False  False          False         False  None  \n97  19608.443460  False  False          False         False  None  \n98  19506.234262   True  False          False         False  None  \n99  19428.812009   True  False          False         False  None  ",
      "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      <th>date_parsed</th>\n      <th>avg</th>\n      <th>sma</th>\n      <th>stdev</th>\n      <th>bbup</th>\n      <th>bbdown</th>\n      <th>sell</th>\n      <th>buy</th>\n      <th>position_sell</th>\n      <th>position_buy</th>\n      <th>stato</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>45</th>\n      <td>1657468800000</td>\n      <td>20507.36</td>\n      <td>20675.06</td>\n      <td>20275.97</td>\n      <td>20553.28</td>\n      <td>319.08563</td>\n      <td>2022-07-10 18:00:00</td>\n      <td>10537.075</td>\n      <td>21156.0630</td>\n      <td>346.675915</td>\n      <td>22000.301789</td>\n      <td>20093.584254</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>1657483200000</td>\n      <td>20555.95</td>\n      <td>20812.17</td>\n      <td>20325.62</td>\n      <td>20514.69</td>\n      <td>232.58279</td>\n      <td>2022-07-10 22:00:00</td>\n      <td>10649.360</td>\n      <td>21155.0480</td>\n      <td>348.614300</td>\n      <td>22027.598749</td>\n      <td>20110.220101</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>1657497600000</td>\n      <td>20520.05</td>\n      <td>20520.05</td>\n      <td>20165.07</td>\n      <td>20236.33</td>\n      <td>205.54144</td>\n      <td>2022-07-11 02:00:00</td>\n      <td>10437.515</td>\n      <td>21093.8870</td>\n      <td>396.405866</td>\n      <td>22146.062665</td>\n      <td>19965.830402</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>1657512000000</td>\n      <td>20226.50</td>\n      <td>20291.91</td>\n      <td>20078.76</td>\n      <td>20211.54</td>\n      <td>183.83038</td>\n      <td>2022-07-11 06:00:00</td>\n      <td>10252.530</td>\n      <td>21042.0975</td>\n      <td>440.511845</td>\n      <td>22195.166613</td>\n      <td>19772.351464</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>1657526400000</td>\n      <td>20211.42</td>\n      <td>20394.42</td>\n      <td>20185.00</td>\n      <td>20290.86</td>\n      <td>272.45973</td>\n      <td>2022-07-11 10:00:00</td>\n      <td>10301.920</td>\n      <td>20967.7405</td>\n      <td>435.236720</td>\n      <td>22130.189301</td>\n      <td>19736.387339</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>1657540800000</td>\n      <td>20291.44</td>\n      <td>20618.18</td>\n      <td>20144.30</td>\n      <td>20261.78</td>\n      <td>423.81371</td>\n      <td>2022-07-11 14:00:00</td>\n      <td>10546.030</td>\n      <td>20902.5955</td>\n      <td>438.679543</td>\n      <td>22064.439359</td>\n      <td>19651.701870</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td>1657555200000</td>\n      <td>20263.79</td>\n      <td>20580.00</td>\n      <td>20243.99</td>\n      <td>20414.83</td>\n      <td>351.10818</td>\n      <td>2022-07-11 18:00:00</td>\n      <td>10458.005</td>\n      <td>20860.2620</td>\n      <td>443.052529</td>\n      <td>22010.226824</td>\n      <td>19573.437912</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td>1657569600000</td>\n      <td>20419.03</td>\n      <td>20466.74</td>\n      <td>19789.47</td>\n      <td>19864.33</td>\n      <td>351.96108</td>\n      <td>2022-07-11 22:00:00</td>\n      <td>10572.005</td>\n      <td>20774.2020</td>\n      <td>461.539514</td>\n      <td>22014.110785</td>\n      <td>19475.643458</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td>1657584000000</td>\n      <td>19863.77</td>\n      <td>19930.50</td>\n      <td>19698.46</td>\n      <td>19879.51</td>\n      <td>291.03943</td>\n      <td>2022-07-12 02:00:00</td>\n      <td>10081.270</td>\n      <td>20696.1135</td>\n      <td>474.667761</td>\n      <td>21960.871402</td>\n      <td>19350.198718</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td>1657598400000</td>\n      <td>19880.40</td>\n      <td>20025.48</td>\n      <td>19579.81</td>\n      <td>19700.16</td>\n      <td>371.97960</td>\n      <td>2022-07-12 06:00:00</td>\n      <td>10235.575</td>\n      <td>20621.0685</td>\n      <td>508.102639</td>\n      <td>21966.370098</td>\n      <td>19171.805583</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td>1657612800000</td>\n      <td>19702.37</td>\n      <td>19788.18</td>\n      <td>19540.05</td>\n      <td>19692.60</td>\n      <td>460.45565</td>\n      <td>2022-07-12 10:00:00</td>\n      <td>10018.155</td>\n      <td>20545.0410</td>\n      <td>528.208849</td>\n      <td>21941.590623</td>\n      <td>19036.441952</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td>1657627200000</td>\n      <td>19692.60</td>\n      <td>19900.00</td>\n      <td>19593.68</td>\n      <td>19747.44</td>\n      <td>611.02470</td>\n      <td>2022-07-12 14:00:00</td>\n      <td>10103.160</td>\n      <td>20468.8090</td>\n      <td>527.777987</td>\n      <td>21864.485968</td>\n      <td>18961.707038</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td>1657641600000</td>\n      <td>19752.45</td>\n      <td>19863.33</td>\n      <td>19210.00</td>\n      <td>19341.82</td>\n      <td>497.03727</td>\n      <td>2022-07-12 18:00:00</td>\n      <td>10258.330</td>\n      <td>20382.1135</td>\n      <td>564.002211</td>\n      <td>21878.814527</td>\n      <td>18776.802367</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td>1657656000000</td>\n      <td>19335.89</td>\n      <td>19483.86</td>\n      <td>19180.00</td>\n      <td>19264.35</td>\n      <td>308.76933</td>\n      <td>2022-07-12 22:00:00</td>\n      <td>9893.860</td>\n      <td>20286.8560</td>\n      <td>584.529019</td>\n      <td>21843.436047</td>\n      <td>18628.526444</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>59</th>\n      <td>1657670400000</td>\n      <td>19269.46</td>\n      <td>19490.98</td>\n      <td>19194.99</td>\n      <td>19387.86</td>\n      <td>197.61018</td>\n      <td>2022-07-13 02:00:00</td>\n      <td>9893.485</td>\n      <td>20194.4345</td>\n      <td>572.517226</td>\n      <td>21718.149066</td>\n      <td>18569.304321</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>60</th>\n      <td>1657684800000</td>\n      <td>19387.60</td>\n      <td>19826.82</td>\n      <td>19346.84</td>\n      <td>19635.00</td>\n      <td>303.94573</td>\n      <td>2022-07-13 06:00:00</td>\n      <td>10153.400</td>\n      <td>20115.4810</td>\n      <td>531.946813</td>\n      <td>21524.301532</td>\n      <td>18598.594062</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>61</th>\n      <td>1657699200000</td>\n      <td>19637.33</td>\n      <td>19849.00</td>\n      <td>19591.88</td>\n      <td>19709.72</td>\n      <td>354.27250</td>\n      <td>2022-07-13 10:00:00</td>\n      <td>10053.060</td>\n      <td>20054.5885</td>\n      <td>503.010742</td>\n      <td>21373.007856</td>\n      <td>18606.448773</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>62</th>\n      <td>1657713600000</td>\n      <td>19709.03</td>\n      <td>19949.11</td>\n      <td>18900.00</td>\n      <td>19307.32</td>\n      <td>1484.33594</td>\n      <td>2022-07-13 14:00:00</td>\n      <td>10499.110</td>\n      <td>19971.8765</td>\n      <td>481.574378</td>\n      <td>21258.524444</td>\n      <td>18609.865367</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>63</th>\n      <td>1657728000000</td>\n      <td>19309.24</td>\n      <td>19847.79</td>\n      <td>19062.30</td>\n      <td>19532.32</td>\n      <td>515.64755</td>\n      <td>2022-07-13 18:00:00</td>\n      <td>10316.640</td>\n      <td>19902.6550</td>\n      <td>435.947571</td>\n      <td>21061.745427</td>\n      <td>18664.033787</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>64</th>\n      <td>1657742400000</td>\n      <td>19546.03</td>\n      <td>20223.49</td>\n      <td>19479.56</td>\n      <td>20170.50</td>\n      <td>260.18959</td>\n      <td>2022-07-13 22:00:00</td>\n      <td>10483.710</td>\n      <td>19885.8120</td>\n      <td>417.470735</td>\n      <td>20946.331838</td>\n      <td>18650.242794</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>65</th>\n      <td>1657756800000</td>\n      <td>20168.33</td>\n      <td>20381.57</td>\n      <td>20102.00</td>\n      <td>20144.87</td>\n      <td>241.58975</td>\n      <td>2022-07-14 02:00:00</td>\n      <td>10330.570</td>\n      <td>19865.3915</td>\n      <td>392.335253</td>\n      <td>20866.650132</td>\n      <td>18708.806242</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>66</th>\n      <td>1657771200000</td>\n      <td>20147.75</td>\n      <td>20196.43</td>\n      <td>19834.99</td>\n      <td>19921.30</td>\n      <td>268.96704</td>\n      <td>2022-07-14 06:00:00</td>\n      <td>10278.935</td>\n      <td>19835.7220</td>\n      <td>361.906043</td>\n      <td>20770.156607</td>\n      <td>18779.673371</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>67</th>\n      <td>1657785600000</td>\n      <td>19921.92</td>\n      <td>19977.74</td>\n      <td>19617.67</td>\n      <td>19720.98</td>\n      <td>419.68195</td>\n      <td>2022-07-14 10:00:00</td>\n      <td>10168.905</td>\n      <td>19809.9545</td>\n      <td>350.033335</td>\n      <td>20710.805336</td>\n      <td>18785.621996</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>68</th>\n      <td>1657800000000</td>\n      <td>19728.41</td>\n      <td>20380.00</td>\n      <td>19620.00</td>\n      <td>20331.35</td>\n      <td>607.69229</td>\n      <td>2022-07-14 14:00:00</td>\n      <td>10570.000</td>\n      <td>19815.9450</td>\n      <td>358.197828</td>\n      <td>20705.449071</td>\n      <td>18735.361015</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>69</th>\n      <td>1657814400000</td>\n      <td>20340.51</td>\n      <td>20833.24</td>\n      <td>20175.04</td>\n      <td>20564.01</td>\n      <td>479.79370</td>\n      <td>2022-07-14 18:00:00</td>\n      <td>10745.720</td>\n      <td>19829.6025</td>\n      <td>381.695280</td>\n      <td>20770.183199</td>\n      <td>18670.859161</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>70</th>\n      <td>1657828800000</td>\n      <td>20568.16</td>\n      <td>20662.00</td>\n      <td>20375.50</td>\n      <td>20512.39</td>\n      <td>150.12464</td>\n      <td>2022-07-14 22:00:00</td>\n      <td>10474.250</td>\n      <td>19842.1330</td>\n      <td>400.290392</td>\n      <td>20830.328479</td>\n      <td>18628.731325</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>71</th>\n      <td>1657843200000</td>\n      <td>20514.86</td>\n      <td>20744.73</td>\n      <td>20321.14</td>\n      <td>20544.46</td>\n      <td>263.46616</td>\n      <td>2022-07-15 02:00:00</td>\n      <td>10584.160</td>\n      <td>19848.6145</td>\n      <td>410.958873</td>\n      <td>20869.530184</td>\n      <td>18609.256380</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>72</th>\n      <td>1657857600000</td>\n      <td>20549.86</td>\n      <td>20868.00</td>\n      <td>20426.76</td>\n      <td>20780.82</td>\n      <td>217.55220</td>\n      <td>2022-07-15 06:00:00</td>\n      <td>10654.620</td>\n      <td>19894.4390</td>\n      <td>460.869838</td>\n      <td>21000.789094</td>\n      <td>18466.004987</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>73</th>\n      <td>1657872000000</td>\n      <td>20779.78</td>\n      <td>20977.27</td>\n      <td>20639.60</td>\n      <td>20656.75</td>\n      <td>416.18591</td>\n      <td>2022-07-15 10:00:00</td>\n      <td>10657.470</td>\n      <td>19933.3010</td>\n      <td>491.309165</td>\n      <td>21122.711913</td>\n      <td>18420.511504</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>74</th>\n      <td>1657886400000</td>\n      <td>20656.75</td>\n      <td>20920.00</td>\n      <td>20589.64</td>\n      <td>20609.10</td>\n      <td>433.58248</td>\n      <td>2022-07-15 14:00:00</td>\n      <td>10625.180</td>\n      <td>19978.7480</td>\n      <td>510.281150</td>\n      <td>21209.003875</td>\n      <td>18402.457550</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>75</th>\n      <td>1657900800000</td>\n      <td>20613.83</td>\n      <td>21008.95</td>\n      <td>20480.00</td>\n      <td>20993.00</td>\n      <td>293.10815</td>\n      <td>2022-07-15 18:00:00</td>\n      <td>10768.950</td>\n      <td>20043.7680</td>\n      <td>552.964481</td>\n      <td>21361.159202</td>\n      <td>18319.854558</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>76</th>\n      <td>1657915200000</td>\n      <td>20994.66</td>\n      <td>21020.85</td>\n      <td>20579.71</td>\n      <td>20656.76</td>\n      <td>138.16319</td>\n      <td>2022-07-15 22:00:00</td>\n      <td>10730.995</td>\n      <td>20089.2340</td>\n      <td>564.578575</td>\n      <td>21455.214439</td>\n      <td>18350.032274</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>77</th>\n      <td>1657929600000</td>\n      <td>20648.49</td>\n      <td>20687.35</td>\n      <td>20440.00</td>\n      <td>20569.58</td>\n      <td>95.83572</td>\n      <td>2022-07-16 02:00:00</td>\n      <td>10467.350</td>\n      <td>20150.6220</td>\n      <td>545.458052</td>\n      <td>21452.879131</td>\n      <td>18452.859843</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>78</th>\n      <td>1657944000000</td>\n      <td>20569.44</td>\n      <td>20591.44</td>\n      <td>20307.92</td>\n      <td>20393.73</td>\n      <td>129.11403</td>\n      <td>2022-07-16 06:00:00</td>\n      <td>10437.480</td>\n      <td>20207.0910</td>\n      <td>505.902723</td>\n      <td>21415.378807</td>\n      <td>18632.913832</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>79</th>\n      <td>1657958400000</td>\n      <td>20383.49</td>\n      <td>20522.53</td>\n      <td>20379.62</td>\n      <td>20455.96</td>\n      <td>102.39892</td>\n      <td>2022-07-16 10:00:00</td>\n      <td>10332.720</td>\n      <td>20260.4960</td>\n      <td>469.970223</td>\n      <td>21382.016558</td>\n      <td>18797.180331</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>80</th>\n      <td>1657972800000</td>\n      <td>20456.78</td>\n      <td>20790.48</td>\n      <td>20426.22</td>\n      <td>20768.94</td>\n      <td>164.80414</td>\n      <td>2022-07-16 14:00:00</td>\n      <td>10577.370</td>\n      <td>20317.1930</td>\n      <td>458.805501</td>\n      <td>21407.509751</td>\n      <td>18884.079498</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>81</th>\n      <td>1657987200000</td>\n      <td>20769.99</td>\n      <td>21400.00</td>\n      <td>20756.11</td>\n      <td>20999.98</td>\n      <td>572.62042</td>\n      <td>2022-07-16 18:00:00</td>\n      <td>11021.945</td>\n      <td>20381.7060</td>\n      <td>459.604141</td>\n      <td>21466.203352</td>\n      <td>18938.380578</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>82</th>\n      <td>1658001600000</td>\n      <td>21005.46</td>\n      <td>21140.04</td>\n      <td>20732.07</td>\n      <td>21000.57</td>\n      <td>161.33142</td>\n      <td>2022-07-16 22:00:00</td>\n      <td>10774.005</td>\n      <td>20466.3685</td>\n      <td>403.850933</td>\n      <td>21391.333334</td>\n      <td>19170.153200</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>83</th>\n      <td>1658016000000</td>\n      <td>20996.17</td>\n      <td>21252.00</td>\n      <td>20892.60</td>\n      <td>21123.65</td>\n      <td>128.20199</td>\n      <td>2022-07-17 02:00:00</td>\n      <td>10805.700</td>\n      <td>20545.9350</td>\n      <td>365.035814</td>\n      <td>21378.958035</td>\n      <td>19371.261058</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>84</th>\n      <td>1658030400000</td>\n      <td>21124.67</td>\n      <td>21479.30</td>\n      <td>21034.31</td>\n      <td>21276.55</td>\n      <td>145.08238</td>\n      <td>2022-07-17 06:00:00</td>\n      <td>10962.145</td>\n      <td>20601.2375</td>\n      <td>388.211233</td>\n      <td>21516.463083</td>\n      <td>19381.301300</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>85</th>\n      <td>1658044800000</td>\n      <td>21276.88</td>\n      <td>21354.24</td>\n      <td>21037.01</td>\n      <td>21261.94</td>\n      <td>164.56054</td>\n      <td>2022-07-17 10:00:00</td>\n      <td>10835.735</td>\n      <td>20657.0910</td>\n      <td>399.296454</td>\n      <td>21599.478634</td>\n      <td>19403.348139</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>86</th>\n      <td>1658059200000</td>\n      <td>21261.82</td>\n      <td>21303.24</td>\n      <td>20903.66</td>\n      <td>20988.20</td>\n      <td>181.59892</td>\n      <td>2022-07-17 14:00:00</td>\n      <td>10851.410</td>\n      <td>20710.4360</td>\n      <td>365.675042</td>\n      <td>21571.278606</td>\n      <td>19560.065873</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>87</th>\n      <td>1658073600000</td>\n      <td>20992.49</td>\n      <td>21166.08</td>\n      <td>20644.14</td>\n      <td>20836.32</td>\n      <td>244.42499</td>\n      <td>2022-07-17 18:00:00</td>\n      <td>10844.010</td>\n      <td>20766.2030</td>\n      <td>282.402376</td>\n      <td>21416.441940</td>\n      <td>19863.228873</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>88</th>\n      <td>1658088000000</td>\n      <td>20840.42</td>\n      <td>20872.01</td>\n      <td>20543.89</td>\n      <td>20584.47</td>\n      <td>125.47296</td>\n      <td>2022-07-17 22:00:00</td>\n      <td>10600.065</td>\n      <td>20778.8590</td>\n      <td>267.148411</td>\n      <td>21434.074028</td>\n      <td>19964.757766</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>89</th>\n      <td>1658102400000</td>\n      <td>20581.98</td>\n      <td>21136.00</td>\n      <td>20554.48</td>\n      <td>21055.32</td>\n      <td>173.82943</td>\n      <td>2022-07-18 02:00:00</td>\n      <td>10858.760</td>\n      <td>20803.4245</td>\n      <td>268.935378</td>\n      <td>21451.197446</td>\n      <td>19972.052865</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>90</th>\n      <td>1658116800000</td>\n      <td>21053.35</td>\n      <td>22119.00</td>\n      <td>20952.36</td>\n      <td>21910.00</td>\n      <td>573.51422</td>\n      <td>2022-07-18 06:00:00</td>\n      <td>11642.820</td>\n      <td>20873.3050</td>\n      <td>356.617227</td>\n      <td>21694.967568</td>\n      <td>19733.572818</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>91</th>\n      <td>1658131200000</td>\n      <td>21919.00</td>\n      <td>22197.00</td>\n      <td>21656.09</td>\n      <td>21828.48</td>\n      <td>450.41436</td>\n      <td>2022-07-18 10:00:00</td>\n      <td>11368.955</td>\n      <td>20937.5060</td>\n      <td>406.404385</td>\n      <td>21889.315964</td>\n      <td>19654.091844</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>92</th>\n      <td>1658145600000</td>\n      <td>21832.43</td>\n      <td>22410.11</td>\n      <td>21624.97</td>\n      <td>22313.67</td>\n      <td>652.80635</td>\n      <td>2022-07-18 14:00:00</td>\n      <td>11597.625</td>\n      <td>21014.1485</td>\n      <td>507.310834</td>\n      <td>22205.783085</td>\n      <td>19415.573498</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>93</th>\n      <td>1658160000000</td>\n      <td>22323.89</td>\n      <td>22362.03</td>\n      <td>21102.61</td>\n      <td>21326.40</td>\n      <td>513.45580</td>\n      <td>2022-07-18 18:00:00</td>\n      <td>11810.725</td>\n      <td>21047.6310</td>\n      <td>504.572102</td>\n      <td>22275.578755</td>\n      <td>19500.432194</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>94</th>\n      <td>1658174400000</td>\n      <td>21335.30</td>\n      <td>22307.00</td>\n      <td>21152.72</td>\n      <td>22109.72</td>\n      <td>280.90632</td>\n      <td>2022-07-18 22:00:00</td>\n      <td>11730.640</td>\n      <td>21122.6620</td>\n      <td>545.816516</td>\n      <td>22412.172289</td>\n      <td>19410.181453</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>95</th>\n      <td>1658188800000</td>\n      <td>22124.02</td>\n      <td>22624.89</td>\n      <td>21519.02</td>\n      <td>21623.42</td>\n      <td>561.46137</td>\n      <td>2022-07-19 02:00:00</td>\n      <td>11865.380</td>\n      <td>21154.1830</td>\n      <td>556.042055</td>\n      <td>22512.767138</td>\n      <td>19454.535834</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>96</th>\n      <td>1658203200000</td>\n      <td>21626.69</td>\n      <td>21809.41</td>\n      <td>21207.68</td>\n      <td>21269.86</td>\n      <td>598.70724</td>\n      <td>2022-07-19 06:00:00</td>\n      <td>11205.570</td>\n      <td>21184.8380</td>\n      <td>543.944150</td>\n      <td>22514.043374</td>\n      <td>19522.350551</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>97</th>\n      <td>1658217600000</td>\n      <td>21270.48</td>\n      <td>21635.08</td>\n      <td>21185.40</td>\n      <td>21372.78</td>\n      <td>597.87930</td>\n      <td>2022-07-19 10:00:00</td>\n      <td>11042.380</td>\n      <td>21224.9980</td>\n      <td>525.464847</td>\n      <td>22498.500117</td>\n      <td>19608.443460</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>98</th>\n      <td>1658232000000</td>\n      <td>21372.11</td>\n      <td>22661.00</td>\n      <td>21369.48</td>\n      <td>22613.43</td>\n      <td>1022.52249</td>\n      <td>2022-07-19 14:00:00</td>\n      <td>11976.260</td>\n      <td>21335.9830</td>\n      <td>572.921246</td>\n      <td>22657.301115</td>\n      <td>19506.234262</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n    <tr>\n      <th>99</th>\n      <td>1658246400000</td>\n      <td>22589.52</td>\n      <td>23169.62</td>\n      <td>22417.49</td>\n      <td>22923.80</td>\n      <td>852.82144</td>\n      <td>2022-07-19 18:00:00</td>\n      <td>11960.875</td>\n      <td>21459.3750</td>\n      <td>635.723664</td>\n      <td>22925.292160</td>\n      <td>19428.812009</td>\n      <td>True</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stato='None'\n",
    "for i in range (0,len(df)):\n",
    "    if (stato =='None') & (df.loc[i,'buy']==True):\n",
    "        df.loc[i,'position_buy']=True\n",
    "        stato='buy'\n",
    "    if (stato=='buy') & (df.loc[i,'sell']==True):\n",
    "        df.loc[i,'position_sell']=True\n",
    "        stato='None'\n",
    "    df.loc[i,'stato']=stato\n",
    "\n",
    "df[45:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "         timestamp      open      high       low     close      volume  \\\n0    1656820800000  18473.64  18597.98  18011.50  18377.86   330.04671   \n1    1656835200000  18377.79  18391.12  18178.44  18319.21   201.72188   \n2    1656849600000  18320.37  18354.71  18205.44  18274.99   183.48512   \n3    1656864000000  18274.43  18763.76  18243.71  18712.49   236.91553   \n4    1656878400000  18714.88  18849.00  18408.16  18510.15   247.36362   \n..             ...       ...       ...       ...       ...         ...   \n995  1671148800000  16311.80  16371.78  16299.42  16355.38   335.18676   \n996  1671163200000  16355.27  16437.38  16286.90  16433.92   379.90982   \n997  1671177600000  16434.12  16443.77  15940.00  16013.39  1122.04752   \n998  1671192000000  16013.53  16063.96  15902.50  15991.63   721.07127   \n999  1671206400000  15991.92  15997.30  15783.62  15861.68   465.31701   \n\n            date_parsed       avg         sma       stdev          bbup  \\\n0   2022-07-03 06:00:00  9592.230         NaN         NaN           NaN   \n1   2022-07-03 10:00:00  9301.900         NaN         NaN           NaN   \n2   2022-07-03 14:00:00  9251.990         NaN         NaN           NaN   \n3   2022-07-03 18:00:00  9641.905         NaN         NaN           NaN   \n4   2022-07-03 22:00:00  9644.920         NaN         NaN           NaN   \n..                  ...       ...         ...         ...           ...   \n995 2022-12-16 01:00:00  8222.070  16573.2490  198.331627  17061.741567   \n996 2022-12-16 05:00:00  8293.930  16578.6950  192.567839  17054.668596   \n997 2022-12-16 09:00:00  8473.770  16565.5945  221.087563  17131.413908   \n998 2022-12-16 13:00:00  8112.710  16551.6175  247.891830  17185.324076   \n999 2022-12-16 17:00:00  8105.490  16516.7725  291.929933  17281.442332   \n\n           bbdown   sell    buy  position_sell  position_buy stato  norm_close  \n0             NaN  False  False          False         False  None    0.342213  \n1             NaN  False  False          False         False  None    0.335647  \n2             NaN  False  False          False         False  None    0.330696  \n3             NaN  False  False          False         False  None    0.379676  \n4             NaN  False  False          False         False  None    0.357024  \n..            ...    ...    ...            ...           ...   ...         ...  \n995  15970.917619  False  False          False         False  None    0.115788  \n996  15995.545484  False  False          False         False  None    0.124581  \n997  15915.432311  False  False          False         False  None    0.077501  \n998  15821.919009  False  False          False         False  None    0.075065  \n999  15675.827702  False  False          False         False  None    0.060517  \n\n[1000 rows x 18 columns]",
      "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      <th>date_parsed</th>\n      <th>avg</th>\n      <th>sma</th>\n      <th>stdev</th>\n      <th>bbup</th>\n      <th>bbdown</th>\n      <th>sell</th>\n      <th>buy</th>\n      <th>position_sell</th>\n      <th>position_buy</th>\n      <th>stato</th>\n      <th>norm_close</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1656820800000</td>\n      <td>18473.64</td>\n      <td>18597.98</td>\n      <td>18011.50</td>\n      <td>18377.86</td>\n      <td>330.04671</td>\n      <td>2022-07-03 06:00:00</td>\n      <td>9592.230</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.342213</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1656835200000</td>\n      <td>18377.79</td>\n      <td>18391.12</td>\n      <td>18178.44</td>\n      <td>18319.21</td>\n      <td>201.72188</td>\n      <td>2022-07-03 10:00:00</td>\n      <td>9301.900</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.335647</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1656849600000</td>\n      <td>18320.37</td>\n      <td>18354.71</td>\n      <td>18205.44</td>\n      <td>18274.99</td>\n      <td>183.48512</td>\n      <td>2022-07-03 14:00:00</td>\n      <td>9251.990</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.330696</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1656864000000</td>\n      <td>18274.43</td>\n      <td>18763.76</td>\n      <td>18243.71</td>\n      <td>18712.49</td>\n      <td>236.91553</td>\n      <td>2022-07-03 18:00:00</td>\n      <td>9641.905</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.379676</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1656878400000</td>\n      <td>18714.88</td>\n      <td>18849.00</td>\n      <td>18408.16</td>\n      <td>18510.15</td>\n      <td>247.36362</td>\n      <td>2022-07-03 22:00:00</td>\n      <td>9644.920</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.357024</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      <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>995</th>\n      <td>1671148800000</td>\n      <td>16311.80</td>\n      <td>16371.78</td>\n      <td>16299.42</td>\n      <td>16355.38</td>\n      <td>335.18676</td>\n      <td>2022-12-16 01:00:00</td>\n      <td>8222.070</td>\n      <td>16573.2490</td>\n      <td>198.331627</td>\n      <td>17061.741567</td>\n      <td>15970.917619</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.115788</td>\n    </tr>\n    <tr>\n      <th>996</th>\n      <td>1671163200000</td>\n      <td>16355.27</td>\n      <td>16437.38</td>\n      <td>16286.90</td>\n      <td>16433.92</td>\n      <td>379.90982</td>\n      <td>2022-12-16 05:00:00</td>\n      <td>8293.930</td>\n      <td>16578.6950</td>\n      <td>192.567839</td>\n      <td>17054.668596</td>\n      <td>15995.545484</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.124581</td>\n    </tr>\n    <tr>\n      <th>997</th>\n      <td>1671177600000</td>\n      <td>16434.12</td>\n      <td>16443.77</td>\n      <td>15940.00</td>\n      <td>16013.39</td>\n      <td>1122.04752</td>\n      <td>2022-12-16 09:00:00</td>\n      <td>8473.770</td>\n      <td>16565.5945</td>\n      <td>221.087563</td>\n      <td>17131.413908</td>\n      <td>15915.432311</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.077501</td>\n    </tr>\n    <tr>\n      <th>998</th>\n      <td>1671192000000</td>\n      <td>16013.53</td>\n      <td>16063.96</td>\n      <td>15902.50</td>\n      <td>15991.63</td>\n      <td>721.07127</td>\n      <td>2022-12-16 13:00:00</td>\n      <td>8112.710</td>\n      <td>16551.6175</td>\n      <td>247.891830</td>\n      <td>17185.324076</td>\n      <td>15821.919009</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.075065</td>\n    </tr>\n    <tr>\n      <th>999</th>\n      <td>1671206400000</td>\n      <td>15991.92</td>\n      <td>15997.30</td>\n      <td>15783.62</td>\n      <td>15861.68</td>\n      <td>465.31701</td>\n      <td>2022-12-16 17:00:00</td>\n      <td>8105.490</td>\n      <td>16516.7725</td>\n      <td>291.929933</td>\n      <td>17281.442332</td>\n      <td>15675.827702</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.060517</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 18 columns</p>\n</div>"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# apply normalization techniques on Column 1\n",
    "column = 'close'\n",
    "column_dest = 'norm_close'\n",
    "df[column_dest] = (df[column] - df[column].min()) / (df[column].max() - df[column].min())\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot: >"
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['close'][-20:].plot(kind = 'bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot: >"
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['norm_close'][-20:].plot(kind = 'bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "Int64Index([137, 175, 282, 325, 351, 393, 435, 579, 645, 735, 736, 768, 841,\n            971],\n           dtype='int64')"
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.position_buy==True].bbup.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
        {
         "marker": {
          "color": "#D22975"
         },
         "mode": "lines",
         "name": "Close",
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure=go.Figure()\n",
    "figure.add_trace(go.Scatter(name='Close', x=df.index, y=df.close, mode='lines', marker_color='#D22975'))\n",
    "figure.add_trace(go.Scatter(name='Up', x=df.index, y=df.bbup, mode='lines', marker_color='#2D2975'))\n",
    "figure.add_trace(go.Scatter(name='Down', x=df.index, y=df.bbdown, mode='lines', marker_color='#D29275'))\n",
    "figure.add_trace(go.Scatter(name='Sell', x=df[df.position_sell==True].index, y=df[df.position_sell==True].close, mode='markers', marker_color='#0000FF'))\n",
    "figure.add_trace(go.Scatter(name='Buy', x=df[df.position_buy==True].index, y=df[df.position_buy==True].close, mode='markers', marker_color='#00FF00'))\n",
    "\n",
    "\n",
    "#df.close.plot()\n",
    "#df.sellscatter(x, y)\n",
    "#df.bbup.plot()\n",
    "#df.bbdown.plot(figsize = [15,8]).grid()\n",
    "figure.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot: >"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.norm_close.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot: >"
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.close.rolling(15).mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot: >"
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df['norm_close'].plot()\n",
    "df.norm_close.rolling(20).mean().plot()\n",
    "df.norm_close.rolling(80).mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "15321.13"
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['close'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "24253.37"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['close'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "         timestamp      open      high       low     close      volume  \\\n0    1656820800000  18473.64  18597.98  18011.50  18377.86   330.04671   \n1    1656835200000  18377.79  18391.12  18178.44  18319.21   201.72188   \n2    1656849600000  18320.37  18354.71  18205.44  18274.99   183.48512   \n3    1656864000000  18274.43  18763.76  18243.71  18712.49   236.91553   \n4    1656878400000  18714.88  18849.00  18408.16  18510.15   247.36362   \n..             ...       ...       ...       ...       ...         ...   \n995  1671148800000  16311.80  16371.78  16299.42  16355.38   335.18676   \n996  1671163200000  16355.27  16437.38  16286.90  16433.92   379.90982   \n997  1671177600000  16434.12  16443.77  15940.00  16013.39  1122.04752   \n998  1671192000000  16013.53  16063.96  15902.50  15991.63   721.07127   \n999  1671206400000  15991.92  15997.30  15783.62  15861.68   465.31701   \n\n            date_parsed       avg         sma       stdev          bbup  \\\n0   2022-07-03 06:00:00  9592.230         NaN         NaN           NaN   \n1   2022-07-03 10:00:00  9301.900         NaN         NaN           NaN   \n2   2022-07-03 14:00:00  9251.990         NaN         NaN           NaN   \n3   2022-07-03 18:00:00  9641.905         NaN         NaN           NaN   \n4   2022-07-03 22:00:00  9644.920         NaN         NaN           NaN   \n..                  ...       ...         ...         ...           ...   \n995 2022-12-16 01:00:00  8222.070  16573.2490  198.331627  17061.741567   \n996 2022-12-16 05:00:00  8293.930  16578.6950  192.567839  17054.668596   \n997 2022-12-16 09:00:00  8473.770  16565.5945  221.087563  17131.413908   \n998 2022-12-16 13:00:00  8112.710  16551.6175  247.891830  17185.324076   \n999 2022-12-16 17:00:00  8105.490  16516.7725  291.929933  17281.442332   \n\n           bbdown   sell    buy  position_sell  position_buy stato  norm_close  \n0             NaN  False  False          False         False  None    0.342213  \n1             NaN  False  False          False         False  None    0.335647  \n2             NaN  False  False          False         False  None    0.330696  \n3             NaN  False  False          False         False  None    0.379676  \n4             NaN  False  False          False         False  None    0.357024  \n..            ...    ...    ...            ...           ...   ...         ...  \n995  15970.917619  False  False          False         False  None    0.115788  \n996  15995.545484  False  False          False         False  None    0.124581  \n997  15915.432311  False  False          False         False  None    0.077501  \n998  15821.919009  False  False          False         False  None    0.075065  \n999  15675.827702  False  False          False         False  None    0.060517  \n\n[1000 rows x 18 columns]",
      "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      <th>date_parsed</th>\n      <th>avg</th>\n      <th>sma</th>\n      <th>stdev</th>\n      <th>bbup</th>\n      <th>bbdown</th>\n      <th>sell</th>\n      <th>buy</th>\n      <th>position_sell</th>\n      <th>position_buy</th>\n      <th>stato</th>\n      <th>norm_close</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1656820800000</td>\n      <td>18473.64</td>\n      <td>18597.98</td>\n      <td>18011.50</td>\n      <td>18377.86</td>\n      <td>330.04671</td>\n      <td>2022-07-03 06:00:00</td>\n      <td>9592.230</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.342213</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1656835200000</td>\n      <td>18377.79</td>\n      <td>18391.12</td>\n      <td>18178.44</td>\n      <td>18319.21</td>\n      <td>201.72188</td>\n      <td>2022-07-03 10:00:00</td>\n      <td>9301.900</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.335647</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1656849600000</td>\n      <td>18320.37</td>\n      <td>18354.71</td>\n      <td>18205.44</td>\n      <td>18274.99</td>\n      <td>183.48512</td>\n      <td>2022-07-03 14:00:00</td>\n      <td>9251.990</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.330696</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1656864000000</td>\n      <td>18274.43</td>\n      <td>18763.76</td>\n      <td>18243.71</td>\n      <td>18712.49</td>\n      <td>236.91553</td>\n      <td>2022-07-03 18:00:00</td>\n      <td>9641.905</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.379676</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1656878400000</td>\n      <td>18714.88</td>\n      <td>18849.00</td>\n      <td>18408.16</td>\n      <td>18510.15</td>\n      <td>247.36362</td>\n      <td>2022-07-03 22:00:00</td>\n      <td>9644.920</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.357024</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      <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>995</th>\n      <td>1671148800000</td>\n      <td>16311.80</td>\n      <td>16371.78</td>\n      <td>16299.42</td>\n      <td>16355.38</td>\n      <td>335.18676</td>\n      <td>2022-12-16 01:00:00</td>\n      <td>8222.070</td>\n      <td>16573.2490</td>\n      <td>198.331627</td>\n      <td>17061.741567</td>\n      <td>15970.917619</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.115788</td>\n    </tr>\n    <tr>\n      <th>996</th>\n      <td>1671163200000</td>\n      <td>16355.27</td>\n      <td>16437.38</td>\n      <td>16286.90</td>\n      <td>16433.92</td>\n      <td>379.90982</td>\n      <td>2022-12-16 05:00:00</td>\n      <td>8293.930</td>\n      <td>16578.6950</td>\n      <td>192.567839</td>\n      <td>17054.668596</td>\n      <td>15995.545484</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.124581</td>\n    </tr>\n    <tr>\n      <th>997</th>\n      <td>1671177600000</td>\n      <td>16434.12</td>\n      <td>16443.77</td>\n      <td>15940.00</td>\n      <td>16013.39</td>\n      <td>1122.04752</td>\n      <td>2022-12-16 09:00:00</td>\n      <td>8473.770</td>\n      <td>16565.5945</td>\n      <td>221.087563</td>\n      <td>17131.413908</td>\n      <td>15915.432311</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.077501</td>\n    </tr>\n    <tr>\n      <th>998</th>\n      <td>1671192000000</td>\n      <td>16013.53</td>\n      <td>16063.96</td>\n      <td>15902.50</td>\n      <td>15991.63</td>\n      <td>721.07127</td>\n      <td>2022-12-16 13:00:00</td>\n      <td>8112.710</td>\n      <td>16551.6175</td>\n      <td>247.891830</td>\n      <td>17185.324076</td>\n      <td>15821.919009</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.075065</td>\n    </tr>\n    <tr>\n      <th>999</th>\n      <td>1671206400000</td>\n      <td>15991.92</td>\n      <td>15997.30</td>\n      <td>15783.62</td>\n      <td>15861.68</td>\n      <td>465.31701</td>\n      <td>2022-12-16 17:00:00</td>\n      <td>8105.490</td>\n      <td>16516.7725</td>\n      <td>291.929933</td>\n      <td>17281.442332</td>\n      <td>15675.827702</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>False</td>\n      <td>None</td>\n      <td>0.060517</td>\n    </tr>\n  </tbody>\n</table>\n<p>1000 rows × 18 columns</p>\n</div>"
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  }
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