HF Data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# High Frequency Data and Limit Order Books - LAB 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import math\n",
    "from scipy.stats import expon\n",
    "from scipy.stats import norm\n",
    "from scipy.stats import expon\n",
    "from scipy.stats import norm\n",
    "import matplotlib.dates as md"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Introduction:** This notebook is dedicated to the study and the exploration of some High-Frequency phenomena, related to limit order books analysis for EDF, Renault and Total stocks."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1. and 2.2.: Date and time, continuous double auction.\n",
    "\n",
    "Loading and preprocessing data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "edf_trades = []\n",
    "edf_quotes = []\n",
    "renault_trades = []\n",
    "renault_quotes = []\n",
    "total_trades = []\n",
    "total_quotes = []\n",
    "edf_pre = \"/Users/jeremymarck/Desktop/M2Finance/S2/HFLOB/TP/TP1/Data/EDF.PA-201509\"\n",
    "renault_pre = \"/Users/jeremymarck/Desktop/M2Finance/S2/HFLOB/TP/TP1/Data/RENA.PA-201509\"\n",
    "total_pre = \"/Users/jeremymarck/Desktop/M2Finance/S2/HFLOB/TP/TP1/Data/TOTF.PA-201509\"\n",
    "end_quote = \"-Quotes.csv.gz\"\n",
    "end_trade = \"-Trades.csv.gz\"\n",
    "for i in range(30):\n",
    "    day = i+1\n",
    "    if day < 10:\n",
    "        date = datetime.strptime('2015-09-'+'0'+str(day),'%Y-%m-%d')\n",
    "        if date.weekday()<5:\n",
    "            trades_edf = pd.read_csv(edf_pre+'0'+str(day)+end_trade)\n",
    "            trades_rena = pd.read_csv(renault_pre+'0'+str(day)+end_trade)\n",
    "            trades_totf = pd.read_csv(total_pre+'0'+str(day)+end_trade)\n",
    "            quotes_edf = pd.read_csv(edf_pre+'0'+str(day)+end_quote)\n",
    "            quotes_rena = pd.read_csv(renault_pre+'0'+str(day)+end_quote)\n",
    "            quotes_totf = pd.read_csv(total_pre+'0'+str(day)+end_quote)\n",
    "        else:\n",
    "            continue\n",
    "    else:\n",
    "        date = datetime.strptime('2015-09-'+str(day),'%Y-%m-%d')\n",
    "        if date.weekday() < 5:\n",
    "            trades_edf = pd.read_csv(edf_pre + str(day) + end_trade)\n",
    "            trades_rena = pd.read_csv(renault_pre + str(day) + end_trade)\n",
    "            trades_totf = pd.read_csv(total_pre + str(day) + end_trade)\n",
    "            quotes_edf = pd.read_csv(edf_pre + str(day) + end_quote)\n",
    "            quotes_rena = pd.read_csv(renault_pre + str(day) + end_quote)\n",
    "            quotes_totf = pd.read_csv(total_pre + str(day) + end_quote)\n",
    "        else:\n",
    "            continue\n",
    "    trades_edf['date_delta'] = pd.to_timedelta(trades_edf['date_xl'],unit = 'D') + datetime(1900,1,1)\n",
    "    trades_edf['ts_delta'] = pd.to_timedelta(trades_edf['ts'],unit='s')\n",
    "    trades_totf['date_delta'] = pd.to_timedelta(trades_totf['date_xl'],unit='D')+datetime(1900,1,1)\n",
    "    trades_totf['ts_delta'] = pd.to_timedelta(trades_totf['ts'],unit='s')\n",
    "    trades_rena['date_delta'] = pd.to_timedelta(trades_rena['date_xl'],unit='D')+datetime(1900,1,1)\n",
    "    trades_rena['ts_delta'] = pd.to_timedelta(trades_rena['ts'],unit='s')\n",
    "    quotes_edf['date_delta']= pd.to_timedelta(quotes_edf['date_xl'],unit='D')+datetime(1900,1,1)\n",
    "    quotes_edf['ts_delta'] = pd.to_timedelta(quotes_edf['ts'],unit='s')\n",
    "    quotes_totf['date_delta'] = pd.to_timedelta(quotes_totf['date_xl'],unit='D')+datetime(1900,1,1)\n",
    "    quotes_totf['ts_delta'] = pd.to_timedelta(quotes_totf['ts'],unit='s')\n",
    "    quotes_rena['date_delta'] = pd.to_timedelta(quotes_rena['date_xl'],unit='D')+datetime(1900,1,1)\n",
    "    quotes_rena['ts_delta'] = pd.to_timedelta(quotes_rena['ts'],unit='s')\n",
    "    trades_edf = trades_edf[trades_edf['lastFtxt'] == 'normal']\n",
    "    trades_totf = trades_totf[trades_totf['lastFtxt'] == 'normal']\n",
    "    trades_rena = trades_rena[trades_rena['lastFtxt'] == 'normal']\n",
    "    trades_edf = trades_edf.reset_index()\n",
    "    del trades_edf['index']\n",
    "    trades_totf = trades_totf.reset_index()\n",
    "    del trades_totf['index']\n",
    "    trades_rena = trades_rena.reset_index()\n",
    "    del trades_rena['index']\n",
    "    quotes_edf = quotes_edf[quotes_edf['ts'] >= trades_edf['ts'][0]]\n",
    "    quotes_edf = quotes_edf[quotes_edf['ts'] <= trades_edf['ts'][len(trades_edf)-1]]\n",
    "    quotes_totf = quotes_totf[quotes_totf['ts'] >= trades_totf['ts'][0]]\n",
    "    quotes_totf = quotes_totf[quotes_totf['ts'] <= trades_totf['ts'][len(trades_totf)-1]]\n",
    "    quotes_rena = quotes_rena[quotes_rena['ts'] >= trades_rena['ts'][0]]\n",
    "    quotes_rena = quotes_rena[quotes_rena['ts'] <= trades_rena['ts'][len(trades_rena)-1]]\n",
    "    edf_trades.append(trades_edf)\n",
    "    edf_quotes.append(quotes_edf)\n",
    "    total_trades.append(trades_totf)\n",
    "    total_quotes.append(quotes_totf)\n",
    "    renault_trades.append(trades_rena)\n",
    "    renault_quotes.append(quotes_rena)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3. Overview\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Number of selected trades per day.**\n",
    "\n",
    "For each stock, we plot the number of selected trades per day, as well as its average on the sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**** EDF ****\n"
     ]
    },
    {
     "data": {
      "image/png": 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bmMpt9KqecwCIiHXAukHFjzHE2UYR8TxwyTDbWQ+sr6UtZhNty85e1t66KxvGmAO9ff2svXUXQMOPb09VqxcvePlvkrTNmMbqxQvq2KqpwZ+QNhslj283nmWLOtmw/Cw629sQ0NnexoblZzmsx0FNRw5mrcTj241p2aJOh8EE8JGD2Sh5fNtaicPBbJRWL15A24yBV3bx+LZNVR5WMhul8tBFNsfwLJ3tbaxevMBDGjYlORzMxqA8vl0qlbjyPd31bo7ZhPGwkpmZFTgczMyswOFgZmYFDgczMytwOJjZuPG1p6YOn61kZuPC156aWnzkYGbjwteemlocDmY2LnztqanF4WBm48LXnppaHA5mNi587ampxRPSZjYufO2pqcXhYGbjxteemjo8rGRmZgUOBzMzK/CwUoPasrOXjdt2s6+vn1keuzWzSeZwaEADPmmKP2lqZpPPw0oNyJ80NbN6czg0IH/S1MzqzeHQgPxJUzOrN4dDA/InTc2s3jwh3YDynzT12UpmVg8OhwZV/qSpmVk9eFjJzMwKHA5mZlbgcDAzswKHg5mZFTgczMyswOFgZmYFDgczMytwOJiZWYHDwczMCmoKB0ntkm6R9E+SHpH0FkmnStou6dH0+5S0riR9VtIeSQ9KelNuOyvS+o9KWlHrTpmZWW1qPXL4DPCtiPgN4A3AI8Aa4K6ImA/cle4DXATMTz+rgGsBJJ0KrAPOAc4G1pUDxczM6qPqcJD0KuB3gOsAIuKFiOgDlgI3ptVuBJal20uBL0fmbqBd0muBxcD2iDgYEc8A24El1bbLzMxqV8uF934V+CnwJUlvAO4HPgx0RMR+gIjYL+k1af1OYG+ufk8qG668QNIqsqMOOjo6KJVKVTX88OHDVddtBe6fytxHI3P/VNbofVRLOEwH3gRcGRH3SPoMLw8hDUVDlMUI5cXCiE3AJoCurq7o7u4eU4PLSqUS1dZtBe6fytxHI3P/VNbofVTLnEMP0BMR96T7t5CFxYE0XET6/VRu/Tm5+rOBfSOUm5lZnVQdDhHxE2CvpPLXk10A/AjYCpTPOFoB3J5ubwUuT2ctnQscSsNP24ALJZ2SJqIvTGVmZlYntX7Zz5XAVyXNBB4D/pAscDZLWgk8CVyS1r0DeCewB/hFWpeIOCjpk8C9ab2rIuJgje0yM7Ma1BQOEfEA0DXEoguGWDeAK4bZzvXA9bW0xczMxo8/IW1mZgUOBzMzK3A4mJlZQa0T0mZm42LLzl42btvNvr5+ZrW3sXrxApYtGvLzsDYJHA5mVndbdvay9tZd9B85BkBvXz9rb90F4ICoE4eD2RTVTO/EN27b/VIwlPUfOcbGbbsbts1TncPBbApqtnfi+/r6x1RuE88T0mZT0EjvxBvRrPa2MZXbxHM4mE1BzfZOfPXiBbTNmDagrG3GNFYvXjBMDZtoDgezKajZ3okvW9TJhuVn0dnehoDO9jY2LD+rIYfAWoXnHMymoNWLFwyYc4DGfye+bFGnw6CBOBzMpqDyi2yznK1kjcfhYDZF+Z241cJzDmZmVuBwMDOzAoeDmZkVOBzMzKygeSekd++G7u6qqr6xrw/a28e3PVOI+6cy99HI3D+VNXof+cjBzMwKmvfIYcECKJWqqvpAqUR3lUcdrcD9U5n7aGTun8rq1kfSqFZr3nAwayLNdPlsM3A4mE24Zrt8thl4zsFswjXb5bNtYm3Z2ct5V+9gV+8hzrt6B1t29ta7SUPykYPZBGu2y2fbxBlwFDmnsY8ifeRgNsGa7fLZNnGa6SjS4WA2wZrxi2zKQx/z1nyzoYc+mk0zHUV6WMlsgjXb5bM9gT5xZrW30TtEEDTiUaTDwWwSNNPls0ca+miWfWhUzfQlTA4HMxugmYY+ajXZnz/JH0XCs3Q28FGkw8HMBmimoY9a1Gv4rHwUWSqVuPI93RP2OLXyhLSZDdCME+jVaKYzh+rBRw5mNkCzTaBXq5WGz6rhcDCzgmaaQK9WqwyfVcvDSmbWklpl+KxaPnIws5bUKsNn1XI4mFnLaoXhs2rVPKwkaZqknZK+ke7Pk3SPpEclfV3SzFT+inR/T1o+N7eNtal8t6TFtbbJzMxqMx5zDh8GHsnd/xRwTUTMB54BVqbylcAzEfE64Jq0HpIWApcCrweWAF+QNHAg0MzMJlVN4SBpNvAu4K/TfQHnA7ekVW4ElqXbS9N90vIL0vpLgZsj4pcR8TiwBzi7lnaZmVltap1z+DTwH4CT0v3TgL6IOJru9wDlAb1OYC9ARByVdCit3wncndtmvs4AklYBqwA6OjoojfE7pPv6j3Dg0POcMvNF/sfNf0/HycfT3jZjTNtoBYcPHx5z37Ya99HI3D+VNXofVR0Okt4NPBUR90vqLhcPsWpUWDZSnYGFEZuATQBdXV0xli/n3rKzl7V37aL/yHH8+Vkv8le7jqNtxjE2LF/oCalBSv5y+IrcRyNz/1TW6H1Uy7DSecDvSXoCuJlsOOnTQLukcujMBval2z3AHIC0/GTgYL58iDrjxh+VNzMbvarDISLWRsTsiJhLNqG8IyLeA3wbuDittgK4Pd3emu6Tlu+IiEjll6azmeYB84EfVNuu4fij8mZmozcRn3P4KHCzpL8EdgLXpfLrgL+RtIfsiOFSgIh4WNJm4EfAUeCKiDhW3Gxt/FF5Mxsvk32p73oYl3CIiBJQSrcfY4izjSLieeCSYeqvB9aPR1uG00xfsmGj0wr/oNA6+9ksWuWb8lrm2krLFnWyYflZdKYjhc72NjYsP2tK/TFbSfkftLevn+Dlf9Cp9l3HrbKfzaRV5i9bJhwgC4jvrTmfszpP5ntrzncwNLFW+Qdtlf1sJq0yf9lS4WBTR6v8g7bKfjaT4eYpp9r8pcPBmlKr/IO2yn42k1a51LfDwZpSq/yDtsp+NpP8/KWYuvOXvmT3KPmMkcbSKtfib5X9bDatcKlvh8MoNNupa80UZLW0tRX+QaF19tMai4eVRqGZzhhpplMfm6mtZq3G4TAKzXTGSDMFWTO11azetuzs5byrdzBvzTc57+odE/4myuEwCs10xkgtQVZ+8u3qPTQpT75mCl2zeqrHUbbDYRSa6YyRaoMs/+SDyXny1St0J/sdmFmt6nGU7XAYhWY6da3aIKv1yVfNC249QtfzHNaM6nGU7bOVRqlZzhip9tTHWoejqjmbqx6naY4Ugs3w97XWVI+rSjscpqBqgqyWJ18tL7iTHbqe57BmVI+rSntYyYDahnia6QW3mU4uMCurx9C2jxwMGDjEA8/SOYYhnmb6IiV/r4c1q8k+yvaRg72k2kuaN9PZXM10coFZPfnIwWrWbNf/aZaTC8zqyeFg48IvuGZTi4eVzMyswOFgZmYFDgczMytwOJiZWYHDwczMChQR9W5DVST9FPhxldVPB54ex+ZMNe6fytxHI3P/VFavPjojIl5daaWmDYdaSLovIrrq3Y5G5f6pzH00MvdPZY3eRx5WMjOzAoeDmZkVtGo4bKp3Axqc+6cy99HI3D+VNXQfteScg5mZjaxVjxzMzGwEDgczMytouXCQtETSbkl7JK2pd3sajaQnJO2S9ICk++rdnkYg6XpJT0l6KFd2qqTtkh5Nv0+pZxvraZj++bik3vQ8ekDSO+vZxnqSNEfStyU9IulhSR9O5Q39HGqpcJA0Dfg8cBGwELhM0sL6tqohvT0i3tjI52BPshuAJYPK1gB3RcR84K50v1XdQLF/AK5Jz6M3RsQdk9ymRnIU+POI+E3gXOCK9LrT0M+hlgoH4GxgT0Q8FhEvADcDS+vcJmtwEfFd4OCg4qXAjen2jcCySW1UAxmmfyyJiP0R8cN0+1ngEaCTBn8OtVo4dAJ7c/d7Upm9LIA7Jd0vaVW9G9PAOiJiP2T//MBr6tyeRvRBSQ+mYaeGGjKpF0lzgUXAPTT4c6jVwkFDlPlc3oHOi4g3kQ29XSHpd+rdIGtK1wK/BrwR2A/8VX2bU3+STgT+Dvh3EfHzerenklYLhx5gTu7+bGBfndrSkCJiX/r9FHAb2VCcFR2Q9FqA9PupOrenoUTEgYg4FhEvAv+TFn8eSZpBFgxfjYhbU3FDP4daLRzuBeZLmidpJnApsLXObWoYkk6QdFL5NnAh8NDItVrWVmBFur0CuL2ObWk45Re95Pdp4eeRJAHXAY9ExH/LLWro51DLfUI6nVL3aWAacH1ErK9zkxqGpF8lO1oAmA58zf0Dkm4CuskusXwAWAdsATYDvwI8CVwSES05KTtM/3STDSkF8ATwJ+Xx9VYj6W3APwK7gBdT8X8km3do2OdQy4WDmZlV1mrDSmZmNgoOBzMzK3A4mJlZgcPBzMwKHA5mZlbgcDAzswKHg5mZFfx/W+tOcfc+BEoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "****************\n",
      "**** Renault ****\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "****************\n",
      "**** Total ****\n"
     ]
    },
    {
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kKZ7NwsHBzBpuJE3xbBYODmbWcCNpimezqBkcJB0h6T5Jv5G0UdIXU/pkSfdKelzSjySNTemvSp870/ZJFcdamtI3S5pTkT43pXVKWjL0l2lmRTZ/ZjtXnj2d9rZWBLS3tXLl2dM9GN1A9cxWegE4IyK6JY0Bfinpp8B/Ba6OiJWSvglcCFybfu6KiJMkLQC+DPxHSdOABcDJwHjgf0n6q3SOa4B3A9uA+yWtjojHhvA6zazgylM8rRhqthwi050+jkmvAM4AbknpNwLz0/t56TNp+zslKaWvjIgXIuIJoBM4Jb06I2JLRLwIrEz7mplZg9R1n4OkFuBB4CSyv/J/C+yOiP1pl21AOeS3A1sBImK/pD3AcSn9norDVubZ2iP91F7KsQhYBDBu3DhKpVI9xc/p7u4ecN5m4PqpzXXUN9dPbUWvo7qCQ0QcAGZIagNuA95Ubbf0U71s6y29WuslqqQRESuAFQCzZs2Kjo6Ovgvei1KpxEDzNgPXT22uo76NlPpp5F3ZRa+jft0hHRG7JZWA04A2SYen1sMEYHvabRswEdgm6XDgaGBnRXpZZZ7e0s3MDgnfld23emYrnZBaDEhqBd4FbALuBs5Juy0Ebk/vV6fPpO3rIiJS+oI0m2kyMAW4D7gfmJJmP40lG7RePRQXZ2bWm8HclV1+1OfkJT8p9KM+B6OelsOJwI1p3OEw4OaIuEPSY8BKSVcA64Hr0v7XAd+T1EnWYlgAEBEbJd0MPAbsBy5K3VVIuhhYC7QA10fExiG7QjOzKgZ6V3aztDhqBoeIeASYWSV9C9lMo57pfwI+0MuxlgHLqqSvAdbUUV4zsyExvq2VriqBoNZd2X21OEZTcPAd0mbWlAZ6V3azrAPl4GBmTWmgd2U3yzpQfp6DmTWtgdyVvXjO1IPGHGB0rgPl4FCnZnlKlZn1rfJRn6P594GDQx2aZXaCmdWnGdaB8phDHfyUKjNrNg4OdWiW2QlmZmXuVqrDQOdDD4bHOMyskdxyqMNwP6WqPMbRtXsfwStjHKPxFn0zKyYHhzoM91OqPMZhZo3mbqU6DefsBI9xmFmjueVQQM1yB6aZFZeDQwEN9xiHmVlP7lYqoGa5A9PMisvBoaCa4Q5MMysudyuZmVmOg4OZmeW4W+kQ853OZjYSOTgcQl7N1cxGqpEbHDZvho6OAWWdsXs3tLUNbXmqeP3vdvOd/Qdy6WNvaoHXH/rzD9Rw1c9I5jrqm+untqLXkcccDqEXqwSGvtLNzIpi5LYcpk6FUmlAWR8ulegYYKujPy5Zvq7qaq7tba38askZh/z8AzVc9TMSlceQFkzcy8qtR3kMqRf+DtXWsDqS6trNLYdDyHc6jy6Vq+WCV8u10c3B4RAa7tVc7dDyarnWTGp2K0maCHwXeB3wMrAiIr4m6QvAR4A/pF0/GxFrUp6lwIXAAeCTEbE2pc8Fvga0AN+OiOUpfTKwEjgWeAg4PyJeHKqLbCTf6Tx6eLVcayb1tBz2A5dExJuA04CLJE1L266OiBnpVQ4M04AFwMnAXOAbkloktQDXAGcB04BzK47z5XSsKcAussBiViheLdeaSc3gEBFPR8RD6f1eYBPQ15/C84CVEfFCRDwBdAKnpFdnRGxJrYKVwDxJAs4Abkn5bwTmD/SCzA4VjyFZM+nXbCVJk4CZwL3AbOBiSRcAD5C1LnaRBY57KrJt45VgsrVH+qnAccDuiNhfZf+e518ELAIYN24cpQHOVuru7h5w3mbg+qmuDbjybS3s2PMSx4yFpTNeZtzRY2nb8zil0uONLl6h+DtUW9HrqO7gIOlI4MfApyPiOUnXAl8CIv38CvAhoNo8qaB6KyX62D+fGLECWAEwa9asGOg0sJKn2fXJ9VNbqVTi711HvfJ3qLai11FdwUHSGLLAcFNE3AoQETsqtn8LuCN93AZMrMg+Adie3ldLfxZok3R4aj1U7m9mZg1Qc8whjQlcB2yKiK9WpJ9Ysdv7gUfT+9XAAkmvSrOQpgD3AfcDUyRNljSWbNB6dUQEcDdwTsq/ELh9cJdlZmaDUU/LYTZwPrBB0sMp7bNks41mkHUBPQl8FCAiNkq6GXiMbKbTRRFxAEDSxcBasqms10fExnS8S4GVkq4A1pMFIzNrEK8mbDWDQ0T8kurjAmv6yLMMWFYlfU21fBGxhWw2k5k1mFcTNvAd0mbWg+8ENxjJC++Z2SHhO8GLabi7+txyMLOD+E7w4qlc9DEYnkUfHRzM7CC+E7x4GtHV524lMztIuavCs5WKoxFdfQ4OZpbj1YSLZXxba9UHhx3Krj53K5mZFVwjuvrccjAzK7hGdPU5OJiZjQDD3dXnbiUzM8txcDAzsxwHBzMzy3FwMDOzHAcHMzPLcXAwM7McBwczM8txcDAzsxwHBzMzy/Ed0tZQflaxWTE5OFjD+FnFZsXlbiVrGD+r2Ky43HKwhmmmZxW7+8xGGrccrGGa5VnFjXj+r9lgOThYwzTLs4rdfWYjUc3gIGmipLslbZK0UdKnUvqxku6U9Hj6eUxKl6SvS+qU9Iikt1Qca2Ha/3FJCyvS3yppQ8rzdUk6FBdrxTJ/ZjtXnj2d9rZWBLS3tXLl2dNHXXdLM3Wf2ehRz5jDfuCSiHhI0lHAg5LuBD4I3BURyyUtAZYAlwJnAVPS61TgWuBUSccClwGzgEjHWR0Ru9I+i4B7gDXAXOCnQ3eZVlTN8KziRjz/12ywarYcIuLpiHgovd8LbALagXnAjWm3G4H56f084LuRuQdok3QiMAe4MyJ2poBwJzA3bXtNRPw6IgL4bsWxbIRYtb6L2cvXMXnJT5i9fJ370ys0S/eZjS7Kfh/XubM0CfgF8GbgdxHRVrFtV0QcI+kOYHlE/DKl30XWougAjoiIK1L6PwP7gFLa/10p/W+BSyPifVXOv4ishcG4cePeunLlyn5ebqa7u5sjjzxyQHmbQX/rZ/e+l+jatY+XK75Lh0m0H9NKW+uYQ1HEP593x54/8eKBlxnbchjjjj7ikJ6v0kDqqFFlbQT/H6utUXV0+umnPxgRs2rtV/dUVklHAj8GPh0Rz/UxLFBtQwwgPZ8YsQJYATBr1qzo6OioUerqSqUSA83bDPpbP7OXr6Nrd0suvb2thV8tqf84/bFqfRdL79rAvpcOo9wAbh1zgCvPnjYs3VT+DvXN9VNb0euortlKksaQBYabIuLWlLwjdQmRfj6T0rcBEyuyTwC210ifUCXdRohGDLh6BpDZoVXPbCUB1wGbIuKrFZtWA+UZRwuB2yvSL0izlk4D9kTE08Ba4ExJx6SZTWcCa9O2vZJOS+e6oOJYNgI04n4FzwAyO7TqaTnMBs4HzpD0cHq9B1gOvFvS48C702fIZhttATqBbwH/CBARO4EvAfen1+UpDeDjwLdTnt/imUojSiMGXJvlBjqzRqk55pAGlnsbYHhnlf0DuKiXY10PXF8l/QGyQW4bgcp9/MO5PMTiOVMPWrQPPAPIbCh5bSUbEsN9v0IjApJZM3FwsBGrGW6gAy/aZ43h4GBWYH7mhTWKF94zKzBP2bVGcXAwKzBP2bVGcXAwKzBP2bVGcXAwKzAv2meN4gFpswLzlF1rFAcHs4Jrlim7VizuVjIzsxwHBzMzy3FwMDOzHAcHMzPL8YC0NR2vVWRWm4ODNRWvVWRWH3crWVPxWkVm9XFwsKbitYrM6uPgYE3FaxWZ1cfBwZqK1yoyq48HpK2peK0is/o4OFjT8VpFZrW5W8nMzHIcHMzMLMfBwczMcmoGB0nXS3pG0qMVaV+Q1CXp4fR6T8W2pZI6JW2WNKcifW5K65S0pCJ9sqR7JT0u6UeSxg7lBVr9Vq3vYvbydWzo2sPs5etYtb6r0UUyswapp+VwAzC3SvrVETEjvdYASJoGLABOTnm+IalFUgtwDXAWMA04N+0L8OV0rCnALuDCwVyQDUx5WYmudDNYeVkJBwiz5lQzOETEL4CddR5vHrAyIl6IiCeATuCU9OqMiC0R8SKwEpgnScAZwC0p/43A/H5egw0BLythZpUGM5X1YkkXAA8Al0TELqAduKdin20pDWBrj/RTgeOA3RGxv8r+OZIWAYsAxo0bR6lUGlDBu7u7B5x3tFowcS9MzN6Pa4VLppf/Sfa6rqrwd6hvrp/ail5HAw0O1wJfAiL9/ArwIUBV9g2qt1Cij/2riogVwAqAWbNmRUdHR78KXVYqlRho3tHqc8vX/blL6ZLp+/nKhuyr0d7WyifO62hgyYrJ36G+uX5qK3odDWi2UkTsiIgDEfEy8C2ybiPI/vKfWLHrBGB7H+nPAm2SDu+RbsPMy0qYWaUBBQdJJ1Z8fD9Qnsm0Glgg6VWSJgNTgPuA+4EpaWbSWLJB69UREcDdwDkp/0Lg9oGUyQZn/sx2rjx7Ou1pAbr2tlauPHu67yQ2a1I1u5Uk/RDoAI6XtA24DOiQNIOsC+hJ4KMAEbFR0s3AY8B+4KKIOJCOczGwFmgBro+IjekUlwIrJV0BrAeuG7Krs34pLytRKpXclWTW5GoGh4g4t0pyr7/AI2IZsKxK+hpgTZX0LbzSLWVmZgXgO6TNzCzHwcHMzHIcHMzMLMfBwczMchwczMwsx8HBzMxyHBzMzCzHwcHMzHIcHMzMLMfBwczMchwczMwsZzAP+7GCWrW+i6vWbmb77n2Mb2tl8ZypXl3VzPrFwWGUKT8LuvzIz/KzoAEHCDOrm7uVRhk/C9rMhoKDwyizPT3qs950M7NqHBxGmfHpSW71ppuZVePgMMr4WdBmNhQ8ID3KlAedPVvJzAbDwWEUKj8L2sxsoNytZGZmOQ4OZmaW4+BgZmY5Dg5mZpbj4GBmZjmKiEaXYUAk/QF4aoDZjweeHcLijDaun9pcR31z/dTWqDp6Q0ScUGunERscBkPSAxExq9HlKCrXT22uo765fmoreh25W8nMzHIcHMzMLKdZg8OKRheg4Fw/tbmO+ub6qa3QddSUYw5mZta3Zm05mJlZHxwczMwsp+mCg6S5kjZL6pS0pNHlKRpJT0raIOlhSQ80ujxFIOl6Sc9IerQi7VhJd0p6PP08ppFlbKRe6ucLkrrS9+hhSe9pZBkbSdJESXdL2iRpo6RPpfRCf4eaKjhIagGuAc4CpgHnSprW2FIV0ukRMaPIc7CH2Q3A3B5pS4C7ImIKcFf63KxuIF8/AFen79GMiFgzzGUqkv3AJRHxJuA04KL0e6fQ36GmCg7AKUBnRGyJiBeBlcC8BpfJCi4ifgHs7JE8D7gxvb8RmD+shSqQXurHkoh4OiIeSu/3ApuAdgr+HWq24NAObK34vC2l2SsC+JmkByUtanRhCmxcRDwN2X9+4LUNLk8RXSzpkdTtVKguk0aRNAmYCdxLwb9DzRYcVCXNc3kPNjsi3kLW9XaRpH/f6ALZiHQt8EZgBvA08JXGFqfxJB0J/Bj4dEQ81+jy1NJswWEbMLHi8wRge4PKUkgRsT39fAa4jawrzvJ2SDoRIP18psHlKZSI2BERByLiZeBbNPn3SNIYssBwU0TcmpIL/R1qtuBwPzBF0mRJY4EFwOoGl6kwJL1a0lHl98CZwKN952paq4GF6f1C4PYGlqVwyr/0kvfTxN8jSQKuAzZFxFcrNhX6O9R0d0inKXX/CrQA10fEsgYXqTAk/SVZawHgcOAHrh+Q9EOgg2yJ5R3AZcAq4Gbg9cDvgA9ERFMOyvZSPx1kXUoBPAl8tNy/3mwkvR3438AG4OWU/FmycYfCfoeaLjiYmVltzdatZGZmdXBwMDOzHAcHMzPLcXAwM7McBwczM8txcDAzsxwHBzMzy/n/Dyr5xZ1Np9YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('**** EDF ****')\n",
    "numb_trades_edf = np.zeros(len(edf_trades))\n",
    "for i in range(len(edf_trades)):\n",
    "    numb_trades_edf[i] = len(edf_trades[i])\n",
    "plt.scatter(range(len(edf_trades)), numb_trades_edf)\n",
    "plt.title('Number of trades EDF')\n",
    "plt.axhline(y = np.mean(numb_trades_edf), color='r')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('****************')\n",
    "\n",
    "print('**** Renault ****')\n",
    "numb_trades = np.zeros(len(renault_trades))\n",
    "for i in range(len(renault_trades)):\n",
    "    numb_trades[i] = len(renault_trades[i])\n",
    "plt.scatter(range(len(renault_trades)), numb_trades)\n",
    "plt.title('Number of trades Renault')\n",
    "plt.axhline(y = np.mean(numb_trades),color='r')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('****************')\n",
    "\n",
    "print('**** Total ****')\n",
    "numb_trades = np.zeros(len(total_trades))\n",
    "for i in range(len(total_trades)):\n",
    "    numb_trades[i] = len(total_trades[i])\n",
    "plt.scatter(range(len(total_trades)), numb_trades)\n",
    "plt.title('Number of trades Total')\n",
    "plt.axhline(y = np.mean(numb_trades), color = 'r')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Number of quotes per day.**\n",
    "\n",
    "For each stock, we plot the number of selected lines of the quote file per day, as well as its average on the sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**** EDF ****\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "****************\n",
      "**** Renault ****\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "**************\n",
      "**** Total ****\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('**** EDF ****')\n",
    "numb_quotes = np.zeros(len(edf_quotes))\n",
    "for i in range(len(edf_quotes)):\n",
    "    numb_quotes[i] = len(edf_quotes[i])\n",
    "plt.scatter(range(len(edf_quotes)),numb_quotes)\n",
    "plt.title('Number of quote lines EDF')\n",
    "plt.axhline(y=np.mean(numb_quotes),color='r')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('****************')\n",
    "\n",
    "print('**** Renault ****')\n",
    "numb_quotes = np.zeros(len(renault_quotes))\n",
    "for i in range(len(renault_quotes)):\n",
    "    numb_quotes[i] = len(renault_quotes[i])\n",
    "plt.scatter(range(len(renault_quotes)), numb_quotes)\n",
    "plt.title('Number of quote lines Renault')\n",
    "plt.axhline(y = np.mean(numb_quotes),color = 'r')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('**************')\n",
    "\n",
    "print('**** Total ****')\n",
    "numb_quotes = np.zeros(len(total_quotes))\n",
    "for i in range(len(total_quotes)):\n",
    "    numb_quotes[i] = len(total_quotes[i])\n",
    "plt.scatter(range(len(total_quotes)),numb_quotes)\n",
    "plt.title('Number of quote lines Renault')\n",
    "plt.axhline(y = np.mean(numb_quotes),color = 'r')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Evolution  of the trade price on the sample.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**EDF**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "edf_price_evol = pd.concat(edf_trades)\n",
    "edf_price_evol = edf_price_evol.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(edf_price_evol['last'],'r--', color = 'r')\n",
    "plt.title('Evolution of the EDF price')\n",
    "plt.xlabel('Time series observations')\n",
    "plt.ylabel('Price')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Renault**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "renault_price_evol = pd.concat(renault_trades)\n",
    "renault_price_evol = renault_price_evol.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BbkA/EekWlax1jkzPYVTHX/7i3jQ6dHDpb7+NmRDxOe00uOqq2vVz8snJeS+9BIcfnl79BQtc2KRJ7eQwjDpMvqakDgY+V9WQn6mh7AXMUdW5qroWeBb4bWTS1TUaNICKimS7S9ngL4YvWhTLSzyf8eSTcPPN2bXvv9k8+2zyvd9m8CfRsaMLV6/OTg7DMPKmME4GngmkzxeRySIyRERahpTvACwIpBd6eUYu6NHDnaXo0yfzunPn1lzm3nszbzcV330Xmj3xjjuyb3P9+uzrGkYdJs2jvtkjIo2Ao4ErvawHgRsA9cI7gD8kVgtpKnTiXUQGAAMAKioqqKqqykrOVatWZV23mMnVuHp54eRnn+XHZ55hY+PGdB4yJOUBumCfvULy0mXTRYvYB/ixUyfGV1X90ta3zZtn3J5f970RI1jXMux3SnFgf4ulRbmOKxRVjfTCTSW9keJeZ2BKSP6+wKhA+krgypr6qqys1GwZM2ZM1nWLmdBxzZqlevTRquPHp9+QW/lQHTIklrdmTSw/8Qqrmw233OLqPvqoS59zjiroe//5T+ZtdexYO1nyRJ36WywDSn1cwARN83mejympfgSmo0SkXeDescCUpBowHugqItt4bygnA2nagjBS8vrr8MADzofEK69Uf0I6kX/+04X+IvO331Z/7uKLL1JOJ2XEFd4GOX+BfuBAqKpibZs2mbfVokUs/sgjMGFC7eUzjDpEpApDRJoAhwIvBrJvE5HPRGQy0Bu42CvbXkRGAqjqeuB8YBQwHXheVadGKWud4PDD4bzzsttWe/nlsGYNbLmlS4cpg4qKWLxLF/eADu7EWrkysz7Hjo3Fly93YePGMTPrmfJ//xeLDxgAe+6ZXTuGUUeJVGGo6mpVba2q3wXyTlPVXVV1N1U9WlW/8vIXq+oRgXIjVXV7Vd1WVW+KUs5ypv6aNe6hPXBgLPOdd1yYybZaEdh001h6q62Sy3z1VfVt/PnP6ff39tswfXosPW9e+nVTcd55yXmTJ4eXveKKeIVlGIad9C53drrJ07UXXRTLzMVp54YN49OVlTUroCeeSK/tH36AXr3grrtiecHDgdki4kyiBOnePaZAg9x6q3uTCbqANYw6jimMMqdJ2Altn9rafjrjDBfWq5fb9QD/TWbmzFje73+fm7YTTaWD8/t9332x9IYNsfiDD+amX8MoA0xhlDmLjzoq9c0vv6xd45995sJMfv1/+218+re/db/8gwf/Ro+OL/PCC/Ge9mrDrrvCJZck519wQSwePNw31ZbODMPHFEY5s3w521X3C7kmf9g1cdttLnz99Vje4MHV10nc3eSf4zj33Fhe4lpIrn1x3HEHfPJJ6vuzZsXiH3yQ274No4QxhVHO+L64E9lzT2cgsGvX2rW/117w0Uewzz6xvKAXv+A0T028+qoLDzwQzj47/t4222QvYyqqU0Kffx6LH3po7vs2jBLFFEZd46ab3EO+adPat7XZZk75BJ0UNWsWiwe3sf761zW39/PP4TuTcmEkMazNoMOnPfaIxU86KRbPxWK7YZQJpjDqEh06wJVX1lyuNjRu7NYANmxwRg5//hnGjYMRI2Jl1q0Lr3vwwdHKlsgmmzjDiOCmqEaMgL33ji9j1m0N4xdMYRQb99/vfv3WxjPcZ5/F/yqfMcOFL78cza/1RBo3jnm4a9TITV0FT1kHz1cECfNVEXxLiYJTTnGn38FNp330Ufz9e+6Jtn/DKCFMYRQb55/vwrBDZuny/PPx6R12cKe7KyuzbzOXzJ/vfIBfdll8fqNG8ekXX8zPttY//Sk57x//iL5fwygxTGEUE8Gpmv/8J/t2fPMdxcann8LOO7uF5E02gdtvj7+/dm18+thj8/NGFMallxamX8MoYkxhFBO5MH8BEDDdvTrMhEehePlld65h//0LLUk8wW20Ps2b518OwyhyTGEUA/Pnu62c22+fm/aee+6X6GT/rEQx4JvZSOdUeOJaQpR07Zp70ymGUYaYwigGOneG7bZLzk+1m6gm/MNwTz/NT8U0PZWu8urUKf+WZIOL20E5i+1tyDAKiCmMYqRLFxd+/33t2vF9VxQLiYvaPkOGxKcLMR3kK4zENZNiUriGUWBMYQB88w31goe48klYv/70SDZ+K4IEt7IWI/6Zh8S3q0KcfTjvPGclN/GgXqEW3Q2jCDGFAdC2LQeE/RrfsAFee809SHLJtGkxZRB23sJ/SNVWYRQjwQdw794wcWLsFHjTpjB8OIwcWRjZgqfUfRK3KBtGHcYURnXceScceaSbIsnVw/udd9zW0htucOkff0wuU9tftR07xtt3KiaCpsNvucX5oxBxp8O//x6OOQZatSqcfIZhpMQURpBEZzk3BRz9PfZY7dt//nnnewFiv6LXr48v45sMh+yU1MqVsHBh8pmGYiGVMgyeDjcMoyiJ7D9URHYQkYmB63sRuUhEbheRGSIyWUSGi0joRLuIzPN8f08UkRx656mGMWPi08EpirPOqn37QaN248a5cMqU+DK77OK8zQ0a5Iz7ZcqyZS6sznx3sfCXvxRaAsMwMiAyhaGqM1W1h6r2ACqB1cBwYDSwi6ruBswCqrOG19tro2dUcsYR/HUPMGpU9H3265ect/POMGBAdh7xVq6svUxRo+p8XiSe9C5W8m0U0TCKlHzNARwMfK6q81X1DVX152E+BDrmSYaaufba+HSiI5/a0jFhqIke73xnPdOmuakbERg6NLM+fPemJ56YnYz5opS2q771VqElMIyioEGe+jkZeCYk/w/AcyH5AAq8ISIKDFLVh8MKicgAYABARUUFVVVVGQvXywu/6tuXmYH6PQcMILhvZu6AAXx1+OGsa9mSpnPnsq55c9YmepCrrp+FC+PS48aOJWhMe/LYsSz/6Sf27tePX94t+vdn6rx5fHPggWn10XTuXPYEpnTrxrKqKlatWpXVZ1Ls5GNc25x6Kp088+f5/AztOystynVcoahqpBfQCFgGVCTkX4WbopIU9dp7YVtgEnBATX1VVlZqVqxerQuOO061qkp12bJYvps8UT3yyFgc3L0mTVQvvTSzfo47Lr6dL76IxS+7THXDhvh+/ev009Pv45NPXJ3hw1VVdcyYMZnJWCLkZVyPPhr/nWfLwoWqTz6punFjWsXtOystSn1cwARN83mejympw4FPVHWpnyEiZwBHAqd4Aiehqou98GucYtkrMgm//56OL7zgFpvbtHFTQUGxwqZ3Vq92vqHTZckSeOGF+LxVq2LxW2+N7RLq3j2+3OOPp9+Pv221fv306xjh5GKjA7ipyFNPTe0y1zBKhHwojH4EpqNEpC9wOXC0qq4OqyAiTUVkMz8O9AGmhJXNCUEXoz7Bbamnn5667mGHpddH8GDgM97H4a9P+D4wfCoq0msTku1NVVY62Y84Iv02jPyQuG3bMEqMSBWGiDQBDgVeDGTfB2wGjPa2zD7klW0vIv4R3wrgXRGZBHwEvKaqr0cmqL9QHGS1p8v23DPZrens2bH4G2+k18cZZ8Ti7du78F//cuGcOfFlTzklvTYHDnT2mWbOjOWJQMOG9oaRaxI3KBhGHSRShaGqq1W1tap+F8jbTlW3Um/Lraqe6+UvVtUjvPhcVe3uXTur6k2p+oiM3Xd3Yfv2cPPN8fduShDnnXdqbs9/i3nooWT/C8GpKQg3c/7uu7BoUfxUmW9z6qmnYnmzZzu7SGE+HozsCXsLNYw6hh2tTcX8+S587bVkg3SJW0LDbBAl8oc/uPDoo2HrrePvrVkTn07sD2DsWDcXPnp08j3fzMiMGfDss85Hda63BNdFGjaMxXOlMIKmUQyjxDCF4fGNb7IjkfPOi5/ygTgHRQBss036HW2yCfTpE5/nKxOfniHnFK+6yoXVGULcaaeYL+oG+doxXcYE14f8E/Tp8sMP7jzN5Mnx+Ymm3A2jhDCF4THt6qvDb3zwgXvIB0l0pZrJr0/fdHdw3WK//eLLNGoU21SbyIwZsfjegVMcb78dX+7NN9OXyaiZMKvC1dG8uTuxn7jjbcCA3MlkGHnGFIaHNmzoTG0n8sQTMYdGPr411b/+Ff74R2dl9bvv4JJLYMcdnd/qRo3g/feT2/MX2Lfd1k0lVVUlP1SCJMo0aVIsP+hK9IEH4ssVq7XaUmV16Ia+1PgbG3z8v6Fbb82NPIZRAGzeIkj37jB9upva8QlbgF6+3IW+LaSff46fathlFxf6bw6prM6meqsJ0rlzfHrePLe+svvu8KtfxfKDfhu6d0+e9jIy5ze/cWtYkNnaww03wOLF8XmHHOJc52ayZdowigx7w0hkhx0yr5POvPTUqeFvHDWRON01fnzs125Ye0cf7d4+zFNc7Xn1Vfj3v118772TpyJTEfb30LGjO7xZW7e7hlFATGEkkupB+8or8N578Xk9eqTX5urV0K0b7Ltv7WTzqc5Pxosvpr5nZE6vXrF4upsbwhSL/51lYh3AMIoMUxjpctRR8VNA4JRIOgwc6HY+3XZbbmTZeefU9+zAXm7JZhvssce6sGtXF+60k5vegth2bcMoQUxhhJFobiPI1KnuV+f69dCuXepywYf63/7m1kYy3WkThm2XzS/BsxjpMny4C33fJK++mp1vE8MoMkxhhNGgATzyCLweYo2kWzfnma9+/eof3u+9F1scBzctleiONV18OUaPdorHyB9bbVX7uhs2QNu2uZHHMAqIKYxUnH12+oYFE6msdPvwE89v3H13du0ddpibAx82DE47LXU5O0UcDZWV6ZddsiQWHz4cbrwRttsu9rfQtGluZTOMPGLzG1Gw++5u8dw/pJcrBg1KzmvSBO67zxnHq2f6PxIy+R6D05Rbbx07oe9PSf34Y+7kMow8Y0+YXPL00y4cPDiW9+ijuWvfXzgNsno1nHkmXHNN7vox4gmuaWXrM93WnowywBRGbbn00lh86tTk+3vuGYt//HHt+vIPkRn5ZfTo2JTSt9/G31u0CI45xr1RBqcc/TcLwygjTGHUln/+MxY/9FD48EMYNSqWt+uubrF70SLYY4/a9ZVoosTID82agefbO8lESMeO8PLLLn7xxbH8c87Jj2yGkUdMYdSWhg2dfaf+/eGAA9yJ4ESzHPXrJ9sWyoagaXN/PeOQQ2rfrlEz/jrGbrtB797Vl91mG+jUKTm/T5/sLAkYRpFgE6u5YLfd4LHHou8nqIh694affkreiWVEQ/Bzrqpy4d//Hl524MDw/NatYe5c5/+kYUNb1zBKjsjeMERkB88Fq399LyIXiUgrERktIrO9sGWK+md4ZWaLyBlhZeocn38ei3ftasoin3zxRXxaxG2ZDSOVt8MttnBm7Zs0iVk8NowSIjKFoaozfTesQCWwGhgOXAH8T1W7Av/z0nGISCvgGmBvYC/gmlSKpU4xYUKhJai7JDq5qo5U52HuuScWr84RlmEUKflawzgY+FxV5wO/BYZ6+UOBY0LKHwaMVtXlqroCGA30zYukxUxlZWrHSka01KuX/pba/v3D84cOjU/bQUujxBDNw8NHRIYAn6jqfSKyUlVbBO6tUNWWCeX/Amyqqjd66b8Da1T1XyFtDwAGAFRUVFQ+++yzWcm4atUqmqXjm7vEsHHllmZz5tAzYQfU4iOP5Mt+/djnlFMAqBozJrSurFvHFmPH0s2bypp14YUsPib595J9Z6VFqY+rd+/eH6tqiF/oEFQ17Qtomkl5r04jYBlQ4aVXJtxfEVLnr8DVgfTfgUtr6quyslKzZcyYMVnXLWZsXBERe9dTnTbN5Z1zjurVV6eus2GDalVVrN7114cWK/jYIsLGVZwAEzTN53laU1Ii8isRmQZM99LdReSBGqr5HI57u1jqpZeKSDuvnXbA1yF1FgJBq28dgcUh5Qwj/3zwQSz+/vsxD40PP+y87aVizZp4/xqHHx6JeIYRFemuYdyFW1f4FkBVJwEHpFm3H/BMIP0K4O96OgN4OaTOKKCPiLT0Frv7eHmGUXiOOy4Wz8QpVqKJc9+UjGGUCGkveqvqgoSsGlfsRKQJcCgQdAN3C3CoiMz27t3ile0pIoO9vpYDNwDjvet6L88wCk/P9KZ7k0g0DrnZZrWXxTDySLoKY4GI/ApQEWnkLUqwLMclAAAgAElEQVTX6JhBVVeramtV/S6Q962qHqyqXb1wuZc/QVXPDpQboqrbeVceTsUZRpr4B/MGDKhdO9dfX3tZDCOPpHvU9FxgINABt77wBnBeVEIZRlGzzTa2tdmok6SlMFR1GXBKxLIYRvnToYMzRLn55s7KrWGUEGkpDBEZClyoqiu9dEvgDlXN4PirYRj897/w2Wdw0EF22tsoOdKdktrNVxYAqrpCRHaPSCbDKF923dVdIi5tU1tGCZHuone9oC0nz9aTmdo0jNry88+FlsAw0ibdh/4dwPsiMsxLnwDcFI1IhlGH2HRTe8swSoZ0F70fF5EJwEGAAL9T1WmRSmYYhmEUFdVOSYlIcy9sBSwBngaeApZ4eYZhZEPwtPjGjYWTwzAyoKY1DN92wcfAhMDlpw3DyIZbbonFly0rnByGkQHVTkmp6pEiIsCBqvplnmQyjPKnc+dYvKICZs+G7bYrmDiGkQ417pLyzN8Oz4MshlF3aNAA7rsvln7kkcLJYhhpku622g9FZM9IJTGMusbJJ8fikyebBz6j6ElXYfTGKY3PRWSyiHwmIpOjFMwwyp7WreGaa1z89dfdgT7DKGLSPYdhnl4MIwquuy4Wn16jAWjDKCg1bavdVEQuwrlM7QssUtX5/pUXCQ2jLjFqFNs+UIMzy2+/hbvuguXmIsbILzW9YQwF1gHv4N4yugEXRi2UYdRZ+vZ1volVY/amEmnTxoWXXGKnxI28UtMaRjdVPVVVBwHHA/vnQSbDMObNK7QEpccll6RWskZOqElhrPMjqro+08ZFpIWIDBORGSIyXUT2FZHnRGSid80TkYkp6s7zFtcnemZJDKP8uOyy8PyHHgrP9739GcncdZcLTWlERk0Ko7uIfO9dPwC7+XER+T6N9gcCr6vqjkB3YLqqnqSqPVS1B/AC8f6+E+ntlc3SibJhFDm33AJ77ZWcf9tt4eUvuig+vWJFLH7PPdC0ae5kKxVWrDAlkSeqVRiqWl9Vm3vXZqraIBBvXl1dzw7VAcCjXltrgz41vBPkJwLP1H4YhlGiiMCHH7ozGEcdlXn9jz5y4WmnwYUXwurVdc82Vb0Uj7GpU91naibkc0a65zCyoQvwDfCYiHwqIoNFJPjzZ39gqarOTlFfgTdE5GMRGRChnIZRWETcQ+/NN6svNy3EQHTfvrB+PTz5ZCxv3brkcuVMmOfC//4Xhg6FV1+Fzz/Pv0xlSpROkBoAewAXqOo4ERkIXAH83bvfj+rfLvZT1cUi0hYYLSIzVHVsYiFPmQwAqKiooKqqKithV61alXXdYsbGVTrs27gxm6xZ80s6cXxt33yTbl582X770ea99wD46qijaBco9+7rr7N+882jFTYLovrOWr/3HklHHo844pfour335r0RI3Ler085/i2mRFUjuYAtgXmB9P7Aa168AbAU6JhmW9cCf6mpXGVlpWbLmDFjsq5bzNi4SogHHlB1G2XdlcjEibF7338fix96aHy9pUvzL3saRPadDRkSP/6wK0JK/W8RmKBpPtcjm5JS1SXAAhHZwcs6GPDfqQ8BZqjqwrC6ItJURDbz40AfYEpUshpGUbBoUSzep0/y/b59Y/HNNnPhTjvB6NHx5Tp0yL1sxUzXruH5W2yRXznqAFGuYQBcADzl2Z3qAdzs5Z9MwnSUiLQXkZFesgJ4V0QmAR/h3kxej1hWwygs110HPXuyrnlzWLw4+f6SJS487bRYXpg5kfUZ74AvbVql8OW2xx75laMOEKnCUNWJqtpTVXdT1WNUdYWX319VH0oou1hVj/Dic1W1u3ftrKrmP9wof+rXh/HjWdWlC0yZAj/+GH/ftzv1t7+5cN994Xe/C29r/Xq3ZXf16ujkrYnvvoMLLoCffoq2nw8+CM8fNSrafusgUb9hGIaRIS0nemdZmzWLv/HNN7Djju4CmDEDXnwxZvE2SMOGcOWVcOON0QpbHddd53x+DB4cy1u2DL74Irf9fPxxzWXMdHxOMIVhGKXCggWw6aax9KGHQtu2sTePMLtSTz2VH9nCWLs2Oa9DB+jSJXd9jBgBDz7o4osXuzMo+4dYMBo50ikrc4dbK0xhGEaRsfC442IJEZg1y8Vfe829Vfg8/zx8/XX1jX1ZQM/KnTq5sKIilhemRGrD0UfH4k2bus/rkEOSy/Xr5xbBbSG8VpjCMIwiY87558dn7OBtNFy/Pn494LDDam7s9ttzJ1imXHih+0V/zDEANA8ePIzCym5zz/hEcCOAb0olcT3IyApTGIZRjHTvXnOZzp2T8157LT69ZwE9K9evD5dfDrvsAt99xx7nnRe7F+XUUNCfyJ13RtdPHcQUhmEUI5Mmxae/+Sa5zF//mpzXsGF8epNNcidTptx2Gzz6qJtSa9Ei/l6UCqNlS/d5jR1rRglzjCkMwyhG9t03Pu0v7AY555xY/Pe/d+HWW8eXmVLA866zU5mJw3kNjLKvNm3CF7+NWmEKwzCKkcSzBf68fHABecyYWNw/vLb99nDwwfDIIy5dSEOE1a1TPP44fJ+Oh4Q02W673LVlpMQUhmGUAv7D9frrY3lB50tffeVCEWf19thjXbqQp76rO/vQrRtsvjl4BhQj5bPP4tOPPRZ9n2WKKQzDKEYS5/hHelZzBgQs/V95ZSx+8cXx5Rt4hqgXLMi87w0bMttVtHBhcvlZs+CJJ8LLv/ACTJ6cvXyZEjw4CIU9m1LimMIwjGIklQ+H4K/l4ELy3nvHl/MXv7PZVnvaacmnzFPx00+w1VZwwAGxvP/8J7YVOJHdd4fjjov9yk9VLpckvlE8/XT0fZYppjAMoxjx5+T794/Pf//98PINElzbBE+EZ8oznl3QdM5KNG7swk8+cUpj3To48cTU5YNrMJAf74Dt27twn31cOHiw88J32211z9lULTGFYRjFSKtWsHKl25YaJLgzCuCSS+Dhh5Prp3JbmglLl2ZW/p13wk9ZB7n66vj02CSfaJnRsWPNC94nneTCDz904VVXuam9yy+PbQ4oFt59153gL1JMYRhGsbL55skP/sT0HXckKxGfpUuzs1br77j64gt3nuGee9I/mZ1KAahSNWYM7LefOyfh45/OzpbOnZO3EoeVSeTxx10YPExYDOy/v1NwI0fm3khjDjCFYRilQq9emZVv2za78w7Ll7vw88/hlFOciQ9/kTob+vWLTwfPR9xyS/btgvtF/tZb1ZfxnVHdc0/t+sonv/lNbo005ghTGIZRKgTPXaRDnz5w8snZ9/f22zFvfole/cCtA6RD27bx6VdeicXnzMlOtkzwT7vXZKjRqBFTGIZR7DRpkl290aNrd84huB01zAxJumc8Es2VJBKFIcIgrVvDihUxM/CJrFoVbf9lhCkMwyh2lixxD7woWbMGhg2Ld/+ayDvvxKeDdqp23vkXq7RJJO7gSqS201Lp0KJF6o0AUX+26ZKPHWO1JFKFISItRGSYiMwQkekisq+IXCsii0RkoncdkaJuXxGZKSJzROSKKOU0jKJms82Sjfelw6WXOh8R1fHKK+4X9sUXwwknwJNPpi77wgvx6auucuGQIc5m1Usvxe4FbV+1aVO9DH/7Gxx4YHqe86KgNluQc0nYyfh8TNllQNRvGAOB11V1R6A74Buqv0tVe3jXyMRKIlIfuB84HOgG9BORbhHLahjlxTffuBPYK1eG3580CX77W7jpJpg7t+b2/G2pPrfd5sI1a5LLBtdOgg6hINyPx9ixzt1s1ITtmCpm960zZxZagjgiUxgi0hw4AHgUQFXXqmqKv9wk9gLmqOpcVV0LPAv8NhpJDaNM6dDBhalMifvOmG65peY3EYiZWF++PN5z3gknJJdt0cIpgOHDkx/SiYf3fG6+uWYZEmnfHn71q/TLf/FF/M6xe+5xb3DFQP36znhkkDlzol/jyYAaJhdrRRfgG+AxEekOfAxc6N07X0ROByYAl6pq4iRiByBoZGYhkGD7wCEiA4ABABUVFVRVVWUl7KpVq7KuW8zYuEqPXI2t48qVbAd8/MYb/LBwYdL9To8/zjZe/Pvp0wk7EfFjp040nT/fJebO5dN772X3P/+Zn9u0wV/BqJo6FYC9OnakiddPVVVV7LyFNxZ/XFt07szOKWQe9+STrOnYMe0x9mzcmJ+AKRl8XvXWrsU3ZPKpKquqqtiQjsJMQS7/Fluffjq7Bg43Ln3lFSouuogvTzqJueeem5M+aoWqRnIBPYH1wN5eeiBwA1AB1Me93dwEDAmpewIwOJA+Dbi3pj4rKys1W8aMGZN13WLGxlV65GxsI0aogur48eH3r77a3YdYWf866CDV7bdXXbZMddiw+HuJl89TTyXnhY3rhx9StzVoUGZjrKa/lGzcmHoMWZCz72vDBtWXXgr/XBo3zk0fIQATNM3nepRrGAuBhao6zksPA/ZQ1aWqukFVNwKP4KafwupuFUh3BBZHKKthlB+NGrkwOH0UZN68WHyvveLNkAwc6ObPW7d2axCpnBHtvnss7hsS7NSpermaNXMnvLfdNvlePsyxi8D//gd9+0bfVyasW+d2mt18c/K6z5o1sbUW35Pg/Pl5Pw0emcJQ1SXAAhHxzVEeDEwTkXaBYscCYS7BxgNdRWQbEWkEnAy8ElLOMIxUdO7sTmmnWjMIevV7910466xYevPN48umshH16qux+E47wUEHJfsVD+O77+B3v0vOz7UnvlQcdFDsfEvPnvnpMxOuuSY5b9AgFx54oAs7d877afCod0ldADwlIpOBHsDNwG0i8pmX1xu4GEBE2ovISABVXQ+cD4zC7ax6XlWnRiyrYZQX228Pd98d/kse4rfqBn/Rbr21M1kepGvX8DZ8S7DgHsD/+587k5EOBx+c/MDbZpvwslHg78pK9QaWb4KL22EL8eedF+6lcGTSRtPIiFRhqOpEVe2pqrup6jGqukJVT1PVXb28o1X1K6/sYlU9IlB3pKpur6rbqupNUcppGGWJP3URdLQUpHfv8Hx/kTuI7yI2lxx2WPI5g2553D3v7+7aK2xWvICIuB1TYYQZd/zNb6KVJ4Cd9DaMcsV3HJTqJPUf/5h+W0F3sE8+6U5vZ2MJNxGR+PTxx9e+zXRp3dqFgwc7r4HFROKUoM9RRyXntWuXnBcRpjAMo1xJNPqXyMsvJ+el2vPfrJk7f/Hll86C7bp1MedJtWXVKjj/fBfPdBG3oiK1SZKauPPOWLwYFsAbNoQRI5zSTOdsiG/W/auvamdNOANMYRhGuXL22S588EE3/SRS/SGwmg6ItWyZvLaRC5o2jZkZyaZutmcoggpvahEskdavD0ce6RxCJb55JdKgQfzUYffu0crmYQrDMMqVrl2dEth++18Oz/Hppy4Mmib/9ltYsCCpel7Zcsvw/Isvdg/PKWGbKXEmTZ56Kjq58smGDc621+zZNZfNx/bjEExhGEY5s+mmbjeSj2/eY9iwWF6rVs7VaTFy990uDPPHUW6sXetse/m7t37/exeed15qO1s33pgf2TxMYRhGOZPo5GjJEncG4tRTCyNPdQRdrQ4bFj8ts8su0fdfbC5Rn37ahR98AMceG/NNHuSqq+Doo/P2fZrCMIy6RP/+MG1aLB3mGKlQBE+NJx5c23pr539DxF3r19fOOVQYn3yS2/YyJXENyfew6CuOf/8bbrjBTSsGLRC//DI88UReRDSFYRjlzOWXJ+cFHQkFT2oXmhkzXPjzz/FKDWDcuPgDduedl+yfo7bkc9orUTl88YUzRQ+xN6tevVw53+TKppvC1VdDjx6pt91GjCkMwyhnws5gfPZZLD5pUv5kqYkBA1z488/Ju7FGjYpPP/ww3HVXbvsPehCMmnr14qfcunRJfZq+iDCFYRjljH+KOehnYeut4cwznf2omvxt55MePZy5EhH4+uv4e/60TBj33Zeb/ocOdb/o+/QJP1GdK4KeBS+5JPbm9N13bjdb0PlUkWEKwzDKmfHjXThrVszm0LRp7qG1226FkyuM1avd3PzFFycv1lfHn/6UfZ9BW1bffef6Hz06ZuAvCu64Ixa/6654ZXjggfGL/0WGKQzDqCusWuXCQYPcyeBUnvgKhW9YL2hmPR1qOuRWHR98EJ8Oczeba555Jj4dNDM/dGjy+k0RYQrDMOoKO+7oQn9xOZWBu0KRzYPy9NNr12fbtvGnvL/6Cu69N5qH9oYN8OyzyfnXXReL9++fV+uzmWIKwzDqCommw4tp/QLcfH6mPP547fvdaadYfMIEuOCC+MOOueL++6Ffv9y3m0dMYRhGXeC445z9oSC18GMdCa1ahecHzxyAewvIJcEpLd9vdq77WLMmtdXgEsIUhmHUBa64IvmNwnfhWszccIM7czBhgjvV/N//OrtTr3gOON99N7q+Bw9223uDZlTSYcECd/7Fn/oD2GKLZCVUggrEFIZhlDP+lM3uuyevWZSCwrj6ahdWVjq7Sb4Z8qOOcltg99svN/08/HBy3jnnOD8ZvqOldJk5E267Ld6arH8oz6dv39jbTCLPPZdZf3kkUoUhIi1EZJiIzBCR6SKyr4jc7qUni8hwEWmRou48z5XrRBGZEKWchlG2nHaae7CGLXDXs9+Lv+Cbgs8F/fu78MQTU5c55ZTUPi8mFO/jLuq/mIHA66q6I9Ad5597NLCLqu4GzAJS+I8EoLeq9lDVIvTSbhgliH/u4NhjCytHsVHT1tx169Jva9EiF/rbhBPbfucdZywwUWEX25pSCJEpDBFpDhwAPAqgqmtVdaWqvqGqvjH3D4EitatsGGXI3LkuHD68sHKk4t//jsVPOaVgYiRx8cWx+Pr14X7Pw1ixIjkvaGTR54ILXJsnn5wb17cRIVqTl61sGxbpATwMTMO9XXwMXKiqPwbKjACeU9UnQ+p/AawAFBikqiGTjCAiA4ABABUVFZXPhu1zToNVq1bRrFmzrOoWMzau0iPKsfXq3RuASbfeygrfbEieSHdcvoxjR41iYx7XWfx+U1HlWY/1y8096yy+PPXUpHFV1847I0eyIeDpzy9b9eabBTsX07t374/TnsVR1UguoCewHtjbSw8EbgjcvwoYjqe0Quq398K2wCTggJr6rKys1GwZM2ZM1nWLGRtX6RHp2NyKhupnn0XXRwrSHpcvY77x+w27zj7blVm/Pj5fQ8aVqo2NG5P7XLVKdcaMaMdVA8AETfO5HuUaxkJgoaqO89LDgD0AROQM4EjgFE/gJFR1sRd+jVMs+f05ZBjljC14J/PYY6nvDR7spqL+8Ifs2r7xxvB1kqZNY+bLS4DI/mpUdQmwQET8T+NgYJqI9AUuB45W1dDJOhFpKiKb+XGgD5DCqa9hGBljCiOZM85w4R//GH7/zDNh+vRY+s03k8skmmX3Oeus2slWJDSouUituAB4SkQaAXOBM4HxwCbAaHEa90NVPVdE2gODVfUIoAIY7t1vADytqq9HLKth1B02bCi0BKn59a+jPZCXCpGYY6MmTZxV2UsugTvvdHlPBpZaH3ggfFfTwoXhbW+5ZW5lLRCRKgxVnYhbywiyXYqyi4EjvPhc3EK5YRhR0Lx5oSVIzTvvFFoCuP12uPVWtxDtK4wgl1/u3hr22Se8/mGHJTt9KgPsvdQw6iJlusMsZ4jEdi2NGJF8v1492LgxPm/x4lj80EOjk62AmMIwjLpIgXxClyTr1yfn1a+frDCGDInFg342auPgqcgwhWEYdYnWrV1oi97ps//+yXlhbxh//3ssPnCg86lx8cW5cyFbBNhfjWHUJaZOLY41glKidWu3GL5ihXNrO2lSuMLwOfts6NDB+dm4887aeQQsMqLeJWUYRjFRUeEuI3NatHDKApzSTWU88F//yp9MecYUhmEYRqZsv33qe2W8PmRTUoZhGJny6KNluW22JkxhGIZhZMr118Mzz8TSS5cWTpY8YgrDMAwjUxK31fonuS+7rDDy5AlTGIZhGJni75L68ks2nzw5lu87qCpTbNHbMAwjU3yF0akTce6Q0nWsVKLYG4ZhGEam+ArjkEPi8//5z8LIkyfsDcMwDCNTxoyBRo3g+OMLLUleMYVhGIaRKe3aubCqKj7/b3/Luyj5xBSGYRhGpjz8cLiJ+Kuuyr8secQUhmEYRqY8+GDM2VKQJk3yL0sesUVvwzCMTKlXL2ZXyuf66wsjSx6JVGGISAsRGSYiM0RkuojsKyKtRGS0iMz2wpYp6p7hlZktImdEKadhGEZGhJmHf+ut/MuRZ6J+wxgIvK6qO+Jcrk4HrgD+p6pdgf956ThEpBVwDbA3sBdwTSrFYhiGkXcmTIhP77knPPtsYWTJI5EpDBFpDhwAPAqgqmtVdSXwW2CoV2wocExI9cOA0aq6XFVXAKOBvlHJahiGUSvGjasTZuOjfMPoAnwDPCYin4rIYBFpClSo6lcAXtg2pG4HYEEgvdDLMwzDKD7CFsDLkCh3STUA9gAuUNVxIjKQkOmnFIS5qAr9RkRkADAAoKKigqrEfdFpsmrVqqzrFjM2rtKjXMdWTuPqFYi/fe+96NixhRIlr0SpMBYCC1V1nJcehlMYS0Wknap+JSLtgK9T1O0VSHcEqsI6UdWHgYcBevbsqb169QorViNVVVVkW7eYsXGVHuU6trIal8gvbxW6yy7lM64aiGxKSlWXAAtEZAcv62BgGvAK4O96OgN4OaT6KKCPiLT0Frv7eHmGYRiFZ9gwF261VWHlyDNRH9y7AHhKRBoBc4EzcUrqeRE5C/gSOAFARHoC56rq2aq6XERuAMZ77VyvqssjltUwDCMzOnUqtAR5JVKFoaoTgZ4htw4OKTsBODuQHgIMiU46wzCMLPn1r+Hkk92J74kTCy1N3jDTIIZhGJnStm28i9Y6gpkGMQzDMNLCFIZhGIaRFqYwDMMwjLQwhWEYhmGkhSkMwzAMIy1MYRiGYRhpYQrDMAzDSAtTGIZhGEZaiJaRWV4R+QaYn2X1NsCyHIpTLNi4So9yHZuNqzjppKpbpFOwrBRGbRCRCaoaZsakpLFxlR7lOjYbV+ljU1KGYRhGWpjCMAzDMNLCFEaMhwstQETYuEqPch2bjavEsTUMwzAMIy3sDcMwDMNIC1MYhmEYRlrUeYUhIn1FZKaIzBGRKwotTypEZJ6IfCYiE0VkgpfXSkRGi8hsL2zp5YuI3OONabKI7BFo5wyv/GwROSOQX+m1P8erKxGOZYiIfC0iUwJ5kY8lVR8Rj+taEVnkfW8TReSIwL0rPRlnishhgfzQv0kR2UZExnnyP+e5PkZENvHSc7z7nXM8rq1EZIyITBeRqSJyoZdf0t9ZNeMq+e8sMlS1zl5AfeBzoAvQCJgEdCu0XClknQe0Sci7DbjCi18B3OrFjwD+CwiwDzDOy2+F863eCmjpxVt69z4C9vXq/Bc4PMKxHADsAUzJ51hS9RHxuK4F/hJStpv397YJsI33d1i/ur9J4HngZC/+EPBHL/4n4CEvfjLwXI7H1Q7Yw4tvBszy5C/p76yacZX8dxbVVXABCjp49wc6KpC+Eriy0HKlkHUeyQpjJtDOi7cDZnrxQUC/xHJAP2BQIH+Ql9cOmBHIjysX0Xg6E/9gjXwsqfqIeFypHj5xf2vAKO/vMfRv0nuQLgMaJP7t+nW9eAOvnET43b0MHFou31nIuMruO8vVVdenpDoACwLphV5eMaLAGyLysYgM8PIqVPUrAC9s6+WnGld1+QtD8vNJPsaSqo+oOd+bmhkSmFLJdFytgZWquj4hP64t7/53Xvmc402d7A6Mo4y+s4RxQRl9Z7mkriuMsHn6Yt1nvJ+q7gEcDpwnIgdUUzbVuDLNLwZKfSwPAtsCPYCvgDu8/FyOKy9jFpFmwAvARar6fXVFU8hTlN9ZyLjK5jvLNXVdYSwEtgqkOwKLCyRLtajqYi/8GhgO7AUsFZF2AF74tVc81biqy+8Ykp9P8jGWVH1EhqouVdUNqroReAT3vUHm41oGtBCRBgn5cW159zcHludyHCLSEPdQfUpVX/SyS/47CxtXuXxnUVDXFcZ4oKu3k6ERbvHplQLLlISINBWRzfw40AeYgpPV32lyBm4OFi//dG+3yj7Ad97r/Cigj4i09F6z++DmVL8CfhCRfbzdKacH2soX+RhLqj4iw3/YeRyL+958WU72dstsA3TFLfyG/k2qm+weAxwfIn9wXMcDb3nlczUGAR4FpqvqnYFbJf2dpRpXOXxnkVHoRZRCX7gdHbNwuxyuKrQ8KWTsgtt5MQmY6suJm/P8HzDbC1t5+QLc743pM6BnoK0/AHO868xAfk/cP8bnwH1Eu2j6DO5Vfx3ul9ZZ+RhLqj4iHtcTntyTcQ+JdoHyV3kyziSwKy3V36T3d/CRN97/AJt4+Zt66Tne/S45HtevcdMlk4GJ3nVEqX9n1Yyr5L+zqC4zDWIYhmGkRV2fkjIMwzDSxBSGYRiGkRamMAzDMIy0MIVhGIZhpIUpDMMwDCMtTGEYeUVEWgesgC5JsAr6fqHlS0REBotIt4javlZE/hJF2xnK0V9E2gfSkY3ZKG0a1FzEMHKHqn6LM7mAiFwLrFLVfxVUqBSISH1VPbvQcmSCJ/OGDKv1x52B8K0JlNSYjfxhbxhG0SAiq7ywl4i8LSLPi8gsEblFRE4RkY/E+UzY1iu3hYi8ICLjvWu/kDZ39upN9IzJdfXyTw3kDxKR+r4MInK9iIwD9hWRKhHp6d3rIyIfiMgnIvIfzwYRnnzTvPaTlJ84nw4vefc/FJHdAre7i8hb4vwlnOOVbyciYz3ZpojI/jX0P09E/iEi7wKXichHgb47i8hkL/4P73OaIiIPeyexj8cdmnvK669xwpj7eZ/5FBG5NfhdichNIjLJG1OFl3+CV3aSiIzN6g/BKF4KfXLQrrp7kWBGGve2AdALWIkzZ70JsAi4zrt3IXC3F38a+LUX3xpn4iGxj3uBU7x4I6AxsBMwAmjo5faSb6cAAANOSURBVD8AnO7FFTgxUL8K90BtA4wFmnr5lwP/wPl2mEnsZHKLFDJc48UPAiYGxj/Jk6kNznppe+BSYqf56+N8NYT278XnAZcF+puId3LYK3e1F28VKPMEcFRwjCFjbg98CWyBm414Czgm8Dn59W8L9PEZ0CHVZ2FXaV82JWUUK+PVM2stIp8Db3j5nwG9vfghQDeJOQdsLiKbqeoPgXY+AK4SkY7Ai6o6W0QOBiqB8V7dxsSM2m3AGaNLZB+cA533vDqNvLa/B34CBovIa8CrIXV/DRwHoKpvees4m3v3XlbVNcAaERmDM3Q3HhgizjDeS6o6UUQOTNG/z3OB+PPAicAtwEneBdBbRC4DmuAU3VSc4kzFnkCVqn4DICJP4ZxEvQSsDYz1Y5wfCYD3gH+LyPPAixhlhSkMo1j5ORDfGEhvJPZ3Ww/nhGZNqkZU9Wlveuk3wCgRORtn62ioql4ZUuUnDV8DEGC0qvZLuiGyF3Awzujc+bi3iMS6SaIlhAGRdaw48/W/AZ4QkduBFan69/gxEH8O+I+IvOi1N1tENsW9SfVU1QXe+tGmKdqqTm6fdarqy74B7ztR1XNFZG9P9oki0kPdupVRBtgahlHKvIF7QAMgIj0SC4hIF2Cuqt6DMyS3G86I3fEi0tYr00pEOtXQ14fAfiKynVeniYhs760jbK6qI4GL8Bb0ExgLnOLV6wUs05g/id+KyKYi0ho3FTfek+VrVX0EZ011j1T9hwmqqp/jHuJ/J/bm4SuHZZ7Mxweq/ICb9kpkHHCgiLTx1nj6AW+n/IScXNuq6jhV/QfOvPdW1ZU3Sgt7wzBKmT8D93uLug1wD+ZzE8qcBJwqIuuAJcD1qrpcRK7GeTCsh7Muex4wP1VHqvqNiPQHnhGRTbzsq3EP25e9X/ACXBxS/VrgMU/O1cTMWoOzVPoabg3mBlVdLCJnAH/1ZF6FW19J1f+sFCI/B9yO8z2Nqq4UkUdwU3rzcNNePv8GHhKRNTg3ov6YvxKRK3EmugUYqao1mRe/XdzGAsEp5kk1lDdKCLNWaxiGYaSFTUkZhmEYaWEKwzAMw0gLUxiGYRhGWpjCMAzDMNLCFIZhGIaRFqYwDMMwjLQwhWEYhmGkxf8DpW/XPMDK1jcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(renault_price_evol['last'],'r--', color = 'r')\n",
    "plt.title('Evolution of the Renault price')\n",
    "plt.xlabel('Time series observations')\n",
    "plt.ylabel('Price')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Total**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_price_evol = pd.concat(total_trades)\n",
    "total_price_evol = total_price_evol.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2ebMySX3oofzJkylVq6pPHHDmar/vvmjkyAadrGvs2PhYt7nx5ZdRSyAInpSOAunWzXub9rl4/PH8yJIJOi86UXzf9J99NmoJMmfBArXs2hU466xw25o9W4WIX78+82MbNcq9PIKQI0pHgRB5b9OB9CrE8Oto314t46BARo+2FZqJs0dSipi9Q+eLyODBwPPPA8cem/l5nf5AghAjYvjEDAlm7wfw2rVquWwZMGAA8Msv+ZMrHXr8u6xMfaKCGejZEzjppOhkCJvevYMfe+SRann66cC++yZu23NPtczG+CDqlwdBcKF0FAgA7NzpXm/GMBo4EPjhh/zIkwn33Qf8/nt07ZdCmtdDDgl+7Pvvq7mU114DevVK3JYLb/2XXlK9UMlKKcSI4lYgzrc2bXXjZObMxHVJ3JTMsGFRS5A7Jk1yr88mpPsee6hEUmF55ut7dNmycM4vCAEobgViRlgFgHPOcd/POblZpUo48mTDm28Gy9WdLWvXqjffadMS66tUibf1UiqGDnWvj5sTodkT1rlGpk+PRhZBcKG4FYie29B89JH7fvvvn7iuczpESbt2QNu29vpXXwEvvJB/OerWda8fODB+D1y/dO/uXp+rIIpe5tY6t71f7rknue6ttzKXRxBCorgViPOtGQC2bk2ucyqM334LRx4/vPaastbZudOefAXiYYVl0qtXtJP62eDllHnAAbk5/8qVwOuvY/KrrybWZ9qDXLcuN/IIQkgUtwJxe+C6BSV0OsLtt1848vihd29g4kQVvt3sMaUyQ46CWrXiJ1M65s1TMpvRhMOgdm3grLOwde+9gUsvtesztfK67LLcyiUIOaa4FYjbkMHw4cl1zknVTz4JR55s0A/rOEzwN26cHDNqxIhoZMmEgw92r69WTeU0D4Pnngt+7Kmn5k4OQQiB4lYgEycm13XokP64fMbNmjYtsad09tnu+2lT41atwpdJc8017vXz5iXXnXtuuLKEye+/5274KhXFEvpeECyKW4EsXqyWTZrYdR07Ju6jvdBN3HJbh8Gnn6rJctNz+fXX3fe96SagYkXgggvyIxsAPPGEe70E9wvG0qW5OU+cgz/GgdWr5TvKE6ErECIqI6KZRDTGWr+KiBYSERNRvVAb12+VnTrZdQcemLiPW/7rfOW4+PFHtZw929/+e++thrLclF4+aNasuMxIr7sufMOEgw5KXPcbD+upp7y3/ec/dnnqVG8H2VKlQQM1LCmETj56IH8DYI55TARwAoAcvY6lQP+xzDmOdu0S9/F6y84HOq7UwoVq+dVX3vs+8YSKOfXf/6JT167hywYkWw117Qq0aZNYd8MN+ZElDPLR09SpcnVMM71Mxbp1wFVXeW/X982sWcDRRwP9+wMjR8bLSk8oCUJVIETUGMApAHbPJDLzTGZeEma7u9GOhHENw6EVx957q6Xz4WzinI/w8qrPJddfr5baksjNJ6RQFcgddwB33RV+O926KbNwHZZ9/vz0PchTTkm9/e231VL3RJ57Ts2dvfNOdrIKQoZUDPn8gwDcBMAl9VtqiKgfgH4A0LBhQ4wfPz7jxttffDGqApiwaxeOM+rNc3XyODZIe5lySNWqqA9gGYBF48e7yqLlcG6b9P772Fa/fpji4ehzz0U1AJNOOgkVunTBlgYNAOf3smsX2rRsiUobNuDLLL6z8vLy0L/zTkZ5wrHHYtfnn4fannlNZturunTBtymUVyedRMzBj717o4ll7TZp5Egc8+STCdvnfPst1oacUTHd79Ri8GA0fvNNzHr0Uaz/wx9ClUXTvndvVP3lF4wfNw7YtWv3d+33fsrHvZdv8nZNzBzKB0APAE9b5U4Axji2LwFQz8+52rRpw4HQMXjff5956FB73WTCBLve/OQD3VbDhonrbnK4bfvqq3Dla9VKtbNtW+r97rqL+eKLs2pq3LhxWR3vC/O727Ur9OYSrimT+8vc75Zb1JKI+eWX3e8D/Rk0KNTrYU7zO23fbsuyzz6hy7Ib8zfdujXj/3Be7r08o68JwHQO6RnPzKEOYXUE0JOIlgAYAaALEb0cYnveEHmbUB5n9E1MBzOdZCof+Akf//DDyXWpJlpzgU66dP75qfe7806V7yLOmJGMly/PvxOklw+KyY4dyrDi9NPtun/9C1izRoXlOe+81Me7GYTkEzOiw88/57/9BQvCC2YpuBKaAmHmAczcmJmbAegNYCwz9wmrvZT83//5i3Nkjk2fcYZabtigwnGHPUGp50O8cPNNMa1xwmTkyNTbn3lGRaONyjrMDzVq2GVnvo58sGFD+n3OPlu96JhDD+Xlau6pTp14ev5v3Kjkqlw50RosCiuoZcvyZ0EpAIjAD4SIriGi5QAaA5hDRFm46vqkQgWgng+LYTMKr/ZMvuYaNVHsFYgxV1x5ZXKdOUHtNbbtFtsrKL/84h4HLF0MpyuuUMdJ7CZvvOJvaXbsUBGXgURT3+uuC0+mXKB/8+3bE++dzZvz076OUgyoQJPm3FKtWv4UtxCYvCgQZh7PzD2s8mCrZ1KRmRsx86Xpjs+a/fbzHpL64x/VcuRI9Zan0cNKOgOfM2JvtmzalLg+d27i+q232lZQAPDFF+7nyaWF2d57uydV8gqD7ySOb8hx4aabUm/3ShaWSWDPsWP975sLdu5MdI40r8ErikGuufZau+wc0i0vT871I+SU4vZENx/65jzD6tV2WVviOLPI6e64fhsM8nD84APg2WeTh6cWL0725naOGd93n23eC3jHVMpV4Ec9bLJsWbIXb7o4UTqXvDi0eUMEnHyyve4cEvVKIZDJXMIRR2QuVzZcdBFw/PH2uhmG56KL8iuLF+KRHirFrUB0KJP16wHT5PWnn+zyiSd6O3c9/bTt0GUe45fu3ZWTV8uWiaHl3SbEg1IxR5bYnTvb5QkT1PK999Ty6KNTH6vnPpz5V+JIuqGkMHn3XbvsTE1rKgpzjiadr4qZNG2vvQKLljGzZgEvO2xiZsywy84edVQ0ahS1BEVNcSsQzdat3rkrdu703mbOS+iHaiaYvQzzLf6ZZ1If17y5/zbCiCKrexLdu6seSTp7/hNOUMt8BnoMSlxCpI8enbh+6KF2Wb+s3HNPYhgeJ126qBeIKN6yhwxJvb1v3/Bl8GO0EbKvVKlTGgqkQgW7NwKoB+Ibb6hyKgVi0qNH5u2a3uKzZtnldBZdqR4aTh57LCORfKGHWj75RA3DpePDD/3tFyVvvw387W/AYYdFK4ce7tNKNxV33JFcZ5pU68CbUaRgjsPLgjNltRs6AoAQCqWhQIiSo/DqP99nnyX2Lho3dj9HtlYlXpOkbmRinntpiDYII0b4C/fRu7cK2ZGP0CBB6dkz0WInKrR5eND5InOuJFfDl0EwDTyi4McfE+cyvfj3v8OXpYQpDQVSoUKihRXgPV7vlY9jzZrsZNCRd4Pi5SCVzskvH6xcqZZuObzjwrffhpc0KhO0P0qqYImpGDrULrsFg9TzVsVO06b+DEji3jMucEpHgTj55BP3h/oee7ifI1sLF63A/PzB3XxO3IYzAPesi/mmXz+17NYtWjlS0bdvtBPoGtNXJtVLhTknYlLLCCvn5lzqzMOeC1asUL14L1NyL3QkgyjZd19g1Cg1lyfknOJWIIMHY1PTpsm9D83FFyfXeYWcyNYTXecmSZem9Icf3JVCw4a7i9OffdauP+aY7OTKBXrSX+e+qFxZPXDy5UyWjmeeUXlM4iCPmdxs9mxlPu3m7Pa//wU7vzM9cy7QJt6ZenmHkSrh998zM6lv1Aj4858Tv3chZxS3Arn6akx78UV7/f33E7e7OV41a+Y+D9K9e3ay6DmQdJYjbr0lIGHsu7xVK/WnAIC2bbOTa9u27L2dtczbtqmlnty8/fbUx33+uf9kWtlwxRVqGYeIq488Ypd79lTm0y+8kLxfUK/+H34IdlwqtJHJnntmdpyf6A+Z0rNnZvub5vNCzslIgRBRjfR7xYhRo3DobbfZZo5+4mG1beve3f3uu+xk8TuJXssj8r1zaGLYMNU9b9pU5YEYMyaYXIMGeVtyPfAAMGVK+nNoZ8uvv06sT5UgC1CBLPPt/BY1bhZTN99sl/XwZTrP9XyiLa78DlHqXlDv3snbysuz6wnqlxSTvn3tVM+jR9shYYTQ8aVAiOgYIvoWVmZBImpNRDHN0mRw++2oN2mS/fbuNy5OtsrCDa/ufJcuietezmBuPZefflJ/1tNOSz805oX5ndRwvB/Uresv8KA2MDBNpYF4vPEXAuZDUb/tz5njvf+6dd4x0DxyiWSFVvLmvdK5sx0GyEnjxsDhhwPff5+8rVat7DJBOlMEA8CTT9qyfPFFPEyMSwS/PZDHAPwJwK8AwMyzgYQcTfFkqSNr7rff+jvOaxz5xhuzk8eNPj4DFN9yi1pWraqW+k3WHBIJgtkrc8bnevddYPDg9OfQgR6j9rEoBrRpbqpx/jp1vK3yOnTIvUzaadAc6tyxw9uMeNs2pQDDiEzQokVyXcWKdqy7Bx6Ix1xXieB7CIuZneM68Q989Kc/qaW2VnnlFff9nJZRXpnqpk7137aZWwSwh6Z0V1tjxgyaNw+e9OihxrenT1fr5p/3sMNs/4JMOfBA721vvgk8+GD6c2Taw8s3Z56pliFn68uauXPt6AVx+i7dfCl27FC9pd9+S55n0HNiqQxPghqluM1PVqyoejwabVbuJFMrMiEtfhXIMiI6BgATUWUiugHWcFasGT4cU15+2X5bNxP1APZwkXOC3Jx4N8kknIlhNQXAjqrq9J413zTNMN5u7L+/e7TcLVuCO5XdeqtdNu3qnQowFXrfL75IHFrJwAqn6bBhyUNguUL7ysTpoWzSoIFatmypPoDKYZMJfuaqguKWyEr3QGrWTA4Mqu/pXbuAjz9W67NmJTpPZhJl2MTNSEArMs2xx7of6zXkJgTGrwLpD+BKAPsCWA7gCGs93lSrhs3mGL5ziCWK4H9uiaP00EDQYHjffx/8D2nO95hWNpnkGdFjzscfn/iQ8Oss99NP2P/FF21T51xj5RGPDeakOWAr4EqVbAOOTK2w2rWzy7mewzMm9Cvpl5x777XrnUNGWoEw26FEhg7NjZJzWvb17avaM/1m4t7TLCJ8KRBmXsPM5zNzQ2ZuwMx9mDmPOV9zhJc/iBPnH9wk1TCTH/QQlMmDD6rzZjP55yctrhtmvK5//MMuZzLRqQPWzZuXOBHvlcmwdetEnwI3y5pcMXmykqNmzeBKNtcMHOjek6xQwX7DNkO/Z0qIaV076qHS+vXtdAlmz7VTJ5WNUN8H+kXk6acTwwmZ91026NEC3XPTQ7JeDsFCTvFrhTWMiOoY63sSUcyTYLvQpo2//QYO9N6mY2hlyznnAN98o8plZZkPWThJlzhn5kz1ppYqda4ZBTiTPCO61+Ec9vIKCzNnTmLcrM8+s8t33um/XT9oR8utW5OHWqLE6yGvx++zyTGfyyyVgLs/R5s2tgLR2085RZkhN2igDDLuv1/lw3Ej2zDrdeok+oRUrqx6PLr39dJLKnimkyBpGQRP/A5hHc7MuwfomXkdgDQxvmOIm5OemxNXKnIVMLB/f2+v9zDQ8wupYnqZE+qbNwOPP57s2+FGJnMLK1Yk15kPqFzH09LzW34it+YTL4u+dKHz/ZCrt3uNH7+KvfdW5uRmeJVFi7zvjWx/j3XrVIRlL3r2dP+viml5TvGrQCoQ0e4BciLaC0CEoUBziF/T3lwThpeuFzt32p7rqbzOK1dWvh+aatX8Dft5Tbi3bp24/vnn7n4lS5akbyMozugDccHLYVR/P9mM4+c6vLvbpHSjRomRoH/+2c61Yg6neikKP0692VKnjuqVmBZfXhZaQiD8KpBHAEwionuJ6F4AkwD4sO8sAB56yHtbq1bBzQ29hqS0U1amYSHc8BvK3ZxvSOVoVlaWmDu+rCzZ0dGNatXc651hSrzCSoRlfRVnvMynddSEbCzGnP482eKcE6xTR/UkvV4c/ISq/zXAFGou5rCOOir7cwi78TuJ/l8AfwbwC4BVAM5k5pfCFCw0vv/en7fu5s3ZpeV0WsJof4p77lE+G34n9FPhfEv1Gp66997gbYwbl36fVA+M/v2BFY6oAAAgAElEQVRtJfzJJ+77PPpo5nIVOl5K1ysWmh/698/+HG44fYG0cnvnHff9Mwl2mAnZpEQYPlwtQzQwKEVS3mlEtIe13AvASgCvABgOYKVVV3i0aKECJmq88pNXrep9sw0bpuzbM2HvvdVyxQo1ppwLnwSn7EECE55zjlpq6x8366B0pPL8ffZZOxd4vtOLugXLjAuNGyf2IPXYvI4aG0TpZ5usKlO0o64TtzDzuSCbFzpzaFbIGeleVbTr9gwA042PXi98dGpbv5xyivIeP+kkf/trD9kLL1SOiDohUK6GGcwu+WmnZX786tXqjVVb1Dg95f2QLoe79m3QYVjyRdeu+W0vU8zkUKYp8++/AwMGZH4+PSxqmmNny/Ll3tu8Xhz8pIgOwrnnBj+2Y0c13+mcl4sr27fn70UgC1JOhDNzDyIiAMczc5Yp9WKE7g0AmQef8wpz4sXs2XaXft48YMYMVdZj3dkybZp9/iBKyfmWHmTOR3tSe/HBByqekh+LrrDI1Nou35hOpF7DW+nQof0//TR7eTSpzLm9IjNEkaM9HTVrugdijCt69CPbPEQhk3awlJkZQPHFR+7bN9hxplVJpg9s82EdxltapultX3KZxmrfPvN205lkvvOO8v1IlwsFUDG/wuDCC8M5b7Zs2aLuC78+SqnIt4/D0x4BubOJthsWS5eqtAWF5gfi5z8TIX5n274koiwzF8WMoArE7LZnOlloWl6FoUD8vvnpB75bzK9OnRLXzSB1Xvidz7nkkvT7jBmTkDwrMGamxjPOyP3Ecq6oUkWFRs8Fo0bZ5Vy8uaZLxpSJT4XfIV8/eBljpGLBAmXCHqbJeCasW6fuyVS+LEA80jCnwO+/qjOUEllERHOIaC4RpUhYUADoifRevdLv6/VWnunbgRmvKIxQC1rOli1Tv3FrBeJnktkrgrHJzz+n3wcA/vMff/tlM1mqMYcmg6aHLTTMYKG5SG07a1aw49xeAPTLVi6Gt7K5P449Nh7OhCtWKCXvDPDqxKuXFxP8KpDuAA4A0AXAqQB6WMvCRT/A/eSw8Eob63zL27Il9aSj6bToTN6UC157TS0XLnQfntLot/Hjj3ffbt7Ufqyy3HpT2Ux4Zmvvr0PEaOLa+8g15nxFLhxk0zkzHueREsjtfvjwQ7WcPz87mYDEmFp+MUcLctXjCwu36McxJZ0Zb1Ui+juAGwF0A/ATMy/Vn7xIGBZ16yoF4MdixZx0N3EqkH33VX9irzc3M/lTLi2SdA+gc2dbiaRCR1T16h5nOh7vNlySzVyGW0rhTFi9OrvjCxn98Ak6EW9y222pt3sNbxIB11xjr19wgYqR1a+fSsGsue++YHJ5vdAVEs5e8cSJ6sVt587k9NUxJt2r2TAARwGYC9ULyTL9XYFy883JeQjq11dhMsyQ8LrsDCDnpixyGYFW293vsQdwxRXJ251hI/Tk/8aN7ue7447M2ne+4W/cqAIpah8Tv+g4UH36uMfM8sv999vlbIP2FRraeicbJbpuHXDllYmBN5s0SQ5Dkyq/xr/+ZZdfegk48UT7f6HD6jhDs4dJWM6NQXHG6Tr2WDUf4syiGnPSKZCDrdDtzwLoBaA0M7KUldl+EpoLLgB693YfqjGjywLuJru5jJiqk0lt355oAbNxoxqPdiqQZ55RHub6IeOVgMfvZLbpmAmoOE8VK/pLKGXOsZgRhf3Mzyxa5B4GxfwO3MLnFzM6/0aQiWbNmDFq7N18wC9dClx7rf9zmL+Bs0ebqe9VLujYUXmyb9oUb/8Kp09VGEPdOSSdAtltn8nMOTCNKSJShd/wkzMkl29E1aqpN5oOHRJ9MmrXVg+Dr75K3P+RR1SMK+2T4jXk5nfuwMy+aPa20oVrWbBAvdlWqIDZTq967ZGdihYt3JNQmZYt+QjaFyemT1dDIQ0apI68nAodMeCUUxLrr74aXweJlpwqnlq+8pdXraqGl7/+Ovsh0lyTatg513HNcky6J0RrItpofX4DcLguE5HH+EeJ4Se2jjPnOuAdjTWoDHfeqRSIU1mYsaycllk6t8lbb7mf16+S+/13u2wGbkyXZrdlS/VmuHMn1rVpkxg/7Pjj/eVjd8Mcfy81Fi1Sv+eLLwb/HnTP1On4Wbky1gRJC2sOKQKJJtb//W/m5wvCkiXAxRcDRx+dPJoQNb17p96uX/RiSEoFwsxlzLyH9anFzBWNsqT8AtQbfjrccjzkMl4Qs3KQWrAgeZv5duPlVey0trnmmsxyrJu53AcNssupEli5pe91TvymygyZisceU3MwGeRkLxqmTrXLQSdj51gW+jo8u3NYpU0bO6q0H5z3kmn+7nzhCYvFi22/J2eI9yjIxJw51wnCckiJ2DdGjNPnw8v8MRsaN3YPEW7mZvAKtuj0Z6lcOTMFZ5ouO4eUnJZejRurpZtvjVOOVN9TugfAkCH+c7IXE5mG6/j44+Q5Aef8k9MXoXZtf2Pz48e750E336ijyhL5zDPRtKvJRCmY+d5jRugKhIjKiGgmEY2x1vcnoilE9D0RvUZExR9f2fm24RVDKCh+h5q8fF5M00pAvXn66Vm54TTfNRM6tW5tKxs373XnZLzTK95kjuHH6swtceGFqoeTLs1vMeKMeDx5snccsHffVR7izvknZ6/AmdumYkV/99zxxyc6z2qiyA7plPe55/IvQ1BiPJGejx7I3wCYs8oPAHiMmVsCWAfAR3yLAkA7SrkRVnTSTPFy7jMnwQGVSMtPIik3TjwxcV2H0e7RQ+Vi0fgJkZJqfNwcAnNmd9Tm1HGMyRQ2TlPbY44B/vIX9321Ml+0KLHe2YtxzvN9+GHmQUVNTAOJqHLBaFPiOPO//wEvvxyf54cLoSoQImoM4BQAz1nrBOXNrr1ohgFI48sfI6680ntbt275k8MNPxkO/XjdB0EPd/XqlWyyqe3ay8oSJ9t1gp9UmL2ZESPUW6Q2Of7gA+/jdBj3UrPAAjJTmtpKy2lmrhX93nsrM2svR9qgDB6c2/P5wdkDyUVCt7Bp3jzzAKl5Juy85oMA3ARAmxzVBbDeMAleDsAlSTZARP0A9AOAhg0bYnzA+DXl5eWBj03ijDNQ48gj0dYRFHBTs2bw6mTqtlv27Il9jQxu2cjkdk3HAEg3Fjh+/Hh0ctRtatoU07L8fqr+9BPaA5jXsiV+cZyr/vjxOARIDhq3cWPCNehrOq5SJVSwhjiWbNiAJdY+nXTvaeJEjB8/Hh1uvRXmwKB5rv0WLEBzABMmTcKufOcgMcjpvZcBnVzq3ORosmQJDgCw/PffsdDY3nbffVFj6VJs3HNPzKleHTtcfqdsqLl6NczEsn7P1wnAjho18EWA9mnnTrSvWxdlW7ag4qZN+PaXX7DKOk++fyfauRMeQYR2893NN2Pl+vWB43bl7ZqYOZQPVLysp61yJwBjANQHsNDYZz8Ac9Odq02bNhyUcePGBT7WE9uOI/1HM3mye30AXK/p1FP9yeKsO/vsrGRhZuaNG5mHD2f+4YfkbU8+mf67Ma9p6lR7+y23MM+bx1xWlv46Ro9mXreOefFi5rffZu7dm3nbtuyvLQtCuff84PZdb9qUvN/JJ7vfj61bp/+dsmH16mD/BYC5bt3g7ZaVMR90kDpP9+67q/P2O737rmr7o4/cf6N33lHLF1/Muil9TQCmc0jPeGYOdQirI4CeRLQEwAiooatBAOoQke75NAaQRcyKiDBNVf1ijv+HQbrgeV5DPtoXJBs2blQms24OlOXlmZ3LjHNUVqbG4/14Dp96qprL2X9/tXz11fBSqxYibr+Dm38SECw1cibUq5doRZdJeminwYRfFi9W95G+R4Nk78wWHVvMNG1/8km17NZNOW7u2hU81UQEhKZAmHkAMzdm5mYAegMYy8znAxgHFRYFAPoCSBMQP4akyq/cqpV7fS4e1KlYtSr1dq/81blg/XoVQsMt46CfuRkvMg22p+OLtW+fHE6m1HEaSjiJMk9GLnOFeOGMkh1FoiYd8cGMn3fllUqZvv++ivwQt5hdaYjCD+RmANcR0UKoORGfSSJiRKo0uF5/VO2UBfiL85Qpbm/bblZX2TzQvdDRgD/6KHmb1x8iqDfwkCH+/vypTICLnSATr9r7vMAeYIGJMh6WjjF2wQXRyZAj8qJAmHk8M/ewyj8wcztmbsHMZzFzfN0svdB+HW7xmr74wv0Y07wyjHwE5luNxq2nFEYEVB2Wxc3qyau3lirib6ow4h07RuNHUEi8/LJ7/Q8/2JZwTkfMdu3CH7pKxRNPpLasy5Yff0xcd/q+REG+4oCFiHiiB+H++4Hnn3f/w5l/zO7d7XIU4/Fu3trXXZdYn4uQDkcfrUJ2u3n39uzpHpo9lXftP//pve3kkxNDpwjuuDkPNm+u8k4A7v4XqZKQhYGWBVDhc7p3Dy96stNvJQ5h070SuhUQokCCULWqCszmZkt+wgl22cyJoHstXvGowiBVkLazzsptW336uIelqFgxsWdy8slKaQVNCrRsWekMs2TDp5+612svc7eItI/kOd2PGVRRYw715hK3HnrUuEWSLjBEgeQac+LXfMvWN3A+QklXqKAcwI49Vk3qP/RQ8j4jR4YvhxvpckBr+vXz3pbKiEFQeIVd1xGOzaCLcSJdHvYOHYKd1xlXzRkxIQryYTwQMqJAck27dspU8PnnE0MQ6J5HqgdjLmXQE+jz5wM33JC8z8UXhy+HGz/95G+/IUO8t6V7yADAqFH+2ilWvIwU9ItMKkMQE7dYVlHizAzqF93bef55FQfr44/t5FtRkUnE65giCiRb3Hwf/u//kh/QjRsr+++nngpfJj/Z6J5/Pr8hrXVyKmfoeC/mz/fe5mcS/Ywz/LVTrOTqt833vMg//6nSEnjlwDCjS2eCNuPduhW49FJVDtqbEXYjCiRbMkkM1bx5ft464hi9c8MG9dbnNy3qqae619eokT7VbimGcXcyaZJ7vTPLYDr8JEzLhpUrE9dHj1ZpCY46yn3/oHTvroaXC8hJrxAQBZItMY6UGStq1kw0MEiHV7Re04x33DjgkEMSHza3316aiaSceE3QOsO9r1uX+jzOSMe5xuk35ZY/JBdUqgTcemty0jIhK0SBZEsUHq2lQM+e7vVTptiOi4Dyfp82TSWu6toVuPfe/MgXd7wi6Jqms0D6qLRRJXzKB6aZvRAIUSDZEpecE26+FoWMW3ZFQA2FaU/runWB//xH5U0YNCizmErFjmnqfP31djnTmGxRviAR2XNhYczX+R1OFTwRBZItfieFw2affZQvhpf5ZqHhzE7oRq1aakL0rLMKMo5Q3nj4Ye85EUDNQ3hNlkf9nepsiLlUIDqdbL7NaLdtsxPPRWUFmWMK344sasw/WDZZ2nJBvi1mwsRPEqN0ASQFG9PiyBk4sWFDoFEje/3yy4Fnn1XlfCiQSy9VnvOp4lNpBZKLxG1hGwZ4sWWLmsPLp/VjyEgPJJfobHmCEAf22MM9na1bumIzrW0+oyUAwNCh6S3r9EN3zpzw5QmLjh2LIoCiifRAhMKAWQ1TmW9vNWsCM2dG90YZdzZscK9fvDi57uST7XIY0aKzYe5c29qx2Ob6ChzpgQjxRzuBOXNp16gBHHEEcPDB+ZepEEnlXGn6M8VBgZjGKeedp8y1w0CsKLNCFIgQf3QkY2ccrWI2MQ2DN99MXDfnmeLQizPDr5hx5NwSleWKTZvCO3cJIApEiD/ae3/ChMT6uFjAFSpmj65qVbWsVMn2Vh89Or/yHHSQXc5Xzpc2bfLTTpEiCiQXfPEF8O9/Ry1F8aLHv3XWPE0RBKPLK86wO25v37VqAa1bq++2R4/8yKU5+mi7nK9hyUz9YrLhiitSp1goQESB5IKOHcPLYyDYCsSPb4jgjVMBOx0vX3oJGD9eRUzesSP/8wNmlkovR1LtF5ItrVrl5jx+YFbh4888Ezj77Py1mwdEgQjxR8cv6tkTeOutcFIClwI6qZnGmdmxTx/gsMPs9Mv5zhtu+pxceKF75snhw3PT1pVX5uY8fvjrX1WE7IYNgV9/zV+7eUDGAIT4s3WrssohAk47Tb09mn4LQjD22MO9PsrwPMcco4bOmja117UX/b33AkcemZt27r47N+fxg3bKBFQ+oDfeyF/bISM9ECG+nHaaWjofaAcdlP/x+WKkVy/3em3GG4WJ68SJwIABieua2bNz1445XBYmRe63Ij0QIb689VbUEhQf9evbcyFaQTuZO1ct4+IjwQyMGAF06pS7c5r52MMcqtPDgUWKKBAhvlxzjUphOmZM1JIUD3PnKvNcIm8rtokT1Xcep9wZubZeMlL1Vty8ObfnLiFEgQjxRRJD5Z7Jk22LwUsucd+nZcvSCnWeaQ+EWZk6jx2becItZwbGAkfmQAShlBDvfZt77wX23Rc7Mv1OzjlH9eSc2R2J1GftWrXuNv+RKqx+ASIKRBBKiQryl9/N7berOGuZpqVu0iS5zvSc11G5i3z+AxAFIgilhTaPFYCRI4Hq1VFt2bLMjjNDrrgxb17JDL+KAhGEUsIMWFjq7NwJbN6MvaZNy+y4Rx9NrnMaJFxzjfuxRabARYEI8eXOO4sm9Wds0OlcBeCBBwAALZ94IrOovGb2RkBZCvqZHN9//+izluYYscIS4stdd0UtQfFRrZryhO7YMWpJosfsNWQyN3TGGSo0iaZ5c3/H/fCD/zYKBOmBCEKpceaZKi5TqWOmoDa939OxZYtaVq1qW1yl4pprkvPQFwmiQARBKE3q1rXLjz8OvPOOrRxSoYcBt2xRE/HpePzxopv70IgCEQShNGnZMnH9tNOAF19Mf5wZkv222xK39emTuJ6r8PMxRRSIIAilidsw3gcfpD9uyBC77AzPfuedieuTJ2cuVwEhCkQQhNKkQ4fkurffTn/cww97b2vRInE9LgEpQyI0BUJEVYloKhHNJqJviOhuq74LEX1FRF8T0TAiEkswQRDyjzPBVhjstVf4bURImD2QrQC6MHNrAEcA6EZExwAYBqA3Mx8KYCmAviHKIAiC4E2YfjGXXx7euWNCaAqEFeXWaiXrsxPAVmZeYNV/DODPYckgCIKQksqVE9edE+tO9JzHwIHAnDmp9811CPoYQswc3smJygDMANACwFMAbgGwBMCfmXk6ET0O1Us5zOXYfgD6AUDDhg3bjBgxIpAM5eXlqFlkEUjlmgoDuabCoFPnzrvLv7VogRlDh3ru2/aii1Bj6VLXbdv23BOTRo3afb6Zjz+ODYcfnlthfaJ/p86dO89g5qNCa4iZQ/8AqANgHIBDAXQA8DmAqQD+CWBmuuPbtGnDQRk3blzgY+OKXFNhINdUIKgMH+pz1FGp961SJXF/8zNsWOL5Jk4MX3YP9O8EYDqH+GzPywQ2M68novEAujHzwwD+CABEdBKAVvmQQRAEIS3Tp6fe7jVn4jaSQ5S9PDEnTCus+kRUxypXA3ACgO+IqIFVVwXAzQCGeJ9FEAQhQjZtAmrXDpZW2StlcBERphXWPgDGEdEcANMAfMzMYwDcSETzAMwBMJqZx4YogyAIQnB++gnYuDF5Qvykk9IfW6lSODLFiDCtsOYw8x+Y+XBmPpSZ77Hqb2Tmg5j5QGYeFFb7giAIfpj82muJYdbnz7fLOgjipk3AuHF2/YMPpj/xoYfmRL44I57ogiCUNFsbNEiMzNuvn13esMEuP/qoUiSffw60bg0ceaSq//RT9xPLEJYgCEKJYebt+Ooru7x2LVC9uq1s9LYuXRKPv+oqYM89w5UxJogCEQRBAOw0tMuX23VnnmmXv/wSuOIK4N571fphSe5rigcfBBYtCkfGmCEKRBAEAQB69Uqua9vWLu/aBTzzjMrvAQBTprgnlKpWrWR6IMU/SCcIguCHzZuT68rLk+t0OJNq1dSnhJEeiCAIAuCe/Klr1/zLUUCIAhEEQQCAJk3U8pBD7Do//h4ljCgQQRAEk2++scsLrMDh1atHI0vMEQUiCILgZNs2tXz9dbUcPTo6WWKMKBBBEAQnM2cmrh90UDRyxBxRIIIgCE4++yxxva8kTnVDFIggCIKTDh0SQ7QvXAi0a2dvEwCIAhEEQbAZawUH37ULOOMMu752baBKFVXWARYFUSCCIAi70QEQt28H3n47cZuO2Pvzz/mVKcaIAhEEQdAsXqyWXhF2ASCiPOdxRBSIIAiCpn17tRw4MLHetMKaNi1/8sQcUSCCIAiaVq3c6195xS5XrpwfWQoAUSCCIAianTujlqCgEAUiCIKg2b49ue622xLzggi7kXDugiAImkqVkuvuuQcoK8u/LAWA9EAEQRA0TkXRvDlQQR6TXsg3IwiC4IUzNe1xx0UjR0wRBSIIgmDCDOyzjypffXXitnPOyb88MUYUiCAIghPtbT54cGL92WfnX5YYIwpEEATBi3XrEtfr1YtGjpgiCkQQBMGLSy5JXJ86NRo5YoooEEEQBCd9+qjlZZcl1r/wQv5liTGiQARBEJzUrq2WW7Yk1m/YkH9ZYowoEEEQBCddu6rloYcm1rdtm39ZYox4oguCIDg54wxg0yagevXEep2VUAAgPRBBEAR3TOXRpQvQoAHQsWN08sQQ6YEIgiCkI1WCqRJGeiCCIAhCIESBCIIgCIEQBSIIgiAEIjQFQkRViWgqEc0mom+I6G6rvisRfUVEs4joCyJqEZYMgiAIQniE2QPZCqALM7cGcASAbkTUHsAzAM5n5iMAvALg9hBlEARBEEIiNCssZmYA5dZqJevD1mcPq742gBVhySAIgiCER6hmvERUBmAGgBYAnmLmKUR0KYD3iGgzgI0A2ocpgyAIghAOpDoKITdCVAfAmwCuBnAPgAcsZXIjgAOZ+VKXY/oB6AcADRs2bDNixIhAbZeXl6NmzZqBZY8jck2FgVxTYVDM19S5c+cZzHxUWO3kRYEAABHdCeB3AP2ZublV1wTAB8x8cJpjVwNYGrDpegDWBDw2rsg1FQZyTYVBMV9TU2auH1YjoQ1hEVF9ANuZeT0RVQNwAoAHANQmolbMvADAiQDmpTtXNl8AEU0PUwNHgVxTYSDXVBjINQUnzDmQfQAMs+ZBKgB4nZnHENFlAN4gol0A1gH4S4gyCIIgCCERphXWHAB/cKl/E2o+RBAEQShgSsET/d9RCxACck2FgVxTYSDXFJC8TaILgiAIxUUp9EAEQRCEEBAFIgiCIASiqBUIEXUjovlEtJCIbomBPM8T0Soi+tqo24uIPiai763lnlY9EdFgS/Y5RHSkcUxfa//viaivUd+GiOZaxwwmIkrVRo6uaT8iGkdE86ygmX8r9OtKEQh0fyKaYrX3GhFVtuqrWOsLre3NjHMNsOrnE9GfjHrXe9OrjVxBRGVENJOIxhTDNRHREuvemEVE0626gr33rHPXIaL/EdF31v+qQ2yviZmL8gOgDMAiAAcAqAxgNoCDI5bpOABHAvjaqHsQwC1W+RYoL30AOBnA+wAIKtzLFKt+LwA/WMs9rfKe1rapADpYx7wPoHuqNnJ0TfsAONIq1wKwAMDBhXxdVjs1rXIlAFMsWV8H0NuqHwLgr1b5CgBDrHJvAK9Z5YOt+64KgP2t+7Es1b3p1UYOf6/roIKYjknVXqFcE4AlAOo56gr23rPONwzApVa5MoA6cb2myB6mYX+sL+hDY30AgAExkKsZEhXIfAD7WOV9AMy3ys8CONe5H4BzATxr1D9r1e0D4Dujfvd+Xm2EdH1vQzmIFsV1AagO4CsAR0N59lZ03l8APgTQwSpXtPYj5z2n9/O6N61jXNvI0bU0BvApgC4AxqRqr4CuaQmSFUjB3ntQgWYXwzJwivs1FfMQ1r4Alhnry626uNGQmX8GAGvZwKr3kj9V/XKX+lRt5BRrmOMPUG/sBX1d1lDPLACrAHwM9Xa9npl3uMixW3Zr+wYAddNck1t93RRt5IJBAG4CsMtaT9VeoVwTA/iIiGaQip8HFPa9dwCA1QBesIYanyOiGnG9pmJWIORSV0g2y17yZ1qfF4ioJoA3APydmTem2tWlLnbXxcw7WeWsaQygHYCDUsiRq2sK7VqJqAeAVcw8w6xO0V7sr8miIzMfCaA7gCuJ6LgU+8ZNdjcqQg1zP8PMfwCwCWo4yYtIr6mYFchyAPsZ640Rz9wjvxDRPgBgLVdZ9V7yp6pv7FKfqo2cQESVoJTHcGYelabNgrkuAGDm9QDGQ40v1yEiHb3BlGO37Nb22gDWIvNrXZOijWzpCKAnES0BMAJqGGtQgV8TmHmFtVwFFeGiHQr73lsOYDkzT7HW/welUGJ5TcWsQKYBaGlZgFSGmgh8J2KZ3HgHgLaQ6As1h6DrL7SsLNoD2GB1Kz8EcBIR7WlZSZwENab8M4DfiKi9ZVVxoeNcbm1kjdXWfwDMY+ZHi+G6iKg+qRQEIDsQ6DwA4wD08rgmLUcvAGNZDSS/A6A3KYum/QG0hJrAdL03rWO82sgKZh7AzI2ZuZnV3lhmPr+Qr4mIahBRLV2Gume+RgHfe8y8EsAyIjrQquoK4NvYXlOuJrPi+IGyUFgANX59WwzkeRXAzwC2Q70JXAI1RvwpgO+t5V7WvgTgKUv2uQCOMs7zFwALrc/FRv1RUH+gRQCehB1pwLWNHF3TsVBd4DkAZlmfkwv5ugAcDmCmdU1fA/iHVX8A1MNyIYCRAKpY9VWt9YXW9gOMc91myT0flrVLqnvTq40c34edYFthFew1WeedbX2+0W0W8r1nnfsIANOt++8tKCuqWF6ThDIRBEEQAlHMQ1iCIAhCiIgCEQRBEAIhCkQQBEEIhCgQQRAEIRCiQARBEIRAiAIRcgIR1SUVEXUWEa0kop+M9UlRy+fEChFxcEjnvouIbgjj3BnKcRERNTLWQ7tmoTQJLSe6UFow869Q9usgorsAlDPzw5EK5QERlTHzpVHLkQmWzDszPOwiKHt/7a1dUJwhr/MAAAR4SURBVNcsxB/pgQihQ0Tl1rITEX1GRK8T0QIiGkhE55PKvTGXiJpb+9UnojeIaJr16ehyzkOs42aRyoPQ0qrvY9Q/S0RlWgYiuoeIpgDoQETjiegoa9tJRDSZiL4iopGk4nrBku9b6/xJypBU/oS3rO1fEtHhxubWRDSWVG6Fy6z99yGiCZZsXxPRH9O0v4SI/kFEXwC4iYimGm03I6I5Vvkf1vf0NRH92/JK7gXlMDbcaq+a45rPtb7zr4noAfO3IqL7SOVC+ZKIGlr1Z1n7ziaiCYFuBKH4yLWXq3zkA+AuADcY6+XWshOA9VChoqsA+AnA3da2vwEYZJVfAXCsVW4CFSbF2cYTAM63ypUBVIMKeDgaQCWr/mkAF1plBnC2cfx4qAdsPQATANSw6m8G8A+oPArzYXvp1vGQ4U6r3AXALOP6Z1sy1YOKitoIwPWwvaXLoPKnuLZvlZcAuMlobxYsj3Brv9ut8l7GPi8BONW8RpdrbgTgRwD1oUYhxgI43fie9PEPGm3MBbCv13chn9L8yBCWkG+msRUymogWAfjIqp8LoLNVPgHAwSpUDwBgDyKqxcy/GeeZDOA2ImoMYBQzf09EXQG0ATDNOrYa7IBwO6ECPjppD5UkaaJ1TGXr3BsBbAHwHBG9C5U/w8mxAP4MAMw81poHqm1te5uZNwPYTETjoIL8TQPwPKngk28x8ywiOt6jfc1rRvl1AGcDGAjgHOsDAJ2J6Cao3CV7QYX1GO0ir6YtgPHMvBoAiGg4VLKztwBsM651BlRuFwCYCOBFInodwCgIAmQORMg/W43yLmN9F+z7sQJUMqPNXidh5les4ahTAHxIRJdCxQUaxswDXA7Zwu5zCATgY2Y+N2kDUTuoYHa9AVwF1ctwHpskmmNpiMwTSIUbPwXAS0T0EIB1Xu1bbDLKrwEYSUSjrPN9T0RVoXpaRzHzMmv+qarHuVLJrdnOzFr2nbB+E2buT0RHW7LPIqIjWM17CSWMzIEIceQjqAc2AICIjnDuQEQHAPiBmQdDRRE9HCoAXC8iamDtsxcRNU3T1pcAOhJRC+uY6kTUypqHqM3M7wH4OywDAQcTAJxvHdcJwBq2c6GcRiq3el2oobtpliyrmHkoVATjI73adxOUmRdBPdTvgN0z0cpijSVzL+OQ36CGyZxMAXA8EdWz5ojOBfCZ5zek5GrOzFOY+R9QIdr3S7W/UBpID0SII9cAeMqaJK4I9aDu79jnHAB9iGg7gJUA7mHmtUR0O1SGugpQUY+vBLDUqyFmXk1EFwF4lYiqWNW3Qz1837be8AnAtS6H3wWVOW4OgN9hh8IGVPTZd6HmcO5l5hVE1BfAjZbM5VDzM17tL/AQ+TUAD0HlIwczryeioVBDgEughsk0LwIYQkSboVLJ6mv+mYgGQIVZJwDvMXO60N0PkTJUIChFPTvN/kIJINF4BUEQhEDIEJYgCIIQCFEggiAIQiBEgQiCIAiBEAUiCIIgBEIUiCAIghAIUSCCIAhCIESBCIIgCIH4f/kYkJhwB6x0AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(total_price_evol['last'],'r--', color = 'r')\n",
    "plt.title('Evolution of the Total price')\n",
    "plt.xlabel('Time series observations')\n",
    "plt.ylabel('Price')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Descriptive statistics using the trade files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EDF"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## 3.1. Trades durations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(edf_trades)):\n",
    "    trades = edf_trades[i]\n",
    "    trades['dif'] = trades['ts'].diff()\n",
    "    edf_trades[i] = trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max difference: 556.4969999999958\n",
      "Min difference: 0.0\n",
      "Mean difference: 6.222301475755643\n"
     ]
    }
   ],
   "source": [
    "trades = pd.concat(edf_trades)\n",
    "print('Max difference:', trades['dif'].max())\n",
    "print('Min difference:', trades['dif'].min())\n",
    "print('Mean difference:', trades['dif'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(trades['dif'])\n",
    "plt.title('Trades durations')\n",
    "plt.xlabel('Observations')\n",
    "plt.ylabel('Trades durations')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# An histogram keeping interesting values only.\n",
    "trades1 = trades[trades['dif'] >= 0.001]\n",
    "\n",
    "plt.hist(trades1['dif'],100)\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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z589fFxF9zfYr+yT1AeMP6bfMBO7LbW8hm87jT4GTgOmSZkXEFQWxLAOWAfT19UV/f39LAVx27XVcur7sGH15m8/sn/A6x2pwcJBWv5dO161t69Z2gdtWZ6V+Q0p6VVF5RNza4nmLLlVFRHwK+FSJeBYCC2fNmtXi6avluZrMrBuU/RP6L3Lv9wVeDqyj9cn6tgBH5LYPBx4oe3BErAJW9fX1nd3i+c3MrImyl5gW5rclHQF8eBznvQOYLeko4H7gDOBPxlFfx/AdTWbWLcrexTTcFuDYpnsBkpYDtwPHSNoiaXGaquM8svmdNgErIqL0LbRectTMrHplxyAuI02zQZZUjgd+UObYiFg0QvkaYE2ZOgqO7fhLTI1xCI9HmFldlR2DWJt7vwtYHhG3VRBPKZ0+SN3gy01mVmdlE8RK4ImI2A3Zg26S9o+IX1UX2sjq0IMwM6u7smMQtwD75bb3AwofZDMzs+5QNkHsGxFDjY30fv9qQmrOg9RmZtUby3oQL2tsSDoBqGCiinIiYlVELJk+vf3TWpThsQgzq6OyYxDnA/8kqfEw22HAf6kmJDMz6wRlH5S7Q9KLgGPIpsn4UUT8ptLIzMysrUpdYpL0XmBaRGyIiPVAj6Rzqw1t1HhqOQbhxYXMrE7KjkGcHRHbGxsR8QjQtltM6zYGAU8nBCcGM6uLsglir/xiQWnBn32qCan7OUmYWR2UXlEOWCHptZJeAwwAX60urMnBicLMOlnZBPE3wLeAc4BzgZuBD1QV1GTiJGFmnWrUBCFpqqQPA/8fOAuYBfQDs5sdW6W6DlKPxEnCzDpRs1/yHwEOAo6OiJdFxEuBo4DpwEerDm4kdRykHisnDTNrt2YJ4g1kdzA92ihI798DnFplYJONE4KZdZpmCSIiIgoKd/P0+hA2QZwkzKyTNEsQd0p6+/BCSW8FflRNSGZm1gmaTbXxXuCfJb0LWEfWa/h9sum+/6ji2MzMrI1GTRARcT8wNz378BKyeZhujIhb9kRwI6nLinJmZnVWdrK+bwDfqDiW0rp9RTmPRZhZJ2jbswxmZtbZnCA6mCf4M7N2coIwM7NCThAdZnhvwb0HM2sXJwgzMyvkBGFmZoVqmSC6bTZXM7NOVMsEMRlmcx3OYxFmtqfVMkFMVkUD2E4cZlYVJwgzMyvkBGFmZoWcIMzMrJATRBcYPg6x/n7f3WVm4+cEUTMelDazPcUJwszMCjlB1NBIvQjf9mpmE8kJoqY8qZ+ZVa1jEoSkoyVdJWllu2MxM7OKE4SkqyVtlbRhWPkCSXdJulvSUoCI+GlELK4ynsmm7IJD7n2YWZGqexDXAAvyBZKmAJcDpwBzgEWS5lQch5mZjZEiotoTSL3A6og4Nm3PAy6KiJPT9gUAEfH3aXtlRJw+Sn1LgCUAM2bMOGFgYKCluLZu28FDj7d0aMebsR/PaNtxM0ee2HD9/TtG/byTDA0N0dPT0+4wJly3tgvctk40f/78dRHR12y/qXsimGFmAvfltrcAcyUdDHwIeKmkCxoJY7iIWAYsA+jr64v+/v6Wgrjs2uu4dH07ml+99x+36xlt23xm/4j7n7X0hlE/7ySDg4O0+t+8k3Vru8Btq7N2DFKroCwi4uGIOCciXjBScniqAq8HMSFGG3sY7VZaM5sc2pEgtgBH5LYPBx4YSwWTcT0IM7M9rR0J4g5gtqSjJO0DnAFc34Y4zMxsFFXf5rocuB04RtIWSYsjYhdwHnATsAlYEREbx1ivLzGNUZlLQ758ZGZ5lY7SRsSiEcrXAGvGUe8qYFVfX9/ZrdZhZmaj65gnqcfCPYjxc4/CzJqpZYLwILWZWfVqmSDMzKx6tUwQvsTUmqK5mcrMCuu5nMwmp1omCF9iMjOrXi0ThJmZVc8JwszMCtUyQXgMonXjmWOp7FiDb6E16w61TBAegzAzq14tE4SZmVXPCcLMzAo5QZiZWaFaJggPUu95Iz1Q58Fms+5VywThQWozs+rVMkGYmVn1nCDMzKyQE4SZmRVygjAzs0K1TBC+i6larU6pMdI04lXe8eS7qMyqU8sE4buYzMyqV8sEYWZm1XOCMDOzQk4QZmZWyAnCzMwKOUGYmVkhJwgzMytUywTh5yD2nLE+Z9DsWYgy9Y9nadOqn4vopOcuOikW6061TBB+DsLMrHq1TBBmZlY9JwgzMyvkBGFmZoWcIMzMrJAThJmZFXKCMDOzQk4QZmZWyAnCzMwKOUGYmVmhqe0OoEHSNOAzwK+BwYi4ts0hmZlNapX2ICRdLWmrpA3DyhdIukvS3ZKWpuI3Aysj4mzgjVXGZWZmzVV9iekaYEG+QNIU4HLgFGAOsEjSHOBw4L602+6K4zIzsyYUEdWeQOoFVkfEsWl7HnBRRJycti9Iu24BHomI1ZIGIuKMEepbAiwBmDFjxgkDAwMtxbV12w4eerylQzvejP2otG3HzZzO+vvLzaRbtO/wssb2aPs2fjbaNlIdo9V53MxscsdGef59vqyh6Ljhdef3LTp+eFmR9ffv4KjpU/jZjt2l9m+l/rHUO9GGhobo6elp2/nLaPU7alfbxvvfdP78+esioq/Zfu1IEKcDCyLi3Wn7bcBc4IPAp4EngG+XGYPo6+uLtWvXthTXZddex6XrO2YIZkK9/7hdlbZt8yWvLz3VdNG+w8sa26Pt2/jZaNtIdYxW5+ZLXg/wVHn+fb6soei44XXn9y06fnhZkd6lN3DNgmmc9dXHSu3fSv1jqXeiDQ4O0t/f37bzl9Hqd9Suto33v6mkUgmiHb8hVVAWEfEY8M5SFUgLgYWzZs2a0MDMzOxp7bjNdQtwRG77cOCBsVTg9SDMzKrXjgRxBzBb0lGS9gHOAK4fSwVeUc7MrHpV3+a6HLgdOEbSFkmLI2IXcB5wE7AJWBERG8dSr3sQZmbVq3QMIiIWjVC+BlhT5bnNzGx8ajnVhi8xmZlVr5YJwpeYzMyqV8sEYWZm1av8QbkqSfoFcG+Lhx8C/HICw+kkblv9dGu7wG3rREdGxKHNdqp1ghgPSWvLPElYR25b/XRru8BtqzNfYjIzs0JOEGZmVmgyJ4hl7Q6gQm5b/XRru8Btq61JOwZhZmajm8w9CDMzG4UThJmZFZqUCWKENbFro2itb0kHSbpZ0k/Sz+ekckn6VGrrDyW9rH2Rj07SEZK+KWmTpI2S/iyVd0Pb9pX0b5J+kNp2cSo/StJ3Utu+lGY4RtKz0vbd6fPedsbfjKQpkr4naXXa7pZ2bZa0XtL3Ja1NZbX/91jWpEsQo6yJXSfXMGytb2ApcEtEzAZuSduQtXN2ei0BPruHYmzFLuD9EfFi4ETgvem/TTe07d+B10TE7wHHAwsknQj8A/Dx1LZHgMVp/8VkS/DOAj6e9utkf0Y2O3NDt7QLYH5EHJ973qEb/j2WExGT6gXMA27KbV8AXNDuuFpoRy+wIbd9F3BYen8YcFd6fyWwqGi/Tn8B1wF/2G1tA/YHvku21O4vgamp/Kl/m2TT4c9L76em/dTu2Edoz+FkvyhfA6wmWzWy9u1KMW4GDhlW1lX/Hkd7TboeBDATuC+3vSWV1d2MiHgQIP18biqvZXvTpYeXAt+hS9qWLsN8H9gK3AzcA2yPbI0U+O34n2pb+nwHcPCejbi0TwAfAJ5M2wfTHe0CCOBrktZJWpLKuuLfYxntWJO63QrXxN7jUew5tWuvpB7g/wLnR8ROqagJ2a4FZR3btojYDRwv6UDgy8CLi3ZLP2vRNklvALZGxDpJ/Y3igl1r1a6cV0TEA5KeC9ws6Uej7Fu3tjU1GXsQ414Tu0M9JOkwgPRzayqvVXsl7U2WHK6NiH9OxV3RtoaI2A4Mko2zHCip8YdaPv6n2pY+nw5s27ORlvIK4I2SNgMDZJeZPkH92wVARDyQfm4lS+ovp8v+PY5mMiaIca+J3aGuB96R3r+D7Pp9o/zt6Q6LE4Edje5xp1HWVbgK2BQRH8t91A1tOzT1HJC0H3AS2aDuN4HT027D29Zo8+nANyJd2O4kEXFBRBweEb1k/y99IyLOpObtApA0TdIBjffA64ANdMG/x9LaPQjSjhdwKvBjsmvAf9XueFqIfznwIPAbsr9aFpNdx70F+En6eVDaV2R3bd0DrAf62h3/KO16JVmX/IfA99Pr1C5p2+8C30tt2wBcmMqPBv4NuBv4J+BZqXzftH13+vzodrehRBv7gdXd0q7Uhh+k18bG74pu+PdY9uWpNszMrNBkvMRkZmYlOEGYmVkhJwgzMyvkBGFmZoWcIMzMrJAThNWWpIPTLJvfl/RzSffntvdpob6TJH1lHPF8UdJprR4/rK6jJZ2R254r6eMTUbdZWZNxqg3rEhHxMNnMqEi6CBiKiI/m90kP3ykinnxmDe0laWo8PV/RcEeTPXg2ABAR3yGbl8psj3EPwrqOpFmSNki6gmzW1MMkLZO0Nq3FcGFu39crWxvk28CbcuU9kq5RtobD9yQtLDjPXpI+I+lOSauAQ3Kfbck9OX2ipK+n9/9T0pWSbgY+L+kFkr6VzrFO0txUxSXA/NQbel++dyPpEEnXpzUH/lXSsbm6r5L0L5J+Kum9qfwASTcqW4tig6TTMSvBPQjrVnOAd0bEOQCSlkbEtjT/zzclrSSbyvlK4NXAT4GVueMvBL4aEWcpWxDmO5JujogncvucDhwFHAs8D7gTuKJEbC8FXhURT0jaH/jD9P5FwP8imwZ8KXBeRJyW4j8pd/zfAt+JiDdKeh3Z+iCNtQpeCLwWOBDYlJLkqcDmiDgl1TW9RIxm7kFY17onIu7IbS+S9F2yHsWLyRLIHODHEXFPZFMKXJvb/3XAXymbnvubZFNEPH/YOV4FLI+IJyNiC9kEfGVcl0s0zwKuUrY64ECKqZlXAl8AiIivAc9LcwVBNtXFryObXG4bcCjZ9B4LJF0i6RURsaNknDbJuQdh3eqxxhtJs8lWPHt5RGyX9EWyX/gw8nTMAk6LiHuanGek43fx9B9g+w777LHc+/eTrSHwVmBvYKjJ+RqxjbT977n3u8kW7dkkqY+sJ/ERSasj4u9KnMcmOfcgbDJ4NvAosDNNz3xyKr8TeGGa2VfAotwxNwHva2xIemlBvbcCZ6SxiJlkl6oaNgMnpPdvGSW26cCDqQfzDp7+Zf8ocMAIx9wKnJniOgnYEhGPjbAvKbahiPgC8DGg9msl257hHoRNBt8lSwYbyMYabgOIiF9JOge4kWzpy9uAY9IxFwOfkLSe7A+pu8kNYicrgfmp3rvIfnE3XAR8TtLPyWYtHcmngZWSFgFf5+kewPeAKZJ+QDYF+p25Yy4kG+D+IVmP451N2v97wCWSngR+DZzTZH8zAM/mamZmxXyJyczMCjlBmJlZIScIMzMr5ARhZmaFnCDMzKyQE4SZmRVygjAzs0L/AZZRCOkrA/QJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Log Scale\n",
    "trades1 = trades[trades['dif'] >= 0.001]\n",
    "\n",
    "plt.hist(trades1['dif'],1000)\n",
    "plt.title('Histogramme - Log-scale')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.yscale('log')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fitting an exponential distribution\n",
    "graph_duration = sns.distplot(trades1['dif'], fit = expon)\n",
    "plt.title('Histogramme + Exponential distribution fitted')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_duration = sns.distplot(trades1['dif'], fit = expon)\n",
    "graph_duration.set_yscale('log')\n",
    "plt.title('Histogramme - Log- scale - + Exponential distribution fitted')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2. Trade sizes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max size: 19530.0\n",
      "Min size: 1.0\n",
      "Mean size: 212.51439302392802\n"
     ]
    }
   ],
   "source": [
    "# Some statistics about trade sizes\n",
    "print('Max size:', trades['lastQ'].max())\n",
    "print('Min size:', trades['lastQ'].min())\n",
    "print('Mean size:', trades['lastQ'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting an histogram of the trade sizes\n",
    "plt.hist(trades['lastQ'],200)\n",
    "plt.title('Histogramme - Trade sizes')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(trades['lastQ'],200)\n",
    "plt.yscale('log')\n",
    "plt.title('Histogramme - Log-scale - Trade sizes')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GuQZjZladE0yDfBWZmVl1TjANcg3GzKw6J5gx4j4YM7PhnGAa5CYyM7PqnGAa5CYyM7PqnGAa5ARjZladE0yDfB+MmVl1TjANcg3GzKw6J5gGuQZjZladE0yDyleRlR88ZmZmGSeYBrkGY2ZWnRPMGHEfjJnZcE4wDSo3kfX29g7VZszMzAmmYfmk4n4YM7MdnGAalE8wbiYzM9vBCaZBTjBmZtU5wTQon2B8JZmZ2Q5OMA1yDcbMrDonmAaVryID12DMzPKcYBoUEXR0dAC+iszMLM8JZgx0dXUBrsGYmeU5wTSoVCrR2dkJuA/GzCzPCaZBEcGUKVMA12DMzPKcYBoUEa7BmJlV4QTToIgY6oNxgjEz28EJpkGuwZiZVdc20QE0u8HBEutT18v196xh+02PAPDWow6awKjMzCaeazANKkXQ1pHVYAYGfB+MmVlZoQlG0nGSVkhaKemsKss7JV2Wlt8kaWFu2YfS/BWSjk3zDpR0raS7JS2X9Pe59feW9AtJ96X/9yry2MoigvZygul3E5mZWVlhCUZSK/Bl4HhgEfAWSYsqVjsVWB8RhwJfAM5L2y4CTgKOAI4DvpLKGwDeHxHPAV4GnJ4r8yzg6og4DLg6vR4HQXt7dif/gO/kNzMbUmQN5khgZUQ8EBF9wKXA0op1lgLfStNXAEdLUpp/aUT0RsSDwErgyIhYExG3AkTEZuBuYEGVsr4FnFjQcQ0TpaClrY2W1jbXYMzMcors5F8APJp7vQo4qtY6ETEgaSMwJ82/sWLbBfkNU3Pai4Cb0qx5EbEmlbVG0r7VgpJ0GnAawLx58+ju7t7NwxouokRbz0Y62tuJjWvoWncPAN3dDzRUblG2bNnS8DGPl2aKFRxvkZopVmiueIuMtcgEoyrzKh9aX2udEbeVNB34PnBmRGzanaAi4gLgAoDFixfHkiVLdmfzKuVBaeretHVNoadlKj1znw3Akj30KrLu7m4aPebx0kyxguMtUjPFCs0Vb5GxFtlEtgo4MPf6AGB1rXUktQGzgKdG2lZSO1lyuTgifpBbZ62k+Wmd+cATY3YkI4gIJNHe0Ul/n4eKMTMrKzLB3AwcJukQSR1knfbLKtZZBpycpt8EXBPZE7yWASelq8wOAQ4DfpP6Zy4E7o6Iz49Q1snAf4/5EVURUUoJpssJxswsp7AmstSncgbwc6AVuCgilkv6OHBLRCwjSxbflrSSrOZyUtp2uaTLgbvIrhw7PSIGJb0SeBtwh6Tb0q7OjogrgU8Bl0s6FXgEeHNRx1ZxnK7BmJlVUeid/OmD/8qKeR/NTfdQIxFExLnAuRXzrqd6/wwR8SRwdIMh77YswbTQ3tlJf1/PeO/ezGyP5Tv5GxQR0JJqMB6u38xsiBNMg8o1mDY3kZmZDeME06AdfTBdDDjBmJkNcYJp0PA+GCcYM7MyJ5gGRQQa6oNxJ7+ZWZkTTAOyW3bIajCpD6Y8z8xssnOCaUCpVAJAgvaO7LHJHvDSzCzjBNOAHQkm64MB3A9jZpY4wTRgRxOZhh465n4YM7OME0wD8jWY8mOTXYMxM8s4wTRgqAbToqE+GCcYM7OME0wDdtRgNNQH45stzcwyu51gJLVImllEMM2m8jJlcB+MmVlZXQlG0nclzZQ0jWwI/RWSPlBsaHu+YTUY98GYmQ1Tbw1mUXo08Ylkw+8fRPZclkltKMG0tDjBmJlVqDfBtKdHFZ8I/HdE9AOT/pb1HXfti/bO1MnvIfvNzID6E8zXgIeAacB1kg4GNhUVVLNwE5mZWW11PdEyIv4D+I/crIcl/UkxITWPHU1k+QTjTn4zM6i/k3+epAsl/TS9XgScXGhkTSB/FVlbewfgGoyZWVm9TWTfBH4O7J9e3wucWURAzSQ/VIxasrv5B9wHY2YG1J9g5kbE5UAJICIGgMHComoS+aFigKEh+83MrP4Es1XSHNKVY5JeBmwsLKomke+DgXKCcR+MmRnU2ckPvA9YBjxT0q+BfYA3FRZVk8j3wYBrMGZmefVeRXarpFcDhwMCVqR7YSa1/GXKAO2dXb4PxswsqfcqstOB6RGxPCLuBKZLek+xoe35ygkG5ZvInGDMzKD+Pph3RsSG8ouIWA+8s5iQmkf+KjJwgjEzy6s3wbSo/CkKSGoFOooJqXlUXkXW5k5+M7Mh9Xby/xy4XNL5ZFeSvQv4WWFRNYmdriLr7PTzYMzMknoTzAeBvwXeTdbJfxXwn0UF1Sx2vorMnfxmZmV1NZFFRCkivhoRb4qIN0bE1yJilzdaSjpO0gpJKyWdVWV5p6TL0vKbJC3MLftQmr9C0rG5+RdJekLSnRVlnSPpMUm3pZ8T6jm2RrgPxsystnqvInuFpF9IulfSA5IelPTALrZpBb4MHA8sAt6SxjDLOxVYHxGHAl8AzkvbLgJOAo4AjgO+ksqDbNia42rs9gsR8cL0c2U9x9YI38lvZlZbvZ38FwKfB14JvBRYnP4fyZHAyoh4ICL6gEuBpRXrLAW+laavAI5OFxMsBS6NiN6IeBBYmcojIq4Dnqoz7kJV64MZHOinNDjpR9ExM6u7D2ZjRPx0N8teADyae70KOKrWOhExIGkjMCfNv7Fi2wV17PMMSW8HbgHeny6nHkbSacBpAPPmzaO7u7uug6nm4YcfBqBz82N0rbuHqf3ZI3JaVt9Od/fDoy63SFu2bGnomMdTM8UKjrdIzRQrNFe8RcZab4K5VtJngB8AQ21AEXHrCNuoyrzKp2DWWqeebSt9FfhEWu8TwOeAd+xUSMQFwAUAixcvjiVLluyi2Npuv/12APpnHkjP3GfTMjdrNdw07QDeuuQloy63SN3d3TRyzOOpmWIFx1ukZooVmiveImOtN8GUax6Lc/MCeM0I26wCDsy9PgBYXWOdVZLagFlkzV/1bDtMRKwtT0v6OvDjkdYfCzuayLKWxo6uqQD0bt9W9K7NzPZ49Y5FNpqnV94MHCbpEOAxsk77t1ass4zswWU3kA2eeU1EhKRlwHclfZ7sGTSHAb8ZaWeS5kfEmvTyz4E7R1p/LFReRdY5JUswfT3bi961mdkeb9RPtJR06kjbpGfGnEF2k+bdwOURsVzSxyW9Ia12ITBH0kqyEZvPStsuBy4H7iK7ofP08mXRki4hS0iHS1qVi+PTku6QdDvwJ8B76zwHo1Y52GVn1xQAentcgzEzq7eJ7JvAN4APp9f3ApeRJYia0qXCV1bM+2huugd4c41tzwXOrTL/LTXWf9tIsRRhqAZTbiKb4iYyM7MyP9GyATvXYLIEc+fDT3Daf90yYXGZme0J6q3B+ImWVVQOFdORmsjWrd/IIw/vdIW0mdmk4idaNmCnGky5iaxnG70DpQmLy8xsT7DLBKPs63kX4CdaVqi8TLmtvYOW1jb6e7bT0z/pWxDNbJLbZR9MRJSAz0XEQPmJlk4umXITWV7nlKn0925noBQMDLoWY2aTV72d/FdJemP+oWO282CXkF2qPNCbPXSsx81kZjaJ7U4fzDRgQFIPWTNZRMTMwiJrApWDXULW0V/qy2607O0fZHpnvafYzOzppd47+WcUHUgzqryKDKC9cyr0ZMO1uQZjZpNZXQlG0quqzU9D509alVeRAbR2dqGBzQDu6DezSa3e9psP5Ka7yJ7N8ltGHuzyaa9aDaa1YwoMZH0wvf2uwZjZ5FVvE9nr868lHQh8upCImki1Phi1d6GBchOZazBmNnnVexVZpVXAc8cykGZUrQaj9k7oTwnGTWRmNonV2wfzRXY88KsFeCHw+6KCahbV+mBo60KDvRAlN5GZ2aRWbx9MfuTGAeCSiPh1AfE0lXKCIZdgoq0zmxjoo9dNZGY2idWbYK4AenLPZGmVNDUiJvW49JUPHAMoDSWYXnpcgzGzSazePpirgSm511OAX459OM2l2p38gy0d2byBXvfBmNmkVm+C6YqILeUXaXpqMSE1j2pXkQ20lGswPU4wZjap1Ztgtkp6cfmFpJcAk/7B89WuIhvI1WA8ZL+ZTWb19sGcCXxP0ur0ej7wF8WE1Dyq9cH0qT2bcB+MmU1y9d5oebOkZ7PjeTD3eMj+6pcp95IlmLbBXt9oaWaTWl1NZJJOB6alZ8HcAUyX9J5iQ9vzVT5wDKCnnGBKfe6DMbNJrd4+mHdGxIbyi4hYD7yzmJCaR2UTWUTsqMFEn/tgzGxSqzfBtOQfNiapFegoJqTmMVSDITs1fQMlSmpDLa20DvoyZTOb3Ort5L8KuFzS+WRDxrwb+FlhUTWJyiay7f2DINHWOYWWgR4PFWNmk1q9CeYjZE1i7yLr5L8KuLCooJpFZRPZ9lRj6Zg6Hfp9H4yZTW4jJhhJbcAngb8GHiVLLgcCD5I1r03qT9DKq8i292Wno2vqDHr6troPxswmtV31wXwG2Bt4RkS8OCJeBBwCzAI+W3Rwe7rKoWLKNZgp02YQvdtcgzGzSW1XCeZ1ZFeQbS7PSNPvBk4oMrBmUh4qplyDmTp9BoO9W30fjJlNartKMBHljobhMwfZ8XyYSatWDWbajJkM9mx1J7+ZTWq7SjB3SXp75UxJfwXcU0xIzaOyD6anfxCRJZiBnm1s75v0gx2Y2SS2qwRzOnC6pG5Jn5P0WUm/Av4PWTPZiCQdJ2mFpJWSzqqyvFPSZWn5TZIW5pZ9KM1fIenY3PyLJD0h6c6KsvaW9AtJ96X/99pVfI2qHOxye/8gXe2tTJ0+Awh6tm0tOgQzsz3WiAkmIh6LiKOAjwMPAY8AH4+IIyPisZG2TTdjfhk4HlgEvEXSoorVTgXWR8ShwBeA89K2i4CTgCOA44CvpPIAvpnmVToLuDoiDiN7fs1OCW2s7XiiZfbf9r5BpnS0MmXaDAB6tm6usaWZ2dNfXXfyR8Q1EfHFiPiPiLi6zrKPBFZGxAMR0QdcCiytWGcp8K00fQVwdBoxYClwaUT0RsSDwMpUHhFxHfBUlf3ly/oWcGKdcY5atT6YKe07Ekzf9i01tzUze7qr90bL0VhAdu9M2SrgqFrrRMSApI3AnDT/xoptF+xif/MiYk0qa42kfautJOk04DSAefPm0d3dXdfBVPPAAw8AMOWpe2lpaaF32wDTWmHWQJb/BrZv5Zprr6UlN9ryRNuyZUtDxzyemilWcLxFaqZYobniLTLWIhNMtU/VyivPaq1Tz7ajEhEXABcALF68OJYsWTLqsu68M+sG6t3nOUhia9zLjGldtCx4LgDq38bLX/EqpnS0jlTMuOru7qaRYx5PzRQrON4iNVOs0FzxFhlrvYNdjsYqsrv+yw4AVtdaJ40aMIus+auebSutlTQ/lTUfeGLUkddppzv5K5rI6PPNlmY2eRWZYG4GDpN0iKQOsk77ZRXrLANOTtNvAq5J990sA05KV5kdAhwG/GYX+8uXdTLw32NwDCOKiGEPG+vpH2RKe8tQglH/Ng8XY2aTVmEJJiIGgDOAnwN3A5dHxHJJH5f0hrTahcAcSSuB95Gu/IqI5cDlwF1kozafnm7uRNIlwA3A4ZJWSTo1lfUp4LWS7gNem14XKp9gBkvBYCnoaGulpbWVzilTUd9212DMbNIqsg+GiLgSuLJi3kdz0z3Am2tsey5wbpX5b6mx/pPA0Y3Eu7tKpdJQghkYzGoq7a3Z66nTZ7C1b5uHizGzSavIJrKnvSzBZKewv5Rdg9DWmr2eNn0m6t9Gj4eLMbNJygmmAVkTWTY9VINJA1/OmDkT+rfT6yYyM5uknGAaMLyJrFyDKSeYWahvGz3u5DezScoJpgH5BNOfLlluS49PnjVrVmoicw3GzCYnJ5gGZE1k2Sks12DKnfyzZ82Cvm1s7xuYsPjMzCaSE0wDqtZgUif/7NmzUJTYvMUjKpvZ5OQE04D8fTBDNZjUyT93zt4ArH/qyYkJzsxsgjnBNKDafTDlGsy8ffcBYP1T1QZ+NjN7+nOCaUBEoFRj6a+4imz+vGww5w3rXYMxs8nJCaYBw2owpfJ9MNkp3S/VYDaudw3GzCYnJ5gGZKMpV6/BzJkzBxCbNzjBmNnk5ATTgIgYepjYjrHIslPa2toKXdPZsnH9hMVnZjaRnGAaMLyJLNVgWnYM398yZSbbN22YkNjMzCaaE0wDht0HMxgIaM0lmLZhYz4wAAAUp0lEQVSps9i+2TUYM5ucnGAakL+KbGCwRFurhj2ArH3aLHq3bJyo8MzMJpQTTAPyN1r2l2JoHLKyjumz6NuygewhnWZmk4sTTAPyz4MZGCwNjUNW1jV9NlEaZONG12LMbPJxgmlAZSd/+S7+sqkz9wJg3bp14x6bmdlEc4JpwLAmssHSsCvIwAnGzCY3J5gGlEo7HiY2MBhD98CUzZjtBGNmk5cTTANKpdKOschKO9dgZs7ORlR2gjGzyahtogNoZpUPHOvI1WC+e9MjrN4GtLRx3e0P0HHTIwC89aiDJiJUM7Nx5xpMAyqH62+ruIqsvbWV6JrB5g0eUdnMJh8nmAYMf6Jl7NRE1t4qSlP2YuO6tRMRnpnZhHKCacDwJ1qWdurkb29tIabuxQYnGDObhJxgGjB8NOXYqYmsrUXE1L3ZvOFJrr/3cVY8vnkiwjQzmxBOMA0Y3kRW2ulGy7bWFmLKXhDBz35zNzc/5GfDmNnk4QTTgOGd/EH7Tn0wLcTU7FJltq2np39wvEM0M5swTjANiAiQiIiqQ8W0t4qYliUYbXuKngEnGDObPApNMJKOk7RC0kpJZ1VZ3inpsrT8JkkLc8s+lOavkHTsrsqU9E1JD0q6Lf28sMhjgx01mPLDxiprMG0tLUTXLEItTOnfSE9/qVoxZmZPS4UlGEmtwJeB44FFwFskLapY7VRgfUQcCnwBOC9tuwg4CTgCOA74iqTWOsr8QES8MP3cVtSxlQ0lmMH0NMsqNRhaWmmZOpsZg5vdRGZmk0qRNZgjgZUR8UBE9AGXAksr1lkKfCtNXwEcraxTYylwaUT0RsSDwMpUXj1ljpvyZcr9aUyyyqvIpnS0ArDX3HkMbn6Snv5BPxvGzCaNIoeKWQA8mnu9Cjiq1joRMSBpIzAnzb+xYtsFaXqkMs+V9FHgauCsiOitDErSacBpAPPmzaO7u3v3jipnw4YNtLS00PqHlQBM3baWrnV/GFr+zAje9dxWbl81nbtW3Ecp4Kqru+lsU60iC7dly5aGjnk8NVOs4HiL1EyxQnPFW2SsRSaYap+ilV/fa61Ta361Gle5zA8BjwMdwAXAB4GP77RyxAVpOYsXL44lS5ZUKbI+559/Plu397Jl1iHAfcSs/emZO3vYOgftAw/eeTi9v70FSgO84KUvZ79ZXaPeZ6O6u7tp5JjHUzPFCo63SM0UKzRXvEXGWmQT2SrgwNzrA4DVtdaR1AbMAp4aYduaZUbEmsj0At8ga04rVLmJbKiTv7X66Zw9dx4QaNt6Nvf0Fx2WmdkeocgEczNwmKRDJHWQddovq1hnGXBymn4TcE1knRTLgJPSVWaHAIcBvxmpTEnz0/8CTgTuLPDYgHwnf+qDaane9DVn/gEAaPMTbOoZKDosM7M9QmFNZKlP5Qzg50ArcFFELJf0ceCWiFgGXAh8W9JKsprLSWnb5ZIuB+4CBoDTI2IQoFqZaZcXS9qHrHntNuBdRR1bWTnB9Ne4iqxs7v4HA9Cy+XE2uQZjZpNEoc+DiYgrgSsr5n00N90DvLnGtucC59ZTZpr/mkbj3V0RgVpaGEhXkbW3Vq/BdE2dxrTZc9i4eS2bXYMxs0nCd/I3oFQqIXI1mJbap3Pu/gfTsnktm7a7BmNmk4MTTAMq+2Bq1WAA9l2wEG1ey8ZtO105bWb2tOQE04Bd3cmfN++Ag1FpgNWPPTZe4ZmZTSgnmAbsdCd/javIAPY9YCEAax59cDxCMzObcE4wDcg6+XfUYGrdBwMwd/+DAPjDqofHJTYzs4nmBNOAocuUa4xFltc5ZSot0/Zi/eOPjFd4ZmYTygmmAUN38g8GrdLQ45Nr6Zh7MJtXPzBO0ZmZTSwnmAZkNZgWBgZLI9Zeyqbufyh9G5/gySefHIfozMwmlhNMA3Y0kcWIHfxlMxccCsBttxX+qBozswnnBNOAiEDAwGCM2MFfNnv/Z4BanWDMbFJwgmlAqVRCLaK/3iayKV2UZi/g1t/9bhyiMzObWE4wDRjqgynVV4Ppam+ltPdC7rzzTvr7PWSMmT29OcE0YMdVZKW6+mC62lsZ3Ptg+np7Wb58+S7XNzNrZk4wDRi6k38wRhwmpmxKewuluYfR0tLKr371q3GI0Mxs4jjBNGBoLLJSacSBLss621uhYyqHLnpe0zyv28xstJxgGpAf7HKkofrLprS3AvDsF72Me+65h9WrK58gbWb29OEE04AdTWT1XUXWlRLMwue9FMDNZGb2tOYE04AdTWRBex01mK72bJ3OvfbjoIMO4pe//GXRIZqZTRgnmAYM3clfZw2msy2rwWzuGeT1r389N9xwA4/5+TBm9jTlBNOAocuU67wPprVFTOtoZXNPP2984xuRxPe+971xiNTMbPw5wTQg/8jkeu6DAZjR1c6mnn7mz5/Pq171Kr7//e/7pksze1pygmlAqVQiJEox8rNg8mZ0tbG5ZwCAY/7sRNatW8dPfvKTIsM0M5sQTjANiAiy4S5Hfppl3swpWQ1m5ROb+eCv+5l30KF88YtfpK+vr8hQzczGnRNMA/IJpv4msqwG85Xu+xkIMXXxUlavXs0ll1xSZKhmZuPOCaYBpVKJ0m7WYJ7a2sd9a7fwo989Rld7C3cPzufgRS/mi1/8Io8++miR4ZqZjSsnmFGKiOE1mDr7YLraW9neP4gQb3rxAQTwjOP+mpaWFj7wgQ8wMDBQYNRmZuPHCWaUIiL7f6iJrL5TWR4u5kUHzebZ82cys6uNh7d3cs455/D73/+ej3zkI5RKpWKCNjMbR04wo/TEpu0AlKLcRFZfDWZmVxstglc9ax9aJJ49fyb3rd3Ca157LP/rr07lRz/6Ef949j/50mUza3pOMKMQEZx84U0AQ30w9QzXD/DShXvz3mOexdzpnQA8Z7+Z9A2W+OI19/GDniPof9Yx/OS/f8gpp5ziu/zNrKk5wYyCJN75x4cA8OiWbF69V5G1tbYwJyUXgGfsM42O1ha+fO397D97Cm8++TT6XvKXLL/rbk444QTO/dSn6b7tvjE/BjOzohWaYCQdJ2mFpJWSzqqyvFPSZWn5TZIW5pZ9KM1fIenYXZUp6ZBUxn2pzI4ij+34I+YBsHpb9rreq8gqtbe28MIDZ7P/7C7+9+IDeda86Uw79KV0ve5s9nnOkXznW9/kXW/9c17+upP40oXf5rqbb+eau9aw4vHNY3UoZvY01z9Y4olNPeO+37aiCpbUCnwZeC2wCrhZ0rKIuCu32qnA+og4VNJJwHnAX0haBJwEHAHsD/xS0rPSNrXKPA/4QkRcKun8VPZXizo+iPKRAvXXYKpZ+sL9kXZsf/xz53PZLQOw8ETmP/MYpj56E48tv5Evf/aT2Z5bOynN2p9995vPomcezNqBLu57aoD5++zFcS9cyPOfsR+PbRxg9eY+DpozgyMO2IuBaGHlum3ctrKHjgPW8YIDZ7O1d4CHntzGwGCJ/WZ1MWdaJ5t6+lm/rY8p7a3sO6OLqZ2tbNrez9beQaZ3tTF7SjstLaJvoET/YInOthbaWlsYGCyxuWeAUgQzp7TT3tpCqRRs7x+ktUV0tmUJuKe/xOaefro6WpnRmf369Q6U6OkfZGpHGx1t2Xbb+gfZ0hfZMDwpeZdKQSmCFgmJYefMbLKJCLb0DrBuSx+dbS3Mnd5J/2CJOx7byH1PbGHhnKk8b8EsrrtvHZ+/agUPPbmNY54zjw8ceziH7zdjXGIsLMEARwIrI+IBAEmXAkuBfIJZCpyTpq8AvqTsU2MpcGlE9AIPSlqZyqNamZLuBl4DvDWt861UbiEJ5lOf+tTQIJX7T2/lEaC9bfSVwcoPyucfMItH129j1pR2/uiZc2lteTmbe/r59e/uoveJh+h94kHWPPIATz50N9fdfSOK7Kqz1cBFP971/n78uR3T5avgUiD5qIb9x67Wo+LDXuzIwfnFuznvH2qtVyWsWouqbTaS0W5XK5zRlFNv2fWYLPtvdD9Fl1/PPnZHDP1TsYMqgba0wIwW8eufBNd/FjpaW/jql7/IK17xijGMaGdFJpgFQP7OwVXAUbXWiYgBSRuBOWn+jRXbLkjT1cqcA2yIiIEq6w8j6TTgtPRyi6QVu3FMO7nnnnvmwqfXnXFeI6XUdv7YFzkXWDf2xRaimWIFx1ukZooVmiDeV77yleXJ0cR6cD0rFZlg6vkyV2udWvOrVRNGWn/nmREXABdUWzYakm6JiMVjVV7RmineZooVHG+RmilWaK54i4y1yE7+VcCBudcHkLXiVF1HUhswC3hqhG1rzV8HzE5l1NqXmZmNoyITzM3AYenqrg6yTvtlFessA05O028CronsFvllwEnpKrNDgMOA39QqM21zbSqDVOZ/F3hsZma2C4U1kaU+lTOAnwOtwEURsVzSx4FbImIZcCHw7dSJ/xRZwiCtdznZBQEDwOkRMQhQrcy0yw8Cl0r6F+B3qezxMGbNbeOkmeJtpljB8RapmWKF5oq3sFhVHlPLzMxsLPlOfjMzK4QTjJmZFcIJpgG7GgpnnGI4UNK1ku6WtFzS36f550h6TNJt6eeE3Da7NQxPATE/JOmOFNctad7ekn6Rhvr5haS90nxJ+o8U0+2SXpwr5+S0/n2STq61vwbiPDx3/m6TtEnSmXvSuZV0kaQnJN2Zmzdm51LSS9J7tTJtO+p7BWvE+hlJ96R4fihpdpq/UNL23Dk+P7dN1ZhqHfcYxztm773GeHirGvFelov1IUm3pfnjc36HHpzln936IbvI4H7gGUAH8Htg0QTEMR94cZqeAdwLLCIbyeAfqqy/KMXaCRySjqF1PI8HeAiYWzHv08BZafos4Lw0fQLwU7J7nV4G3JTm7w08kP7fK03vVfD7/TjZDWZ7zLkFXgW8GLiziHNJdvXmy9M2PwWOH+NY/xRoS9Pn5WJdmF+vopyqMdU67jGOd8zee+By4KQ0fT7w7rGOt2L554CPjuf5dQ1m9IaGwomIPqA8FM64iog1EXFrmt4M3E2NUQySoWF4IuJBoDwMz0Qfz1KyIX5I/5+Ym/9fkbmR7H6n+cCxwC8i4qmIWA/8AjiuwPiOBu6PiIdHWGfcz21EXEd2BWZlHA2fy7RsZkTcENmnyn/lyhqTWCPiqtgxAseNZPew1bSLmGod95jFO4Ldeu9TreA1ZENkFR5v2t//Bi4ZqYyxPr9OMKNXbSickT7YC6dsNOoXATelWWekpoeLctXZWnGP5/EEcJWk3yobugdgXkSsgSxpAvvuQfFCdgl9/o9zTz23MHbnckGarpxflHeQfWMuO0TS7yT9StIfp3kjxVTruMfaWLz3dQ9vNUb+GFgbEflnfxR+fp1gRq/IcQ13m6TpwPeBMyNiE9lAn88EXgisIasew+4Pz1OEV0TEi4HjgdMlvWqEdSc83tQ2/gbge2nWnnxuR7K78Y3nOf4w2T1vF6dZa4CDIuJFwPuA70qaOZ4x1TBW7/14H8dbGP4FaVzOrxPM6NUzFM64kNROllwujogfAETE2ogYjIgS8HV2jEa9u8PwjLmIWJ3+fwL4YYptbaqel6vpT+wp8ZIlwlsjYm2Ke489t8lYnctVDG+yKiTudFHB64C/TM0ypKamJ9P0b8n6MZ61i5hqHfeYGcP3ftyGt0r7+F/AZbnjGJfz6wQzevUMhVO41LZ6IXB3RHw+N39+brU/B8pXluzWMDwFxDtN0ozyNFkn750MHzYoP9TPMuDtyrwM2Jiq5z8H/lTSXqmZ4k/TvCIM+/a3p57bnDE5l2nZZkkvS79nb2eMh2CSdBzZKBxviIhtufn7KHumFJKeQXYuH9hFTLWOeyzjHZP3PiXS8Rre6hjgnogYavoat/PbyFULk/2H7Kqce8my/4cnKIZXklVhbwduSz8nAN8G7kjzlwHzc9t8OMW8gtxVQeNxPGRX0/w+/Swv74esTfpq4L70/95pvsgeMnd/Op7FubLeQdaZuhL464LinQo8CczKzdtjzi1Z4lsD9JN9+zx1LM8lsJjsQ/R+4Euk0T/GMNaVZH0U5d/d89O6b0y/H78HbgVev6uYah33GMc7Zu99+lv4TToH3wM6xzreNP+bwLsq1h2X8+uhYszMrBBuIjMzs0I4wZiZWSGcYMzMrBBOMGZmVggnGDMzK4QTjFkdJM3JjTz7uIaPqLvbo+BKOkbSj8Ygrp+X7ysy29MU9shks6eTyO56fiFkQ7YDWyLis/l10o1piuwu7/GK69hdr2U2MVyDMWuApEMl3anseRq3AvMlXSDpFmXP5/lobt0/U/ZckOvJjaYsabqkb0r6TRp88PVV9rNA0vWpxnSnpD9K81dJmi3pdA1/7scv0vLjJd0g6VZlzwaZluZ/RtJdygZtPK/g02STlG+0NNtN+RqMpEPJ7tI+KiJuTsv3join0hhQ1wJ/S/YMnHuBV5M9b+UKoDUiTpT0abKxzi5NQ7XcBDw/Inpy+/wgQEScl4b4mBIRWyStAp4bERvSeh1AN/AJ4Ldkd4gfHxHblA0oGWRDC12TtgtJs8vbm40lN5GZNe7+cnJJ3iLpVLK/r/3JHkY1Fbg3Iu4HkHQx2ThPkI39dbx2PO2wCziILCGV3Qx8TVIX8KOI+H2NWL4E/DQifirpxLTv/8la7+gArid7ZkgJ+LqknwA/Hv2hm9XmBGPWuK3lCUmHAX8PHBkRGyR9hyxhQO1hzwWcWE4+1UTENZKWAH8GXCzpXyPi4vw6kv4G2I+sxlQu92cR8baddigtBl5LNvjiu8mSnNmYch+M2diaCWwGNmnH0yIB7gKelUbVFdkIzWU/B/5P+YWkF1UWKulg4PGIuIBs8MIXVSw/kiyxvS12tHv/D/DqNFpueSTrw9JVZzMj4sfAeyvLMhsrrsGYja1byZLJnWR9Lb8GSH0g7yJ7YuO6NP/wtM3HgH+TdAfZl76V7PxI5aOB90nqB7YAf1Wx/O+AvYFfpeawGyPiXamp7rLcpdRnA9uBH0jqTPt731gcuFkld/KbmVkh3ERmZmaFcIIxM7NCOMGYmVkhnGDMzKwQTjBmZlYIJxgzMyuEE4yZmRXi/wMZrVIKQFSDUAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Trades sizes\n",
    "graph_trades = sns.distplot(trades['lastQ'], fit = expon)\n",
    "plt.title('Histogramme - Trade sizes + Exp. Distrib. Fitted ')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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csPEGGmtSI8aNG8fkz77h4pvvpaxRKvdf0AeLpa5WtdZoNJr6TYOYqy2SOEbcgNWWyMzJbzLxsTso73sBSZZb+ecFfWMtTaPRaOoF8fKMpx4huDv+gYKz70Pa98O2bgb/e/JuZi7SrxNpNBpNOOjAUwuyDpRgb9acf415lktGP4yUHuS+227gtdffYHd+MTsPlMRaokaj0cQtOvDUEqsISQlWTj7DwSX/epWK9ifxvzfH4xhyKec8Opn/pW+NtUSNRqOJS3TgiQAn9+zI4OvupcPFd5HkKSVh/mt8O3kiLpcr1tI0Go0m7tCBJ0Kc27cNN195Cfc89w627gPZ/st3jBgxgt9++y3W0jQajSau0IEnwtibNGXA5bdT9sfRlDqdXHvttTzzzDOUlOjnPhqNRgM68ESF/u1TcLfpzU1PvsnIkSOZPHkyw4cPZ+nSpbGWptFoNDFHB54o0C7FTovGNuZuLeTOex+g7aX3s6fQxU033cSYMWMoLi6OtUSNRqOJGTrwRAER4fj2KSzanMuQVxeyw9KWoj/dS/czhzFt2mdceumlLFy4MNYyNRqNJibowFMNznI3+4tcuN2eGuXr3yEFt1IUlJZz85ndaNsymX1dL+TGR1+mcePGjB49mjvvuZ+DBw9GSblGo9HEJzrwVMPstXs4bewcdh0srVG+ji0acUG/NG45qxvdWzfF0ac1+4td5NvbceqosZT3Po95P8zkkksuYc6cOVFSr9FoNPGHDjxRwiKCo08bOrZoDMDxHVJo3TSJL1Zm88HSbLoNvgLn2f8kuXlL7r77bu677z727c+NsWqNRqOJPjrw1BEWEc49rg3lbsXg3q254tSOSIsOtLjkARx/uZHZP/zI4POHcP9L73lXYdVoNJpjknoZeETEISILRWSCiDjqev+1DQsndWzOAxf24YJ+aTSz2+id1oxVu4r547CraTbsQTyNWvL928/z1xtvZd++fTjL3WzZVxRR7RqNRhNrYrEQ3Lsisk9EMoLsQ0Rko4hsEZGHqnGjgGLAjrFsdr2heeNERIy1ewZ0aUGRq4JPlmaxhxYM/cezNBowgtUrlnLuBUM5ZdRYzntpPr/vPDwAYV+hk4xdBbGSr9Fo4hilFOe+lM7Xv+2KtZQqiUWL531giL9BRKzAeGAo0A8YKSL9ROQEEZke9NcGWKiUGgo8CDxVx/q9oo/aRZ+2yTRJtLJ+TxG92jTltG6tuHXUKBKGPEh50zRY9gn2pW8z/vtlgHFR/X3KSv46cTHOcr0CqkajCcSjIHP/Ie6b9nuspVRJLFYgXSAiXYPMpwNblFKZACIyFRiulBoHDKvCXT6QFA2ddYHVIpzapQWLM/MYfnIHRISURjbuuvSPVAw9na1Lf+CHT99m4fh/MTHp/+g56HyWbc8HYNHmXM7rlwbAviInSQlWUhrZfL71cyKNRhOvxMsKpB2AnX7b2cDAyhKLyF+AC4HmwBuVpBkNjAZIS0sjPT29VsLW5VQA8PuqVQDYineTkNgJ8Xiw526olU9/hrVRnNvSSnJpJpgjtu3md+1P7k2HtAeY9OFUXnn+GRLafErzAVfiapTKxNkrSNjXmAqP4sEFpbRtIvzrtEYAFJYpHll4iOv2zGFQu3g5xVVTXFxc63NU19QnraD1RpNYa12cU4HNAgPaGr9zj3nDqRQhdcVar5d4qZVC9VtVesuulPoS+LIqh0qpScAkgAEDBiiHw1ErYQW/74LVv3PSSScBUN60HRWNmqMshThTI7PcdSLgrOS79qnQ8/KObFoyB5XxHZ4fX6b1wMvIYCBn/elsvl+zmzzn7+Q5Fe2PO5Xeac14dc5miss3kZfQGofD0F1a5ubzFTv562mdSUyIvzEl6enp1PYc1TX1SStovdEk1lpveuh7ALY/ex4Abo+C2TMQIaSuWOv1Ei+BJxvo5LfdEciJkZa448yerVm3eyAp3U+k/dbpbFk0DU+LpTzYNYEluQm0aGyjyFnBY19nMOyEdkxesgOANX6DEL5bncPj36ylwqP425ndAPgtK59ftubx93N6xuS4NBpNwyReAs8yoJeIdAN2AVcD18RWUmgkAoMKakrXVo05p09reqc1o/Mlp/H7zz/x3YfjmfHf/6O8z/kMveIacg6W8VtWPq2bJpFb7KJrM2HjniLe/3k7iQkWvlxpDP6bMH8rI0/vDMA/pv7GzgOlnN8vjd5pzQAjGFktwokdm9f5cWo0msqZvGQHHy3ewex7z461lKMmFsOpPwEWA31EJFtERimlKoC7gNnAemCaUmptXWuLV0SE8/u1pUurJogIp5x1Hl2ufhp3237Y1s9kzQdP0dteSLlbMTNjN2nJSZzT0YIC9hQYD46255WQ0sjG3kIX//psFXd+vJKdB0oR4Ctz6KWrws2tH67g4S/XVKmn2FXB09+to9BZXmW6yYu38/IPG6s9vn2FTj0YQqOphse/zmDj3mPjvb46DzxKqZFKqXZKKZtSqqNS6h3TPkMp1Vsp1UMpNbaudVVHvFWLJ/bsSNlpN9Br+F0UH8zl25fvp9WOuXjcFZzZI5VOzYyWWfbBUg65KsgtdjGoW0u6tGrMvI37WbBpPyd1TKF3WjO++W0XHo/i299zyC12sXFPUcBw7W25hwK2Z6zZzbs/b+O3rMPvF2Xnl/Dh4u0BGh//Zi2vzd0SYOv96Eye+u7wPcXmvUWc/sxPzNlREcHS0WjqN0opdhfUbH7I+kT8PWXWhMXxHVI477g2DL/4Im5/5i36D3RQ8vsMkhe9RpuKvaQkQtOkBHIOlpJ1wFj9tEurJvy5bxrFrgqsFmHoCe04uXNzcgqcjJ2xnpd/3IRVhAqP4tU5mwE45Kpg6KsLeHH24ZbL/I37j9Bzwzu/8sQ3a8k/VFal7jK3h/d+3u7b3pZ7CIB1B/R7SRqNl8+WZ/PHcXP5LSs/1lKigg489RSb1cK5fdNolGilcdNkLhv9AFff8zR2yvhw7H3M/v472jW1kp1fyva8Q1gtQocWjejRugl/6pXKFad2JNlu47i2ySQlWJi+OofdBU4G92kNGC0lgGXbD+As9/DtqhzcHkWF28PCzUcGnoOlRrebJwJdZpv3FvH3KSurfUn2h7V7WLVTLyuhOfb4dfsBADbvOzYXjYyXwQWaCNDr5IHc3nsScz59i4XpM7GvXktBv8uxWo6jQ/NG2KzGfcbQ49v58iQmWOjfPoWVWfk0TrQyuHdrft12gF35JUxZmsWsjD0A7CtyMW7meiwIhU6jW2zehn3syjcCVCRnUlixI5/vV+/mqgGdGNy7daXpRk9eAcD2Zy/22WZl7OaMnqkk222VZdNo4o65G/YyoGvLBnPd6hZPbYi3Bz5+2Bs3Ydjf7uFvo+/EotwkLnqT3EVT6djMWmmekzsZI9gGdmuFzWqhQ/NGZJsBJTO3mPYpdmxWYXV2AZuqebj5xcpdTFmaxZSlWT6bdzvYVh1LMvN8n99emMk9U3+rMv2OvEPc/tFK7p16eLqQgtJyXpi9gQq/hfxyDpayaHPgEhQHS8oCBkt4PIoTx8xm2rKdRIuKGi4uqDk2yTlYys3vL+efn1R9fR9L6MBTS+p+UHXN6Nm7Dzc+8SbubmeSkLmIjZMfZ9u60Bd2j9ZNuOb0zr7WRYcWjdhf5KKwtJycg6X0aduM49olk7GrgA17irBZI3P0U5ZmsWCTEQDKKjxHBKfFW43Ao5TivZ+38+u2A1X6KzVbXd6gCfDszPWMn7eV79fs9tku/O8CrntnaUDek5/+kRPH/ODbLnN7KHRW8Pg3AXPZHkGxq6JWk7Zu3ltEz0dnMtNP18GSMr76rV7NeVsvWJtTwHer4ve1QO91uyOv5Kh91ZfRoTrwHMOktkim0elX4DrrThJtCXz0/EN8//6rOEsOBaQTEY7vkOKb0aBji0Yo4JeteXgUdG/dlBM7pFBS5mZPoZMerZtGVfdSM8Cszj7Ie4u28dIPm2q8AqwXZ7nRqnB7Dv8gi1y1G0G3YU8hXR/6np1Fh1sqt01ezrDXF1FWcdhWVuHBVRHY9VhSVhHQwvG+3PvDur0+2z+m/s69n64ic//hfn2PR+HxBFYm+4qcFFdzDB6PCvBTVbpg/4XO8oDyAthTEDi3hrPcTU7QOdlf5GJfUWC6DXsKKSg93JJUSjFv474A/wWl5fy0fm9AvvW7C303Hl5mrNnN+t2FAb7emLuZA34DWgqd5Xy0ZEdABXzxa4u4O6g18eQ3Gby9MNO37fEonvwmI6BFX1rm5s30LQFaneXuI8pCU3N04DnG6dKqCWnd+3H7fybwx6FX8tv8WUx8bDSbV/1aaZ4OzY05337dnofVInRu2Zheac1IMgOT92XTaONRsONACev8KptY4n3etXzP4Up/uTlpq/+gijOe/Yk+j80KyNvvidnc/tHKKv3vNSu0Mr8AdeXExXR/ZEZAutPH/sSF/10QYMvYVUC5X763FmZy7kvzA1pjkxZsZdjrCwPy9Xx0Bhe8cthXaZmbE8f8wL+nr/PZZq7ZzaBxPwV0T/7945Wc8ezcAF+njZ3D6WN/CrANeWUhIyct8W3/uG4vf3tvGW/5Vfp3TVnJqA+Ws7fwcIU+9NWFjHxrSYCvOz9eydBXD+tfknmAF3/YxENfrPbZHvsqg8e+zmD5jqpHg32weAf/+X69b3vXwVI+WLyDm99f5rO9/ONGnp+1MWCJgVs+WM6gcYHHuHz7AVbWYPRZhdtzRGCPFLF4wb026MBzjDPilA787cxu2BKTOO+vt/C3x/9LUqMmTP3v43zz1guUFh9ZqTez20hpZMNZ7qFTi8bYrBZsVgsndWxOyyaJtEuxh9hTdMjcX8y6nKoDj7eLbsZqIzAcLC0L6xlStMgtDj2kfE7QXX04rKikAvVvAW7PPcSw1xcx1q8i9ebz73Z8ZsYGMnYFlqVHwRa/kVMlZUZQ/dava+o3c+Tg2pzDQeynDfvCPgb/G4e9RS4Adh443K3kHVLv32oMhwqPx9R8uHXpbf1EYrBLscvw4fRrvS7acuTy9FdMWMxf3vwlwDZlaValLc6ej85kxJs/H7W++owe1XaMY7cFDiro0L0vt4x5g0XTp/Lz9KlsXbOCi268m76nnhmYrnkjCkrL6d66ic827MR2VHgU+wrrpquhRWMbq7ILKCgtR4BDZe6oBxSvf2/rIVp3ppEkz6xsV2XroeXxwiNfraFZUgJrnrow5Persxv2Yo66xdMASbAl4hhxA6OeeJ1mLVrx2etP8/n4/3Co8HDF1bGF0d3mH3gSrJYjAlk06Z7a1Pd8oGtqk2pSazTxRW2fJTYEdIunAdO2Sw9ufvxVFs/8jAXffMz29au48No7OH7QOfyhcwvK3R66tIxdhd+tdRNWZOXTNtlOy8aJAQ+Rw2HK0ixfN87irXm+gQb+3x8NU5Zm+VpEny7b6XtPqro8gO+NdK++2u4fICuv9j40mligWzwNHGtCAmddMpJbnxpPyzbt+Xric3z66hhwFnB+v7ZYLbF7WNm5ZWMa2ayc1EnPlK3RHEvoFk+Y1JPh8bWmdYcu3PTYy/z6w9fM+/IDJjwymgtG3sZJf7ogZiNlbFYLD1zYB1uCha9W7qo+Q5TwtizWmP3ypeWRfdbk9XWw1GjRzVi9h5U7DnLNwM4R20dDY+6Gfew8cOxOslnf0S2eaqgvwxMjgcViZdCQy7nt3/+jbecefPfuy0x58REO5tZ8NFakSLJZsTSgc6DRNATqZYtHRDoDbwC5wCal1LMxlnRM0TKtA9c/+Bwr0r/np2nvMPGx2/jzlaM49ZyLEUsd3KscI63LWA7p9ufAobKQ0xXpFlVkCXW+pyzNqrScven3m0PMC53lVaYPZ9/e98nivYcmFgvBvSsi+0QkI8g+REQ2isgWEXmoGje9ge+VUjcD/aIm1p94P5MRRiwWBpx7Cbf9ZyIde/Zj5uQ3+PC5BziwN3ZdXhqN5tggFl1t7wND/A0iYgXGA0MxAslIEeknIieIyPSgvzbAb8DVIjIXmFfH+o+VG/KwaJ6axjX/N5ZLRt3H3qxMJj5+B2vnfwsqfie4bGD3CBpNvaPOu9qUUgtEpGuQ+XRgi1IqE0BEpgLDlVLjgGHBPkTkfuBJ09c2jKU+AAAgAElEQVTnwHsh0owGRgOkpaWRnp5eK73rdhtj8X9fZcx4bCvejdXWEfF4sOduqJXPusBS4YyovkHHdaHf/Q/yzRfTWP7t+yS16MyhtJHYre0BEI/xdrc9bzP2xMBnMqF0eG2J5rxnog6XZ0KxYUs6sAV7kuHL6qpA3KpqX4eMiGNxu3w2q/kuha1oN/agZ1VV+bK4vdHr8D4TStzmsVb45TXSJeVuJNEa/nHbzOO2OAuwm0OqpcJ4Zynx4Dbs5UJ6+uFpZUJdv77jLjR8FRYU+tLl5hov+a5dm0EPe+C14P0cyn9hmXE85WVlPltWljHoYWvmVtJV4GzdoXRVZducZRxjTk4O6enGXGxOp6F1yZIlbG1sobi4GO80vFX5ysg1zkd+/gGfLd+cqSGxYCf2oG7hqnztL/H4tHhtu3OMLrBNGzeRXrotZD5/rZWdb/9yDv4OIKnEKHNxl/nS79lj7Hvjhg2kF2+t9ji8vtx+d12h0hUXF9e6Lowk8fKMpwPgf0VnAwOrSD8LGCMi1wDbQyVQSk0CJgEMGDBAORyOWgkrXJUDq37j5JNOBqC8WTvc9uZgKcSZ2rdWPusCe+6GiOtLTIUr/nU683/6gQXTJjDj3Zc4dNl1/HHolSjLJsCNs1UvEpK8l9UagCAdgbayskJgB0osPltF0QFgF66WPXE2MtYnce/IRlmLq/ZlcwKbUQlJOFN7G/m27wQOUt6sHc7UFmHrMmYuWAvIYdv+vcA+lCXBL28GoHCl9sHje48nDP8l+UA2HnsKztROAKiETYCLsubdcKbYcQzsDLO+ByDg+jVtvuOWQ0AmySnJOBzGDBRTspbDvr307388JTtWm2kDNYTyn1fsgrlzsCUm+my/lKyH7Zn06N4Dx+AeARpC6arKtnPJDliXQbv27XE4TgAgaclcKC1l0KBBdGrZ2KwYD1Xry7p5Pyz/leYtWuBwDALgrS1LIC+PspROOFO9cwquqV7XgRJYMA+73e6zzT6wBrKz6NW7N45BXULm89da2fl2BD+zCTp/riIXsAllTcSZ2gfHwM5M378KdmXTp29fHAM6VVu+Xl/Ge2UZiASlM0lPTw9pr2viJfCEGrZUaYeJUioDuCJ6cjSVISJ0/8Of+CG3Gb1zfmTeF++zbtlCVJ8R0LhtrOU1aCLZxeg/u3N9mWpfc5h4P2XxMpw6G+jkt90RiN8FNDSQ1Iwzrr2PK+56nOKDB2DOyySsn0VFeXn1eespelB35PAvy6MdLS9+3iQKZ0mP5o888RJ4lgG9RKSbiCQCVwPfxliTJgyOG3AWdzwzCTr/AdumOUx55p/syozfZ1/HMpGsIP3fX2tI77Jp6oZYDKf+BFgM9BGRbBEZpZSqAO4CZgPrgWlKqbV1rU1TOxo1TUZOvxbXoFG4Sg/x3r/vZc7Ut8B97LZ+NBpN7YnFqLaRldhnADNCfaepH3jSjuOGq4ew5Ov3WDzrc5KapFN+ylXACUfvXN90azTHDPHS1aY5Rkhq1JiLb/on1z3wLCgPSYveZNbk8ZQ59bxZGo3GIF5GtdUD4nyYSAyoauRMt36n4Drn/7Ctn8myud+xedVSLv7bPYCtzvRpNJr4RLd4qkH38BwFCUmUn3AZNz3yEpYEGx+/8DC23z+Dct360WgaMjrwaKJOp179Gf30m5xx0VVYd/yKfe6LbPp9SaXpddtSozm20YGnVuiqsabYEpP481WjcJ19N8rWiE9feZKvJz6Pq6Qo4vuK95fnNJqGjn7Go6lTVIvOuBz3cKElg0XTP2HT6uVY+g2HlicdvXPdL6rR1At0i6e2NOBK7qgP3ZLA4BHXM+rJ12mU0pKkZR+yd94HFBfkH53fKLd0dENKU1+I93d+deDRxIy2nXtwzh3jKD/uIkp2rmPCI7ey5pe5lc4NFu6cYfH+o6sLjjZIhjtXW23ncfPPdbRdo8rPm4rC7YHuuo08uqtNE1MsVisVvc+lW9/jYc13fD3pOVr3/gN0vTjW0uodoSrImgbhqqbHiURAj+Q9QVXzskVizrbaHm88TKoaBxKqRLd4NHFBYvM0bnzkJS4YeRt5mRnY577A2kWz4+JH7CVuG1JV1JA1Lb6qWzc18xXSx9G78PNVhdYI7CmOLr1jDh14NHGDxWJl4IV/4cw7nsfTvAM/ffw6H7/4MAf374m1tPgmRA15tEEy2pOE6tmpGzY68GjijsYt0yg74zbOGXknu7ZuZMJjt3Fg1U+oOF5uOx7QFaSmvqADT5jEU5dPg0AsnHj2Rdw+diKde/Vnz/wpuOe9Qd6e7Fgr02g0R4kOPJq4JqVVG0b+31g6nH8z6uBuJj1+B4tnfobH4461NI1GU0viflSbiHQHHgVSlFJXVGaLNt4GTzT6kOsvddMKFBGaH3cmext1ofvOWcz59G3WLVuIdLkElayX29Zo6htRbfGIyLsisk9EMoLsQ0Rko4hsEZGHqvKhlMpUSo2qzhYtdL95/CCNUrjqH0/ylzuMAQdJ6f8lYeMc3BUVsZam0WhqQLS72t4HhvgbRMQKjAeGAv2AkSLST0ROEJHpQX9toqxPE4dUNRRWROg/0MHtYyfhbn8Ctg2zeOfpf7B7x5Y6VKjRaI6GqHa1KaUWiEjXIPPpwBalVCaAiEwFhiulxgHDIrVvERkNjAZIS0sjPT29Vn7W7TbupletXg2ArXg3loT2iEdhz90QEa3RwFLhjJq+xEJjdJmtMBt7gnHvIuYzF3veZuyJgc3EUDq8tsQiw5coj89mKzZ8JR3Ygj3J8GV1VgSUuR0oH3Ad7g4nc2j9l7z71N2cctafIfnPSMVh/1aXcf5sRbux5+4NW5fF7Q1+h/eZUOI2j7XCL6+RLil3I4nW8I/bZh631VWAPfeQ4bfCWCo88eA27OVCenqmL1+o69dXhub5KCwo9KXLzXUCsHZtBj3sgdeC93Mo/4VlxvGUl5X5bFlZZQBszdxKutoZoCE9Pf2I4dahtHptm7OMY8zJySE9PQ8Ap9PQumTJErY2tlBcXIx3wHVVvjJyjfORn3/AZ8vPN5bcSCzYid1iCZkvlG1/icenxWvbneMCYNPGTaSXbguZz1+rt1z9ByLZczcElLM/3vRJJUZ6cZf50u/ZY+x744YNpBdvrfY4vL7cHlVluuLi4lrXhZEkFs94OgD+V282MLCyxCLSChgLnCIiDyulxoWyBedTSk0CJgEMGDBAORyOWoktXp0Dq37jpBNPBKC8aTvcSc3BUoQztW+tfNYF9twNUdNXZikBtlKe3BFnajIAyrIOcONs1YuEJO9ltQYgSEegraysENiBEovPVl6UB+TgatkTZyNj4Th3VjbqiDJfg6fd8dx+4zB+/GQiKxb8SFLTVZSfdT3O1AuMfNt3Agcpb9YOZ2qLsHWVuz3AWkB8tor9e4F9KEuCX94MQOFK7YPHagnpK6T/knwgG3dSCs7UTkYZJmwCXJQ174YzxY5jYGeY9T0AAdevafOVoRwCMklOScbhOBOAKVnLYd9e+vc/npIdq820gRpC+c8rdsHcOdgSE322X0rWw/ZMenTvgWNwjwANDofjcOCpQqvXtnPJDliXQfv27XE4jCXR7UvnQmkpgwYNolPLxmbFeKhaX9bN+2H5r7Ro0RKHw6hC3t6yFPJyKUvphDO1WUDZV6nrQAksmIfdbvfZZh9YA9lZ9O7TG8fALiHz+Wv1lqsReDJ8NsfAzgQQdP5cRS5gE8qaiDO1D46BnZm+fxXsyqZP3744BnSqtnx916jHe90GpTNJT08Paa9rYhF4Qj01qbRvRSmVB9xenU3TcGnUpBmX3nI/7Y4/gxkfvErJ7Jf5ke04RtwQ0f3oAfWRQ8/VFl3i/dl0LAJPNtDJb7sjkBMDHZpjjE7H/QHXOfeTvHkWS2Z9wabfFtPkjOuAhvGo0L+CrLtJQmtWyTWEudo01ROL93iWAb1EpJuIJAJXA9/GQIfmWMRmp9Ggv3L9g8+hPIqdXz2PbdWXVLiO4eW2IzixZ7QnCW0I1MMGUp1T48AjIhYRSQ4z7SfAYqCPiGSLyCilVAVwFzAbWA9MU0qtrakOTQPgKCq6rsedzOj/TKDFSedh3b6Y+W/8i60ZKyKnrZ4Qb91EepLQuiHetYfV1SYiUzCeqbiBFUCKiLyslHqhqnxKqZGV2GcAM2qoVaOpEYlJdtr86Wr2JPel6fovmfLiI5z8pwuh2Vlga1Rjf3F7wx/BSUKjPTu1Fz1JaMMm3BZPP6VUIXAZRsDoDFwfNVUaTQTxtOzK2Xc8yxkX/5VVP/+Ife4LWPYce43sSFaQ0Z6dWtOwCTfw2ETEhhF4vlFKlaO7MjX1CKstkT9feTOjnngNldiEpKXv8dWEZykpKoi1NI2mwRHuqLaJwHZgFbBARLoAhdESpdFEi3Zde+Ea/E8SNs9l3bK5ZK5dydDr7wLVXPepaDR1RFgtHqXUa0qpDkqpi5TBDuCcKGuLK3Tz7kjqbZlYEqjocwG3jHmDlNQ0vnhzLInLPgSnvpfSaOqCsAKPiKSJyDsiMtPc7gfcGFVlcYKejfrYJa1TN25+7BX+fNUoLHvXY5/7Aqt/nqPXXtJooky4z3jexxj+3N7c3gTcEw1BGk1dYrFaOeOiq3A57sPTLI1v3nqBqf99gsID+2MtTaM5Zgk38KQqpaYBHgDzXRy9EpcmLqlNg0U1a0PZWXdy4bV3sGPDKt554nas25fE/wsRGk09JNzAc8icmFMBiMggQA8H0sQXR9srKhZOP/8ybvvPRNK69CJx1edYf55I/v49EZGn0USdenKfFG7guQ9jWpseIvIz8CFwd9RUaeKaY33wV4s27Rh5/zjKTroCyc9i4qOj+fXHb/AoT6ylhU2dzdVWW/8B+6qlE58vPUloMPH+Gw1rOLVSaqWIDAb6YNxXbjTf5WlA1MOrT1NrRAR310FI27702j2b2R+/SbMOPyJ9/wKkxVpeSEJVkPE2V5ueJFQD4Y9q+zvQVCm1VimVATQVkTujK03T0An+3Vcb+qNxb9C4BVff+28uvfV+SnJ3kTTvJbJXzsXjjqNHnLqG1NQzwu1qu1UpddC7oZTKB26NjqQ4R//I455InyIR4aQzz+fkW57Fk9aXbT9P593/3MPenduqz6zRxIB47x4MN/BYxK8NLiJWIDE6kjSa+CSpaXPKTruRvkNuoCB3L2+PuQvLhh/AUxFraZVS0woo2pOE6tmpNRB+4JkNTBORP4vIucAnwKzoydJo4hQRWvc6mdvHTuK4087Cun42SfNfZc/2zbHTFMHZqX35ozxJqJ6dumETbuB5EJgL3AH8HfgJeCBaovwRke7mrAmfB9mbiMgKERlWFzo0Gn+aJDfnL7c/TMXAvyGuQ3ww9h7mfv4uFWVlMdOkK0hNfSHcUW0e4H/mX9iIyLvAMGCfUup4P/sQ4FXACrytlHq2in1nAqOCAw9GMJxWEz2a+ku8Vqqq/fE4W3ZjYNEifp7+KRtW/IKl53A8LbvGWppGE7eEO6rtTBH5UUQ2iUimiGwTkcwwsr4PDAnyZQXGA0OBfsBIEeknIieIyPSgvzaV6DkPWAfsDUd/JND9vSHQZWKQ2JiL/nYv19z/DBVlLhIXjseW8S3lLmeslWk0cUm4yyK8A9yLsfpo2ONIlVILRKRrkPl0YIvZkkFEpgLDlVLjMFpH4XAO0AQjcJWKyAyzVeZDREYDowHS0tJIT08PV3YA6/YYD45Xr14NgK1oN1ZLO8SjsOduqJXPusBS4YyavsQio6hthdnYbca9i3iMy8Ketxl7YmDzJJQOr83rS5THZ7MVG76SDmzx+bI6Kyotc5+vQ0YklAqXz2Z1GefPVrQbe+7ekPlC2Sxub1Q9vM+EErd5rBV+eY10Sbkb6d+2CT3v/T+eePsbErYuYNIj6xhx5dV079nrCP8287itrgLsuYdM3carcYkHt2EvF9LTD9/bhbp+fcddaPgqLCj0pcvNNYLe2rUZ9LAHXgvez6H8F5YZx1NeVuazZWUZ3YdbM7eSrnYGaJg/Px1LUHM0lFavbXOWcYw5OTmkp+cB4HQaWpcsWcLWxhaKi4vxPgWqyldGrnE+8vMP+Gz5+aVGmRTsxG6xhMwXyra/xOPT4rXtznEBsGnjJtJLt4XM56/VW64ev7tUe+6GgHL2x5s+qcS8bt1lvvR79hj73rhhA+nFW6s9Dq+vCo+qMl1xcXGt68JIEm7gKVBKzYzQPjsA/ldvNjCwssTmVD1jgVNE5GGl1Dil1KPmdzcBucFBB0ApNQmYBDBgwADlcDhqJbZkzW74fSUnnngiAOXN2uG2N0dZinCm9q2Vz7rAnrshavrKrCXAVsqTO+JMTQZAWdYBbpytepGQ5L2s1gAE6Qi0lZUVAjtQYjlsK8wDcnC17InTbgPAvTM7RJkH+bI5gc2ohCScqb2NfNt3Agcpb9YOZ2qLsHWVuz3AWkB8tor9e4F9KEuCX94MQOFK7YPHalR05SdZcXc4CbX5a96Z8AannjsM7IPAZj/svyQfyMadlIIztZNRhgmbABdlzbvhTLHjGNgZZn0PQMD1a9p8xy2HgEySU5JxOM4EYErWcti3l/79j6dkx2ozbeAxhvKfV+yCuXOwJSb6bL+UrIftmfTo3gPH4B4BGgYPdmC1SIAtlFavbeeSHbAug/bt2+NwnACAfelcKC1l0KBBdGrZ2KwYD1Xry7p5Pyz/lRYtWuJwGFXI21uWQl4uZSmdcKY2MzOuqV7XgRJYMA+73e6zzT6wBrKz6N2nN46BXULm89fqLVcj8GT4bI6BnQkg6Py5ilzAJpQ1EWdqHxwDOzN9/yrYlU2fvn1xDOhUbfn6rlHfdRuUziQ9PT2kva4JN/DME5EXgC8Bl9eolFpZi32G6q2vtNNGKZUH3F7Jd+/XYv9Hje5him8iMuz3KH14Untw2w0TSP/yA5b88BVJ9kWUn3wlcMLRi9NoKqG+1E3hBh5vi2SAn00B59Zin9lAJ7/tjkBOLfzEFL0OfRwS5VNS1Y86VKCyJdk5f+RtHHfan3jnlXEkLX6LbxN2cP7Vo6OmsSGi52o7knivnsId1RbJ1UaXAb1EpBuwC7gauCaC/jWauKJjz364HPeSsHEOq3+ew9bVy+l70c1A24jux7+CrLNJQpWiNhE/EpOE6rna6i+1XoFUREaFke8TYDHQR0SyRWSUuZbPXRgvpa4Hpiml1tb+EDSaeoDVRkW/oYx64jUaJ6ew/JMXsS3/iIrSoqP3HcGJPevTJKHxSn1sIdU1UV2BVCk1UinVTillU0p1VEq9Y9pnKKV6K6V6KKXG1ka4RlMfade1F7c8+Tq9z70Sa84atn/8OGuXpuvltjUNCr0Cqab+UF3dXE/qbmuCjd6Oy3E57sGWnMqX/xvHZ2/8G0+JXltR0zAId3CBXoFUU2+oL33zKrkdna94mE65y5j/1YdUrFmJtf+lKNUzcvuIs2CsJwmtG+Jdu16BVKMJk2jEM7FYOeOiKxn97/9hbd6OxN8+ZdbEpynI2xe+kwhOEhrt2am96ElCGzbVtnhExALYgQa+AqlGEz1ate1I4wv+Sd6qeezZOIsJj95Gy6IHQDUGCe/+MJIVZLRnp9Y0bKq9os1ZAV5SSlV4VyDVQUdT9xz7lZ+IBXf3s7j8oddo3603Y8aMIfGXicihvFhL02giSrhdbT+IyOXSgG994rzLNCboMokOya3SuO6BZ3nqqaewHNxF0rwX+fDDD3HH03LbGs1RUJNnPJ8BLhEpFJEiESmMoq64wRtp9XBXTV0iIlx11VU4z70fT2oPxo0bx/XXX09mZjiTwms08U1YgUcp1UwpZVFKJSqlks3t5GiLi0sEfasf5xxT9wiNmlM2cBTPPfccmZmZjBgxgoTNc8GjWz+a+ku4MxecHeov2uI0mhpxrHYEi3DppZfy3XffMXjwYGzrZpC04HX27txWfV6NJg4J9z2ef/l9tmOsqbOC2k0SqqnnRGPIan0g1g2p1q1b89prr9H9hmdIXPUlb4+5i7MuGUnnPx65jFWdzdVWW/8B+6qlE58vPUloMPH+ND7cSUIv8d8WkU7A81FRpNFoqsTT/iScrXpyWsF8Fnw9mRZLFyC9LkN1an5E2mN5rjY9SWj9JdzBBcFkA8dHUohGE0wDHkRZPUlNGHHbg/z1n0/hPFRE0oLX2P/L57hcrurzajQxJqwWj4i8zuHWsQU4GVgVLVEajSY8ep8yiMva9GDyxNc4sHIWI0ZsZOxYPe+uJr4J9xnPcr/PFcAnSqmfo6BHo6k99bAvPhIkNmpC+SlX0fXkM3Et/5Rrr72WdqdeAGl6/I8mPgk38HwOOJVSbgARsYpIY6VUSfSkGYhId+BRIEUpdYVp+xNwLYb+fkqpM6KtQxN7wo0rDbWHrknn/nz8xLe8/PLLTJkyhaTGy9l8WiPaN7XGWpqmjon3ARHhPuP5CWjkt90ImFNdJhF5V0T2iUhGkH2IiGwUkS0i8lBVPpRSmUqpUUG2hUqp24HpwAdhHoNGc2ziV8s0adKExx9/nBOufRREGD/mPr7+/FNcpYfCdBXdSUL17NQaCL/FY1dKFXs3lFLFItI4jHzvA29gzGYNGK0lYDxwPsYghWUi8i1gBcYF5b9ZKVXVNL3XALeEdQQazVES7w0p/5Ze8859cTnu4yLLKtKnT2PjptFYeg/Hk3ZcmL6iO0monp26YVOT9Xj+oJRaCSAipwKl1WVSSi0Qka5B5tOBLUqpTNPXVGC4UmoccOQLCZUgIp2BAqVUyKl7RGQ0MBogLS2N9PT0cF0HkLGnAoDVq9cAkFi0G6u0QzwKe+6GWvmsCywVzqjpSywybgUTC7Ox24xGs5hv0tvzNmNPDPylhtLhtSUWeYz8yuOz2YoNX0l+vhKcbsTjqdrXIUOXVLh8NqvLOH+2ot3Yc/eGrUvc3tvdw+c5ocRtHmuFX15lat1IkjX847aZx211FWDPPWTqNubeTTy4DXu5kJ5+eHqcUNev77gLDV+FBYW+dLm5TkhIpMcpZ9G3UypffPEFSUveoaLTADynltG4cZOQ/gvLjOMpLyvz2bKyygDYmrmVdLUzQMP8+fNJsAQedyitXtvmLOMYc3JySE83Jj91Op0ALFmyhK2NLRQXF+MNTVX5ysg1zkd+/gGfLT/fqJYSC3Zit1hC5gtl21/i8Wnx2nbnGCMEN23cRHrptpD5/LV6z4fbc7ipZM/dEFDO/njTJ5WY1627zJd+zx5j3xs3bCC9eGu1x+H1ZXGrKtMVFxfXui6MJOEGnnuAz0Qkx9xuB/y1lvvsAPhfvdnAwMoSmwvQjQVOEZGHzQAFMAp4r7J8SqlJwCSAAQMGKIfDUSuxpWt2w+8rOeGEEwAoa9YOd1JzlKUYZ2rfWvmsC+y5G6Kmr8xaCmyhLLkjzlRj5iRlWQe4cbbqRUKS97IygnWgjkBbWVkhsAMlFp+tvDAPyMHVqhc205d75y6UpbBqXzYnsBmVkIQztbeRb/tO4CDlzdrhTG0Rvq4KD7AWEJ+tYv9eYB/KkuCXNwNQuFr1QSVYQvoKZSsvyQeycSel4EztZJRhwibARVnzbjhT7DgGdoZZ3wMQcP2aNp9WOQRkkpySjMNxJgBTspbDvr307388JU09jPrPWzz9wqskbJ7Lqy9lMvSGu3n6zquP8J9X7IK5c7AlJvpsv5Ssh+2Z9OjeA8fgHgEaBg8ejM1qCbCF0uq17VyyA9Zl0L59exwO4zdlXzoXSksZNGgQnVo2NivGQ9X6sm7eD8t/pUWLljgcRhXy9palkJdLWUonnKnNAsq+Sl0HSmDBPOx2u882+8AayM6id5/eOAZ2CZnPX6v3fBiBJ8NncwzsTABB589V5AI2oayJOFP74BjYmen7V8GubPr07YtjQKdqy9d3Xbm9121QOpP09PSQ9rom3BdIl4lIXw6vx7PhKJZGCNVwrbQ3VSmVB9wewv5kLfdfI3Qzu+7RXeuRJ8GWSMVxQ3C3O4G2277ls9efonjLr6AGQlLTWMvTNDDCnavt70ATcy2eNUBTEbmzlvvMBjr5bXcEcipJG5foijG+icxD8GPzLKvmHRj1xGs4/nIjc+bMwT73BazZv+nZ1zV1Srij2m5VSh30biil8oFba7nPZUAvEekmIonA1RjLatcrdEMoDonySamqaq5PgcqakMCfLr2GL774AtW4JYkrPubuu+9m374aLLetiUvqy/1DuIHH4r8InDkyLbG6TCLyCbAY6CMi2SIySilVAdwFzAbWA9OUUmtrLl0TM3TUjUv8K51w6p9evXrhOvtuyvsPY9GiRVxyySXM+O4bUCr8SUJrWdHpSUKjS7w/Igh7BVJgmoj8WUTOBaYCs6rLpJQaqZRqp5SyKaU6KqXeMe0zlFK9lVI9lFJ6fg+N5mg4mok9xUJFTwdff/01vXr14pmnnyRxyduoQwdq7isMGsIkofWp9Rsrwg08jwMLMR7y3wn8CDwQLVEajaZu6dq1Kx9++CH3PfAwlrxtuGY8yyeffILH44m1NM0xSJWBR0QSROR5IAu4CegJOIBe1eXVaDT1C4vFwuVXXY3r3PuxtOrC008/zU033URR7u5YS9McY1QXPF4AWgLdlVJ/UEqdAnQDUoAXoy0urqiPHb0aTS1QjVtiO+dO/v3vf7N+/Xqmv3Qf1q0L8OjltjURorrAMwxjRFuR12B+vgO4KJrCNJpgqg39+t4gYogIV1xxBdOnT6dtzxNIzPiWac8/wNatW6vPrNFUQ3WBR6kQQ1rMWaob5M+8oS77XJ+I9xE9dcnRNtTT0tJw3PwwZX+4hvx9OYwYMYJJkyZBLVs/epLQuiHetVc3c8E6EblBKfWhv1FErgPid6IyjSYKxG08C1HL1FZrqKHTIoK70x+4/uqhZP30Ef/9739JSulA2Sm1nTVLTxLa0KmuxfN34O8iki4iL4nIi91sbOgAACAASURBVCIyH/gHRnebRqOJEyJZQYaanbpJcgteeeUVXn31VcRZQNL8V3hz/BuUlZVFbseaBkGVLR6l1C5goPnuTn+MG5WZSqmf6kJcPBHnLdeYUKfNeX3XGTdccMEFOGcdxLbmWyZO+B9zf5qjl9vW1IiwhkQrpeYqpV5XSr3W8IKOrvHqnHjvoNZAYhPKTx3J6+PfpLCwkKuvvpqEtdPBXdu5gzUNCf0uTq3QFWM8E5G4pU9xWJx99mC+++47Lr/8cmxb0kma9zIrVqyItSxNnKMDT21pwA2huD30GE4SGm+B6mjlhD1XG4pmzZrx9NNP4/rjaFAVXH/99YwdO9ZcJK16fXqutsgT7wMiwl0ITqPRxDmhKsiaVkBVLXNdnS9Pm964zrmfW1us56OPPmLevHlYugzD07rXYR81k1Ml8TpXW7zdhMQjusWjiVvi/KYtfoin29uEJB599FEmT55MQkICSb9MxPb75xQVFVWfV9NgiPvAIyKXichbIvKNiFxg2pqIyAem/dpYa9RoNIEMGDCAr776ivKeDqw7lnLppZcyf/78WMvSxAlRDTwi8q6I7BORjCD7EBHZKCJbROShqnwopb5WSt2KMUmp9421vwCfm/ZLo6Fdo9EcHXa7nYr+w3CdfTdNmzbl9ttv59u3XoCyklhL08SYaLd43geG+BvMReTGA0OBfsBIEeknIieIyPSgvzZ+WR8z84GxXPZO87OeuVCjiWNUi8588cUX3Hnnnaxdmo597gvsylgaa1maGBLVwKOUWgAEryh1OrBFKZWplCrDWFRuuFJqjVJqWNDfPjF4DuPF1ZWmj2yM4BP1Y9BoNEdPYmIid999N3974jWUPZlfp7zEvffeS15eXqylaWJALEa1deBwawWMIDKwivR3A+cBKSLSUyk1AfgSeENELga+C5VJREYDo8GY6DA9Pb1WYtfurQBgzZrVANiKd2OlLeJW2HPjd7o6S4UzavoSi41hO4lF2dhzjbgv5qSR9rzN2BMDH3aH0uG1JRYZC42J8vhsCYcMX0kHNmO3Gb4SSt2Ix1O1r0OGLovb5bNZXcb5sxXtxp67N2xdVHiHJh0+zwklbvNYK/zyGumS8jZhTwj/uG3mcVucBdhzDxl+K4yXLxMPbsNeLqSnZ/ryhbp+fcddaPgqLCz0pcvNdQKQkZFBD3vgteD9HMp/UZlxPOXl5T7bzp0uALZuzSTd4//ThQULFmCzBB63N5//MGyvrdDpxnX2P+i1fwFz5sxm4cKFlJ9wGbQ5mSVLlrC1scUchi2VHrfXtjbXOB/5+fk+W35+qVEmBVnYLZaQ+ULZ9pcYZeh0On22nBzjuDdt2kS6c1vIfP5aveVa4Tl83PbcDQHl7I83fVKJkV7cZb70e/YY+964YQPpxYEzgld1LYjb3LcKne7/2zv3+KjKM49/n5lkZqRACKRSkPsloKCrbhTUCiOoFRVl6xbUrdrFxargrutqtcWPH7veVlC74g2xpdYWFW8VRAXtQqReoiAKhAjhIpdwDwRDEmYymXn3j3MmzMTJlbmS5/v55JOTJ+d9zu+9zHnOeec9z6mqqmrzuTCepCLwxFqC0+gCRGPMLGBWA1s18K9NHcQYMweYA1BQUGC8Xm+rhQL4ivfAV19y6qmnARDo2IOgJwdTVY0vb2ibfCYDT/n6hOmrzToCbKK2Uy98eZ0BMI4SIIiv22Cy3OFhtRaggY5oW21tJbANI456W9135cBu/F2P+qor24mR75r2le0DNmKy3Pjy8gEIbt0BHCLQqQe+vNwW6/IHgkAJIEd17d8L7MM4siLKFgMGf7d8yHa22H+gpgIoI+TJwZfX22rDrFLAT22X/vhyPHhH9IHF7wIQNX5tW329pRrYQufOnfF6zwNg3vaVsG8vw4YNp2bbGnvfaA2x/B+o8sPSv5GdnV1v+6S6BLZ+y4ABA/COHhilYdSoUbiznFG2cDljDCx5L8q2o2gblBRz1hU3MHn6zUyfPp01RfNw/egrBk1+nDOG9LNPjNWN1jtsc27cDyu/IDc3F693JAAvbCqCAwfw5/TGl9cpqu2b8rXjYA0sX4bH46m3LTm4FnZsJz8/H+/IvlHlRo8ejYhEaa0fJ8EQsK7e5h3Rhyga9J//sB8oxThd+PKG4B3Rh0X7V8POMoYMHYq3oHdMzbF81dZZxzYN97MpLCyMaU82qZimKgN6R/zdC9iVAh2K0irSaNFyTCJXVR+r1lhJQuOJAIMGDeLll1+mw1k/xbF/I1N+/jPefPPNJh9Yje1Ls1NnGqm441kBDBaR/sBO4Grg2hToaBWJeCI680lem+hn//jE6XRywrCxHOyczz8c/JB7772Xk08+Gen1T5gOXVMtT0kQiV5O/QrwGTBERMpE5EZjTB0wDVgCfAO8ZoxZl0gdx4Je7SQfDfHtD9MxjxmzZnPfffexZcsW3Esfx/ntJ4RCoVRLUxJAQu94jDHXNGJ/D3gvkcdOJJmYu6k9EY/+aa0LHRLHjsPh4JprrsHlcvHrJ1/Cteav3HDDDh588EH69u2bankZQabMzOhS5BbScN5Zb4TSkFQmCU0DIodo0pKENnGgJv/XxH7dunWj9pwp1J4+kQ0bNjBhwgT++Mc/gol995NuSULTYZyk+0yNBh4lbUnzz076cAyJPb+/f/x8xfTRciEE+57NokWLOOecc5gxYwbuvz+NVO6J8JWmSUKVZtHA01p0NCpK0jjxxBN55plneOyxx5Dqctwf/Y7Zs2cTCOgL5zIZDTyKoqQ1IsJll12Gb8xdBH80nCeffJJJkyaxfcvGVEtT2ogGHkVRMgN3JwJnXceTTz7J/v37efi/ppD1zWJCdXr3k2lo4FEUJaO4+OKLeeeddzh71EVkl/6N9X+5n9WrV6daltIKNPAoipJxdOnShcn/OR3/yBsJ+o9w7bXXMnPmTEKB2lRLU1qAvvpaUZSMJdT9ZE4peIih+z9i7ty5uHPfxTHsKqB/qqUpTaB3PErG0OzzEenwAEWakW4PO8dTTviZHaf7BO6//37mzp2LCYVwf/wsK9/+PbW+I8fmv43PKKUD6a5PA49y3JGoFe9pu5A+xlmmrVrb+rBoa4nUd6z9FX5m55xzzuGU6x+gbsCP2fjZYp6/95dsWbeqmdIt8J+2HZ+5aOBpIel+BZEKtEnSi3ieIBOdnTpROF0eAqdOYOwtD+DIymbezF+T/fXrEDi2ux8lvmjgaYbM+cgpYfQiQflhv6Hc9N/Pcu6lE3Fu+wLP0sdYtmxZqmUpNhp4lOOHdp6rLZJk5Wprq4amcrW1/jixc7Vlu9yMnXgj/lG3YbJP4NZbb+VXv/oVFRUVrfPfnjo+SeiqNqXVZNDMS7si1gkyY3O1tchXy3K1mdw++L23c2efHTz//PN8+umnOAZcRqjnaU37z+Bxnu7a0/6OR0QmiMgLIrJARC62bSeLyGwReUNEbkm1RiVBpPmHJ21I97NMOuDIYtq0abz++ut0794d94qXcH3xJ8rLy1OtrF2S6BfBzRWRfSJS3MB+iYhsEJFNInJPUz6MMW8bY6YAvwAm2bZvjDE3AxOBggTJVxTlOGPo0KHMnz+fwMmX4tj7DZdffjkLFy5s83Si0jYSPdX2IvA08FLYICJO4BngIqAMWCEiCwEn8EiD8pONMfvs7XvtcmE/VwD32P4VRVFaRFZWFnX5Ywj2GEb/gx9y9913M+LcH0NHL+SekGp57YJEv4F0uYj0a2A+G9hkjNkCICKvAlcaYx4BLm/oQ6xJ5/8B3jfG1C/KN8YsBBaKyLvAyzHK3QTcBNC9e3cKCwvbVIfivXUArCu2btpch3fh7NgdCRk85evb5DMZOOp8CdPnqrKuDrMrd+Jx7QZAQkEAPAc24nFFT/3E0hG2uQ5bL/cSE6q3ZVVZvtwHNuLJtnxl+YJIKNSkL3e1pcsR9NfbnH6r/7IP78ZTvrfFukxd+Ar4aD9n1QTtutZFlDW21lI8WS2vd3aVVW+H7zs85dWWXzvZpevQt3gCQmHhlvpyscZvfRtWWr4qKyvr9ysv9wFQXFzMQE/0WAhvx/J/uNaqTyAQqLft2OEHYPPmLRSGdkRpWL58OS5ndL3D5UIRdxFhW+l2q467du2isPAAAD6fpbWoqIjNHRxUVVURnmeNVe+wbV251R8VFRX1tooKa9m067vteByOmOXCmE7dmXLVFJYtW8aCBQvwmJUcPmM8y5YJIsKuXVa9S0tLKfR9G+3ro0IcIlFaw+3qCB6tt6d8fVQ7R1I/bmus/SVYW7//nj3WsTesX09h1eYm6xHpi/C4NbH3q6qqavO5MJ6kYnHBSUDk6C0DRjSx/23AhUCOiAwyxswWES/wU8BNI6/QNsbMAeYAFBQUGK/X2yaxtev2wFdfMmz4cOvvTj0JunIwjmp8eUPb5DMZeMrXJ0xfbfYRYBOBzifhy8sBwDhKgCC+boPJcoeH1VqABjqibbW1lcA2jDjqbXXflQO78XcbjNNl+aor24lxfNekL7/LB2wk5HTjy8sHILh1B3CIQKce+PJyW6zLHwgCJYAc1bV/L7AP48iKKFsMGPzd8pFsZ4v9B2oqgDJCnhx8eb2tNswqBfzUdumPL8eDd0QfWPwuAFHj17bVt6GjBthM586d8XrPA2De9pWwby/Dhw+neusae99oDbH8H6yuhaUfkp2dXW/7pLoEtn7LwIED8I4aGKVh1KhReML1buArGDKw5L0oW1nRNigppmfPnni9pwLgKVoKviOMHDmS3l072CfG6kbrHbZlbSyHlZ+Tm5uL1zsSgBc2FcGBA9Tm9MGX1zGq7WP5GjNmDGPGjOHyn/2c66b+F7UrXufPWWU88MAD9Kw4CDu2k5+fj3dk32gNo704HBKltb5vgyFgXb3NO6IPUTToP/9hP1CKcbrw5Q3BO6IPi/avhp1lDBk6FG9B75j1j+krPG6lwX42hYWFMe3JJhWBJ9Y3oY1OsBpjZgGzGtgKgcK4qlIUpd3Ss1dvas/9JXn7VrFmzTtcccUVDBp7NUj6XlxmMqlY1VYG9I74uxewKwU6FEVRjiIOPEPPZ+HChZx55pmseWcuro+f48CeslQrO+5IReBZAQwWkf4i4gKuBhamQEfr0FUv6Y92kRIHevbsyZw5czjzn2/FcXgPv7/vVubOnUswGEy1tOOGRC+nfgX4DBgiImUicqMxpg6YBiwBvgFeM8asS6SOeNLUQ2tKetDuHmuJY2LPRCcJTUR26tb+ryWICH3O8OIbcxcDhv8jM2fO5Nprr0Uq99j+05t0v05O9Kq2axqxv0cjiwKUzCHdB3e8Sfd4Fhlwj1VropOEJiI7dcPtuODpzM/+/T66HizhwQcfxL32d9QNuYhA4CKcbld8j9VCjDEZlbg1FmmfuSDVxOrgdna+TTrHmvolLlfm2smKjYhw6aWXsmjRIoI9TyV7/WKunjSRkpKSVEv7HpkybDXwtJFMv+I4LklhktB0CFSRGpKVJLTpl6U1NRXWMh8tobEkofEirK9r164ECn6O/+xfcODAASZOnMiCBQsgWBdz/1SS7qcnDTxK2qLfp7WQBCf2jKevVCQJbbP/RlyEegxnwUJryfXixYtxFz6BHNx2zMdrT2jgURRFaSU5OTk8/PDDTJs2DYK1uP/+NB++OoeA35dqaRmBBh5FUZQ2MmzYMPwX3Emw30iKFr/JnPtuYfuGNamWlfZo4FEURTkWsj0E/uEqrrv7UUzI8MrMu8le/RYE9O6nMTTwKIqixIF+J5/OTQ/OpuDCCTi3foZ72WNsLv4y1bLSEg08iqIoccLl9jD26l9Se/5UcGbz8mO/Yfr06VRWVqZaWlqhgUdRFCXOhLr2w++9g3Mvm8SCBQsYP348S5cuTbWstEEDj6IoSiJwZjP2Z5OZP38+ubm5TJ06lbvuugv81alWlnI08CiKoiSQYcOG8dprrzFt2jSWLFmCZ+kMHDtXt+vXbWvgUTKGZj+n7fdz3Cjpdm7LlCSh0PasDLFwuVxMnTqVN954A9MhF/fKP/PG0w9QdejgMapsTF9C3MaNVLwILiNJ945UjpKodCFpm0chxuBsq9ZkpQXKmCShxHc85efn4z//NrI2L2fj6g/Yun4K5/50CpieLfZhTPqnxGkOveNphgzv36STuOmDlvdEoiSk+7VH5MkoWVqbvutoqlzEdobkaosbDid1gy/gpgeeI69HH5b++Xe4Pv8DoeqKOB8ofUn7wCMiE0TkBRFZICIX2zaHiDwkIk+JyA2p1tjeSNscamkqK1kca1bv5tBcbfElr0dvbvjNY5x31RQc5Zs5suhhVhW+F5eLt3S/I0r0i+Dmisg+ESluYL9ERDaIyCYRuacpH8aYt40xU4BfAJNs85XASUAA61XaitJ+SfezjNIoDoeTU73j8V9wJ45ufXj3xSeZPHkyNQf3plpaQkn0dzwvAk8DL4UNIuIEngEuwgoaK0RkIeAEHmlQfrIxZp+9fa9dDmAI8Jkx5nkReQP4v4TVQFEUJcGYH3TDM3YaF7i2UPj67/F9+RXOoeMIhYanWlpCSPQbSJeLSL8G5rOBTcaYLQAi8ipwpTHmEeDyhj7EevHN/wDvG2NW2eYyoNbejvkidBG5CbgJoHv37hQWFrapDmv3We/aKF5n3bRlV+3C0eFEJGjwlK9vk89k4KjzJUyfq9qaCsg+vBNP+W4AJGR1g+fgJjyu6CvwWDrCNtfhkFXehOptWdVhX6V4sixfWUeCUfvE8uW2dTmC/nqb019na92Np3xvzHKxbKFAeLrjaD9n1QTtutZFlLX2cx8oxZPd8npnV1n1dvi+w1NuPdchdQGrTQ59iycgFBZuqS8Xa/zWt2Gl5auysrJ+v/JyK09YcXExAz3RYyG8Hct/pd+qTyAQqLft2OEHYPPmLRSGdkRp+Pvyv+POiq53uFxdyHzPVrrdquOuXbsoLDwAgM9naS0qKmJzBwdVVVWEJ+Vi1TtsW1du9UdFRUW9raLiiNUm323H43DELBfLtr8mVK8lbNu1y6p3aWkphb5vo8p99NFHOB0SpTXcrhI8Wm9P+fqodo6kftzW2OM2FODc4QM4d/BvePT5vxBc+zbPTl+D/Nv1dO/e/ajmjwpxSOyxZursY5vY9a2qqmrzuTCepGJV20lA5OgtA0Y0sf9twIVAjogMMsbMBt4CnhKR84HlsQoZY+YAcwAKCgqM1+ttk9i6kr2waiXDhllXHoGOPQm5cjA1NfjyhrTJZzLwlK/Hlzc0Ib5rs33ARgKdTsKXlwOAcZQAQXxdB5Htybb3XAvQQEe0rba2EtiGEUe9re5QObAbX9d8xOW0bDt3YeRQk778LktXyOnGl5cPQHDrDuAQgU498OXltliXvzYIlAByVNf+vcA+jCMromwxYPB3y8dha22J/0BNBVBGyJODL6+31YZZpYCf2i798eV48I7oA4vfBSBq/Nq2+jZ01ACb6dy5M17veQDM274S9u1l+PDhVG9dY+8brSGW//IqPyz7G9nZ2fW2T6pLYOu3DBw4AO+ogVEazh91Ph1cWVG2cLlAMAQfvB9lKyvaBiXF9OzZE6/3VAA8RUvBd4SRI0fSu2sH+8RY3Wi9w7asjeWw8nNyc3PxekcC8MKmIjhwgNqcPvjyOka1fVO+dhysgeXL8Hg89bYPKtbCju3k5+fjHdk3qtzo0aPJcjqitNb3R10IWFdv847oQxQN+s9/2A+UYpwufHlDuHZEHz6pG8Dbby/g8IZFPPzww9x2220QOhEcTryjvTgcEttXwB630qC+NoWFhTHtySYVgSfWhHSj36YZY2YBsxrYaoAb46yrZeh0uqIoCUZECPYpYNrkK/l6wR94/PHHcXfpRe0Zk5ovnAGkYlVbGdA74u9ewK4U6FAURUlrOnXpxqxZs3jiiSeQmgrchf/Ls88+S21tbfOF05hUBJ4VwGAR6S8iLuBqYGEKdCiKoqQ9IsK4cePwjbmLYM/TeOaZp5k4cSLr1q1LtbQ2k+jl1K8AnwFDRKRMRG40xtQB04AlwDfAa8aYzG1BRVGUZODuSKDgX3jqqac4ePAgkyZNIqvkPQgGUq2s1SR6Vds1jdjfA95L5LEVRVGOR8aMGctZZ53FjBkzeOutt3DuLqbs9F/Ta9ApqZbWYtI+c4GiKIoSTU5ODg899BD+c6ZAsJY/PnQHH7zyPAF/ZrxuW5OEtpBE5IDKdNKuRdJOUJJoIsVKa7OvNJ2RuXW+Yvo4dhcRvlKYnfqYvbedyGOHThyC/4I7Od/3OZ8veYsNqz7DkX8lJm9QyvS1BL3jaYZY2Uja83s0kkGs1k32KvbWnrja64VJogNVJpL0sZDtYdz107j+npkAuD+ZTdbqN6muTt8XzmngaSPt+nGeJFW+1SnI2munNNFQmiT0GPxn2HjqO/Q0brjvGQIDR+HcWsT48eP5+OOPUy0rJhp4FEVRjhOy3R7qhl9BYNRUOnTowJQpU/jtb3+balnfQ7/jURRFOc4wXfvx5qw3ee655+jSpUuq5XwPDTyKoijHIW63m9tvvz3VMmKiU22KoihKUtHAoyiKoiQVDTyKoihKUtHAoyiKoiQVDTyKoihKUtHAoyiKoiQVDTyKoihKUtHA00Laa96p1pLIZjqWHFixSsY1514bXcXS0NZ6xq5jm1y12FdbWzCuTR9TVxvbsIV1TMT5IKbPWHpacPB0P19Je0h4KSL7gW1xcJUHlMfBTzLIJK2QWXozSSuo3kSSSVqh9Xr7GmN+GG8R7SLwxAsRWWmMKUi1jpaQSVohs/RmklZQvYkkk7RC+ujVqTZFURQlqWjgURRFUZKKBp7WMSfVAlpBJmmFzNKbSVpB9SaSTNIKaaJXv+NRFEVRkore8SiKoihJRQOPoiiKklQ08LQAEblERDaIyCYRuSdFGnqLyDIR+UZE1onIf9j2+0Vkp4h8bf9cGlHm17bmDSLyk2TXR0S2ishaW9dK29ZVRD4UkY3271zbLiIyy9a0RkTOjPBzg73/RhG5IUFah0S04dciUikit6dL+4rIXBHZJyLFEba4taWI/KPdV5vsspIAvTNFZL2t6a8i0sW29xORIxFtPLs5XY3VPc5649b3ItJfRD639c4XEVectc6P0LlVRL627Slv25gYY/SniR/ACWwGBgAuYDVwSgp09ADOtLc7AaXAKcD9wJ0x9j/F1uoG+tt1cCazPsBWIK+BbQZwj719D/CovX0p8D4gwEjgc9veFdhi/861t3OT0Od7gL7p0r7AKOBMoDgRbQl8AZxjl3kfGJcAvRcDWfb2oxF6+0Xu18BPTF2N1T3OeuPW98BrwNX29mzglnhqbfD/x4H70qVtY/3oHU/znA1sMsZsMcbUAq8CVyZbhDFmtzFmlb19GPgGOKmJIlcCrxpj/MaYb4FNWHVJdX2uBP5kb/8JmBBhf8lYFAFdRKQH8BPgQ2PMQWNMBfAhcEmCNY4FNhtjmsp2kdT2NcYsBw7G0HDMbWn/r7Mx5jNjnW1eivAVN73GmA+MMXX2n0VAr6Z8NKOrsbrHTW8TtKrv7TuJMcAb8dDblFb7WBOBV5rykcy2jYUGnuY5CdgR8XcZTZ/wE46I9APOAD63TdPs6Yu5EbfFjelOZn0M8IGIfCkiN9m27saY3WAFU+DENNIb5mqiP7jp2r7xasuT7O1kaA4zGesqO0x/EflKRD4SkfNtW1O6Gqt7vIlH33cDDkUE3US27/nAXmPMxghb2rWtBp7miTXXnbI16CLSEXgTuN0YUwk8BwwETgd2Y91mQ+O6k1mf84wxZwLjgKkiMqqJfdNBL/bc+xXA67Ypndu3MVqrLdltPB2oA+bZpt1AH2PMGcAdwMsi0jnZumIQr75PZj2uIfqiKS3bVgNP85QBvSP+7gXsSoUQEcnGCjrzjDFvARhj9hpjgsaYEPAC1u0+NK47afUxxuyyf+8D/mpr22vf5odv9/eli16bccAqY8xeW3vati/xa8syoqe9EqbZXtBwOfAv9hQP9pTVAXv7S6zvSfKb0dVY3eNGHPu+HGu6MytGPeKG7f+nwPyIOqRl22rgaZ4VwGB7VYoLaxpmYbJF2HO3fwC+McY8EWHvEbHbPwHhlS4LgatFxC0i/YHBWF8mJqU+IvIDEekU3sb6YrnYPlZ4NdUNwIIIvdeLxUjgO/s2fwlwsYjk2lMdF9u2RBF1xZiu7Ruh4Zjb0v7fYREZaY+z6yN8xQ0RuQS4G7jCGFMTYf+hiDjt7QFYbbmlGV2N1T2eeuPS93aAXQb8cyL1AhcC640x9VNo6dq2cV2pcLz+YK0SKsW6WpieIg0/xroVXgN8bf9cCvwZWGvbFwI9IspMtzVvIGKVUjLqg7WyZ7X9sy58HKz57v8DNtq/u9p2AZ6xNa0FCiJ8Tcb6AncT8K8JbOMOwAEgJ8KWFu2LFQx3AwGsq9Ub49mWQAHWiXUz8DR2VpM4692E9R1IePzOtve9yh4jq4FVwPjmdDVW9zjrjVvf25+HL+w2eB1wx1OrbX8RuLnBvilv21g/mjJHURRFSSo61aYoiqIkFQ08iqIoSlLRwKMoiqIkFQ08iqIoSlLRwKMoiqIkFQ08ihKBiHSLyOS7R6KzE7c6o7CIXCgib8dB15Lwc1GKkulkNb+LorQfjPWU9+lgpcUHqowxj0XuYz9wJ8Z6oj1Zun7S/F6KkhnoHY+itAARGSQixWK9z2QV0ENE5ojISrHej3RfxL6XifVOlo+JyEwtIh1F5EUR+cJO2jg+xnFOEpGP7TusYhE517aXiUgXEZkq0e9d+dD+/zgR+UxEVon1bpYf2PaZIlIiVqLLRxPcTIrSIvQBUkVphMg7HhEZhPVE+ghjzAr7/12NMQftHFnLgF9ivYOoFBiN9b6bNwCnMWaCiMzAygP3qp2y5nPgNGOML+KYdwMYYx61U52cYIypEpEyYLgxmDfF3AAAAcpJREFU5pC9nwsoBB4AvsR6Gn6cMaZGrCScBivF0lK7nBGRLuHyipJKdKpNUVrO5nDQsblGRG7E+hz1xHpBWAeg1BizGUBE5mHlwQIrN9o4OfpmSg/QBytQhVkBPC8iHuBtY8zqRrQ8DbxvjHlfRCbYx/7UmgXEBXyM9c6WEPCCiLwLLGp71RUlfmjgUZSWUx3eEJHBwH8AZxtjDonIX7ACCTSeXl6ACeGgFAtjzFIR8QKXAfNE5BFjzLzIfUTk34AfYd1hhf0uNsZc970DihQAF2ElrLwFK/gpSkrR73gUpW10Bg4DlXL07Z4AJUC+naFYsLJdh1kC/Hv4DxE5o6FTEekL7DHGzMFK+nhGg/+fjRXwrjNH58k/BUbb2YfDmcEH26vgOhtjFgH/2dCXoqQKveNRlLaxCivIFGN9l/MJgP0dy81Yb9cst+1D7DK/Bf5XRNZiXfRt4vuvxR4L3CEiAaAK+HmD/98GdAU+sqfViowxN9tTfvMjlnz/BjgCvCUibvt4d8Sj4opyrOjiAkVRFCWp6FSboiiKklQ08CiKoihJRQOPoiiKklQ08CiKoihJRQOPoiiKklQ08CiKoihJRQOPoiiKklT+Hwqrw0fPLUJQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the empirical distribution and fitting an exponential distribution\n",
    "graph_trades = sns.distplot(trades['lastQ'], fit = expon)\n",
    "graph_trades.set_yscale('log')\n",
    "plt.title('Histogramme - Log-scale - Trade sizes + Exp. Distrib. Fitted ')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Renault\n",
    "## 3.1. Trades durations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(renault_trades)):\n",
    "    trades = renault_trades[i]\n",
    "    trades['dif'] = trades['ts'].diff()\n",
    "    edf_trades[i] = trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max difference: 283.4779999999955\n",
      "Min difference: 0.0\n",
      "Mean difference: 2.4011447683403144\n"
     ]
    }
   ],
   "source": [
    "trades = pd.concat(edf_trades)\n",
    "print('Max difference:', trades['dif'].max())\n",
    "print('Min difference:', trades['dif'].min())\n",
    "print('Mean difference:', trades['dif'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(trades['dif'])\n",
    "plt.title('Trades durations')\n",
    "plt.xlabel('Observations')\n",
    "plt.ylabel('Trades durations')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# An histogram keeping interesting values only.\n",
    "trades1 = trades[trades['dif'] >= 0.001]\n",
    "\n",
    "plt.hist(trades1['dif'],100)\n",
    "plt.title('Histogramme')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEWCAYAAAB8LwAVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAHnJJREFUeJzt3X+cXHV97/HXO4HIj8UgP7qFEFkwSBvJvQp7CVxb3K1UghqhSu8logJGclG4ipe2hNra8OhVqYqVX4qxIFXSbHNTFRKCoNQtaqmFIJiEGEUMDxaQCIGERVADn/vHOQvH5czO2dk5mTmz7+fjMY/MOXN+fL4zm/nM9/s95/tVRGBmZjbalFYHYGZm7ckJwszMcjlBmJlZLicIMzPL5QRhZma5nCDMzCyXE4Q1naQNkvpaHYe1nqRBSe9rdRzWGCcIGxdJmyUdP2rdGZK+O7IcEa+JiME6x+mRFJJ2KSnUjpK+V7NaHYdNLk4Q1pGceMwmzgnCmi5by5B0tKQ7JW2X9Kikz6Sb3Zb++6SkYUnHSpoi6a8kPSBpi6QvS5qeOe570tcel/TXo86zRNJKSddJ2g6ckZ77dklPSnpE0hWSpmWOF5I+IOknkp6S9LeSXpXus13SipHtJfVJGpL0F2lsj0g6WdKbJf1Y0lZJf5k59hRJiyX9NI13haR9SnivG37Pco61W/r+PZ6+Z3dI6k5f20fSlyQ9LOkJSV9P179C0mpJv0jXr5Z00BjxvlfSxnTbmyUd3Oz3xJrHCcLKdilwaUS8HHgVsCJdf1z6794R0RURtwNnpI9+4FCgC7gCQNJs4HPAacABwHRgxqhznQSsBPYGlgHPAR8G9gOOBd4IfGDUPvOAo4BjgL8AlqbnmAkcASzIbPu7wG7peT8KfBF4V7r/HwIflXRouu0HgZOBNwAHAk8AV9Z7sxpwBhN7z7JOT7eZCewLnA08k772FWAP4DXA7wB/n66fAnwJOBh4Zbr9FXkHl3Qy8JfA24H9ge8Ay8dTWNvJIsIPPwo/gM3AMPBk5vFL4Lujtjk+fX4bcBGw36jj9AAB7JJZdyvwgczy4cBvgF1IvpCXZ17bA/h15jxLgNvqxH4e8LXMcgCvzyyvBS7ILF8CfDZ93kfy5Tc1Xd4r3X/uqP1PTp9vBN6Yee2AkbI0+L4HMCtnfcPvWc6x3gv8O/BfRq0/AHgeeEWBOF8LPJFZHgTelz6/CViYeW1K+rdzcKv/rv3If7gGYY04OSL2Hnnw0l/lWQuBVwM/Spss3jrGtgcCD2SWHyD5outOX3tw5IWI+CXw+Kj9H8wuSHp12uTx87TZ6eMktYmsRzPPn8lZ7sosPx4Rz2Vey9t/ZPuDga+lTTVPkiSM59Ky/BZJN6XNbMOSThv9eh0Nv2eZcw5LeiVJLeFmYCBtSvqkpF1JahRbI+KJnNj3kPSFtBlrO8kPgr0lTc2J9WDg0sx7shUQY9dqrIXckWelioifAAskTSFpWlgpaV+SX8SjPUzyJTLilcAOki/hR0h+HQMgaXeSZpDfOt2o5c8DPwAWRMRTks4DTplAccbjQeC9EfG9ehtGxIkTOE/D71lEZJPfiIuAiyT1AGuATem/+0jaOyKeHLX9+ek55kbEzyW9luQ9V86xHwQ+FhHLxlNAax3XIKxUkt4laf+IeJ6kOQqSX9K/IGm2ODSz+XLgw5IOkdRF8ov/nyNiB0nfwnxJ/z3tOL6I/C+hrL2A7cCwpN8D3t+0gtV3FfCxkU5YSftLOmmCx5yWdiSPPKbSxPdMUr+kOelxt5M0VT0XEY+QNA99Lu2U3lXSSB/SXiQ1pyfTTvi/GSP+q4ALJb0mPd90SX86gffDSuYEYWWbB2yQNEzSYX1qRDybNnd8DPhe2uRwDHANSTPHbcDPgGeB/w0QERvS5wMkv4yfArYAvxrj3H8GvDPd9ovAPze/eDVdCtwA3CLpKeA/gLkTPOYGki/jkceZNPc9+12SpLKdpEns34Dr0tfeTZIwfpQe47x0/WeB3YHH0jJ+o1bwEfE14O9ImrC2A+uBidSerGRKO4vMKiX9tfwkcFhE/KzV8VSB3zMbL9cgrDIkzU87RfcEPg2sI7liymrwe2YT4QRhVXISSafsw8BhJM1VrgKPze+ZNcxNTGZmlss1CDMzy1Xp+yD222+/6OnpaWjfp59+mj333LO5AbUBl6s6OrFM4HJVwdq1ax+LiP3rbVfpBNHT08Odd97Z0L6Dg4P09fU1N6A24HJVRyeWCVyuKpD0QP2t2qiJSclomd+RdJU82YyZWcuVmiAkXZMOQbx+1Pp5kjZJuk/S4nR1kAwCtxswVGZcZmZWX9k1iGtJ7qR9QXob/5Ukd1DOJhmnZzbwnXRMmgtIhgQwM7MWKv0y13TQr9URcUS6fCywJCJOSJcvBIiIT6TL04B/iojcQdUkLQIWAXR3dx81MDDQUFzDw8N0deWNVVZtLld1dGKZwOWqgv7+/rUR0Vtvu1Z0Us/gt4dlHgLmSno7cALJZC+5E44ARMRSkkld6O3tjUY7jTqpwynL5aqOTiwTuFydpBUJIm80yYiIrwJfLXQAaT4wf9Ysz+FuZlaWVlzFNEQyAcmIg0iGASgsIlZFxKLp06fX39jMzBrSigRxB3BYOn79NOBUkmGRC0sHIFu6bdu2UgI0M7PyL3NdDtwOHC5pSNLCdCKTc0mmNtwIrEjHrS+sGTWIdQ9to2fxjfQsvrHhY5iZdbJS+yAiYkGN9WtIpjFsiPsgzMzK1zZ3Uo+H+yDMzMpXyQRhZmblq2SCcCe1mVn5Kpkg3MRkZla+SiYIMzMrXyUThJuYzMzKV8kE4SYmM7PyVTJBmJlZ+ZwgzMwsVyUThPsgzMzKV8kE4T4IM7PyVTJBmJlZ+ZwgzMwslxOEmZnlqmSCcCe1mVn5Kpkg3EltZla+SiYIMzMrnxOEmZnlcoIwM7NcThBmZpbLCcLMzHJVMkH4Mlczs/JVMkH4Mlczs/JVMkGYmVn5nCDMzCyXE4SZmeVygjAzs1y7tDqAdtCz+MYXnm+++C0tjMTMrH24BmFmZrmcIMzMLFdbJQhJe0paK+mtrY7FzGyyKzVBSLpG0hZJ60etnydpk6T7JC3OvHQBsKLMmMzMrJiyaxDXAvOyKyRNBa4ETgRmAwskzZZ0PHAv8GjJMZmZWQGlXsUUEbdJ6hm1+mjgvoi4H0DSAHAS0AXsSZI0npG0JiKeLzM+MzOrTRFR7gmSBLE6Io5Il08B5kXE+9LldwNzI+LcdPkM4LGIWF3jeIuARQDd3d1HDQwMNBTXlq3bePSZl66fM6Pa4zsNDw/T1dXV6jCarhPL1YllAperCvr7+9dGRG+97VpxH4Ry1r2QpSLi2rF2joilkh4B5u+1115H9fX1NRTE5cuu55J1Ly3+5tMaO167GBwcpNH3pJ11Yrk6sUzgcnWSVlzFNATMzCwfBDw8ngN4NFczs/K1ogZxB3CYpEOAh4BTgXe2II5cvqvazCxR9mWuy4HbgcMlDUlaGBE7gHOBm4GNwIqI2DDO43rCIDOzkpV9FdOCGuvXAGsmcNxVwKre3t6zGj2GmZmNra3upC7KNQgzs/JVMkG4k9rMrHyVTBBmZla+SiYINzGZmZWvkhMG7axOal/yamaTWSVrEGZmVr5KJgg3MZmZla+SCcJXMZmZla+SCcLMzMrnBGFmZrkqeRWTpPnA/FmzZu20c/qKJjObbCpZg3AfhJlZ+SqZIMzMrHxOEGZmlssJwszMclUyQfhGOTOz8lXyKqZWTxiUvaIJfFWTmXWmStYgzMysfE4QZmaWywnCzMxyOUGYmVmuSnZStxsPw2FmnaiSNQhf5mpmVr5KJgiPxWRmVr5KJggzMyuf+yCazP0RZtYpXIMwM7NcThBmZpbLCcLMzHI5QZiZWa5xd1JLmgJ0RcT2EuLpKO6wNrMqK1SDkPRPkl4uaU/gXmCTpD9vZiCSfl/SVZJWSnp/M49tZmbjV7SJaXZaYzgZWAO8Enh3vZ0kXSNpi6T1o9bPk7RJ0n2SFgNExMaIOBv4H0DvuEphZmZNVzRB7CppV5IEcX1E/AaIAvtdC8zLrpA0FbgSOBGYDSyQNDt97W3Ad4FbC8ZlZmYlUUT973lJHwQuAO4B3kJSg7guIv6wwL49wOqIOCJdPhZYEhEnpMsXAkTEJzL73BgRuY32khYBiwC6u7uPGhgYqBt/ni1bt/HoMw3t2pA5M3bOsCDDw8N0dXXtlHPtTJ1Yrk4sE7hcVdDf3782Iuq21BTqpI6Iy4DLMqsekNTfYGwzgAczy0PAXEl9wNuBl5E0Y9WKZSmwFKC3tzf6+voaCuLyZddzybqdeCP5uqdfeFpmh/Xg4CCNviftrBPL1YllAperkxT6hpTUDXwcODAiTkybhI4Frm7gnMpZFxExCAwWjGc+MH/WrFkNnN7MzIoo2gdxLXAzcGC6/GPgvAbPOQTMzCwfBDw8ngNUfTTXnsU3vvAwM2tXRRPEfhGxAngeICJ2AM81eM47gMMkHSJpGnAqcMN4DuD5IMzMylc0QTwtaV/SK5ckHQPU/XaWtBy4HThc0pCkhWlyOZekRrIRWBERG8YTdNVrEGZmVVC0l/b/kPzKf5Wk7wH7A6fU2ykiFtRYv4YxOqLrcR+EmVn5il7FdJekNwCHk3Qyb0rvhWiJiFgFrOrt7T2rVTE0i4fjMLN2VXSojXNIxl/aEBHrgS5JHyg3NDMza6WifRBnRcSTIwsR8QTQsl/v7qQ2Mytf0QQxRdIL9y+kw2VMKyek+txJbWZWvqKd1DcDKyRdRXIl09nAN0qLapJyf4SZtZOiCeIC4H8B7yfppL4F+IeygqrHVzGZmZWvUBNTRDwfEZ+PiFMi4h0R8YWIaPRGuQlzE5OZWfmKjsX0emAJcHC6j0jGTzq0vNAmNzc3mVmrFW1iuhr4MLCWxofYMDOzCimaILZFxE2lRjIO7oMwMytf0ctcvy3pU5KOlXTkyKPUyMbgPggzs/IVrUHMTf/NzkAUwB81NxzL4/4IM2uFomMxNTp7nJmZVVTRsZi6JV0t6aZ0ebakheWGZmZmrdSKGeUmbDKPxeTZ6MxsZ2nFjHIT5k5qM7PylTqjnJmZVVepM8qZmVl11U0QkqYAuwFtM6OcJXz5q5mVqW6CiIjnJV0SEccCG3ZCTGZm1gaK9kHcIukd2UmDzMyss42nD2JPYIekZ3lxNNeXlxaZmZm1VNE7qfcqO5Dx8GB9LzXSH3H+nB30tTYUM+sQReeDOC5vfUTc1txwiomIVcCq3t7es1pxfjOzyaBoE9OfZ57vBhxNMjeEB+trQ766ycyaoWgT0/zssqSZwCdLicjMzNpC0RrEaEPAEc0MxMrh2oSZNapoH8TlpMNskFwa+1rgnrKCMjOz1itag7gz83wHsDwivldCPGZm1iaKJoiVwLMR8RyApKmS9oiIX5YXmjWbm5vMbDyK3kl9K7B7Znl34FvNDkbSyZK+KOl6SW9q9vHNzKy4ojWI3SJieGQhIoYl7VFkR0nXAG8FtkTEEZn184BLganAP0TExRHxdeDrkl4BfBq4pWB8Nk6uTZhZPeOZD+LIkQVJRwHPFNz3WmBedoWkqcCVwInAbGCBpNmZTf4qfd3MzFqkaA3iPOD/SXo4XT4A+J9FdoyI2yT1jFp9NHBfRNwPIGkAOEnSRuBi4KaIuKtgbGZmVgJFRP2tAEm78uJ8ED8az3wQaYJYPdLEJOkUYF5EvC9dfjcwl2Su69OBO4C7I+KqnGMtAhYBdHd3HzUwMFA0jN+yZes2Hi1aB6qQ7t2ZULnmzGjPaVyHh4fp6upqdRhN1YllAperCvr7+9dGRG+97YreB3EOsCwi1qfLr5C0ICI+12B8ecOGR0RcBlw21o4RsRRYCtDb2xt9fX0NBXD5suu5ZF2j9wm2r/Pn7JhQuTaf1te8YJpocHCQRj/rdtWJZQKXq5MU7YM4KyKeHFmIiCeAiQyUNwTMzCwfBDxcY9uXkDRf0tJt2zwttplZWYomiCnZyYLSTuZpEzjvHcBhkg6RNA04lWTO60IiYlVELJo+vT2bQ8zMOkHhGeWAFZLeKOmPgAHgG0V2lLQcuB04XNKQpIURsQM4F7gZ2AisiIjC05m6BmFmVr6ijdV/TdKkdDZJ/8EtwNVFdoyIBTXWrwHWFDz/6H09H0RJfH+EmY0YM0FI2gX4OHAm8CBJcpgJ/Iyk9vFc2QHWiMszypmZlaxeE9OngH2AQyPiyIh4HXAIMJ3kTueWcB+EmVn56jUxvRV4dWRuloiIpyS9H/gR8KEyg7PWcnOT2eRWrwYRkXMnXTqqa7E77ErgTmozs/LVSxD3SnrP6JWS3kVSg2gJNzHtfD2Lb3zhYWaTQ70mpnOAr0p6L7CWpNbw30iG+/6TkmMzM7MWGjNBRMRDwNz03ofXkFzFdFNE3LozgqvFVzGZmZWv0H0QEfGvwL+WHEthvg/CzKx8nTdanZWu1tVNo/snfOWTWbU5QdiEuNParHMVHYuprfgyVzOz8lWyBuE+iGrwjXZm1VbJGoSZmZWvkjUIqx7XJsyqxzUIMzPLVckE4U5qM7PyVTJBeCwmM7PyuQ/Cdjr3R5hVQyVrEGZmVj4nCDMzy+UmJmupWkN1uOnJrPVcgzAzs1yVTBC+zNXMrHyVbGLyWEydz1c6mbVeJWsQNrn0LL6RdQ9t89DiZjuZE4SZmeWqZBOTTV5uejLbeVyDMDOzXK5BWGW5NmFWLtcgzMwslxOEmZnlapsEIelQSVdLWtnqWMzMrOQEIekaSVskrR+1fp6kTZLuk7QYICLuj4iFZcZjZmbFld1JfS1wBfDlkRWSpgJXAn8MDAF3SLohIu4tORbrYO6wNms+RUS5J5B6gNURcUS6fCywJCJOSJcvBIiIT6TLKyPilDGOtwhYBNDd3X3UwMBAQ3Ft2bqNR59paNe21r07LlfGnBntO+vg8PAwXV1drQ6j6Vyu9tff3782InrrbdeKy1xnAA9mloeAuZL2BT4GvE7ShSMJY7SIWAosBejt7Y2+vr6Ggrh82fVcsq7zrvI9f84Olytj82l9zQ+mSQYHB2n077eduVydoxXfJMpZFxHxOHB2oQNI84H5s2bNampgZmb2olZcxTQEzMwsHwQ8PJ4DRMSqiFg0fXr7Nh+YmVVdK2oQdwCHSToEeAg4FXjneA7gGoQV5RnrzBpX9mWuy4HbgcMlDUlaGBE7gHOBm4GNwIqI2DCe47oGYWZWvlJrEBGxoMb6NcCaMs9tZmYT0zZ3Uo+Hpxw1MytfJROEm5jMzMpXyQvm3Ult7c53dlsncA3CzMxyVTJBmJlZ+ZwgzMwsl/sgbNJr1s10tY4zen32uO6rsHZWyRqE+yDMzMpXyQRhZmblcxOTTUq1moPM7EWVrEG4icnMrHyVTBBmZlY+JwgzM8vlBGFmZrmcIMzMLJevYjKrocgNdL4ayjpZJWsQvorJzKx8lUwQZmZWPicIMzPL5QRhZma5nCDMzCyXE4SZmeXyZa5m4zTRS1tH9j9/zg6y/wUnMjfEeOe0KGMeimy5+ppyRGu1StYgfJmrmVn5KpkgzMysfE4QZmaWywnCzMxyOUGYmVkuJwgzM8vlBGFmZrmcIMzMLFfb3CgnaU/gc8CvgcGIWNbikMzMJrVSaxCSrpG0RdL6UevnSdok6T5Ji9PVbwdWRsRZwNvKjMvMzOoru4npWmBedoWkqcCVwInAbGCBpNnAQcCD6WbPlRyXmZnVoYgo9wRSD7A6Io5Il48FlkTECenyhemmQ8ATEbFa0kBEnFrjeIuARQDd3d1HDQwMNBTXlq3bePSZhnZta92743JVxFhlmjNjfMPIrHtoW8NxZM9V6zhF4hnZd3S5ah1/9DHHem2s85W1/WjDw8N0dXWNe79mmmgZRvT396+NiN5627WiD2IGL9YUIEkMc4HLgCskvQVYVWvniFgKLAXo7e2Nvr6+hoK4fNn1XLKubbpgmub8OTtcrooYq0ybT+sb17HOmMAAgtlz1TpOkXjOyAzWly1XreOPPuZYr411vrK2H21wcJBGv2+aZaJlGK9W/I9TzrqIiKeBMwsdwKO5mpmVrhWXuQ4BMzPLBwEPj+cAHs3VzKx8rUgQdwCHSTpE0jTgVOCG8RxA0nxJS7dta7zd1czMxlb2Za7LgduBwyUNSVoYETuAc4GbgY3AiojYMJ7jugZhZla+UvsgImJBjfVrgDWNHtd9EGZm5avkUBuuQZiZla+SCcLMzMpXyQThTmozs/KVfid1mST9Anigwd33Ax5rYjjtwuWqjk4sE7hcVXBwROxfb6NKJ4iJkHRnkVvNq8blqo5OLBO4XJ2kkk1MZmZWPicIMzPLNZkTxNJWB1ASl6s6OrFM4HJ1jEnbB2FmZmObzDUIMzMbgxOEmZnlmpQJosac2JUjabOkdZLulnRnum4fSd+U9JP031e0Os568uYur1UOJS5LP7sfSjqydZGPrUa5lkh6KP3M7pb05sxrF6bl2iTphNZEPTZJMyV9W9JGSRskfShdX+nPa4xyVfrzmrCImFQPYCrwU+BQYBpwDzC71XE1WJbNwH6j1n0SWJw+Xwz8XavjLFCO44AjgfX1ygG8GbiJZOKpY4Dvtzr+cZZrCfBnOdvOTv8WXwYckv6NTm11GXLiPAA4Mn2+F/DjNPZKf15jlKvSn9dEH5OxBnE0cF9E3B8RvwYGgJNaHFMznQT8Y/r8H4GTWxhLIRFxG7B11Opa5TgJ+HIk/gPYW9IBOyfS8alRrlpOAgYi4lcR8TPgPpK/1bYSEY9ExF3p86dIhuyfQcU/rzHKVUslPq+JmowJIm9O7LH+ENpZALdIWitpUbquOyIegeSPHvidlkU3MbXK0Qmf37lpc8s1mSbAypVLUg/wOuD7dNDnNapc0CGfVyMmY4LInRN7p0fRHK+PiCOBE4FzJB3X6oB2gqp/fp8HXgW8FngEuCRdX6lySeoC/gU4LyK2j7VpzroqlasjPq9GTcYEMeE5sdtFRDyc/rsF+BpJFffRkSp8+u+W1kU4IbXKUenPLyIejYjnIuJ54Iu82CxRmXJJ2pXkS3RZRHw1XV35zyuvXJ3weU3EZEwQE54Tux1I2lPSXiPPgTcB60nKcnq62enA9a2JcMJqleMG4D3p1THHANtGmjaqYFT7+5+QfGaQlOtUSS+TdAhwGPCfOzu+eiQJuBrYGBGfybxU6c+rVrmq/nlNWKt7yVvxILmy4sckVx58pNXxNFiGQ0muorgH2DBSDmBf4FbgJ+m/+7Q61gJlWU5Sff8NyS+zhbXKQVK1vzL97NYBva2Of5zl+koa9w9JvmQOyGz/kbRcm4ATWx1/jTL9AUlTyg+Bu9PHm6v+eY1Rrkp/XhN9eKgNMzPLNRmbmMzMrAAnCDMzy+UEYWZmuZwgzMwslxOEmZnlcoKwypK0b2aUzZ+PGnVzWgPHO17S1ycQz3WSmjL2laRDJZ2aWZ4r6e+bcWyzonZpdQBmjYqIx0mGQEDSEmA4Ij6d3Sa9AUqR3AnbViTtEhE7arx8KMlNnAMAEfF9XhwbyGyncA3COo6kWZLWS7oKuAs4QNJSSXemY/1/NLPtW9Lx/L9LZlRfSV2SrpX0n5J+IGl+znmmSPqcpHslrQL2y7w2JGnv9Pkxkr6VPv+/kr4g6ZvAlyS9StJ30nOslTQ3PcTFQH9aG/pgtnYjaT9JN6QDyP27pCMyx75a0r9Jul/SOen6vSTdJOme9H05palvuHUs1yCsU80GzoyIswEkLY6IrZJ2Ab4taSXJfBpfAN4A3A+szOz/UeAbEXFGOoLn9yV9MyKezWxzCslcAEcABwL3AlcViO11wHER8aykPYA/Tp//HslQ2XNJ5lQ4NyJOTuM/PrP/35LMq/A2SW8CrgV609deDbwR2BvYmCbJNwObI+LE9FjTC8Ro5hqEdayfRsQdmeUFku4iqVH8PkkCmQ38OCJ+GsmQAssy278J+Iiku4FvA7sBrxx1juOA5RHxfEQMAYMFY7s+k2heBlytZNa5gTSmev6AZAgIIuIW4MB0PC6A1RHx60gGcNwK7E8yTMQ8SRdLen1EbCsYp01yrkFYp3p65Imkw4APAUdHxJOSriP5wofaQzQLODkiflrnPLX238GLP8B2G/Xa05nn55PMK/AuYFdguM75RmKrtfyrzPPngF0iYqOkXpKaxKckrY6Ijxc4j01yrkHYZPBy4Clgezo658j8wfcCr05H9hWwILPPzcAHRxYkvS7nuLeRjOg5RdIMkqaqEZuBo9Ln7xgjtunAI2kN5nRe/LJ/imTqyzy3AaelcR0PDEXE0zW2JY1tOCK+AnyGZBpUs7pcg7DJ4C6SZLCepK/hewAR8UtJZ5PMmfxYuv7wdJ+LgM9KWkfyQ+o+Xjo17UqgPz3uJpIv7hFLgC9K+jljDwN9BbBS0gLgW7xYA/gBMFXSPSTDUN+b2eejJB3cPySpcZxZp/z/FbhY0vPAr4Gz62xvBuDRXM3MLJ+bmMzMLJcThJmZ5XKCMDOzXE4QZmaWywnCzMxyOUGYmVkuJwgzM8v1/wHroUlzZmDZGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Log Scale\n",
    "trades1 = trades[trades['dif'] >= 0.001]\n",
    "\n",
    "plt.hist(trades1['dif'],100)\n",
    "plt.yscale('log')\n",
    "plt.title('Histogramme - Log-scale')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.yscale('log')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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mZqVVcy6sRcCqiFgNIOkG4FzgseIOEbEm3VbIHhgRT2SW10vaBMwEtlUx3uz5+5d7uz2hoplZKdVswjoCWJt5vC5dd0AkLQJagKdGKK5B7duE5RqImVkp1ayBqMS6AxrSJGk28E3gwsj2bO/dfhFwEcCsWbPo6OgYQpj7i0Jf/3LD80/Q1rIbgI6O1SPy/LXQ2dk5Yq/PWFBv5YH6K1O9lQfqr0ydnZ3DOr6aCWQdcFTm8ZHA+koPljQF+D7wdxFxT6l9IuIq4CqAhQsXxpIlS4YcbNYnP/Xp/uXd7UfQNeNEAJaM4+ncOzo6GKnXZyyot/JA/ZWp3soD9Vem4SbDajZhLQOOlzRPUgtwPrC0kgPT/f8b+EZEfLuKMZYUETQ2NQPQ2+M+EDOzUqqWQCKiF7gYuA14HLgpIpZLulzSOQCSTpW0Dng78BVJy9PD3wGcDrxP0i/Tn1dWK9a8QgTNra2Ah/GamZVT1TsSRsQtwC25dZdmlpeRNG3lj/sW8K1qxjaQiKCltY2uXZ3uRDczK8NXopcQETS1tAEehWVmVo4TSCkRNLcUm7CcQMzMSnECKSEiaG5pATwjr5lZOU4gJYRrIGZmg3ICKcF9IGZmg3MCKSEiaGpuBskJxMysDCeQEiKChoZGmppb6PFkimZmJTmBlBBRQBItrW1OIGZmZTiBlBARSA00t7TSs6er1uGYmY1JTiAlRCFQg2hubaNnj2sgZmalOIGUEICUJpBu10DMzEpxAikh6QNpoKWljW43YZmZleQEUkJEgERzq/tAzMzKcQIpIelEF80tHoVlZlaOE0gJ/Qmktc01EDOzMpxASkhGYTXQ3NrqPhAzszKqekOp8aq/BtLc6iYsM7MyXAMpof9CwtY2erv3EIVCrUMyMxtznEBK2NsHkkzp7lqImdn+nEBKCNI+kHRKdycQM7P9VTWBSDpL0kpJqyRdUmL76ZIekNQr6bzctgslPZn+XFjNOPOKNZCW1iSBuCPdzGx/VUsgkhqBK4GzgfnABZLm53Z7BngfcF3u2EOBfwAWA4uAf5B0SLVizYtCIERTsQnLCcTMbD/VrIEsAlZFxOqI6AZuAM7N7hARayLiYSDfS/1m4PaI2BIRW4HbgbOqGOs+IgIaREt/E5YTiJlZXjWH8R4BrM08XkdSoxjqsUfkd5J0EXARwKxZs+jo6BhSoHkRBZq7ttLetSk5z6YnaZsCHR2rR+T5a6Gzs3PEXp+xoN7KA/VXpnorD9RfmTo7O4d1fDUTiEqsi5E8NiKuAq4CWLhwYSxZsqTi4AYSEfRNnAGHnQBAZ9tMumacyJLFR4/I89dCR0cHI/X6jAX1Vh6ovzLVW3mg/so03GRYzSasdcBRmcdHAutH4dhhK14H4j4QM7PyqplAlgHHS5onqQU4H1ha4bG3AW+SdEjaef6mdN2oiEhuKNXiYbxmZmVVLYFERC9wMck//seBmyJiuaTLJZ0DIOlUSeuAtwNfkbQ8PXYL8DGSJLQMuDxdV3URSUtZ8Up0cA3EzKyUqs6FFRG3ALfk1l2aWV5G0jxV6tivAV+rZnxlzgvsvSMh+DoQM7NSfCV6TiGd9yqZTLEFcBOWmVkpB5xAJDVImlKNYMaCbAJJpjPxXQnNzEqpKIFIuk7SFEntwGPASkl/Wd3QaiPbBwL4plJmZmVUWgOZHxE7gLeR9GkcDby3alHVUH8NpCG5FMW3tTUzK63SBNIsqZkkgXwnInqo/KLAcSXbhAX4roRmZmVUmkC+AqwB2oGfSjoG2FGtoGrJTVhmZpWpaBhvRHwB+EJm1a8kvb46IdVWvgbS0uIEYmZWSqWd6LMkXS3p1vTxfGBU79ExWvb2gWRqIO4DMTPbT6VNWNeQXFE+J338BPAn1Qio1rIXEoL7QMzMyqk0gcyIiJtI79uRTlPSV7Woami/PhA3YZmZlVRpAtklaTrpyCtJpwHbqxZVDRWbsIoTyre4CcvMrKRK58L6M5KZdF8i6WfATOC8gQ8Zn/Z2onsUlpnZQCodhfWApDOAl5J8N1+ZXgtSd/brA2lppbenm0KhLlvszMyGrNJRWB8GJkXE8oh4FJgk6UPVDa02StVAAHr2uBnLzCyr0j6QD0TEtuKDiNgKfKA6IdVWfiqT1rYJAHTvebFmMZmZjUWVJpAGFdt0AEmNQEt1Qqqt/CislgkTAdjz4u6axWRmNhZV2ol+G3CTpC+TjMT6IPCDqkVVQ/kr0VvbkgTS3eUaiJlZVqUJ5K+B/wf8AUkn+g+Bf69WULWUr4G0ugZiZlZSpaOwCsC/pT91Ld8H4iYsM7PSKh2F9euSbpf0hKTVkp6WtLqC486StFLSKkmXlNjeKunGdPu9kuam65slXSvpEUmPS/rIgRZsqPLDePtrIF27RisEM7NxodImrKuBPwXup8IpTNKO9iuBNwLrgGWSlkbEY5nd3g9sjYjjJJ0PfBp4J/B2oDUiXi5pIvCYpOsjYk2F8Q7Z3ivRc30groGYme2j0lFY2yPi1ojYFBEvFH8GOWYRsCoiVkdEN3ADcG5un3OBa9Plm4E3pKO9AmiX1ARMALoZpfuP5K8DcR+ImVlpldZAfizpn4D/AvqvqIuIBwY45ghgbebxOmBxuX0iolfSdmA6STI5F9gATAT+NCK2VBjrsOSbsJqaW2hsanYCMTPLqTSBFP/xL8ysC+A3BjhGJdblb4Nbbp9FJE1lc4BDgP+V9KOI2KffRdJFwEUAs2bNoqOjY4BwKrN2bZLzWjvX07Z5RbLc2kLftvUj8vy10tnZOa7jz6u38kD9laneygP1V6bOzs5hHV/pKKyh3H1wHXBU5vGRwPoy+6xLm6umAluAdwE/SOfb2pRO4LgQ2CeBRMRVwFUACxcujCVLlgwhzH0tX74cgJ6pR9E140QAWiZOZne0MhLPXysdHR3jOv68eisP1F+Z6q08UH9lGm4yHPIdCSW9f5DDlgHHS5onqQU4n2RG36yl7L2z4XnAnZG0IT0D/IYS7cBpwIrKijQ8+SYsSDrSPQrLzGxfVbsjYXrTqYvT4x4HboqI5ZIul3ROutvVwHRJq0imjC8O9b0SmAQ8SpKIvh4RD1cY67DkLySEpCPdfSBmZvuqtA9kRkTcVLweI+3wHnQ4b0TcAtySW3dpZrmLZMhu/rjOUutHQ34qE0gSyM5to9KHb2Y2bviOhDl7r0Tf+9K0TJhId5drIGZmWb4jYU5/E1ZmXWubm7DMzPIGTSBKOgPagIPijoSlaiCtE9rZ49l4zcz2MWgTVjqR4j9HRG/xjoT1mjygfB9Ib/ceenrqtthmZges0j6QH0r67exNpepVuVFYALt2eSivmVnRgfSBtAO9krpImrEiIqZULbIaKVUDaUlva7tr1y6mTZtWk7jMzMaaSq9En1ztQMaKkn0g6Yy8w73s38ysnlSUQCSdXmp9RPx0ZMOpvZJXok9wAjEzy6u0CesvM8ttJJMd3s/AkymOS6X7QNoBJxAzs6xKm7Demn0s6SjgM1WJqMZK9oG4E93MbD+VjsLKWwe8bCQDGSvydyQEN2GZmZVSaR/IF9l7L48G4JXAQ9UKqpbKzcYLroGYmWVV2gdyX2a5F7g+In5WhXhqLn9LW4CW1jaQXAMxM8uoNIHcDHRFRB+ApEZJEyOi7iaI2juMd28NRA0NtLROcAIxM8uotA/kDmBC5vEE4EcjH07tlRqFBdA2sZ2dO3fWIiQzszGp0gTSlt6jA+i/X8fE6oRUW6VGYQFMaJ/Mjh07ahGSmdmYdCD3Azml+EDSq4G6nJ62XAJpa5/Etm3bahGSmdmYVGkfyJ8A35a0Pn08G3hndUIaG7JTmUBSA9m+fWONojEzG3sqvZBwmaQT2Xs/kBX1OqX7QE1Y6555ohYhmZmNSRU1YUn6MNCe3gvkEWCSpA9VN7TaKHUhIUDbpMls3769v5PdzOxgV2kfyAcior8DICK2Ah8Y7CBJZ0laKWmVpEtKbG+VdGO6/V5JczPbTpZ0t6Tlkh6R1FZhrMNSbhTWhPbJdHd309XVNRphmJmNeZUmkIbszaQkNQItAx2Q7nMlcDYwH7hA0vzcbu8HtkbEccAVwKfTY5uAbwEfjIgFwBJgVJrMBmrCAti+fftohGFmNuZVfEdC4CZJb5D0G8ANwA8GOWYRsCoiVkdEd3rMubl9zgWuTZdvBt6QJqo3AQ9HxEMAEfFC8SLGanMCMTOrTKWjsP6epMnqgySd6D8Erh7kmCOAtZnH64DF5faJiF5J24HpwAlASLoNmAncEBH7zf4r6SLgIoBZs2bR0dFRYXHKW7FiBQBt21bTFlv610/tS1rwfvKTn7Bhw4Zhn2e0dXZ2jsjrM1bUW3mg/spUb+WB+ivTcGfXGDCBpE1JnwB+l+QfvYCjgKdJai8D1QpK3T893wNdbp8m4LXAqcBu4A5J90fEHfvsGHEVcBXAwoULY8mSJQMVpyIbNyZDdbunH0/XtOn96xt2NwMwd+5cRuI8o62jo2Ncxl1OvZUH6q9M9VYeqL8yDTcZDtaE9U/AocCxEXFKRLwKmAdMBT47yLHrSJJN0ZHA+nL7pMlqKrAlXf+TiNiczrd1C3AKo6DUZIrgJiwzs7zBEshvkYzA6p8EKl3+A+Atgxy7DDhe0jxJLcD5wNLcPkuBC9Pl84A7IxkGdRtwsqSJaWI5A3iskgINV6np3AEmTJoCOIGYmRUN1gcSUeLCh4jokzTgBRFpn8bFJMmgEfhaRCyXdDlwX0QsJelH+aakVSQ1j/PTY7dK+hxJEgrgloj4/oEWbij6E0juSvTmllaam5udQMzMUoMlkMck/U5EfCO7UtJ7gBWDPXlE3ELS/JRdd2lmuQt4e5ljv0UylHdUlRuFJYmpU6c6gZiZpQZLIB8G/kvS7wH3k9QGTiWZzv3/VDm2muhPICX6951AzMz2GjCBRMSzwOL02o8FJKOmbs2Phqone5uw9k8g06ZNcwIxM0tVOpnincCdVY5lTCg3CguSGsj69fmBZGZmB6dKr0Q/aJTrAwE3YZmZZTmB5JSbTBGcQMzMspxAcvprICX6QKZOncru3bvp7u4e7bDMzMYcJ5CcwWoggG9ta2aGE8h+BuoDOeSQQwDYunXrqMZkZjYWOYHk9F94XyKBzJgxA4DNmzePZkhmZmOSE0jOQDWQ6dOT2XmdQMzMnED2UygUSiYPgJkzZwLwwgsvjGZIZmZjkhNITkSUTSDt7e20trY6gZiZ4QSyn4FqIJKYPn06zz///ChHZWY29jiB5CQJpPzLMmPGDNdAzMxwAtnPQE1YkCQQd6KbmTmB7CciSl6FXuQaiJlZwgkkZ6A+EEiG8m7dupW+vr5RjMrMbOxxAsmpJIEUCgW2bNkyilGZmY09TiA5EVHyboRFvhbEzCzhBJJTSQ0EnEDMzKqaQCSdJWmlpFWSLimxvVXSjen2eyXNzW0/WlKnpL+oZpxZlSYQXwtiZge7qiUQSY3AlcDZwHzgAknzc7u9H9gaEccBVwCfzm2/Ari1WjGWMtgoLDdhmZklqlkDWQSsiojVEdEN3ACcm9vnXODadPlm4A1Kv/5LehuwGlhexRj3M1gNZOLEibS1tflaEDM76DVV8bmPANZmHq8DFpfbJyJ6JW0Hpkt6Efhr4I1A2eYrSRcBFwHMmjWLjo6OYQf97LPPIqBt84r9tnV0rAaSObGWL18+IucbLZ2dneMq3sHUW3mg/spUb+WB+itTZ2fnsI6vZgIp9TU+Ktzno8AVEdE5UG0gIq4CrgJYuHBhLFmyZGiRZtx+++0sf+wxumacuN+2JYuPBmDu3LkUCgVG4nyjpaOjY1zFO5h6Kw/UX5nqrTxQf2UabjKsZgJZBxyVeXwksL7MPuskNQFTgS0kNZXzJH0GmAYUJHVFxJeqGC9QnMpk4Ja9OXPmcP/991c7FDOzMa2afSDLgOMlzZPUApwPLM3tsxS4MF0+D7gzEq+LiLkRMRf4PPCJ0UgeMHgfCCQJZOPGjb4a3cwOalVLIBHRC1wM3AY8DtwUEcslXS7pnHS3q0n6PFYBfwbsN9R3tCUJZOB95syZQ19fH5s2bRqdoMzMxqBqNmEREbcAt+TWXZpZ7gLePshzXFaV4Mqfb78aSE9fgWtnZza4AAAUCUlEQVR+voaXHj6ZVx9zCLNnzwZgw4YN/ctmZgcbX4meU+p+IJs79/D05l38bFUydHfOnDlAkkDMzA5WTiA5pfpAtu7qBmD9thcBOPzww5PH6/NjAszMDh5OIDmlmrC27O4B4Nk0gbS3tzN16lQnEDM7qDmB5AxUA9mwvat/3Zw5c9yEZWYHNSeQnFI1kK279zZhRSTXQs6ZM8c1EDM7qDmB5JRswkprILu7+9jxYi/gGoiZmRNITr4JKyLYurubqROagb39ILNnz6azs5MdO3bUJE4zs1pzAsnJJ5DOPb309AXzZrQDsGF7kkCKQ3mfffbZ0Q/SzGwMcALJKRQKZC9F35qOwJo3PUkgxaG8xxxzDABr1qwZ3QDNzMYIJ5CciKAhm0DS/o+jDp1Ic6NYn47EOuaYY5DE008/XZM4zcxqzQkkJ9+EVRyBdWh7C4dPbeuvgUyYMIHZs2c7gZjZQcsJJCefQLbs6qa9tYmWpgbmTJ3Ahm17rwWZN2+eE4iZHbScQHLy9wPZurubQycmI7COmDahfxQWwLHHHsvTTz/df22ImdnBxAkkJ38dyNbdPRzS3gLA7GltbNzRRV8hSRhz585l9+7dntbdzA5KTiA52SasvkKwbXc3h0xMEsicaRPoLQTP79wDJE1YAKtXr65NsGZmNeQEkhMRqCFJIDte7KEQSQc6wJypE4C9FxMee+yxAO4HMbODkhNITrYGsiUdgZWtgcDeiwkPO+wwJk6c6ARiZgclJ5CcQqEAJAmkeA3IoZk+ENh7MaEk5s2bx6pVq0Y/UDOzGnMCycl2ou/oSiZOnDIhufPvlLZmJrc2sT4zlPekk07i8ccf90gsMzvoVDWBSDpL0kpJqyRdUmJ7q6Qb0+33Spqbrn+jpPslPZL+/o1qxpmVbcJ6sbuXlqYGmhr2vkyzp+29mBBgwYIFbN++3XNimdlBp2oJRFIjcCVwNjAfuEDS/Nxu7we2RsRxwBXAp9P1m4G3RsTLgQuBb1YrzrxsAtnd3cfElsZ9ts+d3s4jz27vH8q7YMECAJYvXz5aIZqZjQnVrIEsAlZFxOqI6AZuAM7N7XMucG26fDPwBkmKiAcjoni3puVAm6TWKsbaLzsKK59Arrv3GWZMamXD9i4+unQ51937DA9un0Bzc7MTiJkddJqq+NxHAGszj9cBi8vtExG9krYD00lqIEW/DTwYEXvyJ5B0EXARwKxZs+jo6Bh20Dt37mTKlKm0bV7Bnt29TGqEts0r+re/qjn4Xgvc98QzvLI5efkOP/xw7rrrLk455ZRhn79aOjs7R+T1GSvqrTxQf2Wqt/JA/ZWps7NzWMdXM4GoxLp8T/OA+0haQNKs9aZSJ4iIq4CrABYuXBhLliwZUqBZV1xxBWpspGvGiXTGSma3T6BrxtH77PPqeRvpWLmJDROP5ZCJLSxevJjbb7+dM844Y7+7GY4VHR0djMTrM1bUW3mg/spUb+WB+ivTcJNhNZuw1gFHZR4fCeRvIt6/j6QmYCqwJX18JPDfwO9ExFNVjHMfSR9I8rKU6gMBOHXuIQAsW7MFcEe6mR2cqplAlgHHS5onqQU4H1ia22cpSSc5wHnAnRERkqYB3wc+EhE/q2KM+ykO4y1E8GKZBDJtYgsvPXwy963ZSm+hwMknnwzAgw8+OJqhmpnVVNUSSET0AhcDtwGPAzdFxHJJl0s6J93tamC6pFXAnwHFob4XA8cBfy/pl+nPYdWKNSu5IyHs6SkQwISW0q18i+YeSueeXlZt7OTEE09k6tSp3HPPPaMRopnZmFDNPhAi4hbglty6SzPLXcDbSxz3ceDj1YytnOIw3t3dyUWEpWogAMfPmszElkZ+uW4bDQ0NLFq0iLvvvnu/2XzNzOqVr0TPKSaA3d19AExsLp1AGhvEy+ZM5fENO9jd3cvixYvZsGEDa9euLbm/mVm9cQLJKXaiv9iTJpAyNRCAk4+aSk9fcPtjG3nNa14D4GYsMztoOIHk7N+EVb6Vb+70dqa0NfHdh9Yzb948Zs6cyd133z1aoZqZ1ZQTSE6+CWvCADWQBomTj5zGT554nu0v9vC6172Ou+66i+7u7tEK18ysZpxAcg4kgQC84shp9PQF3314A2eddRadnZ387GejOvLYzKwmnEByik1YL3b30dbcQMMgI6rmTGvjFUdN4wt3PMnLXvlqpk6dyq233jpK0ZqZ1Y4TSE62D2Sg/o8iSXz0nAU8v3MP//a/v+LMM8/kjjvuoKura9BjzczGMyeQnGwT1kAjsLJeedQ03rHwSL5219O84jWvZ/fu3dx5551VjtTMrLacQHL6m7B6Kk8g1937DMcdNpmmRvGvj4lDDpvNFf92dZUjNTOrLSeQnL1NWH1MKHMRYSmTWpt484LDefqFF5n5qjNZt+oxHn744SpGamZWW04gOXubsCrrA8laNPdQXjprMsubT6S5bSLXXnvt4AeZmY1TTiA5yWSKoqunUHETVpEk/u8pR9AyYSINL/l1br31Vt+p0MzqlhNITqFQoC+SobuDXQNSyuS2Zn77lCPZdszpNLS184+f/BQR+ftomZmNf04gJfSmCeRAm7CKTpo9hXf+2gn0vPTNPHj/fVxzw3+OZHhmZmOCE0hOoVDIJJADr4EUveLIaXz98j9EM+bxmU98nC985+cUCq6JmFn9cALJGakEArBmyx7e+8d/hxoaufKTf8+ST97KJ77/+EiEaWZWc04gORHRn0AOZBhvOcccdSTv/PBHaNy5ked/cCVX/fhx3v3v9/DjFZvoc43EzMYxJ5CcQqFATyFZHmofSN7xr1jE//2Dj6AX1jDzvqtY8dSv+N1rlnH6Z37MF+94kk07PO2JmY0/TiA5hUKBnhACWptH7uWZf+rrOP9PL6d35wsUfvhZTmMlrU3wz7c/wWmfvIM3X/FTPnf7E3zv4fWsfG4n3b2FETu3mVk1VPWe6OPN8zu7kiasgpjQ0jjoTLwH6riTT+X9l32R733tCh76zleZMedo3vL6t7Ft+gJWbt7DF+98kuKI38YGMXf6RE6YNZnjD5vE8bMmc/ysScyb0U5r0/Cb1szMhquqCUTSWcC/AI3Av0fEp3LbW4FvAK8GXgDeGRFr0m0fAd4P9AF/FBG3VTPWh9Zu4/yv/ByAntCINV/lHXrYHN7715/hsWU/5a6l1/Pj//gCza1tHLvgFF5zwsuZcvRJ9LTP4vnObjbt3MMvnt7Cbcufo5BJLMdMn8i86e3MnNzKjEmtzJjUwozJrUxvb2X6pBYObW/hkIktNDaMbAI0M8uqWgKR1AhcCbwRWAcsk7Q0Ih7L7PZ+YGtEHCfpfODTwDslzQfOBxYAc4AfSTohIvqqFe9xh03i115yKD8HNr0oDh/mCKyBSGLBojOYf+rprH3iUR65+06eXv4gKx9IElhjUzOHHDab6YcfyYJDZ9LaPplC80T2NExkNy1s2ywe3gAv9ondfQ0UGpqgsRkQSKAGJDFlYpJMpk9qZc+uF7l+7X20NDXS0thAS1MDrU3J7/0eNzXQ3NBAQ4NoatDe30p+NzaKRuW2pb8b05+9+zfQ0ABNDUlzYE9fgUIEzY3J+ZJ1QRBMam2ivaWJ3kLwYk8fEUFDQ3Ku4vM2KjlXIYIXu/vo7i2ghuTukMm2ZFnp65z8TpbNRkOhEAT0f4GLCPb0FmiQaEk/8109fexO7zk0obmRvkLwwq5udu3pZXp7K1MmNPF85x6e2rSLiOAlh02ivbWJn6x8np88sYnZUyfwpgWzmD97Sk0/29WsgSwCVkXEagBJNwDnAtkEci5wWbp8M/AlJa/GucANEbEHeFrSqvT5RvyG41u3buXMM88E6L9ivICGPYS3EpI4+qUv5+iXvhyAbZs38szKR9j07Bq2PPcsLzy3jl+teJiu3Z1ln6N1gOfvBp5LfwBW9ScYAWLYY8Bq9sEd5nnHaTIZb1EHw4t5tMYoloux5PkHKJSKx0RmRf7JlHs80LoyL4CUbPpKQENDMlr05S9/Oddcc03pA6qomgnkCGBt5vE6YHG5fSKiV9J2YHq6/p7csUfkTyDpIuCi9GGnpJUjEvmKFTOe+u8rNle1zWz0zQA21zqIEVRv5YH6K1O9lQfGaJkeeOCBoU7eOgM4ZqjnrWYCKZWn8zm13D6VHEtEXAVcdeChDUzSfRGxcKSft5bqrUz1Vh6ovzLVW3mg/sqUlmfuUI+v5jDedcBRmcdHAuvL7SOpCZgKbKnwWDMzq6FqJpBlwPGS5klqIekUX5rbZylwYbp8HnBnJB0RS4HzJbVKmgccD/yiirGamdkBqloTVtqncTFwG8kw3q9FxHJJlwP3RcRS4Grgm2kn+RaSJEO6300kHe69wIerOQKrhBFvFhsD6q1M9VYeqL8y1Vt5oP7KNKzyyPeqMDOzofBUJmZmNiROIGZmNiROIDmSzpK0UtIqSZfUOp6hkLRG0iOSfinpvnTdoZJul/Rk+vuQWsc5EElfk7RJ0qOZdSXLoMQX0vfsYUmn1C7y0sqU5zJJz6bv0y8lvSWz7SNpeVZKenNtoi5P0lGSfizpcUnLJf1xun48v0flyjQu3ydJbZJ+IemhtDwfTdfPk3Rv+h7dmA5yIh20dGNannslzR30JBHhn/SHpLP/KeBYoAV4CJhf67iGUI41wIzcus8Al6TLlwCfrnWcg5ThdOAU4NHBygC8BbiV5Pqh04B7ax1/heW5DPiLEvvOTz97rcC89DPZWOsy5GKcDZySLk8GnkjjHs/vUbkyjcv3KX2tJ6XLzcC96Wt/E3B+uv7LwB+kyx8Cvpwunw/cONg5XAPZV//0KxHRDRSnX6kH5wLFS1WvBd5Ww1gGFRE/JRmZl1WuDOcC34jEPcA0SbNHJ9LKlClPOf1T+UTE00BxKp8xIyI2RMQD6fJO4HGS2SLG83tUrkzljOn3KX2ti/MgNac/AfwGydRRsP97VHzvbgbeoEEm2nIC2Vep6VcG+gCNVQH8UNL96XQvALMiYgMkfyjAYTWLbujKlWE8v28Xp006X8s0K46r8qRNHa8i+YZbF+9RrkwwTt8nSY2SfglsAm4nqSVti4jedJdszPtMLQUUp5YqywlkXxVNoTIO/HpEnAKcDXxY0um1DqjKxuv79m/AS4BXAhuAf07Xj5vySJoE/CfwJxGxY6BdS6wbL2Uat+9TRPRFxCtJZvNYBJxUarf09wGXxwlkX3UxhUpErE9/bwL+m+SDs7HYZJD+3lS7CIesXBnG5fsWERvTP/AC8FX2Nn+Mi/JIaib5R/sfEfFf6epx/R6VKtN4f58AImIb0EHSBzItnToK9o253NRSZTmB7KuS6VfGNEntkiYXl4E3AY+y77QxFwLfqU2Ew1KuDEuB30lH+pwGbC82o4xluT6A/0PyPsE4mMonbRu/Gng8Ij6X2TRu36NyZRqv75OkmZKmpcsTgDNJ+nV+TDJ1FOz/HpWaWqq8Wo8UGGs/JKNFniBpK/zbWsczhPiPJRkZ8hCwvFgGkrbMO4An09+H1jrWQcpxPUlzQQ/JN6P3lysDSdX7yvQ9ewRYWOv4KyzPN9N4H07/eGdn9v/btDwrgbNrHX+J8ryWpHnjYeCX6c9bxvl7VK5M4/J9Ak4GHkzjfhS4NF1/LEmiWwV8G2hN17elj1el248d7ByeysTMzIbETVhmZjYkTiBmZjYkTiBmZjYkTiBmZjYkTiBmZjYkTiBWFyRNz8yW+lxu9tSWITzfmZL+ZxjxfEvSiMw3JulYSednHi+WdMVIPLfZcFTtlrZmoykiXiCZagJJlwGdEfHZ7D7phWKK5IriMUVSU+ydnyjvWJKLWm8AiIh72TtHk1nNuAZidU3ScZIelfRl4AFgtqSrJN2X3iPh0sy+v5ne1+EuMrMwS5ok6Zr03goPSnprifM0SPpXSY9J+i4wI7NtXeaK4NMk/Shd/rikr0i6Hfi6pJdI+t/0HPdLWpw+xaeA16e1qT/K1o4kzZC0NJ3o7+eSXpZ57qsl/UTSakkfTtdPlnSrkntEPCrpPMyGyDUQOxjMB343Ij4IIOmSiNiSzvfzY0k3k9xD5SvAGcBq9k53DXAp8IOIeF86E+u9km6PiK7MPueR3BPiZcAc4DGSey0M5lXA6RHRJWki8MZ0+USSqbUXk9xX4+KIeFsa/5mZ4z9Gcm+NcyS9CbgGWJhuOwF4AzANeDxNom8B1kTE2elzTa0gRrOSXAOxg8FTEbEs8/gCSQ+Q1EhOIkkw84EnIuKpSKZn+I/M/m8C/jadFvvHJFM+HJ07x+nA9RFRiIh1JBPXVeI7mUTUClyt5K6FN6QxDea1JFNtEBE/BOakc6ABfC8iuiOZVHMLMJNkWouzJH1K0q9HxPYK4zTbj2sgdjDYVVyQdDzwx8CiiNgm6VskCQHKT10t4G0R8dQg5yl3fC97v6y15bbtyiz/Ocn9GN5DcvOfTgaXn4I7+3hPZrkPaIqIxyUtJKmJ/JOk70XEJyo4j9l+XAOxg80UYCewI51ltXgf68eAE9KZmAVckDnmNuCPig8kvarE8/6UZGbWBklHkDSFFa0BXp0u//YAsU0FNqQ1oAvZmwx2ktxitZSfAu9O4zoTWBcRu8rsSxpbZ0R8E/gcyW12zYbENRA72DxAkiweJenr+BlAROyW9EGS+3ZvTte/ND3mo8DnJT1C8qVrFfvf6vhm4PXp864k+cdedBnwVUnPMfB0318CbpZ0AfAj9tYgHgQaJT1EMt34Y5ljLiXpgH+YpMbyu4OU/xXApyQVgG7gg4Psb1aWZ+M1M7MhcROWmZkNiROImZkNiROImZkNiROImZkNiROImZkNiROImZkNiROImZkNyf8HfeyY2OaSW3EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fitting an exponential distribution\n",
    "graph_duration = sns.distplot(trades1['dif'], fit = expon)\n",
    "plt.title('Histogramme + Exponential distribution fitted')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_duration = sns.distplot(trades1['dif'], fit = expon)\n",
    "graph_duration.set_yscale('log')\n",
    "plt.title('Histogramme - Log- scale - + Exponential distribution fitted')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2. Trade sizes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max size: 19530.0\n",
      "Min size: 1.0\n",
      "Mean size: 212.51439302392802\n"
     ]
    }
   ],
   "source": [
    "# Some statistics about trade sizes\n",
    "\n",
    "print('Max size:', trades['lastQ'].max())\n",
    "print('Min size:', trades['lastQ'].min())\n",
    "print('Mean size:', trades['lastQ'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting an histogram of the trade sizes\n",
    "plt.hist(trades['lastQ'],200)\n",
    "plt.title('Histogramme - Trade sizes')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(trades['lastQ'],200)\n",
    "plt.yscale('log')\n",
    "plt.title('Histogramme - Log-scale - Trade sizes')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Trades sizes\n",
    "graph_trades = sns.distplot(trades['lastQ'], fit = expon)\n",
    "plt.title('Histogramme - Trade sizes + Exp. Distrib. Fitted ')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the empirical distribution and fitting an exponential distribution\n",
    "graph_trades = sns.distplot(trades['lastQ'], fit = expon)\n",
    "graph_trades.set_yscale('log')\n",
    "plt.title('Histogramme - Log-scale - Trade sizes + Exp. Distrib. Fitted ')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total\n",
    "## 3.1. Trades durations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(total_trades)):\n",
    "    trades = total_trades[i]\n",
    "    trades['dif'] = trades['ts'].diff()\n",
    "    total_trades[i] = trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max difference: 116.596000000005\n",
      "Min difference: 0.0\n",
      "Mean difference: 1.1720445667999386\n"
     ]
    }
   ],
   "source": [
    "trades = pd.concat(total_trades)\n",
    "print('Max difference:', trades['dif'].max())\n",
    "print('Min difference:', trades['dif'].min())\n",
    "print('Mean difference:', trades['dif'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(trades['dif'])\n",
    "plt.title('Trades durations')\n",
    "plt.xlabel('Observations')\n",
    "plt.ylabel('Trades durations')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# An histogram keeping interesting values only.\n",
    "trades1 = trades[trades['dif'] >=0.001]\n",
    "\n",
    "plt.hist(trades1['dif'],100)\n",
    "plt.title('Histogram - Trades durations')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ux2MQw2zcPuDBazMbV0UHqa8APg/8MfBakqkwXltWpepxC8LMrHxFxyAGIuK6Umti48YzwZrZeCiaIL4n6QLgKuD3Qysj4rZSalWHB6nNzMpXNEHMTf/Nzt0RwJvGtzrF+DJXM7PyFZ2LyU+PMzObYMb0RLmI8BPlWpzHI8ysUS3zRLnR8GWuZmblK/WJcmXxZa5mZuUrOkjd6BPlrIW4u8nMRqNogvgoyYyrL5f0Q9InypVWKyudk4WZ1VM3QUjaC9gPGK8nylmLcbIwszx1xyAi4hngwojYFRGbI2JTs5ODB6nNzMpXdJD6Bknvyj40qJk8SG1mVr7RjEFMBnZJepKkmyki4vml1czMzJqq6J3UB5ZdETMzay1F76R+Q976iLhpfKtjzeYBazMbUrSL6W8y7/cDjgU20KTJ+szMrHxFu5gWZpclTQf+Zyk1spbh1oTZxFa0BTFcPzBnPCsyGn4exJ7nZGE28RQdg7iYdJoNkktjXwP8rKxK1ePnQZiZla9oC+LWzPtdwMqI+GEJ9TEzsxZRNEGsBp6MiKcBJE2SdEBE/K68qpmZWTMVTRA3AicAg+ny/sANwOvKqJS1tux4RJbHJszaS9GpNvaLiKHkQPr+gHKqZGZmraBognhc0tFDC5KOAZ4op0pmZtYKinYxfRj4D0k70uWXAH9WTpXMzKwVFL1Rbr2kV7L7eRB3ljHlt6STgbcCLwYujYgbxvsYVp7hYxMekzCrtkJdTJI+CExOnwWxEeiQ9IGC+14paaekTcPWz5d0l6StkpYCRMS3IuIM4DTcQjEza6qiYxBnRMQjQwsR8Vug6E1qy4H52RWSJgGXAguA2cBiSbMzm3wy/dzMzJqk6BjEXpIUEQHPfsHvU2THiLhJUtew1ccCWyPinrS8XuAkSVuA84HrIuK2gnWzCvBUHWbVo/Q7f+SNpM8BLwMuJ5ly4/3ALyPi7EIHSRLE2oiYky6fAsyPiL9Ml/8cmAv8HHgvsB74aURcnlPWEmAJQGdn5zG9vb1FqvAcOx8e4ME2ug6rc39aLp4jp+1+4t/G7QO560cyODhIR0fHuNerWRxPa2u3eKB2TPPmzdsQEd319i/agvg7ki6lM0kGqW8ArhhFPYfLe3RpRMRFwEUj7RgRyyQ9ACw88MADj+np6WmoAhevuJoLNzY6V2HrOfvIXS0Xz7ZTe559f1q2BZFZP5K+vj4aPb+tyPG0tnaLB8Ye04jfKJL2Bj4LvA+4n+SLfTpwL8n4xdMNHrc/LWfIocCOGts+hyfrq4Zad1z7Tmyzaqg3SH0B8ELgsIg4OiKOAmYAU4DPjeG464FZkmZI2gdYBKwpurOkhZKWDQwM1N/YzMwaUi9BvI3kCqbHhlak798PvKXIASStBG4GDpfUL+n0iNgFnAVcD2wBVkXE5qKVjohrImLJlCnF+rLNzGz06nVaR+SMYkfE05Lqj24n2y6usX4dsK5IGWZmtufVa0HcIek9w1dKejdwZzlVqs9dTO2va+m1bNw+UHO8wszKV68F8UHgKkl/AWwgucT1tSTTfb+j5LrV5EFqM7PyjZggImI7MFfSm4BXkVzFdF1E3LgnKleLn0ltZla+opP1fRf4bsl1KcwtiPY02u4k351tVq6iczGZmdkE01q33hbkLqaJxS0Fs+aoZIJwF9PEVeTubCcRs/HhLiYzM8vlBGFmZrkqmSB8o5yZWfk8BmFtx+MRZuOjki0IMzMrnxOEmZnlcoIwM7NclRyD8I1yVpTHI8waV8kWhB8YZGZWvkq2IMwa4daE2ehUsgVhZmblc4IwM7Nc7mIyq8FdUjbROUHYhOdEYJavkgnCl7naWBWZNtxsoqvkGIQvczUzK18lWxBmzeQuKZsonCDMxsDJwtqZE4TZOHGysHZTyTEIMzMrnxOEmZnlcheTWRO5W8paWcu0ICQdJukKSaubXRczMys5QUi6UtJOSZuGrZ8v6S5JWyUtBYiIeyLi9DLrY2ZmxZXdxbQcuAT46tAKSZOAS4E/AfqB9ZLWRMQdJdfFrDLc9WStQBFR7gGkLmBtRMxJl48Hzo2IE9PlcwAi4rx0eXVEnDJCeUuAJQCdnZ3H9Pb2NlSvnQ8P8OATDe3akjr3p63igdaK6chpu+/a37h9oKHt68VT6xjZ9a1kcHCQjo6OZldj3LRbPFA7pnnz5m2IiO56+zdjkHoacH9muR+YK+lFwGeAoySdM5QwhouIZcAygO7u7ujp6WmoEhevuJoLN7bPGP3ZR+5qq3igtWLadmrPs+9PKzBfU9729eKpdYzs+lbS19dHo///WlG7xQNjj6kZ//uUsy4i4jfAmYUK8GR9tod5Ej+biJpxFVM/MD2zfCiwYzQFeLI+M7PyNSNBrAdmSZohaR9gEbBmNAVIWihp2cBA/b5gMzNrTNmXua4EbgYOl9Qv6fSI2AWcBVwPbAFWRcTm0ZTrFoSZWflKHYOIiMU11q8D1jVarscgzJqnKzPo3tPcqljJWuZO6tFwC8LMrHyVTBBmZla+1rjIfJTcxWRWTK07ske73iamSrYg3MVkZla+SiYIMzMrn7uYzEownndeu9vHmqWSLQh3MZmZla+SCcLMzMrnBGFmZrk8BmHWIkY7blFre49T2HipZAvCYxBmZuWrZIIwM7PyOUGYmVkuj0GYTXB+Wp7VUskWhMcgzMzKV8kEYWZm5XOCMDOzXE4QZmaWywnCzMxyOUGYmVkuX+ZqViFFLkkdr8tWi0wzPp7TfRQpa7RTn3uq9LGpZAvCl7mamZWvkgnCzMzK5wRhZma5nCDMzCyXE4SZmeVygjAzs1xOEGZmlssJwszMcrXMjXKSJgOXAU8BfRGxoslVMjOb0EptQUi6UtJOSZuGrZ8v6S5JWyUtTVe/E1gdEWcAby+zXmZmVl/ZXUzLgfnZFZImAZcCC4DZwGJJs4FDgfvTzZ4uuV5mZlaHIqLcA0hdwNqImJMuHw+cGxEnpsvnpJv2A7+NiLWSeiNiUY3ylgBLADo7O4/p7e1tqF47Hx7gwSca2rUlde5PW8UD7RfTRIrnyGmjnwZn4/aBumVlt6l1jCLl5BkcHKSjo6NeNWsqUrexGu0xasU0b968DRHRXW//ZoxBTGN3SwGSxDAXuAi4RNJbgWtq7RwRy4BlAN3d3dHT09NQJS5ecTUXbmyZIZgxO/vIXW0VD7RfTBMpnm2n9oy6vNNqTdaXKSu7Ta1jFCknT19fH41+nww/biPxl3GMscbUjN9W5ayLiHgceF+hAjybq5lZ6ZpxmWs/MD2zfCiwYzQFeDZXM7PyNSNBrAdmSZohaR9gEbBmNAVIWihp2cBAfl+jmZmNXdmXua4EbgYOl9Qv6fSI2AWcBVwPbAFWRcTm0ZTrFoSZWflKHYOIiMU11q8D1jVarscgzMzKV8mpNtyCMDMrXyUThMcgzMzKV8kE4RaEmVn5Sr+TukySHgLua3D3qcCvx7E6zdZu8UD7xeR4Wlu7xQO1Y3pZRBxcb+dKJ4ixkHRrkVvNq6Ld4oH2i8nxtLZ2iwfGHlMlu5jMzKx8ThBmZpZrIieIZc2uwDhrt3ig/WJyPK2t3eKBMcY0YccgzMxsZBO5BWFmZiNwgjAzs1wTMkHUeCZ2ZUiaLul7krZI2izpr9P1L5T0bUm/SP99QbPrOhqSJkn6iaS16fIMSbek8Xwjnf23EiQdJGm1pDvT83R8lc+PpI+kv2ubJK2UtF/Vzo+kKyXtlLQpsy73nChxUfodcbuko5tX83w14rkg/Z27XdI3JR2U+eycNJ67JJ1Y5BgTLkGM8EzsKtkFnB0RRwDHAR9MY1gK3BgRs4Ab0+Uq+WuSGX6H/DPwL2k8vwVOb0qtGvNF4D8j4pXAq0niquT5kTQN+BDQnT46eBLJNP1VOz/LgfnD1tU6JwuAWelrCfClPVTH0VjOc+P5NjAnIv4I+DlwDkD6/bAIeFW6z2Xpd+GIJlyCAI4FtkbEPRHxFNALnNTkOo1KRDwQEbel7x8j+fKZRhLHv6Wb/RtwcnNqOHqSDgXeCnwlXRbwJmB1ukll4pH0fOANwBUAEfFURDxChc8PyczP+0vaGzgAeICKnZ+IuAl4eNjqWufkJOCrkfgRcJCkl+yZmhaTF09E3JA+UgHgRyQPZIMknt6I+H1E3AtsJfkuHNFETBB5z8Se1qS6jJmkLuAo4BagMyIegCSJAC9uXs1G7QvAx4Bn0uUXAY9kftmrdJ4OAx4C/lfaZfYVSZOp6PmJiO3A54BfkiSGAWAD1T0/WbXOSTt8T/wFcF36vqF4JmKCyH0m9h6vxTiQ1AH8b+DDEfFos+vTKElvA3ZGxIbs6pxNq3Ke9gaOBr4UEUcBj1OR7qQ8ab/8ScAM4BBgMkkXzHBVOT9FVPn3D0mfIOmKXjG0KmezuvFMxAQx5mditwJJzyNJDisi4qp09YNDzeD0353Nqt8ovR54u6RtJF1+byJpURyUdmlAtc5TP9AfEbeky6tJEkZVz88JwL0R8VBE/AG4Cngd1T0/WbXOSWW/JyS9F3gbcGrsvtGtoXgmYoIY8zOxmy3tn78C2BIRn898tAZ4b/r+vcDVe7pujYiIcyLi0IjoIjkf342IU4HvAaekm1Upnl8B90s6PF31ZuAOKnp+SLqWjpN0QPq7NxRPJc/PMLXOyRrgPenVTMcBA0NdUa1M0nzg48DbI+J3mY/WAIsk7StpBsng+4/rFhgRE+4FvIVkhP9u4BPNrk8D9f9jkubh7cBP09dbSPrtbwR+kf77wmbXtYHYeoC16fvD0l/ircB/APs2u36jiOM1wK3pOfoW8IIqnx/g08CdwCbga8C+VTs/wEqSMZQ/kPxFfXqtc0LSJXNp+h2xkeQKrqbHUCCerSRjDUPfC5dntv9EGs9dwIIix/BUG2ZmlmsidjGZmVkBThBmZpbLCcLMzHI5QZiZWS4nCDMzy+UEYZUl6UWSfpq+fiVpe2Z51DOLSjpB0rfGUJ+vSxqX+YgkHSZpUWZ5rqR/GY+yzYrau/4mZq0pIn5Dcr8Bks4FBiPic9lt0hu7FBHPPLeE5pK0d+yey2i4w0huGuwFiOSu7FtqbGtWCrcgrO1Impk+t+By4DbgJZKWSbo1fabBpzLbvjWdH/8HZGb1ldQhabmkH6cT7i3MOc5eki6TdIeka4Cpmc/6h+bil3ScpO+k7/9J0pclfZtkMr+XS/p+eowNkuamRZwPzEtbQx/Ktm4kTZW0Jp3z//9KmpMp+wpJ/0fSPZI+mK4/UNJ1kn6W/lxOwawAtyCsXc0G3hcRZwJIWhoRD6dzB31P0mpgG/Bl4I3APeyeuhrgUyTPczgtnazuFknfjognM9ucQjKB3RySSezuAC4vULejgDdExJOSDgD+JH3/SpIpp+eSTO53VkScnNb/hMz+/wjcEhFvl/SnJM8F6E4/ewXJVBgHAVvSJPkWYFtELEjLmlKgjmZuQVjbujsi1meWF0u6jaRFcQRJApkN/Dwi7o5kSoEVme3/FPiEpJ+SzDm0H/DSYcd4A7AyIp6JiH6gr2Ddrs4kmn2BK5Q8Faw3rVM9f0wy3QURcQNwSDqdOCTTlDwVETtJnhVwMMl0H/MlnS/p9RExULCeNsG5BWHt6vGhN5JmkTyt7tiIeETS10m+8KH2lMcCTo6Iu+scp9b+u9j9B9h+wz57PPP+bJK5c94NPA8YrHO8obrVWv595v3TwN4RsUVSN0lL4gJJayPiswWOYxOcWxA2ETwfeAx4NJ3Seeh5vHcAr0hn9hWwOLPP9SSP2QRA0lE55d5EMkPmXkoey/nGzGfbgGPS9+8aoW5TgAfSFsx72f1l/xhwYI19bgJOTet1AsnU4o/X2HbokaGDEfE14PMkU4+b1eUWhE0Et5Ekg00kYw0/BIiI30k6k+SpW79O1w9N0f1p4AuSNpL8IbWV5z6adjUwLy33LpIv7iHnAv8q6VeMPK3yJcBqSYuB77C7BfATYJKkn5FM7X5HZp9PkQxw307S4nhfnfhfDZwv6RngKeDMOtubAXg2VzMzy+cuJjMzy+UEYWZmuZwgzMwslxOEmZnlcoIwM7NcThBmZpbLCcLMzHL9P6ArKpN4YRA9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Log Scale\n",
    "trades1 = trades[trades['dif'] > 0.001]\n",
    "\n",
    "plt.hist(trades1['dif'],100)\n",
    "plt.yscale('log')\n",
    "plt.title('Histogram - Log-scale')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.yscale('log')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fitting an exponential distribution\n",
    "graph_duration = sns.distplot(trades1['dif'], fit = expon)\n",
    "plt.title('Histogramme + Exponential distribution fitted')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_duration = sns.distplot(trades1['dif'], fit = expon)\n",
    "graph_duration.set_yscale('log')\n",
    "plt.title('Histogramme - Log- scale - + Exponential distribution fitted')\n",
    "plt.xlabel('Trade durations')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2. Trade sizes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max size: 19530.0\n",
      "Min size: 1.0\n",
      "Mean size: 212.51439302392802\n"
     ]
    }
   ],
   "source": [
    "# Some statistics about trade sizes\n",
    "\n",
    "print('Max size:', trades['lastQ'].max())\n",
    "print('Min size:', trades['lastQ'].min())\n",
    "print('Mean size:', trades['lastQ'].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting an histogram of the trade sizes\n",
    "plt.hist(trades['lastQ'],200)\n",
    "plt.title('Histogramme - Trade sizes')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(trades['lastQ'],200)\n",
    "plt.yscale('log')\n",
    "plt.yscale('log')\n",
    "plt.title('Histogramme - Log-scale - Trade sizes')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Trades sizes\n",
    "graph_trades = sns.distplot(trades['lastQ'], fit = expon)\n",
    "plt.title('Histogramme - Trade sizes + Exp. Distrib. Fitted ')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the empirical distribution and fitting an exponential distribution\n",
    "graph_trades = sns.distplot(trades['lastQ'], fit = expon)\n",
    "graph_trades.set_yscale('log')\n",
    "plt.title('Histogramme - Log-scale - Trade sizes + Exp. Distrib. Fitted ')\n",
    "plt.xlabel('Trade sizes')\n",
    "plt.ylabel('Occurences')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Durations are, in average, short. \n",
    "\n",
    "Trade sizes are more important, in average.\n",
    "\n",
    "For more informations, look at the statistics edited for each stock."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.3 Intraday activity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**EDF intraday activity.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = edf_trades[0]\n",
    "df['ts_delta'] = df['ts_delta'] + df['date_delta']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = df.set_index('ts_delta').groupby(pd.Grouper(freq = '2Min')).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(t['date_delta'])\n",
    "xfmt = md.DateFormatter('%H:%M:%S')\n",
    "ax = plt.gca()\n",
    "plt.title('Intraday activity - EDF')\n",
    "ax.xaxis.set_major_formatter(xfmt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Renault intraday activity.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = renault_trades[0]\n",
    "df['ts_delta'] = df['ts_delta'] + df['date_delta']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = df.set_index('ts_delta').groupby(pd.Grouper(freq = '2Min')).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(t['date_delta'])\n",
    "xfmat = md.DateFormatter('%H:%M:%S')\n",
    "ax = plt.gca()\n",
    "plt.title('Intraday activity - Renault')\n",
    "ax.xaxis.set_major_formatter(xfmt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Total intraday activity.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = total_trades[0]\n",
    "df['ts_delta'] = df['ts_delta'] + df['date_delta']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = df.set_index('ts_delta').groupby(pd.Grouper(freq = '2Min')).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(t['date_delta'])\n",
    "xfmat = md.DateFormatter('%H:%M:%S')\n",
    "ax = plt.gca()\n",
    "plt.title('Intraday activity - Total')\n",
    "ax.xaxis.set_major_formatter(xfmt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Intraday activities are quite different between the the 3 stocks. The most traded one seems to be Total, the second one is Renault and the last one is EDF."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. Descriptive statistics using the quote files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.1. Spread distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**EDF.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_spread = []\n",
    "for i in range(len(edf_quotes)):\n",
    "    quotes = edf_quotes[i]\n",
    "    quotes_best = quotes[quotes['level'] == 1]\n",
    "    quotes_best = quotes_best.reset_index()\n",
    "    del quotes_best['index']\n",
    "    ask = 0\n",
    "    bid = 0 \n",
    "    spread = np.zeros(len(quotes_best))\n",
    "    for j in range(len(quotes_best)):\n",
    "        if quotes_best['type'][j] == 'A':\n",
    "            ask = quotes_best['price'][j]\n",
    "        else:\n",
    "            bid = quotes_best['price'][j]\n",
    "        if (ask!=0) & (bid!=0):\n",
    "            spread[j] = ask - bid\n",
    "    spread = spread[spread!=0]\n",
    "    l_spread.append(spread)\n",
    "\n",
    "l = []\n",
    "for elem in l_spread:\n",
    "    for think in elem:\n",
    "        l.append(think)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comment: mean of the spread distribution is: 0.012913529936582149\n"
     ]
    }
   ],
   "source": [
    "plt.hist(l,40)\n",
    "plt.title('Spread distribution - EDF')\n",
    "plt.xlabel('Spread')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('Comment: mean of the spread distribution is:', np.mean(l))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## In calendar time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "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>date_xl</th>\n",
       "      <th>ts</th>\n",
       "      <th>type</th>\n",
       "      <th>level</th>\n",
       "      <th>price</th>\n",
       "      <th>qty</th>\n",
       "      <th>date_delta</th>\n",
       "      <th>ts_delta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>42277.0</td>\n",
       "      <td>32428.358</td>\n",
       "      <td>B</td>\n",
       "      <td>1</td>\n",
       "      <td>15.665</td>\n",
       "      <td>837.0</td>\n",
       "      <td>2015-10-02</td>\n",
       "      <td>09:00:28.358000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>42277.0</td>\n",
       "      <td>32428.378</td>\n",
       "      <td>B</td>\n",
       "      <td>1</td>\n",
       "      <td>15.665</td>\n",
       "      <td>1287.0</td>\n",
       "      <td>2015-10-02</td>\n",
       "      <td>09:00:28.378000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>42277.0</td>\n",
       "      <td>32428.447</td>\n",
       "      <td>B</td>\n",
       "      <td>1</td>\n",
       "      <td>15.670</td>\n",
       "      <td>568.0</td>\n",
       "      <td>2015-10-02</td>\n",
       "      <td>09:00:28.447000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>42277.0</td>\n",
       "      <td>32428.508</td>\n",
       "      <td>B</td>\n",
       "      <td>1</td>\n",
       "      <td>15.665</td>\n",
       "      <td>1287.0</td>\n",
       "      <td>2015-10-02</td>\n",
       "      <td>09:00:28.508000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>42277.0</td>\n",
       "      <td>32429.545</td>\n",
       "      <td>B</td>\n",
       "      <td>1</td>\n",
       "      <td>15.665</td>\n",
       "      <td>1172.0</td>\n",
       "      <td>2015-10-02</td>\n",
       "      <td>09:00:29.545000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   date_xl         ts type  level   price     qty date_delta        ts_delta\n",
       "0  42277.0  32428.358    B      1  15.665   837.0 2015-10-02 09:00:28.358000\n",
       "1  42277.0  32428.378    B      1  15.665  1287.0 2015-10-02 09:00:28.378000\n",
       "2  42277.0  32428.447    B      1  15.670   568.0 2015-10-02 09:00:28.447000\n",
       "3  42277.0  32428.508    B      1  15.665  1287.0 2015-10-02 09:00:28.508000\n",
       "4  42277.0  32429.545    B      1  15.665  1172.0 2015-10-02 09:00:29.545000"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quotes_best.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_spread = []\n",
    "for i in range(len(edf_quotes)):\n",
    "    quotes = edf_quotes[i]\n",
    "    quotes_best = quotes[quotes['level'] == 1]\n",
    "    quotes_best = quotes_best.reset_index()\n",
    "    del quotes_best['index']\n",
    "    ask = 0\n",
    "    bid = 0 \n",
    "    spread = np.zeros(len(quotes_best))\n",
    "    for j in range(len(quotes_best)):\n",
    "        if quotes_best['type'][j] == 'A':\n",
    "            ask = quotes_best['price'][j]\n",
    "            ask_time = quotes_best['ts_delta'][j]\n",
    "        else:\n",
    "            bid = quotes_best['price'][j]\n",
    "            bid_time = quotes_best['ts_delta'][j]\n",
    "        if (ask!=0) & (bid!=0):\n",
    "            spread[j] = np.absolute((ask - bid)*(ask_time-bid_time).total_seconds())\n",
    "    spread = spread[spread!=0]\n",
    "    l_spread.append(spread)\n",
    "\n",
    "l = []\n",
    "for elem in l_spread:\n",
    "    for think in elem:\n",
    "        l.append(think)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comment: mean of the spread distribution is: 0.032168863774575465\n"
     ]
    }
   ],
   "source": [
    "plt.hist(l,100)\n",
    "plt.title('Spread distribution - EDF - calendar time')\n",
    "plt.xlabel('Spread')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('Comment: mean of the spread distribution is:', np.mean(l))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Renault"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_spread = []\n",
    "for i in range(len(renault_quotes)):\n",
    "    quotes = renault_quotes[i]\n",
    "    quotes_best = quotes[quotes['level'] == 1]\n",
    "    quotes_best = quotes_best.reset_index()\n",
    "    del quotes_best['index']\n",
    "    ask = 0\n",
    "    bid = 0 \n",
    "    spread = np.zeros(len(quotes_best))\n",
    "    for j in range(len(quotes_best)):\n",
    "        if quotes_best['type'][j] == 'A':\n",
    "            ask = quotes_best['price'][j]\n",
    "        else:\n",
    "            bid = quotes_best['price'][j]\n",
    "        if (ask!=0) & (bid!=0):\n",
    "            spread[j] = ask - bid\n",
    "    spread = spread[spread!=0]\n",
    "    l_spread.append(spread)\n",
    "\n",
    "l = []\n",
    "for elem in l_spread:\n",
    "    for think in elem:\n",
    "        l.append(think)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comment: mean of the spread distribution is: 0.04096194986501571\n"
     ]
    }
   ],
   "source": [
    "plt.hist(l,40)\n",
    "plt.title('Spread distribution - Renault')\n",
    "plt.xlabel('Spread')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('Comment: mean of the spread distribution is:', np.mean(l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_spread = []\n",
    "for i in range(len(renault_quotes)):\n",
    "    quotes = renault_quotes[i]\n",
    "    quotes_best = quotes[quotes['level'] == 1]\n",
    "    quotes_best = quotes_best.reset_index()\n",
    "    del quotes_best['index']\n",
    "    ask = 0\n",
    "    bid = 0 \n",
    "    spread = np.zeros(len(quotes_best))\n",
    "    for j in range(len(quotes_best)):\n",
    "        if quotes_best['type'][j] == 'A':\n",
    "            ask = quotes_best['price'][j]\n",
    "            ask_time=quotes_best['ts_delta'][j]\n",
    "        else:\n",
    "            bid = quotes_best['price'][j]\n",
    "            bid_time=quotes_best['ts_delta'][j]\n",
    "        if (ask!=0) & (bid!=0):\n",
    "            spread[j] = np.absolute((ask - bid)*(ask_time-bid_time).total_seconds())\n",
    "    spread = spread[spread!=0]\n",
    "    l_spread.append(spread)\n",
    "\n",
    "l = []\n",
    "for elem in l_spread:\n",
    "    for think in elem:\n",
    "        l.append(think)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comment: mean of the spread distribution is: 0.041399577414395705\n"
     ]
    }
   ],
   "source": [
    "plt.hist(l,100)\n",
    "plt.title('Spread distribution - Renault - calendar time')\n",
    "plt.xlabel('Spread')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('Comment: mean of the spread distribution is:', np.mean(l))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_spread = []\n",
    "for i in range(len(total_quotes)):\n",
    "    quotes = total_quotes[i]\n",
    "    quotes_best = quotes[quotes['level'] == 1]\n",
    "    quotes_best = quotes_best.reset_index()\n",
    "    del quotes_best['index']\n",
    "    ask = 0\n",
    "    bid = 0 \n",
    "    spread = np.zeros(len(quotes_best))\n",
    "    for j in range(len(quotes_best)):\n",
    "        if quotes_best['type'][j] == 'A':\n",
    "            ask = quotes_best['price'][j]\n",
    "        else:\n",
    "            bid = quotes_best['price'][j]\n",
    "        if (ask!=0) & (bid!=0):\n",
    "            spread[j] = ask - bid\n",
    "    spread = spread[spread!=0]\n",
    "    l_spread.append(spread)\n",
    "\n",
    "l = []\n",
    "for elem in l_spread:\n",
    "    for think in elem:\n",
    "        l.append(think)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comment: mean of the spread distribution is: 0.01239783190116231\n"
     ]
    }
   ],
   "source": [
    "plt.hist(l,40)\n",
    "plt.title('Spread distribution - Total')\n",
    "plt.xlabel('Spread')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('Comment: mean of the spread distribution is:', np.mean(l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [],
   "source": [
    "l_spread = []\n",
    "for i in range(len(total_quotes)):\n",
    "    quotes = total_quotes[i]\n",
    "    quotes_best = quotes[quotes['level'] == 1]\n",
    "    quotes_best = quotes_best.reset_index()\n",
    "    del quotes_best['index']\n",
    "    ask = 0\n",
    "    bid = 0 \n",
    "    spread = np.zeros(len(quotes_best))\n",
    "    for j in range(len(quotes_best)):\n",
    "        if quotes_best['type'][j] == 'A':\n",
    "            ask = quotes_best['price'][j]\n",
    "            ask_time=quotes_best['ts_delta'][j]\n",
    "        else:\n",
    "            bid = quotes_best['price'][j]\n",
    "            bid_time=quotes_best['ts_delta'][j]\n",
    "        if (ask!=0) & (bid!=0):\n",
    "            spread[j] = np.absolute((ask - bid)*(ask_time-bid_time).total_seconds())\n",
    "    spread = spread[spread!=0]\n",
    "    l_spread.append(spread)\n",
    "\n",
    "l = []\n",
    "for elem in l_spread:\n",
    "    for think in elem:\n",
    "        l.append(think)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comment: mean of the spread distribution is: 0.005344470699712605\n"
     ]
    }
   ],
   "source": [
    "plt.hist(l,40)\n",
    "plt.title('Spread distribution - Total-calendar time')\n",
    "plt.xlabel('Spread')\n",
    "plt.ylabel('Occurences')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "print('Comment: mean of the spread distribution is:', np.mean(l))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4.2. Average Shape of the LOB"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## EDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEICAYAAABWJCMKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAHgtJREFUeJzt3Xu0HXV99/H3h4RrwFxIgJAEApqq0BaMEbB4oWJDAmrQgqIuCYhPaoV6WXbVYPtIitAGnypIfURRUoKCgCgSBYWUS6l9DBCuAgETQiTHhCRwkkDAC8Hv88f8dpjs7H323idn77Ph93mtNWvP/OY3M9+ZPTPfmd/M2UcRgZmZ5WeHwQ7AzMwGhxOAmVmmnADMzDLlBGBmliknADOzTDkBmJllygkgY5JOkfTzwY6jEUnvlbRS0iZJb2ii/lGSejoRm9UmaaKkkDS0DfOeI+m7Az3fqmVsknRgO5fRDZwAapB0m6T1knYe7FgMgH8DzoiI3SPi3uqR6UTzmnYsuFGSlPQuSXdKek7S05IulzS+avoX0wllk6Tlkv52O2OKtLxNpe4f0rg5kl6Q9GzqfiXpa5LGlqY/StIfq6b/8fbE9HKWjvePlcvSvrZ8sGLqFCeAKpImAm8FAnhPm5Yx4FdFr3D7Aw8NdhDVJJ0AXAF8FRgNHAz8Hvi5pJGlqr9IJ5TdgROALzVzJ9PAIZV5pu5LpXFXRcQewCjgvcA+wN3lJACsqpr+3dsZz8uCpCGDHUM3cQLY1snAIuBSYGalUNIRkp4s70CpaeKB1L+DpNmSHktXgldLGpXGVW6HT5P0BHBLKv9+mudGSbdLOrg07z0l/VjSM5LuknRO+UpU0uskLZTUK+lRSe+vt0LpKnR5uiJ8XNKHq8b/W7rjeVzS9FL5qZKWpOmWS/qb0rijJPVI+rykpyStKM9X0s5pvk9IWiPpG5J2rRPfDpL+SdKvJa2VdJmk4Wkem4AhwP2SHqsx7e2p9/50JfuB0rjPpvmtlnRqf2LrY5sK+DJwTkRcHhG/jYgngY8Bm4DP1JouIu4BlgCvb2V5/RERL0TEQ8AHgHXAZ/szH0lvkfT/JG1Q0RR3Sio/TtK9aR9dKWlOH/MYLumS9F38Ju3PQ9K4UyT9vI/98ABJ/5X2w4UUybY8776Oo0slXSTpBknPAX9ZNe25FBd8X0v7z9dS+Za7yjSPr0v6aarzP5L2kXRBivcRlRK6pH0l/UDSurQun+zPdu+IiHBX6oBlwCeANwIvAHuXxj0G/FVp+PvA7NT/aYrEMR7YGfgm8L00biLFHcVlwDBg11T+UWCPVP8C4L7SvK9M3W7AQcBK4Odp3LA0fCowFJgMPAUcXGN9hgHPAK9Nw2Mr9YBT0jr+L4qT7N8CqwCl8ccBrwYEvB14Hpicxh0FbAa+kuJ/O/BcaTkXAAsorkL3AH4M/Gudbf7RtN0PBHYHfgh8pzQ+gNf08Z1tNb4U29nAjsCxKfaR/YjtlMp2ryp/XVruATXG/TPFVf820wNvAjYAf7Id+2jd7QHMAb5bo/xs4I7S9ulpcln7Ac8CH0zbck/g0NJ8/oziQvLPgTXA8VX7/NA0/COKY2IYsBdwJ/A3Te6HvyjtZ29L8Xy3FGNfx9GlwEbgyBTnLjXW8TbgY/W2cZrHUxTnhF0oLuAep7hYHAKcA9ya6u4A3A18AdiJYp9eDhzTifNXy/vSYAfQTR3wlrQjjk7DjwCfKY0/B5iX+vegOOHtn4aXAEeX6o5N8xpaOhgO7GPZI1Kd4WmneoF0Mi0tu5IAPgD8d9X03wTOqjHfYRQnnL8mJZ7SuFOAZaXh3VIM+9SJ8UfAp1L/URQn2WGl8VcD/5siYTwHvLo07s3A43XmezPwidLwayvbLg33JwH8tjJ9KlsLHNGP2E6hdgJ4S1purRPKx4Glpek3p+9gU5rm30knt37up0GR1DeUumPSuDnUTgDlmI4C/lg1/fvrLOtM4Nom47oAOD/1V/b5ocDeFE1ju5bqfpCXTpp190OKBFS9n11Rax2rj6M0fClwWYO4b6NxAvhWadzfAUtKw38GbEj9hwNP1NiG/9Hf77udnZuAtjYTuCkinkrDV1BqBkrD71PxcPh9wD0R8es0bn/g2nSbvIEiIbxIsfNXrKz0SBoiaa6KJqNngBVp1GhgDMWBs7LWtGlZh1eWlZb3YYoDZisR8RxFwvg4sFrS9ZJeV6ryZKnu86l39xTjdEmLUjPTBoor6fLt9/o0/4pfA/um+HejaHeuxPezVF7Lvmna8nwqJ47+ejoiNpeGn0/r1Wps9VT2kbE1xo0tjQdYFBEjongGsA/Fs4J/qTXTUjPDpuqmuiqT0zwr3Y0N4h0H9JaGV1VNf3VafvnB8H7ABIo731qxHi7p1tTUsZFiHxtdo+r+FHcPq0vb/JsUdwIV9fbDfam9n1Vi6Os4qigfO/21ptT/2xrDu6f+/YF9q47Nz7N9+3Lb+GFkktqA3w8MkVTZGXcGRkg6JCLuj4iHJf0amA58iCIhVKwEPhoR/1Nj3hNTb/mnVz8EzADeSbHTDgfWU1yhrqO46hkP/CrVn1C1rP+KiL9qZt3SyeHGtI7nAN+iaPesKyW5H1Dc5l4XES9I+lGKr2KkpGGlg3M/4EGKk99vKZqaftNEiKsoDpyKylXfmtrVt0ursdXzKNADnAhseQAraQeKu60f1ZooItZI+gFFM8eZNcZP33aq7ZNiejfwn43qpiRVnnYlcFid6lcAXwOmR8TvJF1A7QSwkuIOYHRVUm7GamrvZ5Vjqa/jaMtqNVjGQP4k8kqKu8lJAzjPtvEdwEuOp7hiPwg4NHWvB/6b4iRYcQXwSYq2yO+Xyr8BnCtpfwBJYyTN6GN5e1AcFE9TXJFuuSKMiBcp2sHnSNotXbGXY/gJ8CeSPiJpx9S9SdI2DxYl7S3pPZKGpeVtSuvZyE4UCXAdsDk9lJtao94/S9pJ0luBdwHfj4g/UiSZ8yXtleIYJ+mYOsv6HvCZ9LBv97QtrmrhZLGGoq21oX7Elqpol3IXxb393wP/JOlDknaVtA/wbeBVwPl1ZrQnxZs5bX+rKe0Xr6fYvvtQtKO36nLgnZLeL2moipcTDk3j9gB608n/MIqT8TYiYjVwE/BlSa9S8dD/1ZLe3mjh6Q57MS/tZ2+hSGYVdY+jFjS9/zThTuAZSZ9L+8QQSX8q6U0DNP8B5QTwkpkU7XRPRMSTlY7iCufDeunVze9RtKHeUmoqguJVwAXATZKepXggfHgfy7uM4lb2N8DDqX7ZGRRXM08C30nL/T1ARDxLcTI+ieLq+UngPIoTdrUdKN7+WEXRBPB2iofcfUrL+CRFu/56ioN7QVW1J9O4VRQnio9HxCNp3OcoHuwuSrfm/0nRtl/LvLSOt1M8XPsdRTtrs+YA89Mtd923oUpaiQ3gLyjuGrZ0koZGxFXARyje+HmK4nvcFTgyIp4uTf/mSrMKRdPguhbXr5bKW0+V7oLSuA+kZW2g+M6eBt4YEataXUhEPEHR9PdZiv3nPuCQNPoTwNlpf/8Cxb5Sz8kUFxUPU+wz11C7+ayWD1EcS73AWRTHTkWj46gZXwVOUPFGz4X9mH6LdPH2booLyMcp9otvUxzLXafylN26nKTzKB7OzmxYuQMkHUXxIG58o7pm1p18B9ClVLzn/+cqHAacBlw72HGZ2SuHHwJ3rz0omn32pXiF8cvAdYMakZm9orgJyMwsU24CMjPLVFc3AY0ePTomTpw42GGYmb2s3H333U9FRMM/buzqBDBx4kQWL1482GGYmb2spD9YbchNQGZmmXICMDPLlBOAmVmmnADMzDLlBGBmliknADOzTDkBmJllygnAzCxTTgBmZpnq6r8ENrMuNafF/28yZ2N74rDt4jsAM7NMOQGYmWXKTUBm1lnb03zU6rTV09tWfAdgZpYpJwAzs0w5AZiZZcoJwMwsU04AZmaZcgIwM8uUE4CZWaacAMzMMuUEYGaWKScAM7NMOQGYmWWqqQQgaYSkayQ9ImmJpDdLGiVpoaSl6XNkqitJF0paJukBSZNL85mZ6i+VNLNdK2VmZo01+2NwXwV+FhEnSNoJ2A34PHBzRMyVNBuYDXwOmA5MSt3hwEXA4ZJGAWcBU4AA7pa0ICLWD+gaWb9NnH19y9OsmHtcGyIxs05oeAcg6VXA24BLACLiDxGxAZgBzE/V5gPHp/4ZwGVRWASMkDQWOAZYGBG96aS/EJg2oGtjZmZNa6YJ6EBgHfAfku6V9G1Jw4C9I2I1QPrcK9UfB6wsTd+TyuqVb0XSLEmLJS1et25dyytkZmbNaSYBDAUmAxdFxBuA5yiae+pRjbLoo3zrgoiLI2JKREwZM2ZME+GZmVl/NJMAeoCeiLgjDV9DkRDWpKYd0ufaUv0JpenHA6v6KDczs0HQ8CFwRDwpaaWk10bEo8DRwMOpmwnMTZ/XpUkWAGdIupLiIfDGiFgt6UbgXypvCwFTgTMHdnXMzPrgf2a/lWbfAvo74PL0BtBy4FSKu4erJZ0GPAGcmOreABwLLAOeT3WJiF5JXwTuSvXOjojeAVkL26LVN3kG8i2ewVy2mbWuqQQQEfdRvL5Z7egadQM4vc585gHzWgnQzMzaw38JbGaWqWabgMzslaTVtnB4xbeH58h3AGZmmXICMDPLlBOAmVmmnADMzDLlBGBmliknADOzTDkBmJllygnAzCxTTgBmZplyAjAzy5QTgJlZppwAzMwy5QRgZpYpJwAzs0w5AZiZZcoJwMwsU04AZmaZcgIwM8uU/yWkdYWJs69vqf6Kuce1KRKzfDgBdCGfDM2sE9wEZGaWqaYSgKQVkn4p6T5Ji1PZKEkLJS1NnyNTuSRdKGmZpAckTS7NZ2aqv1TSzPaskpmZNaOVO4C/jIhDI2JKGp4N3BwRk4Cb0zDAdGBS6mYBF0GRMICzgMOBw4CzKknDzMw6b3uagGYA81P/fOD4UvllUVgEjJA0FjgGWBgRvRGxHlgITNuO5ZuZ2XZoNgEEcJOkuyXNSmV7R8RqgPS5VyofB6wsTduTyuqVb0XSLEmLJS1et25d82tiZmYtafYtoCMjYpWkvYCFkh7po65qlEUf5VsXRFwMXAwwZcqUbcabmdnAaOoOICJWpc+1wLUUbfhrUtMO6XNtqt4DTChNPh5Y1Ue5mZkNgoYJQNIwSXtU+oGpwIPAAqDyJs9M4LrUvwA4Ob0NdASwMTUR3QhMlTQyPfydmsrMzGwQNNMEtDdwraRK/Ssi4meS7gKulnQa8ARwYqp/A3AssAx4HjgVICJ6JX0RuCvVOzsiegdsTczMrCUNE0BELAcOqVH+NHB0jfIATq8zr3nAvNbDNDOzgea/BDYzy5QTgJlZppwAzMwy5QRgZpYpJwAzs0w5AZiZZcoJwMwsU/6PYGYvV3OGt1h/Y3visJct3wGYmWXKCcDMLFNOAGZmmXICMDPLlBOAmVmmnADMzDLl10DNzJrR6mu30PWv3voOwMwsU04AZmaZcgIwM8uUnwG0wcTZ17c8zYq5x7UhEjOz+nwHYGaWKScAM7NMOQGYmWWq6QQgaYikeyX9JA0fIOkOSUslXSVpp1S+cxpelsZPLM3jzFT+qKRjBnplzMysea3cAXwKWFIaPg84PyImAeuB01L5acD6iHgNcH6qh6SDgJOAg4FpwNclDdm+8M3MrL+aSgCSxgPHAd9OwwLeAVyTqswHjk/9M9IwafzRqf4M4MqI+H1EPA4sAw4biJUwM7PWNXsHcAHwD8Af0/CewIaI2JyGe4BxqX8csBIgjd+Y6m8przHNFpJmSVosafG6detaWBUzM2tFwwQg6V3A2oi4u1xco2o0GNfXNC8VRFwcEVMiYsqYMWMahWdmZv3UzB+CHQm8R9KxwC7AqyjuCEZIGpqu8scDq1L9HmAC0CNpKDAc6C2VV5SnMTOzDmt4BxARZ0bE+IiYSPEQ95aI+DBwK3BCqjYTuC71L0jDpPG3RESk8pPSW0IHAJOAOwdsTczMrCXb81MQnwOulHQOcC9wSSq/BPiOpGUUV/4nAUTEQ5KuBh4GNgOnR8SL27F8MzPbDi0lgIi4Dbgt9S+nxls8EfE74MQ6058LnNtqkGZmNvD8l8BmZplyAjAzy5QTgJlZppwAzMwy5QRgZpYpJwAzs0w5AZiZZcoJwMwsU/6n8PaKMHH29S3VXzH3uDZFYvby4TsAM7NMOQGYmWXKCcDMLFNOAGZmmXICMDPLlBOAmVmmnADMzDLlBGBmliknADOzTDkBmJllygnAzCxTTgBmZplyAjAzy1TDXwOVtAtwO7Bzqn9NRJwl6QDgSmAUcA/wkYj4g6SdgcuANwJPAx+IiBVpXmcCpwEvAp+MiBsHfpXMzLrQnOEt1t/YnjhKmrkD+D3wjog4BDgUmCbpCOA84PyImASspzixkz7XR8RrgPNTPSQdBJwEHAxMA74uachAroyZmTWv4R1ARASwKQ3umLoA3gF8KJXPB+YAFwEzUj/ANcDXJCmVXxkRvwcel7QMOAz4xUCsiNnLUhdeFVo+mnoGIGmIpPuAtcBC4DFgQ0RsTlV6gHGpfxywEiCN3wjsWS6vMY2ZmXVYUwkgIl6MiEOB8RRX7a+vVS19qs64euVbkTRL0mJJi9etW9dMeGZm1g8tvQUUERuA24AjgBGSKk1I44FVqb8HmACQxg8HesvlNaYpL+PiiJgSEVPGjBnTSnhmZtaChglA0hhJI1L/rsA7gSXArcAJqdpM4LrUvyANk8bfkp4jLABOkrRzeoNoEnDnQK2ImZm1ppl/Cj8WmJ/e2NkBuDoifiLpYeBKSecA9wKXpPqXAN9JD3l7Kd78ISIeknQ18DCwGTg9Il4c2NUxM7NmNfMW0APAG2qUL6d4HlBd/jvgxDrzOhc4t/UwzcxsoPkvgc3MMuUEYGaWKScAM7NMOQGYmWWqmbeAzF7RJs6+vqX6K+Ye16ZIzDrLCaAOnxTM7JXOTUBmZplyAjAzy5QTgJlZppwAzMwy5QRgZpYpJwAzs0w5AZiZZcoJwMwsU04AZmaZcgIwM8uUE4CZWaacAMzMMuUEYGaWKScAM7NMOQGYmWXKCcDMLFNOAGZmmWqYACRNkHSrpCWSHpL0qVQ+StJCSUvT58hULkkXSlom6QFJk0vzmpnqL5U0s32rZWZmjTRzB7AZ+GxEvB44Ajhd0kHAbODmiJgE3JyGAaYDk1I3C7gIioQBnAUcDhwGnFVJGmZm1nkNE0BErI6Ie1L/s8ASYBwwA5ifqs0Hjk/9M4DLorAIGCFpLHAMsDAieiNiPbAQmDaga2NmZk1r6Z/CS5oIvAG4A9g7IlZDkSQk7ZWqjQNWlibrSWX1yquXMYvizoH99tuvlfDMOm/O8H5Ms3Hg4zDrh6YfAkvaHfgB8OmIeKavqjXKoo/yrQsiLo6IKRExZcyYMc2GZ2ZmLWoqAUjakeLkf3lE/DAVr0lNO6TPtam8B5hQmnw8sKqPcjMzGwTNvAUk4BJgSUR8pTRqAVB5k2cmcF2p/OT0NtARwMbUVHQjMFXSyPTwd2oqMzOzQdDMM4AjgY8Av5R0Xyr7PDAXuFrSacATwIlp3A3AscAy4HngVICI6JX0ReCuVO/siOgdkLUwM7OWNUwAEfFzarffAxxdo34Ap9eZ1zxgXisBmplZe/gvgc3MMuUEYGaWKScAM7NMOQGYmWXKCcDMLFNOAGZmmXICMDPLlBOAmVmmnADMzDLlBGBmliknADOzTDkBmJllqqX/CPZyM3H29S3VXzH3uDZFYmbWfXwHYGaWKScAM7NMOQGYmWXKCcDMLFNOAGZmmXICMDPLlBOAmVmmnADMzDLlBGBmlqmGCUDSPElrJT1YKhslaaGkpelzZCqXpAslLZP0gKTJpWlmpvpLJc1sz+qYmVmzmrkDuBSYVlU2G7g5IiYBN6dhgOnApNTNAi6CImEAZwGHA4cBZ1WShpmZDY6GCSAibgd6q4pnAPNT/3zg+FL5ZVFYBIyQNBY4BlgYEb0RsR5YyLZJxczMOqi/zwD2jojVAOlzr1Q+DlhZqteTyuqVb0PSLEmLJS1et25dP8MzM7NGBvohsGqURR/l2xZGXBwRUyJiypgxYwY0ODMze0l/E8Ca1LRD+lybynuACaV644FVfZSbmdkg6W8CWABU3uSZCVxXKj85vQ10BLAxNRHdCEyVNDI9/J2ayszMbJA0/Icwkr4HHAWMltRD8TbPXOBqSacBTwAnpuo3AMcCy4DngVMBIqJX0heBu1K9syOi+sGymZl1UMMEEBEfrDPq6Bp1Azi9znzmAfNais7MzNrGfwlsZpYpJwAzs0w5AZiZZcoJwMwsU04AZmaZcgIwM8uUE4CZWaacAMzMMuUEYGaWKScAM7NMOQGYmWXKCcDMLFNOAGZmmXICMDPLlBOAmVmmnADMzDLlBGBmliknADOzTDkBmJllygnAzCxTTgBmZplyAjAzy5QTgJlZpjqeACRNk/SopGWSZnd6+WZmVuhoApA0BPi/wHTgIOCDkg7qZAxmZlbo9B3AYcCyiFgeEX8ArgRmdDgGMzMDFBGdW5h0AjAtIj6Whj8CHB4RZ5TqzAJmpcHXAo/WmNVo4Kk2h9tf3Rpbt8YF3Rub42pdt8bWrXFBe2LbPyLGNKo0dIAX2ohqlG2VgSLiYuDiPmciLY6IKQMZ2EDp1ti6NS7o3tgcV+u6NbZujQsGN7ZONwH1ABNKw+OBVR2OwczM6HwCuAuYJOkASTsBJwELOhyDmZnR4SagiNgs6QzgRmAIMC8iHurHrPpsIhpk3Rpbt8YF3Rub42pdt8bWrXHBIMbW0YfAZmbWPfyXwGZmmXICMDPLVFcngEY/GyFpZ0lXpfF3SJrYgZgmSLpV0hJJD0n6VI06R0naKOm+1H2h3XGVlr1C0i/TchfXGC9JF6Zt9oCkyR2I6bWlbXGfpGckfbqqTse2maR5ktZKerBUNkrSQklL0+fIOtPOTHWWSprZgbj+j6RH0nd1raQRdabt83tvU2xzJP2m9J0dW2fatv38S524rirFtELSfXWmbds2q3ee6Ib9bCsR0ZUdxUPix4ADgZ2A+4GDqup8AvhG6j8JuKoDcY0FJqf+PYBf1YjrKOAng7TdVgCj+xh/LPBTir/JOAK4YxC+1ycp/lBlULYZ8DZgMvBgqexLwOzUPxs4r8Z0o4Dl6XNk6h/Z5rimAkNT/3m14mrme29TbHOAv2/i++7zOB7ouKrGfxn4Qqe3Wb3zRDfsZ+Wum+8AmvnZiBnA/NR/DXC0pFp/bDZgImJ1RNyT+p8FlgDj2rnMATYDuCwKi4ARksZ2cPlHA49FxK87uMytRMTtQG9VcXlfmg8cX2PSY4CFEdEbEeuBhcC0dsYVETdFxOY0uIjib2c6rs42a0Zbf/6lr7jSueD9wPcGannN6uM8Mej7WVk3J4BxwMrScA/bnmi31EkHyUZgz45EB6QmpzcAd9QY/WZJ90v6qaSDOxUTxV9W3yTp7vSzGtWa2a7tdBL1D8jB2mYAe0fEaigOXmCvGnUGe9t9lOLurZZG33u7nJGap+bVac4YzG32VmBNRCytM74j26zqPNFV+1k3J4CGPxvRZJ22kLQ78APg0xHxTNXoeyiaOA4B/h34USdiSo6MiMkUv7h6uqS3VY0fzG22E/Ae4Ps1Rg/mNmvWYG67fwQ2A5fXqdLoe2+Hi4BXA4cCqymaW6oN2jYDPkjfV/9t32YNzhN1J6tR1pZt1s0JoJmfjdhSR9JQYDj9u01tiaQdKb7UyyPih9XjI+KZiNiU+m8AdpQ0ut1xpeWtSp9rgWspbsHLBvPnOKYD90TEmuoRg7nNkjWVprD0ubZGnUHZdukh4LuAD0dqJK7WxPc+4CJiTUS8GBF/BL5VZ5mDtc2GAu8DrqpXp93brM55oqv2s25OAM38bMQCoPKE/ATglnoHyEBJ7YqXAEsi4it16uxTeRYh6TCK7fx0O+NKyxomaY9KP8UDxAerqi0ATlbhCGBj5Za0A+pekQ3WNisp70szgetq1LkRmCppZGrumJrK2kbSNOBzwHsi4vk6dZr53tsRW/nZ0XvrLHOwfv7lncAjEdFTa2S7t1kf54nu2s/a8WR5oDqKN1Z+RfEWwT+msrMpDgaAXSiaE5YBdwIHdiCmt1Dcjj0A3Je6Y4GPAx9Pdc4AHqJ442ER8Bcd2l4HpmXen5Zf2Wbl2ETxT3keA34JTOlQbLtRnNCHl8oGZZtRJKHVwAsUV1unUTw7uhlYmj5HpbpTgG+Xpv1o2t+WAad2IK5lFO3BlX2t8tbbvsANfX3vHYjtO2kfeoDixDa2OrY0vM1x3M64UvmllX2rVLdj26yP88Sg72flzj8FYWaWqW5uAjIzszZyAjAzy5QTgJlZppwAzMwy5QRgZpYpJwAzs0w5AZiZZer/AySVR4Wu8n/zAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "quotes = edf_quotes[0].reset_index()\n",
    "del quotes['index']\n",
    "\n",
    "bid_price = np.zeros(10)\n",
    "bid_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'B']\n",
    "    bid_price[i-1] = np.mean(level['price'])\n",
    "    bid_volume[i-1] = np.mean(level['qty'])\n",
    "\n",
    "ask_price = np.zeros(10)\n",
    "ask_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'A']\n",
    "    ask_price[i-1] = np.mean(level['price'])\n",
    "    ask_volume[i-1] = np.mean(level['qty'])\n",
    "\n",
    "plt.bar(range(1,11),bid_volume)\n",
    "\n",
    "plt.bar(range(11,21),ask_volume)\n",
    "\n",
    "plt.title('Average shape of the LOB - EDF-event time')\n",
    "\n",
    "plt.show()\n",
    "\n",
    "bid_price = np.zeros(10)\n",
    "bid_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'B']\n",
    "    level = level.reset_index()\n",
    "    total_time=(level['ts_delta'][len(level['ts_delta'])-1]-level['ts_delta'][0])/np.timedelta64(1, 's')\n",
    "    bid_price[i-1] = sum(level['price'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "    bid_volume[i-1] = sum(level['qty'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "ask_price = np.zeros(10)\n",
    "ask_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'A']\n",
    "    level = level.reset_index()\n",
    "    total_time = (level['ts_delta'][len(level['ts_delta'])-1]-level['ts_delta'][0]).total_seconds()\n",
    "    ask_price[i-1] = sum(level['price'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "    ask_volume[i-1] = sum(level['qty'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "\n",
    "plt.bar(range(1,11),bid_volume)\n",
    "\n",
    "plt.bar(range(11,21),ask_volume)\n",
    "\n",
    "plt.title('Average shape of the LOB - EDF-calendar time')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Shapes are quite similar."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Renault"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "quotes = renault_quotes[0].reset_index()\n",
    "del quotes['index']\n",
    "\n",
    "bid_price = np.zeros(10)\n",
    "bid_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level']==i]\n",
    "    level = level[level['type']=='B']\n",
    "    bid_price[i-1] = np.mean(level['price'])\n",
    "    bid_volume[i-1] = np.mean(level['qty'])\n",
    "\n",
    "ask_price = np.zeros(10)\n",
    "ask_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level']==i]\n",
    "    level = level[level['type']=='A']\n",
    "    ask_price[i-1] = np.mean(level['price'])\n",
    "    ask_volume[i-1] = np.mean(level['qty'])\n",
    "\n",
    "plt.bar(range(1,11),bid_volume)\n",
    "\n",
    "plt.bar(range(11,21),ask_volume)\n",
    "\n",
    "plt.title('Average shape of the LOB - Renault-event time')\n",
    "\n",
    "plt.show()\n",
    "\n",
    "bid_price = np.zeros(10)\n",
    "bid_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'B']\n",
    "    level = level.reset_index()\n",
    "    total_time = (level['ts_delta'][len(level['ts_delta'])-1]-level['ts_delta'][0])/np.timedelta64(1, 's')\n",
    "    bid_price[i-1] = sum(level['price'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "    bid_volume[i-1] = sum(level['qty'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "ask_price = np.zeros(10)\n",
    "ask_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'A']\n",
    "    level = level.reset_index()\n",
    "    total_time = (level['ts_delta'][len(level['ts_delta'])-1]-level['ts_delta'][0]).total_seconds()\n",
    "    ask_price[i-1] = sum(level['price'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "    ask_volume[i-1] = sum(level['qty'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "\n",
    "plt.bar(range(1,11),bid_volume)\n",
    "\n",
    "plt.bar(range(11,21),ask_volume)\n",
    "\n",
    "plt.title('Average shape of the LOB - Renault-calendar time')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Shapes are quite similar."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [],
   "source": [
    "quotes = total_quotes[0].reset_index()\n",
    "del quotes['index']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "bid_price = np.zeros(10)\n",
    "bid_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level']==i]\n",
    "    level = level[level['type']=='B']\n",
    "    bid_price[i-1] = np.mean(level['price'])\n",
    "    bid_volume[i-1] = np.mean(level['qty'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [],
   "source": [
    "ask_price = np.zeros(10)\n",
    "ask_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level']==i]\n",
    "    level = level[level['type']=='A']\n",
    "    ask_price[i-1] = np.mean(level['price'])\n",
    "    ask_volume[i-1] = np.mean(level['qty'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Average shape of the LOB - Total-event time')"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(range(1,11),bid_volume)\n",
    "\n",
    "plt.bar(range(11,21),ask_volume)\n",
    "\n",
    "plt.title('Average shape of the LOB - Total-event time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "bid_price = np.zeros(10)\n",
    "bid_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'B']\n",
    "    level = level.reset_index()\n",
    "    total_time = (level['ts_delta'][len(level['ts_delta'])-1]-level['ts_delta'][0])/np.timedelta64(1, 's')\n",
    "    bid_price[i-1] = sum(level['price'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "    bid_volume[i-1] = sum(level['qty'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "ask_price = np.zeros(10)\n",
    "ask_volume = np.zeros(10)\n",
    "for i in range(1,11):\n",
    "    level = quotes[quotes['level'] == i]\n",
    "    level = level[level['type'] == 'A']\n",
    "    level = level.reset_index()\n",
    "    total_time = (level['ts_delta'][len(level['ts_delta'])-1]-level['ts_delta'][0]).total_seconds()\n",
    "    ask_price[i-1] = sum(level['price'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time\n",
    "    ask_volume[i-1] = sum(level['qty'][:-1]*(np.diff(level['ts_delta'])/np.timedelta64(1, 's')))/total_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Average shape of the LOB - Total-calendar time')"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(range(1,11),bid_volume)\n",
    "\n",
    "plt.bar(range(11,21),ask_volume)\n",
    "\n",
    "plt.title('Average shape of the LOB - Total-calendar time')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Shapes are quite similar."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5 Autocorrelation of trade signs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Signing the trades with a tick test."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = renault_trades[0]\n",
    "trades_sign = np.zeros(len(test))\n",
    "ask = 0\n",
    "bid = test['last'][0]\n",
    "trades_sign[0] = 1\n",
    "for i in range(1,len(test)):\n",
    "    if trades_sign[i-1] == 1:\n",
    "        if test['last'][i] > bid:\n",
    "            ask = test['last'][i]\n",
    "            trades_sign[i] = 1\n",
    "        else:\n",
    "            bid = test['last'][i]\n",
    "            trades_sign[i] =- 1\n",
    "    else:\n",
    "        if test['last'][i] < ask:\n",
    "            bid = test['last'][i]\n",
    "            trades_sign[i] =- 1\n",
    "        else:\n",
    "            ask = test['last'][i]\n",
    "            trades_sign[i] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.graphics.tsaplots as tsa\n",
    "tsa.plot_acf(trades_sign, lags = 40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Autocorrelation is important for lags = 40."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}