5 - Real Example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's get started by importing Bitcoin and Ether data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\n",
    "    'data/btc-eth-prices-outliers.csv',\n",
    "    index_col=0,\n",
    "    parse_dates=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>Bitcoin</th>\n",
       "      <th>Ether</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-04-02</th>\n",
       "      <td>1099.169125</td>\n",
       "      <td>48.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-03</th>\n",
       "      <td>1141.813000</td>\n",
       "      <td>44.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-04</th>\n",
       "      <td>1141.600363</td>\n",
       "      <td>44.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-05</th>\n",
       "      <td>1133.079314</td>\n",
       "      <td>44.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-06</th>\n",
       "      <td>1196.307937</td>\n",
       "      <td>43.23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Bitcoin  Ether\n",
       "Timestamp                     \n",
       "2017-04-02  1099.169125  48.55\n",
       "2017-04-03  1141.813000  44.13\n",
       "2017-04-04  1141.600363  44.43\n",
       "2017-04-05  1133.079314  44.90\n",
       "2017-04-06  1196.307937  43.23"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And now we can run a simple visualization:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x112958cc0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(figsize=(16, 9))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are clearly some invalid values, both ETH and BTC have huge spikes. On top of that, there seems to be some data missing in Ether between December 2017 and and January 2018:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x112e01b00>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc['2017-12': '2017-12-15'].plot(y='Ether', figsize=(16, 9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x113077f60>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc['2017-12': '2017-12-15'].plot(y='Ether', figsize=(16, 9))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_na = df.loc['2017-12': '2017-12-15']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Are those null values?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_na['Ether'].isna().values.any()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When? what periods of time?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Bitcoin</th>\n",
       "      <th>Ether</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-12-08</th>\n",
       "      <td>16007.436667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-09</th>\n",
       "      <td>15142.834152</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-10</th>\n",
       "      <td>14869.805000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Bitcoin  Ether\n",
       "Timestamp                      \n",
       "2017-12-08  16007.436667    NaN\n",
       "2017-12-09  15142.834152    NaN\n",
       "2017-12-10  14869.805000    NaN"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_na.loc[df_na['Ether'].isna()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's add a little bit more context:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\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>Bitcoin</th>\n",
       "      <th>Ether</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-12-06</th>\n",
       "      <td>13540.980000</td>\n",
       "      <td>422.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-07</th>\n",
       "      <td>16501.971667</td>\n",
       "      <td>421.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-08</th>\n",
       "      <td>16007.436667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-09</th>\n",
       "      <td>15142.834152</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-10</th>\n",
       "      <td>14869.805000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-11</th>\n",
       "      <td>16762.116667</td>\n",
       "      <td>513.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-12</th>\n",
       "      <td>17276.393333</td>\n",
       "      <td>656.52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Bitcoin   Ether\n",
       "Timestamp                       \n",
       "2017-12-06  13540.980000  422.48\n",
       "2017-12-07  16501.971667  421.15\n",
       "2017-12-08  16007.436667     NaN\n",
       "2017-12-09  15142.834152     NaN\n",
       "2017-12-10  14869.805000     NaN\n",
       "2017-12-11  16762.116667  513.29\n",
       "2017-12-12  17276.393333  656.52"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['2017-12-06': '2017-12-12']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now need to decide what we'll do with the missing values. Drop them? fill them? If we decide to fill them, what will be use as fill value? For example: we can use the previous value and just assume the price stayed the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Bitcoin</th>\n",
       "      <th>Ether</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timestamp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-12-06</th>\n",
       "      <td>13540.980000</td>\n",
       "      <td>422.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-07</th>\n",
       "      <td>16501.971667</td>\n",
       "      <td>421.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-08</th>\n",
       "      <td>16007.436667</td>\n",
       "      <td>513.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-09</th>\n",
       "      <td>15142.834152</td>\n",
       "      <td>513.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-10</th>\n",
       "      <td>14869.805000</td>\n",
       "      <td>513.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-11</th>\n",
       "      <td>16762.116667</td>\n",
       "      <td>513.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-12</th>\n",
       "      <td>17276.393333</td>\n",
       "      <td>656.52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Bitcoin   Ether\n",
       "Timestamp                       \n",
       "2017-12-06  13540.980000  422.48\n",
       "2017-12-07  16501.971667  421.15\n",
       "2017-12-08  16007.436667  513.29\n",
       "2017-12-09  15142.834152  513.29\n",
       "2017-12-10  14869.805000  513.29\n",
       "2017-12-11  16762.116667  513.29\n",
       "2017-12-12  17276.393333  656.52"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['2017-12-06': '2017-12-12'].fillna(method='bfill')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.fillna(method='bfill', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look now:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x113066ac8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(figsize=(16, 9))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Much better. We now need to fix the huge spikes. The first step is identifying them. How can we do it? The simple answer is of course visually. They seem to be located in the last 10 days of Dec 2017 and first of March 2018:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x113615ef0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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L+b44Lx8+NaXbNSaTWdIwOW/bFNczkhrd9atsiMrkE0saJudFojFKC4NctbBqSrdbV1HMsrpyK4abvGJJw+S8LS3trFlaQ+EU1jOSmsIhtkVjxBN2WTSTHyxpmJzWea6X146fnvCl0MfTFK7ldE8/e492Tcv2jck0ljRMTtsajaHKhG+6NJ5kXcOGqEy+sKRhclokGqO4IMCqxVNbz0haUF3K4lApkeiIt3oxJudY0jA5LRJt55ol1RQXBKdtH431te6IxuoaJvdZ0jA5q6u7jz1Humic4vMzhmsKh+g418frJ85M636MyQSWNEzO2r6/g4TC2mkqgiclz/+w8zVMPrCkYXLWlmg7hUHhmiU107qfJaEy5lYWWzHc5AVLGiZnRVpirFpUTWnR9NUzAESEpnAtkZZ2q2uYnGdJw+Sksz397D58asovHTKaxnCIE6d7ONB+bkb2Z4xfxk0aIvKoiJwQkZdT2kIisllEXnfPNa5dRORBEdknIi+JyLUp79no+r8uIhtT2teIyG73ngdFRMbahzHp2H6gg3hCp/wihaNpGrgOlU29NbktnSON7wLrh7XdAzyvqsuB591rgJuA5e5xB/At8BIAcB/QBDQC96UkgW8BH0953/px9mHMuLZGYwQDwpqlM/Nd49I5swiVF1kx3OS8cZOGqv4KGP4/YQPwmFt+DLglpf176tkCVIvIfOBGYLOqxlS1A9gMrHfrKlV1i3qDwd8btq2R9mHMuCLRdlYurKK8uGBG9iciNNaHrBhuct5EaxpzVfWoWz4GzHXLC4FDKf1aXdtY7a0jtI+1D2PG1N0X58VDp6Z9qu1wTctCtHac53Dn+RndrzEzadKFcHeEMK1TRsbbh4jcISLNItLc1tY2naGYLLDjYAe98cSMFcGTBq9DZXUNk7smmjSOu6El3PMJ134YWJzSb5FrG6t90QjtY+3jAqr6kKo2qGpDXV3dBH8kkysiLTECAg31M5s0Lp9XSUVJgQ1RmZw20aTxLJCcAbUReCal/TY3i2otcMoNMT0HrBORGlcAXwc859Z1ichaN2vqtmHbGmkfxowpEm1nxYJKKksKZ3S/wYBX14i0WNIwuSudKbePA78DLhORVhG5HXgAeLeIvA68y70G2AS0APuAh4FPAKhqDPgSsM09vujacH2+497zBvAT1z7aPowZVU9/nJ0HO2dsqu1wjeEQLSfPcuJ0ty/7N2a6jTu1RFU/NMqqG0boq8Cdo2znUeDREdqbgZUjtLePtA9jxvJS6yl6+hMD9YWZlrxvx9ZojPdcvcCXGIyZTnZGuMkpkRavCN04w/WMpCsXVFJWFLS6hslZljRMTolEY1w+r4Ka8iJf9l8YDLBmaY0lDZOzLGmYnNEXT7D9QMe03Q88XU3hEK8eO03H2V5f4zBmOljSMDlj9+FTnOuNT9v9wNOVvOnTtv12tGFyjyUNkzOSU139KoInrVpcRVFBwK5DZXKSJQ2TMyLRdi6dM4vZs4p9jaO4IMg1i6utrmFykiUNkxPiCaV5f4fvRxlJTeEQrxw5xenuPr9DMWZKWdIwOWHPkS7O9PT7XgRPalpWS0Kh+UCH36EYM6UsaZickLz50Vqfi+BJ1yyppiAgNkRlco4lDZMTtrTEqK8tY25lid+hAFBWVMDVi6oGTjY0JldY0jBZL5FQtu2P+Xa9qdE0hmt5qfUU53vjfodizJSxpGGy3qvHTnPqfN+M3z9jPE3hEP0JZedBq2uY3GFJw2S9ZD3D75P6hltTX0NAYIvVNUwOsaRhst7WaIyF1aUsrC71O5QhKksKWbGg0u7kZ3KKJQ2T1VSVrdFYxg1NJTWFa9l5sJOefqtrmNxgScNktX0nztB+tpe1GVYET2oMh+jpT/BS6ym/QzFmSljSMFktWS/I1CON69x9Pex8DZMrLGmYrBZpaWdeZQlLQmV+hzKiUHkRl82tYIudr2FyhCUNk7VUlYirZ4iI3+GMqjEcYvuBDvrjCb9DMWbSJpU0ROQuEXlFRF4WkcdFpEREwiISEZF9IvKEiBS5vsXu9T63vj5lO/e69tdE5MaU9vWubZ+I3DOZWE3uiZ48S9vpnoy5SOFoGsMhzvXGeeVIl9+hGDNpE04aIrIQ+BTQoKorgSBwK/CPwFdV9VKgA7jdveV2oMO1f9X1Q0RWuPddCawH/kVEgiISBL4J3ASsAD7k+hoDDNYJMu1M8OGSF1GM2NRbkwMmOzxVAJSKSAFQBhwF3gk85dY/Btzilje417j1N4g3prAB+IGq9qhqFNgHNLrHPlVtUdVe4AeurzGAdz/w2bOKuaSu3O9QxjSnsoTw7HIrhpucMOGkoaqHgS8DB/GSxSlgO9Cpqv2uWyuw0C0vBA659/a7/rWp7cPeM1r7BUTkDhFpFpHmtra2if5IJouoKpGWdprCmV3PSGoKh9gajRFPqN+hGDMpkxmeqsH75h8GFgDleMNLM05VH1LVBlVtqKur8yMEM8NaO85z5FR3xk61Ha4xHKKru5/Xjp32OxRjJmUyw1PvAqKq2qaqfcAPgbcC1W64CmARcNgtHwYWA7j1VUB7avuw94zWbszAFNZMr2ckJYv1dkkRk+0mkzQOAmtFpMzVJm4A9gAvAO9zfTYCz7jlZ91r3PpfqKq69lvd7KowsBzYCmwDlrvZWEV4xfJnJxGvySGRaIyaskKWz5nldyhpWVRTxsLqUiJW1zBZrmD8LiNT1YiIPAXsAPqBncBDwH8APxCR/+7aHnFveQT4VxHZB8TwkgCq+oqIPImXcPqBO1U1DiAinwSew5uZ9aiqvjLReE1uiUTbua4+RCCQ+fWMpKZwiF/+vg1VzYo6jDEjmXDSAFDV+4D7hjW34M18Gt63G3j/KNu5H7h/hPZNwKbJxGhyz5HO8xyKnedP3xL2O5SL0rQsxA93HuaNtjNcOqfC73CMmRA7I9xkncHzM7KjCJ7U6OovNkRlspklDZN1ItF2KkoKuGJ+pd+hXJT62jLqKortfA2T1SxpmKwTaYnRWB8imEX1DAARoSkcItISw5sDYkz2saRhssqJrm5aTp7NmvMzhmsKhzjW1c2h2Hm/QzFmQixpmKySrAc0Zsn5GcMl72O+xc7XMFnKkobJKpFoO+VFQVYuyK56RtKldbOoKSu0uobJWpY0TFbZGo2xpj5EQTA7/3QDAeG6+pAlDZO1svN/nslLsbO9/P74maybajtc07JaDsbOcfSU1TVM9rGkYbJG8rpNa7O0CJ7UFLb7hpvsZUnDZI0tLTFKCgNctbDa71Am5Yr5lVQUF7ClxZKGyT6WNEzWiERjrFlaQ1FBdv/ZBgNCQ32NXfHWZKXs/t9n8sapc328eqyLxvrsnGo7XGO4ljfaznLyTI/foRhzUSxpmKywbX8MVbL2pL7hkj+H1TVMtrGkYbJCJNpOUUGA1Yuzu56RdNXCKkoLg5Y0TNaxpGGyQiQaY/XiakoKg36HMiUKgwHWLK0ZuAOhMdnCkobJeKe7+3j58CnWZvn5GcM1hkO8dvw0ned6/Q7FmLRZ0jAZr/lABwkdvG5TrmgMh1CF5v0dfodiTNosaZiMF2mJURAQrlmSG/WMpNWLqykKBojY1FuTRSaVNESkWkSeEpFXRWSviLxZREIisllEXnfPNa6viMiDIrJPRF4SkWtTtrPR9X9dRDamtK8Rkd3uPQ+K3Vg5L0Wi7Vy9qIqyokndnTjjlBQGWb242orhJqtM9kjj68BPVfVyYBWwF7gHeF5VlwPPu9cANwHL3eMO4FsAIhLCu894E969xe9LJhrX5+Mp71s/yXhNljnX28/u1lM5NzSV1LQsxMtHujjT0+93KMakZcJJQ0SqgD8EHgFQ1V5V7QQ2AI+5bo8Bt7jlDcD31LMFqBaR+cCNwGZVjalqB7AZWO/WVarqFvVuc/a9lG2ZPLHjQCf9Cc36ixSOpjEcIp5Qth+wuobJDpM50ggDbcD/JyI7ReQ7IlIOzFXVo67PMWCuW14IHEp5f6trG6u9dYR2k0ci0XZ32Y3cTBrXLqkhGBC7pIjJGpNJGgXAtcC3VPUa4CyDQ1EAuCOEab8ZsojcISLNItLc1tY23bszMyjSEmPlgkpmFedWPSOpvLiAqxZWEbGLF5osMZmk0Qq0qmrEvX4KL4kcd0NLuOcTbv1hYHHK+xe5trHaF43QfgFVfUhVG1S1oa6ubhI/kskk3X1xdh3qzNl6RlJTOMSLrZ1098X9DsWYcU04aajqMeCQiFzmmm4A9gDPAskZUBuBZ9zys8BtbhbVWuCUG8Z6DlgnIjWuAL4OeM6t6xKRtW7W1G0p2zJ5YOfBTnrjCRpzdGgqqWlZiL64svNgp9+hGDOuyR7z/yXwfREpAlqAj+EloidF5HbgAPAB13cTcDOwDzjn+qKqMRH5ErDN9fuiqiaP1T8BfBcoBX7iHiZPRKLtiMB1OVoET1qzNISI9/O++ZLcPqoy2W9SSUNVdwENI6y6YYS+Ctw5ynYeBR4dob0ZWDmZGE322hqNccW8SqpKC/0OZVpVlRZyxbxKO1/DZAU7I9xkpN7+BDsOduTMpdDH07QsxI6DHfT2J/wOxZgxWdIwGeml1k66+xI0hfNjuKYpHKK7L8Huw1bXMJnNkobJSBE3VNOY4/WMpOtcsT9iQ1Qmw1nSMBlpS0s7b5o7i1B5kd+hzIjaWcUsnzPLztcwGc+Shsk4ffEE2w905M3QVFJjOMT2Ax30x62uYTKXJQ2TcV4+fIpzvfG8KYInNS2r5UxPP3uOdvkdijGjsqRhMs7WPKtnJCVPYrSptyaTWdIwGScSjbGsrpw5FSV+hzKj5lWVsLS2zIrhJqNZ0jAZJZ5QtkVjeVfPSGoKh9i2P0YiMe3X+TRmQixpmIyy92gXp3v6WZtn9YykxnAtnef6+P2J036HYsyILGmYjLKlxbuvRL7VM5KSN5uyqbcmU1nSMBklEo2xJFTG/KpSv0PxxaKaUhZUlVgx3GQsSxomYyQSyrb9sZy9tWs6RITGcIhINIZ3jU9jMoslDZMxfn/iNJ3n+nL+pkvjaVpWy8kzPbScPOt3KMZcwJKGyRjJcfx8PtKAwXqODVGZTGRJw2SMSLSdhdWlLA6V+R2Kr5bNLmf2rGJLGiYjWdIwGUFV2RqN5e2sqVQiQlM4RKSl3eoaJuNY0jAZ4Y22M5w805v3Q1NJjeEQR05109px3u9QjBnCkobJCFuS9Yw8L4InJS/WaJcUMZlm0klDRIIislNEfuxeh0UkIiL7ROQJESly7cXu9T63vj5lG/e69tdE5MaU9vWubZ+I3DPZWE3mikRjzKkopr42v+sZSW+aU0F1WSFbo+1+h2LMEFNxpPFpYG/K638EvqqqlwIdwO2u/Xagw7V/1fVDRFYAtwJXAuuBf3GJKAh8E7gJWAF8yPU1OcarZ7TTtKwWEfE7nIwQCAjX1YesGG4yzqSShogsAv4I+I57LcA7gadcl8eAW9zyBvcat/4G138D8ANV7VHVKLAPaHSPfaraoqq9wA9cX5NjDrSf43hXj9UzhmkKh9jffo7jXd1+h2LMgMkeaXwN+CyQvNVYLdCpqv3udSuw0C0vBA4BuPWnXP+B9mHvGa39AiJyh4g0i0hzW1vbJH8kM9MibggmXy9SOJrkTDKra5hMMuGkISLvAU6o6vYpjGdCVPUhVW1Q1Ya6ujq/wzEXKdISo7a8iEvqZvkdSkZZMb+SWcUFRFqsrmEyR8Ek3vtW4L0icjNQAlQCXweqRaTAHU0sAg67/oeBxUCriBQAVUB7SntS6ntGazc5JOLOz7B6xlAFwQBrltZYXcNklAkfaajqvaq6SFXr8QrZv1DVDwMvAO9z3TYCz7jlZ91r3PpfqHfm0rPArW52VRhYDmwFtgHL3WysIrePZycar8lMh2LnONx53uoZo2haFuL1E2doP9PjdyjGANNznsbdwF+JyD68msUjrv0RoNa1/xVwD4CqvgI8CewBfgrcqapxd6TySeA5vNlZT7q+Jockx+vt/IyRJZPptv12tGEyw2SGpwao6n8C/+mWW/BmPg3v0w28f5T33w/cP0L7JmDTVMRoMtPWaDvVZYVcNrfC71Ay0lULqykpDBCJxli/cr7f4RhjZ4Qbf0Ugu9KKAAAVn0lEQVSiMa6rDxEIWD1jJEUFAa5dUmN38jMZw5KG8c2xU90caD9n9YxxNIZD7D3WxanzfX6HYowlDeOf5PkZTWGrZ4ylKVyLKmw/YEcbxn+WNIxvtrTEqCguYMWCSr9DyWjXLKmmMCg2RGUygiUN45tItJ2G+hqCVs8YU0lhkFWLqu3McJMRLGkYX7Sd7qGl7axNtU1T07IQuw+f4mxP//idjZlGljSML5JnOVsRPD2N4VriCWXHwQ6/QzF5zpKG8UUk2k5ZUZCVC6v8DiUrrFnqDePZJUWM3yxpGF9EWmKsWVpDYdD+BNMxq7iAlQsqrRhufGf/Y82Mi53t5bXjp21o6iI1hkPsOtRJd1/c71BMHrOkYWbcVrve1IQ0hWvpjSfYdajT71BMHrOkYWZcJNpOcUGAqxdZPeNiXFcfQgSraxhfWdIwM25rNMa1S2ooLgj6HUpWqSor5PJ5lZY0jK8saZgZdep8H3uOdtFkt3adkKZwiO0HOuiLJ8bvbMw0sKRhZlTz/hiqdr2piWoMhzjfF2f34VN+h2LylCUNM6Mi0RhFwQDXLKn2O5Ss1OhmnNkQlfGLJQ0zoyIt7axaXEVJodUzJmL2rGIuqSsn0tLudygmT1nSMDPmTE8/Lx/psqGpSWpaVkvz/g7iCfU7FJOHLGmYGdO8P0Y8oVYEn6SmcIjTPf3sPdrldygmD004aYjIYhF5QUT2iMgrIvJp1x4Skc0i8rp7rnHtIiIPisg+EXlJRK5N2dZG1/91EdmY0r5GRHa79zwoInYN7Sy2NRqjICCsWVrjdyhZLVnXsEulGz9M5kijH/hrVV0BrAXuFJEVwD3A86q6HHjevQa4CVjuHncA3wIvyQD3AU1AI3BfMtG4Ph9Ped/6ScRrfBaJxrhqURVlRQV+h5LV5leVsiRUxtao1TXMzJtw0lDVo6q6wy2fBvYCC4ENwGOu22PALW55A/A99WwBqkVkPnAjsFlVY6raAWwG1rt1laq6RVUV+F7KtkyWOd8b56XWzoFvyWZyGsMhtkZjJKyuYWbYlNQ0RKQeuAaIAHNV9ahbdQyY65YXAodS3tbq2sZqbx2hfaT93yEizSLS3NbWNqmfxUyPHQc76Isra60IPiUawyE6zvWxr+2M36GYPDPppCEis4Cngc+o6pDKnDtCmPavQqr6kKo2qGpDXV3ddO/OTECkpZ2AQEO91TOmQjL52tRbM9MmlTREpBAvYXxfVX/omo+7oSXc8wnXfhhYnPL2Ra5trPZFI7SbLLQlGuPKBVVUlBT6HUpOWBwqZV5liRXDzYybzOwpAR4B9qrqV1JWPQskZ0BtBJ5Jab/NzaJaC5xyw1jPAetEpMYVwNcBz7l1XSKy1u3rtpRtmSzS3Rdn16FOu3/GFBIRmpZ5dQ3vgN6YmTGZaSxvBT4K7BaRXa7tb4EHgCdF5HbgAPABt24TcDOwDzgHfAxAVWMi8iVgm+v3RVVNfn36BPBdoBT4iXvkLVXlbG+crvN9nO3pR4GACAUBIRgQAgFvOSDe64FHyuuAeB84M+nFQ5309ifs/hlTrDEc4pldR9jffo7w7HK/wzF5YsJJQ1V/DYz26XPDCP0VuHOUbT0KPDpCezOwcqIxZhJVpac/Qdf5Prq6+znd3cfp7n663PPp7j66zqe2D1/Xx5mefqZiskwykQQCUBAIEBDXFggQDOAlmWCyz9BEVOCSU3B4YgoM6+9eFwSEaPtZRKCx3o40plLTwHWo2i1pmBljE+bT1BdPeB/m51M+yLuTCWBo+wXJwD33xcf+xA8IVJQUUlFSQEVJIZUlBSysLqWypIKKkgIqSwfXzSouQATiCSWhSn/ce44nIJ5IEE8ocU0uM9AnrkoiofQnkv1THqrEh/UZ0j/ZJ+U9vf2Jof2T8aT2jyvvXbWAqjKrZ0ylS+pmUVtexE9fPkZ49izKioLuUUBZcZCywiAFdg92M8UsaTg/fukIv9l30vuGf/7CD/zuvvHvXzCruMB9qBdQWVLI7FlFhGeXX/CBX+nWD7wu9Z7Li4IzPnRkspeI8Lbls3lm1xFeeG3kqeZFBQHKk4mkKEhZcQFlhUHKi4OUFhUMW+clmrJi73V5sj2ZhFL6FmZYMlJVeuMJevoT9PZ7zz198aGv++NDlnv6Et57+tzrYX17+r0vX8kj6IFndzSe2uYdiV/YnjwCl4Gj+ZTh45TtBWSwfXB4mRH6ekPMF/b1lhdUl0z7ybOWNJzdraf4+d4TAx/4Fe5b/sAHvksI3od/4ZB+lSWFzCopIBiwD3wzs/7hj6/itjfXc743ztnefs719nOuN865nrj33Nvv2l1bX5xzPf0c6exz6+ID772YenpRMDAkyZQXBSl1iWbIc/FgoikvKqCkKEh/PDHyh/coH/Q9A8ve+sEP+qGJYCoUFwQoLghQVBCkuCBAMCADR89Dnxly5J3a7qfvfuw63nHZnGndh+TazIuGhgZtbm72Owxjskqy5na2xyUYl0jO98Y529PP+b44Z3viA0lpcN1g2+CzW+7x+qXzQSqS/MAOUuQ+uC94XRikKBiguHBwXXFq32Hri4b0Sd3OhfspKghQFAxM+khf1SWU4ckkwZAEM1p7cthX9cL2ZJIaSFgpw8fJvm9eVsucypIJxS4i21W1Ybx+dqRhjEFEKCkMUlIYZCrnuCWTUTKRnO+NUxgMXJAICoOSE0OzIkJQIIiQq7eMsaRhjJk2qckoVF7kdzhmCmRWNcsYY0xGs6RhjDEmbZY0jDHGpM2ShjHGmLRZ0jDGGJM2mz1l8lsiAe374MjOwceJvVC9BBashoXXwoJrYM6VUGCzf4yxpGHyhyp07IcjO1yC2OU9ek976wvLYN7VsPKPofMgvPpj2Pmv3rpgEcy9Eha4JLLgGqi7HIL2X8jkF/uLN7lJFboOe8nh8I7Bo4juTm99sAjmXQWrPjiYCGa/aWgSUIXOA4PvPbwDdv8bND/irS8ohflXDyaRBddC7aUQsFFfk7vsMiImN5w+PnSI6cgOOOsu4hcogDkrBj/cF14LdVdMbLgpkYBYy+A+juyEoy9C3zlvfVEFzF81dGirJuxdJ8OYDGaXETG561ws5UN7l7fc5e4ELAGYfRksXzeYJOauhMKJXY/nAoEAzL7Ue1z9fq8tEYe214Ymra0PQ7zHW19SnXI04h5ViyyRmKxkScNktu5T3jf51GGmzgOD62svhaVvGRximncVFM+a2RgDQZi7wntc82Gvrb8X2vYOHdr67YOQ6PfWl9cNSyTXQsXcmY3bmAmwpGEyR+9ZOPrS0CGm9n2D66uXeh+wDX/mDf3MXwUlVf7FO5aCIi+++atgzZ96bX3dcPyVlEL8Ttj3c1B3We+KBSlDaNfA/Gug3G6RazJLxicNEVkPfB0IAt9R1Qd8DslMhZE+QNteHfoBuvBaWHWr9yGaCx+ghSWwaI33SLogUe6E1/5jcH31kqEzthasztxEafJCRicNEQkC3wTeDbQC20TkWVXdM+U76zkD/T0pDcMmCFwwYcDv9WlKa9x8nD5TsY2zJ4YO1ZzYMzhUUzbbSxBXvHfwg7FiXhr7zAFF5bD0zd4jKXVILvn72vOjwfW1lw4d2hpSaE/5dxjy7zZS+2h9031/SvvF7GuA+5se8rd9kW0XtA9vG6lfum3D2keS1v/LNPpM1XbK66CwNI1tTVxGJw2gEdinqi0AIvIDYAMw9Unj5/fBtu9M+WbNMMmi8Fs+NTi7qHKhFYVTlVRB+A+9R9Lw4v+B33rTf41J9eGnYfm7pnUXmZ40FgKHUl63Ak3TsqcVt3izblKN90F2wXqZ2fXjmopvOFP0Lamk0qafTkZZCC69wXskJacZnz7ivZ7QN/HR+o7zzTutfY3WN92jnos5OhrjiCfdo6i0jqxGksbf81QcraeznTlXpLGfycn0pJEWEbkDuANgyZIlE9tI+A+8hzHZomIuXLbe7yhMnsn0U1cPA4tTXi9ybUOo6kOq2qCqDXV1dTMWnDHG5JtMTxrbgOUiEhaRIuBW4FmfYzLGmLyV0cNTqtovIp8EnsObcvuoqr7ic1jGGJO3MjppAKjqJmCT33EYY4zJ/OEpY4wxGcSShjHGmLRZ0jDGGJM2SxrGGGPSlnM3YRKRNuDAuB1HVgWcmsJwpls2xZtNsUJ2xZtNsUJ2xZtNsQIsAQ5O8L1LVXXcE91yLmlMhog8pKp3+B1HurIp3myKFbIr3myKFbIr3myKFbwvzel88E+GDU8N9e9+B3CRsinebIoVsivebIoVsivebIoVoHO6d2BHGsYYkyNEpDmd+3xPhh1pGGNM7nhoundgRxrGGGPSlrdHGiKyWEReEJE9IvKKiHzatX9BRA6LyC73uDlTY3Xr/lJEXnXt/9PPOJPG+N0+kfJ73S8iuzI41tUissXF2iwijRkc6yoR+Z2I7BaRfxeRSr9jBRCREhHZKiIvunj/3rWHRSQiIvvc30RRBsf6SRenishsv+PMCKqalw9gPnCtW64Afg+sAL4A/I3f8aUZ6/XAz4Fit26O37GOFe+wPv8L+Hymxgr8DLjJtd8M/GcGx7oNeLtr/zPgS37H6mIRYJZbLgQiwFrgSeBW1/5t4C8yONZrgHpgPzDb7ziHxbweeA3YB9zj2j7pXut0xZu3RxqqelRVd7jl08BevDsFZpwxYv0L4AFV7XHrTvgX5aDxfrciIsAHgMf9iXDQGLEqkPzGXgUc8SfCQWPE+ibgV67bZuBP/IlwKPWccS8L3UOBdwJPufbHgFt8CG+I0WJV1Z2qut+/yEYmIkHgm8BNeF8cPiQiK4DfAO9i4ueqjStvk0YqEanH+0YRcU2fFJGXRORREanxLbARDIv1TcAfuEP9X4rIdX7GNpIRfrcAfwAcV9XX/YhpNMNi/QzwTyJyCPgycK9/kV1oWKyvABvcqvcz9MZlvhKRoBuGPIGX0N4AOlW133VpJUO+rA2PVVUj473HR43APlVtUdVe4AfAhplIcnmfNERkFvA08BlV7QK+BVwCrAaO4g2jZIQRYi0AQniH0f8v8KT7Fp8RRog36UNkwFFGqhFi/QvgLlVdDNwFPOJnfKlGiPXPgE+IyHa8YateP+NLpapxVV2Nd9fNRuByn0Ma1fBYRWSl3zGNYSFwKOX1jCXfvE4aIlKI95/v+6r6QwBVPe7+eBLAw3h/6L4bKVa8P5QfukPrrUACyIhi3SjxIiIFwB8DT/gV23CjxLoRSC7/Gxn8d6Cqr6rqOlVdg5eM3/AzxpGoaifwAvBmoNr9HcAot3D2U0qsdgP2EeRt0nDfyB8B9qrqV1La56d0+3+Al2c6tuFGixX4EV4xHBF5E1AEnJz5CIcaI17wxltfVdXWmY/sQmPEegR4u1t+J+D7UNoYf7Nz3HMA+Bxecdl3IlInItVuuRR4N14d5gXgfa7bRuAZfyIcNEqsr/ob1ZgOM3QYcuaSr98zAPx6AG/DK8q9BOxyj5uBfwV2u/ZngfkZHGsR8L/xEtsO4J1+xzpWvG7dd4E/9zvGNH63bwO2Ay/i1Q3WZHCsn8abSfV74AHc+Vd+P4CrgZ0u3pdxs+WAZcBWvFk+/4ab/ZehsX4K74i+H++LxHf8jtXFVQC0AGH3OfAicGXK+v1M0+wpO7nPGGOykDuH7GtAEHhUVe8XkU8BnwXm4RX0N6nqf53S/VrSMMYYk668rWkYY4y5eJY0jDHGpM2ShjHGmLRZ0jDGmCwiImfG7zV9LGkYY4xJmyUNY4zJMiIyS0SeF5Ed7pL4G1x7vYjsFZGH3SXef+ZOVpy6fduUW2OMyR5ueKoaKFPVLnefjy3AcmAp3kmTDaq6S0SeBJ5V1f89VfsvGL+LMcaYDCPA/xCRP8S75txCYK5bF1XV5A3OtuPdD2TKWNIwxpjs82GgDu/yNn0ish8ocet6UvrFgSkdnrKahjHGZJ8q4IRLGNfjDUvNCDvSMMaYLOEuKd8DfB/4dxHZDTQzg1fktUK4McZkCRFZBTysqr7d38WGp4wxJguIyJ/j3WTrc77GYUcaxhhj0mVHGsYYk6FEZLGIvCAie9zJep927SER2Swir7vnGtd+uYj8TkR6RORvhm3rLreNl0XkcREpGWmf47GkYYwxmasf+GtVXQGsBe4UkRXAPcDzqroceN69Bojh3W3wy6kbEZGFrr1BVVfi3bjp1okEZEnDGGMylKoeVdUdbvk03j3WFwIbgMdct8eAW1yfE6q6DegbYXMFQKmbgVWGd/vai2ZJwxhjsoCI1APX4N2zfq6qHnWrjjF4NviIVPUw3tHHQeAocEpVfzaROCxpGGNMhhORWcDTwGdUtSt1nXqzmcac0eRqHhuAMLAAKBeRj0wkFksaxhiTwUSkEC9hfF9Vf+iaj4vIfLd+PnBinM28C++aVG2q2gf8EHjLROKxpGGMMRlKRAR4BNirql9JWfUssNEtbwSeGWdTB4G1IlLmtnkDXn3k4mOy8zSMMSYzicjbgP8D7Ma7mi3A3+LVNZ4ElgAHgA+oakxE5uFdVqTS9T8DrHCXUP974IN4M7J2Av9VVVMvbpheTJY0jDHGpMuGp4wxxqTNkoYxxpi0WdIwxhiTNksaxhhj0mZJwxhjTNrszn0mb4lILd7F3gDm4d1Puc29PqeqEzr5KY391gNvUdX/fzq2b8x0sim3xgAi8gXgjKp+eby+U7CvdwB/o6rvme59GTPVbHjKmBGIyBn3/A4R+aWIPCMiLSLygIh8WES2ishuEbnE9asTkadFZJt7vNW1v11EdrnHThGpAB4A/sC13SUi9SLyf0Rkh3u85SL3/V0R+baINIvI70XEkpGZNjY8Zcz4VgFX4N2roAX4jqo2uhvi/CXwGeDrwFdV9dcisgR4zr3nb4A7VfU37qJz3Xj3Phg40hCRMuDdqtotIsvxbunZcBH7BqgHGoFLgBdE5FJV7Z6+X4nJV5Y0jBnftuRlqEXkDSB5SendwPVu+V3ACu+yPgBUuiTxG+ArIvJ94Ieq2prSJ6kQ+IaIrMarq7zpIvcN8KSqJoDXRaQFuBzYNYmf2ZgRWdIwZnyp1+dJpLxOMPh/KACsHeHb/QMi8h/AzcBvROTGEbZ/F3Ac76gigHc0cjH7hgsvjW3FSjMtrKZhzNT4Gd5wEQDuqAERuURVd6vqPwLb8I4ATgMVKe+tAo66I4WP4t2K82K9X0QCrs6xDHhtYj+GMWOzpGHM1PgU0CAiL4nIHuDPXftnRORlEXkJ7xacPwFeAuIi8qKI3AX8C7BRRF7ESypnJ7D/g8BWt/0/t3qGmS425daYLCci3wV+rKpP+R2LyX12pGGMMSZtdqRhjDEmbXakYYwxJm2WNIwxxqTNkoYxxpi0WdIwxhiTNksaxhhj0mZJwxhjTNr+L/LTjMdyBTX7AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['2017-12-25':'2018-01-01'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x113870b00>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['2018-03-01': '2018-03-09'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apparently, they're located in '2017-12-28' and '2018-03-04':"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_cleaned = df.drop(pd.to_datetime(['2017-12-28', '2018-03-04']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1139694a8>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cleaned.plot(figsize=(16, 9))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now it looks much better. Our data seems to be clean."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cleaning Analysis \n",
    "\n",
    "Visualizations helps make sense of the data and let us judge if our analysis and work is on the right track. But we need a more powerful method to handle our data. That's what we call \"analysis\". We'll use _analytical_ methods to identify these outliers or these skewed values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Central Tendency\n",
    "\n",
    "We'll use a set of common indicators of to measure central tendency and identify these outliers:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### mean\n",
    "The mean is probably the most common and popular one. The problem is that it's really sensitive to outliers. The mean of our dataset with invalid values is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bitcoin    6996.004022\n",
       "Ether       469.609068\n",
       "dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both values seem too high. That's because the outliers are skewing with the mean:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bitcoin    6323.509186\n",
       "Ether       428.628402\n",
       "dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cleaned.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### median"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bitcoin    4594.98785\n",
       "Ether       309.49000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.median()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### mode\n",
    "\n",
    "It doesn't make much sense to measure the mode, as we have continuous values. But you can do it just with `df.mode()`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use a few of the charts that we saw before + seaborn to visualize the distribution of our values. In particular, we're interested in **histograms**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x116152a90>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cleaned.plot(kind='hist', y='Ether', bins=150)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1162f4f98>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_cleaned.plot(kind='hist', y='Bitcoin', bins=150)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using seaborn:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x115f360b8>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df_cleaned['Ether'], ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1159dbef0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df_cleaned['Bitcoin'], rug=True, ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seaborn's `distplot` is a general method that will plot a histogram, a KDE and a rugplot. You can also use them as separate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.kdeplot(df_cleaned['Ether'], shade=True, cut=0, ax=ax)\n",
    "sns.rugplot(df_cleaned['Ether'], ax=ax);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also visualize a cumulative plot of our distribution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10b383780>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df_cleaned['Bitcoin'], ax=ax,\n",
    "             hist_kws=dict(cumulative=True),\n",
    "             kde_kws=dict(cumulative=True))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This plot shows how many samples fall behind a certain value. We can increase the number of bins in order to have more detail:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10bdcd438>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df_cleaned['Bitcoin'], ax=ax, bins=50,\n",
    "             hist_kws=dict(cumulative=True),\n",
    "             kde_kws=dict(cumulative=True))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing bivariate distributions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most common way to observe a bivariate distribution is a scatterplot, the `jointplot` will also include the distribution of the variables:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x117685e80>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x=\"Bitcoin\", y=\"Ether\", data=df_cleaned, size=9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want only a scatter plot, you can use the `regplot` method, that also fits a linear regression model in the plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x117aafb00>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.regplot(x=\"Bitcoin\", y=\"Ether\", data=df_cleaned, ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quantiles, quartiles and percentiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2438.8627342857144"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cleaned['Bitcoin'].quantile(.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x10be5da58>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df_cleaned['Bitcoin'], ax=ax, bins=50,\n",
    "             hist_kws=dict(cumulative=True),\n",
    "             kde_kws=dict(cumulative=True))\n",
    "ax.axhline(0.2, color='red')\n",
    "ax.axvline(df_cleaned['Bitcoin'].quantile(.2), color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4580.3874799999985"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cleaned['Bitcoin'].quantile(.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4580.3874799999985"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cleaned['Bitcoin'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x10c6b8e80>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df_cleaned['Bitcoin'], ax=ax, bins=50,\n",
    "             hist_kws=dict(cumulative=True),\n",
    "             kde_kws=dict(cumulative=True))\n",
    "ax.axhline(0.5, color='red')\n",
    "ax.axvline(df_cleaned['Bitcoin'].quantile(.5), color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x10cdc6fd0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df_cleaned['Bitcoin'], ax=ax, bins=50,\n",
    "             hist_kws=dict(cumulative=True),\n",
    "             kde_kws=dict(cumulative=True))\n",
    "ax.axhline(0.5, color='red')\n",
    "ax.axvline(df_cleaned['Bitcoin'].median(), color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Quantile `0.25` == Percentile `25%` == Quartile `1st`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dispersion\n",
    "\n",
    "We'll use a few methods to measure dispersion in our dataset, most of them well known:\n",
    "\n",
    "* Range\n",
    "* Variance and Standard Deviation\n",
    "* IQR"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Range\n",
    "\n",
    "Range is fairly simple to understand, it's just the max - min values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "142706.6475416667"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Bitcoin'].max() - df['Bitcoin'].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Range is **really** sensitive to outliers. As you can see, the range value is extremely high (might indicate the presence of outliers / invalid values)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18399.514208333334"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cleaned['Bitcoin'].max() - df_cleaned['Bitcoin'].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This value now makes a lot more sense. We know that Bitcoin had a high in about 20k, and it was around 900 when we started measuring. It makes more sense now."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Variance and Standard Deviation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "103766537.75278121"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Bitcoin'].var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10186.586167739475"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Bitcoin'].std()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both variance and std are sensible to outliers as well. We can check with our cleaned dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4513.757662530282"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cleaned['Bitcoin'].std()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IQR\n",
    "\n",
    "The [Interquartile range](https://en.wikipedia.org/wiki/Interquartile_range) is a good measure of \"centered\" dispersion, and is calculated as `Q3 - Q1` (3rd quartile - 1st quartile)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6597.494147619047"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Bitcoin'].quantile(.75) - df['Bitcoin'].quantile(.25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6548.249242559523"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cleaned['Bitcoin'].quantile(.75) - df_cleaned['Bitcoin'].quantile(.25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, IQR is more robust than std or range, because it's not so sensitive to outliers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analytical Analysis of invalid values\n",
    "\n",
    "We can now use the measurements we've seen to analyze those values that seem invalid."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Using `std`: Z scores\n",
    "\n",
    "We can now define those values that are a couple of Z scores above or below the mean (or the max/min value). Example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "upper_limit = df['Bitcoin'].mean() + 2 * df['Bitcoin'].std()\n",
    "lower_limit = df['Bitcoin'].mean() - 2 * df['Bitcoin'].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Upper Limit: 27369.17635730169\n",
      "Lower Limit: -13377.16831365621\n"
     ]
    }
   ],
   "source": [
    "print(\"Upper Limit: {}\".format(upper_limit))\n",
    "print(\"Lower Limit: {}\".format(lower_limit))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1129d0588>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df['Bitcoin'], ax=ax)\n",
    "ax.axvline(lower_limit, color='red')\n",
    "ax.axvline(upper_limit, color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Seems like this is a good measurement. Our lower limit doesn't make a lot of sense, as negative values are invalid. But our upper limit has a really good measure. Anything above \\$27,369 is considered to be an invalid value. Pretty accurate."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Using IQRs\n",
    "\n",
    "We can use the IQR instead of std if we think that the standard deviation might be **too** affected by the outliers/invalid values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6597.494147619047"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iqr = df['Bitcoin'].quantile(.75) - df['Bitcoin'].quantile(.25)\n",
    "iqr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "upper_limit = df['Bitcoin'].mean() + 2 * iqr\n",
    "lower_limit = df['Bitcoin'].mean() - 2 * iqr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Upper Limit: 20190.992317060834\n",
      "Lower Limit: -6198.9842734153535\n"
     ]
    }
   ],
   "source": [
    "print(\"Upper Limit: {}\".format(upper_limit))\n",
    "print(\"Lower Limit: {}\".format(lower_limit))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/santiagobasulto/.virtualenvs/ds-classes/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x112866d30>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15, 7))\n",
    "sns.distplot(df['Bitcoin'], ax=ax)\n",
    "ax.axvline(lower_limit, color='red')\n",
    "ax.axvline(upper_limit, color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our measurement now is a little bit less precise. There are a few valid values (20k) that seem to be above our upper limit. Regardless, it's still a good indicator."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cleaning invalid values analytically\n",
    "\n",
    "It's time now to remove these invalid values analytically, we'll use the upper limit defined by standard deviation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "upper_limit = df['Bitcoin'].mean() + 2 * df['Bitcoin'].std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x112035eb8>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Bitcoin'] < upper_limit].plot(figsize=(16, 7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1119addd8>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.drop(df[df['Bitcoin'] > upper_limit].index).plot(figsize=(16, 7))"
   ]
  }
 ],
 "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}