rs_column_distribution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Redshift: column value distribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import db_diff as db"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def connect():\n",
    "    config = db.load_config('../../etc/prod-ostro/aws.json')\n",
    "    engine = db.rs_connect('ostro', config)\n",
    "    conn = engine.connect()\n",
    "    conn.execute(\"SET search_path TO leviathan\")\n",
    "    return conn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sql functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_base(table_id, column_name, timestamp='timestamp'):\n",
    "    return \"\"\"\n",
    "    derived_base AS (\n",
    "        SELECT\n",
    "            to_char(\"{timestamp}\", 'YYYYMMDD') as event_day,\n",
    "            extract(hour from \"{timestamp}\") as event_hour,\n",
    "            {column} AS event_column\n",
    "        FROM {table}\n",
    "        WHERE date(\"{timestamp}\") BETWEEN '2017-09-04' AND '2017-10-05'\n",
    "        AND test = false\n",
    "        )\n",
    "    \"\"\".format(table=table_id, column=column_name, timestamp=timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_base_percentile(table_id, column_name, timestamp='timestamp'):\n",
    "    return \"\"\"\n",
    "    outlier_percentiles AS (\n",
    "        SELECT\n",
    "            percentile_cont(0.05) within group (order by {column}) as ptile_lower,\n",
    "            percentile_cont(0.95) within group (order by {column}) as ptile_upper\n",
    "        FROM {table}\n",
    "        ),\n",
    "    \n",
    "    derived_base AS (\n",
    "        SELECT\n",
    "            to_char(\"{timestamp}\", 'YYYYMMDD') as event_day,\n",
    "            extract(hour from \"{timestamp}\") as event_hour,\n",
    "            {column} AS event_column\n",
    "        FROM {table}\n",
    "        WHERE date(\"{timestamp}\") BETWEEN '2017-09-04' AND '2017-10-05'\n",
    "        AND test = false\n",
    "        AND {column} > (SELECT ptile_lower FROM outlier_percentiles)\n",
    "        AND {column} < (SELECT ptile_upper FROM outlier_percentiles)\n",
    "        )\n",
    "    \"\"\".format(table=table_id, column=column_name, timestamp=timestamp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_bool_convert():\n",
    "    return \"\"\"\n",
    "    derived_number AS (\n",
    "        SELECT\n",
    "            event_day,\n",
    "            event_hour,\n",
    "            CASE event_column\n",
    "            WHEN true  THEN 0.75\n",
    "            WHEN false THEN 0.25\n",
    "            END AS number_column\n",
    "        FROM derived_base\n",
    "        )\n",
    "    \"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_time_convert():\n",
    "    return \"\"\"\n",
    "    derived_number AS (\n",
    "        SELECT\n",
    "            event_day,\n",
    "            event_hour,\n",
    "            extract(epoch from event_column) AS number_column\n",
    "        FROM derived_base\n",
    "        )\n",
    "    \"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_number_convert():\n",
    "    return \"\"\"\n",
    "    derived_number AS (\n",
    "        SELECT\n",
    "            event_day,\n",
    "            event_hour,\n",
    "            event_column AS number_column\n",
    "        FROM derived_base\n",
    "        )\n",
    "    \"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_string_convert(slice_size=5):\n",
    "    if slice_size >= 0:\n",
    "        substr_parameters = \"event_column,0,{no_characters}\".format(no_characters=slice_size)\n",
    "    else:\n",
    "        substr_parameters = \"reverse(event_column),0,{no_characters}\".format(no_characters=(-1*slice_size))\n",
    "\n",
    "    return \"\"\"\n",
    "    string_substr AS (\n",
    "        SELECT\n",
    "            event_day,\n",
    "            event_hour,\n",
    "            SUBSTRING({parameters}) AS string_column\n",
    "        FROM derived_base\n",
    "        ),\n",
    "\n",
    "    derived_number AS (\n",
    "        SELECT\n",
    "            event_day,\n",
    "            event_hour,\n",
    "            STRTOL(SUBSTRING(MD5(string_column),0,15), 16) AS number_column\n",
    "        FROM string_substr\n",
    "        )\n",
    "    \"\"\".format(parameters=substr_parameters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_hash_convert():\n",
    "    return \"\"\"\n",
    "    derived_number AS (\n",
    "        SELECT\n",
    "            event_day,\n",
    "            event_hour,\n",
    "            STRTOL(SUBSTRING(event_column,0,15), 16) AS number_column\n",
    "        FROM derived_base\n",
    "        WHERE regexp_count(event_column, '[ABCDEF0123456789]') = length(event_column)\n",
    "        )\n",
    "    \"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_normalized():\n",
    "    return \"\"\"\n",
    "    derived_stats AS (\n",
    "        SELECT\n",
    "            min(number_column) AS min_value,\n",
    "            max(number_column) AS max_value,\n",
    "            max(number_column) - min(number_column) AS range_value,\n",
    "            median(number_column) AS mean_value\n",
    "        FROM derived_number\n",
    "        WHERE number_column > 0\n",
    "        ),\n",
    "\n",
    "    derived_norm AS (\n",
    "        SELECT\n",
    "            event_day,\n",
    "            event_hour,\n",
    "            number_column as raw_value,\n",
    "            (number_column::float - (SELECT min_value from derived_stats))\n",
    "                / (SELECT range_value from derived_stats)\n",
    "            AS normed_value\n",
    "        FROM derived_number\n",
    "        )\n",
    "    \"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_normed(sql_with):\n",
    "    return \"\"\"\n",
    "    WITH\n",
    "    {sql_with}\n",
    "\n",
    "    SELECT\n",
    "        event_day,\n",
    "        event_hour,\n",
    "        raw_value,\n",
    "        normed_value\n",
    "    FROM derived_norm\n",
    "    \"\"\".format(sql_with=sql_with)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_normed_stats(sql_with):\n",
    "    return \"\"\"\n",
    "    WITH\n",
    "    {sql_with}\n",
    "\n",
    "    SELECT\n",
    "        min_value,\n",
    "        max_value,\n",
    "        range_value\n",
    "    FROM derived_stats\n",
    "    \"\"\".format(sql_with=sql_with)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_normed_percentiles(sql_with):\n",
    "    queries = []\n",
    "    for tile in np.linspace(0.0, 1.0, num=21):\n",
    "        queries.append(\"\"\"\n",
    "            SELECT\n",
    "            {tile:.2f} AS ptile,\n",
    "            percentile_cont({tile:.2f}) within group (order by normed_value) as ptile_value\n",
    "            FROM derived_norm\n",
    "            \"\"\".format(tile=tile))\n",
    "    ptile_sql = ' UNION '.join(queries)\n",
    "    \n",
    "    return \"\"\"\n",
    "    WITH\n",
    "    {sql_with}\n",
    "    \n",
    "    {ptiles}\n",
    "    \"\"\".format(ptiles=ptile_sql, sql_with=sql_with)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## plot functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_one_per_day_overlay(df):\n",
    "    sns.set(style=\"white\", palette=\"muted\")\n",
    "    f, axes = plt.subplots(1, 1, figsize=(10, 7), sharex=True)\n",
    "    sns.despine(left=True)\n",
    "\n",
    "    b, g, r, p = sns.color_palette(\"muted\", 4)\n",
    "\n",
    "    for d in df['event_day'].unique():\n",
    "        if int(d) % 2 == 0: c=g\n",
    "        else: c=b\n",
    "        sns.distplot(df[(df['event_day'] == d)]['normed_value'], color=c)\n",
    "\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_one_hour(df, bins=20):\n",
    "    df[(df['event_day'] == '20171004') & (df['event_hour'] == 12)]['normed_value'].plot.hist(bins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_all(df, bins=20):\n",
    "    df['normed_value'].plot.hist(bins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_raw_all(df, bins=20):\n",
    "    df['raw_value'].plot.hist(bins)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## distribution of string values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sql_with = ','.join([create_base('power_out', 'model'),\n",
    "                     create_string_convert(),\n",
    "                     create_normalized()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conn = connect()\n",
    "df = pd.read_sql(create_normed(sql_with), con=conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conn = connect()\n",
    "df_percentiles = pd.read_sql(create_normed_percentiles(sql_with), con=conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_day</th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>6177464392961464</td>\n",
       "      <td>0.085728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>4365244226672665</td>\n",
       "      <td>0.060579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>13561380986287748</td>\n",
       "      <td>0.188201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>46970283633066291</td>\n",
       "      <td>0.651844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>13121254510359646</td>\n",
       "      <td>0.182093</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  event_day  event_hour          raw_value  normed_value\n",
       "0  20170904           0   6177464392961464      0.085728\n",
       "1  20170904           0   4365244226672665      0.060579\n",
       "2  20170904           0  13561380986287748      0.188201\n",
       "3  20170904           0  46970283633066291      0.651844\n",
       "4  20170904           0  13121254510359646      0.182093"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ptile</th>\n",
       "      <th>ptile_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.05</td>\n",
       "      <td>0.047714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.10</td>\n",
       "      <td>0.097805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.15</td>\n",
       "      <td>0.147331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.20</td>\n",
       "      <td>0.198825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.25</td>\n",
       "      <td>0.245646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.30</td>\n",
       "      <td>0.300022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.35</td>\n",
       "      <td>0.347340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.40</td>\n",
       "      <td>0.397380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.45</td>\n",
       "      <td>0.445246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.50</td>\n",
       "      <td>0.497417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.55</td>\n",
       "      <td>0.546627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.60</td>\n",
       "      <td>0.595178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.65</td>\n",
       "      <td>0.643337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.70</td>\n",
       "      <td>0.694191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.75</td>\n",
       "      <td>0.746664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.80</td>\n",
       "      <td>0.797602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.85</td>\n",
       "      <td>0.849671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.90</td>\n",
       "      <td>0.897146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.95</td>\n",
       "      <td>0.947318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.00</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ptile  ptile_value\n",
       "14   0.00     0.000000\n",
       "0    0.05     0.047714\n",
       "15   0.10     0.097805\n",
       "16   0.15     0.147331\n",
       "11   0.20     0.198825\n",
       "18   0.25     0.245646\n",
       "2    0.30     0.300022\n",
       "19   0.35     0.347340\n",
       "3    0.40     0.397380\n",
       "17   0.45     0.445246\n",
       "1    0.50     0.497417\n",
       "4    0.55     0.546627\n",
       "8    0.60     0.595178\n",
       "9    0.65     0.643337\n",
       "12   0.70     0.694191\n",
       "13   0.75     0.746664\n",
       "5    0.80     0.797602\n",
       "20   0.85     0.849671\n",
       "6    0.90     0.897146\n",
       "7    0.95     0.947318\n",
       "10   1.00     1.000000"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_percentiles.sort_values('ptile')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>9.694862e+10</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.05</th>\n",
       "      <td>1.0</td>\n",
       "      <td>3.438280e+15</td>\n",
       "      <td>0.047714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.10</th>\n",
       "      <td>3.0</td>\n",
       "      <td>7.047652e+15</td>\n",
       "      <td>0.097805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.15</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1.061642e+16</td>\n",
       "      <td>0.147331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.20</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.432690e+16</td>\n",
       "      <td>0.198825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.25</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1.770072e+16</td>\n",
       "      <td>0.245646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.30</th>\n",
       "      <td>9.0</td>\n",
       "      <td>2.161891e+16</td>\n",
       "      <td>0.300022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.35</th>\n",
       "      <td>10.0</td>\n",
       "      <td>2.502850e+16</td>\n",
       "      <td>0.347340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.40</th>\n",
       "      <td>11.0</td>\n",
       "      <td>2.863432e+16</td>\n",
       "      <td>0.397380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.45</th>\n",
       "      <td>12.0</td>\n",
       "      <td>3.208336e+16</td>\n",
       "      <td>0.445246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.50</th>\n",
       "      <td>13.0</td>\n",
       "      <td>3.584268e+16</td>\n",
       "      <td>0.497417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.55</th>\n",
       "      <td>14.0</td>\n",
       "      <td>3.938863e+16</td>\n",
       "      <td>0.546627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.60</th>\n",
       "      <td>15.0</td>\n",
       "      <td>4.288708e+16</td>\n",
       "      <td>0.595178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.65</th>\n",
       "      <td>16.0</td>\n",
       "      <td>4.635734e+16</td>\n",
       "      <td>0.643337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.70</th>\n",
       "      <td>17.0</td>\n",
       "      <td>5.002170e+16</td>\n",
       "      <td>0.694191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.75</th>\n",
       "      <td>18.0</td>\n",
       "      <td>5.380281e+16</td>\n",
       "      <td>0.746664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.80</th>\n",
       "      <td>19.0</td>\n",
       "      <td>5.747325e+16</td>\n",
       "      <td>0.797602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.85</th>\n",
       "      <td>20.0</td>\n",
       "      <td>6.122523e+16</td>\n",
       "      <td>0.849671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.90</th>\n",
       "      <td>21.0</td>\n",
       "      <td>6.464614e+16</td>\n",
       "      <td>0.897146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.95</th>\n",
       "      <td>22.0</td>\n",
       "      <td>6.826144e+16</td>\n",
       "      <td>0.947318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.00</th>\n",
       "      <td>23.0</td>\n",
       "      <td>7.205755e+16</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      event_hour     raw_value  normed_value\n",
       "0.00         0.0  9.694862e+10      0.000000\n",
       "0.05         1.0  3.438280e+15      0.047714\n",
       "0.10         3.0  7.047652e+15      0.097805\n",
       "0.15         4.0  1.061642e+16      0.147331\n",
       "0.20         6.0  1.432690e+16      0.198825\n",
       "0.25         7.0  1.770072e+16      0.245646\n",
       "0.30         9.0  2.161891e+16      0.300022\n",
       "0.35        10.0  2.502850e+16      0.347340\n",
       "0.40        11.0  2.863432e+16      0.397380\n",
       "0.45        12.0  3.208336e+16      0.445246\n",
       "0.50        13.0  3.584268e+16      0.497417\n",
       "0.55        14.0  3.938863e+16      0.546627\n",
       "0.60        15.0  4.288708e+16      0.595178\n",
       "0.65        16.0  4.635734e+16      0.643337\n",
       "0.70        17.0  5.002170e+16      0.694191\n",
       "0.75        18.0  5.380281e+16      0.746664\n",
       "0.80        19.0  5.747325e+16      0.797602\n",
       "0.85        20.0  6.122523e+16      0.849671\n",
       "0.90        21.0  6.464614e+16      0.897146\n",
       "0.95        22.0  6.826144e+16      0.947318\n",
       "1.00        23.0  7.205755e+16      1.000000"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.quantile(np.linspace(0.0, 1.0, num=21))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot all data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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YQpKkbgwhSVI3hpAkqRtDSJLUjSEkSerGEJIkdWMISZK6MYQkSd0YQpKkbgwhSVI3hpAk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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb04aaac550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_all(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot one hour of a given day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb000e59668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_hour(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### one plot per day, overlayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KCsQyVvpTJsLVwzB4Ju96mRBg5dX7ydsNokr3qi0WwVlMlKtlQkREZEgpEMtY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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7faf76360da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_per_day_overlay(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## distribution of numeric values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sql_prepare = ','.join([create_base_percentile('power_out', 'kwh'),\n",
    "                        create_number_convert(),\n",
    "                        create_normalized()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conn = connect()\n",
    "df = pd.read_sql(create_normed(sql_prepare), con=conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_day</th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>660</td>\n",
       "      <td>0.337179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>265</td>\n",
       "      <td>0.130047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>665</td>\n",
       "      <td>0.339801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>1670</td>\n",
       "      <td>0.866807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>146</td>\n",
       "      <td>0.067646</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  event_day  event_hour  raw_value  normed_value\n",
       "0  20170904           0        660      0.337179\n",
       "1  20170904           0        265      0.130047\n",
       "2  20170904           0        665      0.339801\n",
       "3  20170904           0       1670      0.866807\n",
       "4  20170904           0        146      0.067646"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>0.021500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.2</th>\n",
       "      <td>6.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.045621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>0.074463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.4</th>\n",
       "      <td>11.0</td>\n",
       "      <td>217.0</td>\n",
       "      <td>0.104877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.5</th>\n",
       "      <td>13.0</td>\n",
       "      <td>255.0</td>\n",
       "      <td>0.124803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.6</th>\n",
       "      <td>15.0</td>\n",
       "      <td>255.0</td>\n",
       "      <td>0.124803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.7</th>\n",
       "      <td>17.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>0.143157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.8</th>\n",
       "      <td>19.0</td>\n",
       "      <td>420.0</td>\n",
       "      <td>0.211327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.9</th>\n",
       "      <td>21.0</td>\n",
       "      <td>643.0</td>\n",
       "      <td>0.328264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>23.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     event_hour  raw_value  normed_value\n",
       "0.0         0.0       17.0      0.000000\n",
       "0.1         3.0       58.0      0.021500\n",
       "0.2         6.0      104.0      0.045621\n",
       "0.3         9.0      159.0      0.074463\n",
       "0.4        11.0      217.0      0.104877\n",
       "0.5        13.0      255.0      0.124803\n",
       "0.6        15.0      255.0      0.124803\n",
       "0.7        17.0      290.0      0.143157\n",
       "0.8        19.0      420.0      0.211327\n",
       "0.9        21.0      643.0      0.328264\n",
       "1.0        23.0     1924.0      1.000000"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.quantile(np.linspace(0.0, 1.0, num=11))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot all data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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PV0VFhWbNmjVkHTscjj4XHh1KJvoAAPTPaU+1JSUl6Stf+YoOHz486M4mTZoUO70ViUQ0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb0416c5748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_all(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot one hour of a given day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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HDwfgzjvvpKSkhD59+tDY2EhSUhKNjY0kJCQAZ2YYbrfbt73b7cZqtWK1Wtm9e7dv3OPx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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb041718ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_hour(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### one plot per day, overlayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mhxgAADSDQIyWlrqQV4hdfmE6ELu0YU+oz/qJbaGqkBZkopQpEwAAoCkEYrQ0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\nrBDEAeEgSS2wc3WEFmMVVtH0iNqRQ2S3nKRx/CFSozOkJ84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SwiaLTQaheusoiqIoyoem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\nS51KuTBPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7faf76a17588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_per_day_overlay(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## distribution of time values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sql_prepare = ','.join([create_base_percentile('power_out', 'first_on_at'),\n",
    "                        create_time_convert(),\n",
    "                        create_normalized()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conn = connect()\n",
    "df = pd.read_sql(create_normed(sql_prepare), con=conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_day</th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20170927</td>\n",
       "      <td>5</td>\n",
       "      <td>1506488972</td>\n",
       "      <td>0.000030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20170927</td>\n",
       "      <td>5</td>\n",
       "      <td>1506489026</td>\n",
       "      <td>0.000101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20170927</td>\n",
       "      <td>5</td>\n",
       "      <td>1506488955</td>\n",
       "      <td>0.000008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20170927</td>\n",
       "      <td>5</td>\n",
       "      <td>1506488993</td>\n",
       "      <td>0.000058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20170927</td>\n",
       "      <td>5</td>\n",
       "      <td>1506489017</td>\n",
       "      <td>0.000090</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  event_day  event_hour   raw_value  normed_value\n",
       "0  20170927           5  1506488972      0.000030\n",
       "1  20170927           5  1506489026      0.000101\n",
       "2  20170927           5  1506488955      0.000008\n",
       "3  20170927           5  1506488993      0.000058\n",
       "4  20170927           5  1506489017      0.000090"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.506489e+09</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.506533e+09</td>\n",
       "      <td>0.057578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.2</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.506599e+09</td>\n",
       "      <td>0.145347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>1.506634e+09</td>\n",
       "      <td>0.190697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.4</th>\n",
       "      <td>11.0</td>\n",
       "      <td>1.506678e+09</td>\n",
       "      <td>0.249018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.5</th>\n",
       "      <td>14.0</td>\n",
       "      <td>1.506717e+09</td>\n",
       "      <td>0.300982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.6</th>\n",
       "      <td>16.0</td>\n",
       "      <td>1.506773e+09</td>\n",
       "      <td>0.374089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.7</th>\n",
       "      <td>17.0</td>\n",
       "      <td>1.506824e+09</td>\n",
       "      <td>0.441462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.8</th>\n",
       "      <td>19.0</td>\n",
       "      <td>1.506897e+09</td>\n",
       "      <td>0.537868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.9</th>\n",
       "      <td>21.0</td>\n",
       "      <td>1.507006e+09</td>\n",
       "      <td>0.681283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>23.0</td>\n",
       "      <td>1.507248e+09</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     event_hour     raw_value  normed_value\n",
       "0.0         0.0  1.506489e+09      0.000000\n",
       "0.1         3.0  1.506533e+09      0.057578\n",
       "0.2         6.0  1.506599e+09      0.145347\n",
       "0.3         9.0  1.506634e+09      0.190697\n",
       "0.4        11.0  1.506678e+09      0.249018\n",
       "0.5        14.0  1.506717e+09      0.300982\n",
       "0.6        16.0  1.506773e+09      0.374089\n",
       "0.7        17.0  1.506824e+09      0.441462\n",
       "0.8        19.0  1.506897e+09      0.537868\n",
       "0.9        21.0  1.507006e+09      0.681283\n",
       "1.0        23.0  1.507248e+09      1.000000"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.quantile(np.linspace(0.0, 1.0, num=11))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot all data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kEwYGBkbcJzMzk5/97GdXjE+cOJG9e/deMW4YBtu2bRvyWCUlJZFw+bw5c+Zw6NChqGuI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\niIhYTuEiIiKW+39CLHczLU4kEwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb00374b278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_all(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot one hour of a given day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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c9PX10d3dzfDhw3E6nXi93sC+DMMIbCMD3+lcAtPlL5HQCepuqMbGRpYvX86ll17K+PHj\nWbp0KY2NjVx44YVceOGF/W7z1Vdf0dXVBcA333zDO++8w9ixY7niiiuora0FoKqqKvAZGZmZmVRV\nVQFQW1sbOJvJzMykpqaG3t5edu/eTWtrK5dffvlp/+AiIhK8oM4sDhw4wFdffUViYiJwtAgOHDhw\nwm18Ph+LFy/G7/djmiZXX301V111FRdffDH33HMPpaWljB8/noKCAgA8Hg+LFi3C7XYTHx/Pk08+\nCcC4ceOYMWMGM2fOJCoqimXLlulOKBGREAuqLG666SauvfZarrrqKuDomcbtt99+wm0uvfRSqqur\njxtPSUnpd5mQIUOGBN6L8X3z589n/vz5wUQVEREbBFUWRUVF/PjHP+aDDz4IPL7kkktsDSYiIpEj\n6FVnR48ejd/v57LLLrMzj4iIRKCgJ7hzc3O58847Afjoo4/49a9/bWswERGJHEGdWTz99NNUVlYy\nb948ACZOnMgXX3xhazCRSKZbfmWwCXohwaSkpGMex8TEnPEwIiISmYI6sxg2bBj79u0LvIv7vffe\nIzY21tZgIiLhpLPHYwVVFvfddx/z5s2jra2NuXPn0trayrp16+zOJiIiESKospg0aRIvvvgiH374\nIQCTJ08mLi7O1mAicvbQX+kDn2VZ+P1+PB4PVVVVTJ8+PRSZREQkwlhOcEdFRXH++efT09MTijwi\nIhKBgroM9cMf/pCioiJycnI4//zzA+NFRUW2BRMRkcgRVFn4/X7GjRunz6MQERmkTlgWa9asYfHi\nxTz22GO8/fbbpKenhyqXiIhEkBPOWbz33nuBr9euXWt7GBERiUwnLAvTNPv9WkREBpcTXobq7e3l\n008/xTTNY77+1sUXX2x7QBERCb8TlsU333wTWDwQOOZrh8NBfX29fclERCRinLAsGhoaQpVDREQi\nWNCrzoqIyOAV9CfliUj4aY0lCRedWYiIiCWVhYiIWNJlKJFBQpew5HTozEJERCzpzEIGpdP5K1tk\nMLLtzGLPnj3MnTuXmTNnkpubS0VFBQAdHR0UFxeTnZ1NcXExnZ2dwNHlRFatWoXb7SYvL4+dO3cG\n9lVVVUV2djbZ2dlUVVXZFVlERP4H28oiKiqKxYsX89prr/HKK6/wxz/+kV27dlFeXk5aWhp1dXWk\npaVRXl4OQFNTE62trdTV1bFy5UpWrFgBHC2XsrIyNm7cyKZNmygrKwsUjIiIhIZtl6GSk5NJTk4G\n4IILLuCiiy7CMAzq6+t56aWXAMjPz2fu3LksWrSI+vp68vPzcTgcpKam0tXVhc/n4/333yc9PZ2E\nhAQA0tPT2bp1K7NmzbIr+mnRJKKInI1CMsHd1tbGP/7xDyZNmkR7e3ugRJKSkmhvbwfAMAxcLldg\nG5fLhWEYx407nU4MwwhFbBER+X9sn+A+ePAgd911F7/5zW+44IILjvmew+HA4XDYHeGkafJzYNB/\nJ5HQsfXM4vDhw9x1113k5eWRnZ0NwIgRI/D5fAD4fD4SExOBo2cMXq83sK3X68XpdB43bhgGTqfT\nztgiIvI9tpWFaZo8/PDDXHTRRRQXFwfGMzMzqa6uBqC6upqsrKxjxk3TpKWlhdjYWJKTk8nIyKC5\nuZnOzk46Oztpbm4mIyPDrtgiItIP2y5D/e1vf2PLli386Ec/4tprrwXg3nvv5bbbbqOkpITKykpG\njRpFaWkpANOnT6exsRG3283QoUNZvXo1AAkJCSxYsACPxwPAwoULA5PdEhl0OUjspJtGIoNtZTFl\nyhT+9a9/9fu9b99z8V0Oh4Ply5f3+3yPxxMoCxERCT0t9yEiIpZUFiIiYkllISIillQWIiJiSavO\nioicYWfjHYI6sxAREUsqCxERsaSyEBERSyoLERGxpLIQERFLKgsREbGkshAREUsqCxERsaQ35Z0l\nzsY3AYlI5FBZiMhZS39EnTkqC5EQ0y8wGYhUFiJiSQUnmuAWERFLKgsREbGkshAREUsqCxERsaSy\nEBERS7obKoLojhMRiVQ6sxAREUu2lcVDDz1EWloas2bNCox1dHRQXFxMdnY2xcXFdHZ2AmCaJqtW\nrcLtdpOXl8fOnTsD21RVVZGdnU12djZVVVV2xRURkROwrSyuu+46nn/++WPGysvLSUtLo66ujrS0\nNMrLywFoamqitbWVuro6Vq5cyYoVK4Cj5VJWVsbGjRvZtGkTZWVlgYIREZHQsa0sfvKTnxAfH3/M\nWH19Pfn5+QDk5+fz5ptvHjPucDhITU2lq6sLn89Hc3Mz6enpJCQkEB8fT3p6Olu3brUrsoiI/A8h\nnbNob28nOTkZgKSkJNrb2wEwDAOXyxV4nsvlwjCM48adTieGYYQysoiIEMYJbofDgcPhCNfLi4jI\nSQhpWYwYMQKfzweAz+cjMTEROHrG4PV6A8/zer04nc7jxg3DwOl0hjKyiIgQ4rLIzMykuroagOrq\narKyso4ZN02TlpYWYmNjSU5OJiMjg+bmZjo7O+ns7KS5uZmMjIxQRhYREWx8U969997L+++/z/79\n+5k2bRp33nknt912GyUlJVRWVjJq1ChKS0sBmD59Oo2NjbjdboYOHcrq1asBSEhIYMGCBXg8HgAW\nLlxIQkKCXZFFROR/sK0snnjiiX7HKyoqjhtzOBwsX7683+d7PJ5AWYiISHjoHdwiImJJZSEiIpZU\nFiIiYkllISIillQWIiJiSWUhIiKWVBYiImJJZSEiIpZUFiIiYkllISIillQWIiJiSWUhIiKWVBYi\nImJJZSEiIpZUFiIiYkllISIillQWIiJiSWUhIiKWVBYiImJJZSEiIpZUFiIiYkllISIillQWIiJi\nSWUhIiKWVBYiImJpwJRFU1MTOTk5uN1uysvLwx1HRGRQGRBl4ff7eeSRR3j++eepqanh1VdfZdeu\nXeGOJSIyaESHO0Awtm/fzpgxY0hJSQEgNzeX+vp6Lr744uOe6/f7AfB6vaf8eocP+k55WxGRcGpr\nazul7b79nfnt79DvGxBlYRgGLpcr8NjpdLJ9+/Z+n7t3714AioqKQpJNRCSSZNWe3vZ79+5lzJgx\nx40PiLI4GRMmTGDDhg0kJSURFRUV7jgiIgOC3+9n7969TJgwod/vD4iycDqdx1xWMgwDp9PZ73PP\nO+88pkyZEqpoIiJnjf7OKL41ICa4J06cSGtrK7t376a3t5eamhoyMzPDHUtEZNAYEGcW0dHRLFu2\njFtvvRW/38/111/PuHHjwh1LRGTQcJimaYY7hIiIRLYBcRlKRETCS2UhIiKWBm1ZWC0f0tvbS0lJ\nCW63m4KCglN+o8tAZnWM1q9fz8yZM8nLy+Omm27iyy+/DEPK8Ap2GZra2louueQSPvrooxCmiwzB\nHKPXXnuNmTNnkpuby3333RfihOFndYz++9//MnfuXPLz88nLy6OxsTH0Ic1BqK+vz8zKyjK/+OIL\ns6enx8zLyzM/+eSTY57zhz/8wVy6dKlpmqb56quvmnfffXc4ooZNMMdo27Zt5qFDh0zTNM0NGzbo\nGPVzjEzTNLu7u83CwkKzoKDA3L59exiShk8wx+jzzz83r732WrOjo8M0TdPct29fOKKGTTDHaMmS\nJeaGDRtM0zTNTz75xLzqqqtCnnNQnll8d/mQmJiYwPIh39XQ0MDs2bMByMnJYdu2bZiD6F6AYI7R\n1KlTGTp0KACpqamntcTKQBTMMQJ46qmnmDdvHkOGDAlDyvAK5hht3LiRoqIi4uPjARgxYkQ4ooZN\nMMfI4XBw4MABALq7u0lOTg55zkFZFv0tH2IYxnHPGTlyJHD01t3Y2Fj2798f0pzhFMwx+q7Kykqm\nTZsWimgRI5hjtHPnTrxeLz/72c9CnC4yBHOMWltb+fzzz7nxxhv5xS9+QVNTU6hjhlUwx+iOO+7g\nz3/+M9OmTeO2225jyZIloY45OMtCzqwtW7awY8cObr311nBHiShHjhxhzZo1PPjgg+GOEtH8fj//\n+c9/eOmll3j88cdZunQpXV1d4Y4VUWpqapg9ezZNTU2Ul5fzwAMPcOTIkZBmGJRlEczyIU6nkz17\n9gDQ19dHd3c3w4cPD2nOcAp2iZV33nmHZ599lnXr1hETExPKiGFndYwOHjzIv//9b375y1+SmZlJ\nS0sL8+fPH1ST3MH+v5aZmcm5555LSkoKP/jBD2htbQ1x0vAJ5hhVVlYyY8YMACZPnkxPT0/Ir3QM\nyrIIZvmQzMxMqqqqgKN3skydOhWHwxGOuGERzDH6+OOPWbZsGevWrRt015nB+hjFxsby3nvv0dDQ\nQENDA6mpqaxbt46JEyeGMXVoBfPv6Oc//znvv/8+AF999RWtra2BjyMYDII5RiNHjmTbtm0AfPrp\np/T09JCYmBjSnANiuY8z7X8tH/LUU08xYcIEsrKy8Hg8LFq0CLfbTXx8PE8++WS4Y4dUMMfo97//\nPYcOHeLuu+8Gjv6DfvbZZ8OcPHSCOUaDXTDH6Morr+Ttt99m5syZREVF8cADDwyqs/hgjtHixYtZ\nsmQJL7zwAg6HgzVr1oT8j1ct9yEiIpYG5WUoERE5OSoLERGxpLIQERFLKgsREbGkshAREUsqCxER\nsaSyEBERS/8HFcTEax02rx8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb00372eac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_hour(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### one plot per day, overlayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZqBADAABsj5aJALmuK9eVAir+ViVOhRgAAGBbBOIAOeXRv5deqlsryOqwRIUYAABgJwTi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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7faf903159e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_per_day_overlay(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## distribution of bool values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sql_prepare = ','.join([create_base('power_out', 'generating'),\n",
    "                        create_bool_convert(),\n",
    "                        create_normalized()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conn = connect()\n",
    "df = pd.read_sql(create_normed(sql_prepare), con=conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_day</th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20170904</td>\n",
       "      <td>0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  event_day  event_hour  raw_value  normed_value\n",
       "0  20170904           0       0.25           0.0\n",
       "1  20170904           0       0.25           0.0\n",
       "2  20170904           0       0.25           0.0\n",
       "3  20170904           0       0.25           0.0\n",
       "4  20170904           0       0.25           0.0"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.2</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.4</th>\n",
       "      <td>11.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.5</th>\n",
       "      <td>13.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.6</th>\n",
       "      <td>15.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.7</th>\n",
       "      <td>17.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.8</th>\n",
       "      <td>19.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.9</th>\n",
       "      <td>21.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>23.0</td>\n",
       "      <td>0.75</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     event_hour  raw_value  normed_value\n",
       "0.0         0.0       0.25           0.0\n",
       "0.1         3.0       0.25           0.0\n",
       "0.2         6.0       0.25           0.0\n",
       "0.3         9.0       0.25           0.0\n",
       "0.4        11.0       0.25           0.0\n",
       "0.5        13.0       0.25           0.0\n",
       "0.6        15.0       0.25           0.0\n",
       "0.7        17.0       0.25           0.0\n",
       "0.8        19.0       0.25           0.0\n",
       "0.9        21.0       0.25           0.0\n",
       "1.0        23.0       0.75           1.0"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.quantile(np.linspace(0.0, 1.0, num=11))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot all data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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jIiIyOyR1VZvP5yM/P5+f/exn/PnPf+ab3/wmN9544wXn/OpXv6Kjo4NgMMiZM2cYGhri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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7faf95921ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_all(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot one hour of a given day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7faf78206518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_hour(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### one plot per day, overlayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JAACAzhGIPXTiprrse8McYgAAgC4QiD3UyL1h+9g1w6Y6AACAbhCIPWTtvzSHmEQMAADQ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7faf76fda1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_per_day_overlay(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## distribution of \"unique\" values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conn = connect()\n",
    "\n",
    "sql_prepare = ','.join([create_base('power_out', 'mill_signature'),\n",
    "                        create_string_convert(-8),\n",
    "                        create_normalized()])\n",
    "\n",
    "df = pd.read_sql(create_normed(sql_prepare), con=conn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>9.694862e+10</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>7.047652e+15</td>\n",
       "      <td>0.097805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.2</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.432690e+16</td>\n",
       "      <td>0.198825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>2.161891e+16</td>\n",
       "      <td>0.300022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.4</th>\n",
       "      <td>11.0</td>\n",
       "      <td>2.863432e+16</td>\n",
       "      <td>0.397380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.5</th>\n",
       "      <td>13.0</td>\n",
       "      <td>3.584268e+16</td>\n",
       "      <td>0.497417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.6</th>\n",
       "      <td>15.0</td>\n",
       "      <td>4.288708e+16</td>\n",
       "      <td>0.595178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.7</th>\n",
       "      <td>17.0</td>\n",
       "      <td>5.002170e+16</td>\n",
       "      <td>0.694191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.8</th>\n",
       "      <td>19.0</td>\n",
       "      <td>5.747325e+16</td>\n",
       "      <td>0.797602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.9</th>\n",
       "      <td>21.0</td>\n",
       "      <td>6.464614e+16</td>\n",
       "      <td>0.897146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>23.0</td>\n",
       "      <td>7.205755e+16</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     event_hour     raw_value  normed_value\n",
       "0.0         0.0  9.694862e+10      0.000000\n",
       "0.1         3.0  7.047652e+15      0.097805\n",
       "0.2         6.0  1.432690e+16      0.198825\n",
       "0.3         9.0  2.161891e+16      0.300022\n",
       "0.4        11.0  2.863432e+16      0.397380\n",
       "0.5        13.0  3.584268e+16      0.497417\n",
       "0.6        15.0  4.288708e+16      0.595178\n",
       "0.7        17.0  5.002170e+16      0.694191\n",
       "0.8        19.0  5.747325e+16      0.797602\n",
       "0.9        21.0  6.464614e+16      0.897146\n",
       "1.0        23.0  7.205755e+16      1.000000"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.quantile(np.linspace(0.0, 1.0, num=11))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot all data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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R0ylcRETEdAoXERExncJFRERMp3ARERHTKVxERMR0QxIudrud7OxscnJyWLBg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\nmE7hIiIiplO4iIiI6RQuIiJiuv8H9mT76geqKYcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ab8073f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_all(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot one hour of a given day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ab7f57e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_hour(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### one plot per day, overlayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xg9+iNLyZaOcNcvF+vvNOO//zV7oe8Lv5cKpLuoTmEt/xeW2lyqGt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NXL+7BbCUJD14mOTBIanPY1g10Bo5bBqKV9TnKigtmI010eorM8RndpFeCS2HTKb7R0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u7IVWLz46YUJdSJmwVYqrs3M4WiGEEOLyMdOmsC4LnSZwGlen6PY+6FBMN+sIJc6XBMSX1E+3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\nh6sbPomq+Ldh7fNdACx7n0droZV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ddx/3umma3HjjjaxcuZKrr756WHoei5Pfh3vvvZfV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\nEAshhBBCiAnt/wfZ4Zr/hQc5dQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b16807cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_per_day_overlay(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## distribution of categorial values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "conn = connect()\n",
    "\n",
    "sql_prepare = ','.join([create_base('power_out', 'country'),\n",
    "                        create_string_convert(),\n",
    "                        create_normalized()])\n",
    "\n",
    "df = pd.read_sql(create_normed(sql_prepare), con=conn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_hour</th>\n",
       "      <th>raw_value</th>\n",
       "      <th>normed_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.00</th>\n",
       "      <td>0.0</td>\n",
       "      <td>5.184839e+13</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.05</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.977339e+15</td>\n",
       "      <td>0.068414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.10</th>\n",
       "      <td>3.0</td>\n",
       "      <td>7.269088e+15</td>\n",
       "      <td>0.100245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.15</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1.036419e+16</td>\n",
       "      <td>0.143235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.20</th>\n",
       "      <td>6.0</td>\n",
       "      <td>1.641676e+16</td>\n",
       "      <td>0.227304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.25</th>\n",
       "      <td>7.0</td>\n",
       "      <td>1.760655e+16</td>\n",
       "      <td>0.243829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.30</th>\n",
       "      <td>9.0</td>\n",
       "      <td>2.574811e+16</td>\n",
       "      <td>0.356913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.35</th>\n",
       "      <td>10.0</td>\n",
       "      <td>3.295785e+16</td>\n",
       "      <td>0.457054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.40</th>\n",
       "      <td>11.0</td>\n",
       "      <td>3.295785e+16</td>\n",
       "      <td>0.457054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.45</th>\n",
       "      <td>12.0</td>\n",
       "      <td>3.295785e+16</td>\n",
       "      <td>0.457054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.50</th>\n",
       "      <td>13.0</td>\n",
       "      <td>3.295785e+16</td>\n",
       "      <td>0.457054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.55</th>\n",
       "      <td>14.0</td>\n",
       "      <td>3.295785e+16</td>\n",
       "      <td>0.457054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.60</th>\n",
       "      <td>15.0</td>\n",
       "      <td>3.295785e+16</td>\n",
       "      <td>0.457054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.65</th>\n",
       "      <td>16.0</td>\n",
       "      <td>3.428236e+16</td>\n",
       "      <td>0.475451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.70</th>\n",
       "      <td>17.0</td>\n",
       "      <td>3.428236e+16</td>\n",
       "      <td>0.475451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.75</th>\n",
       "      <td>18.0</td>\n",
       "      <td>4.376616e+16</td>\n",
       "      <td>0.607178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.80</th>\n",
       "      <td>19.0</td>\n",
       "      <td>5.963416e+16</td>\n",
       "      <td>0.827580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.85</th>\n",
       "      <td>20.0</td>\n",
       "      <td>6.813966e+16</td>\n",
       "      <td>0.945719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.90</th>\n",
       "      <td>21.0</td>\n",
       "      <td>7.014065e+16</td>\n",
       "      <td>0.973512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.95</th>\n",
       "      <td>22.0</td>\n",
       "      <td>7.014065e+16</td>\n",
       "      <td>0.973512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.00</th>\n",
       "      <td>23.0</td>\n",
       "      <td>7.204767e+16</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      event_hour     raw_value  normed_value\n",
       "0.00         0.0  5.184839e+13      0.000000\n",
       "0.05         1.0  4.977339e+15      0.068414\n",
       "0.10         3.0  7.269088e+15      0.100245\n",
       "0.15         4.0  1.036419e+16      0.143235\n",
       "0.20         6.0  1.641676e+16      0.227304\n",
       "0.25         7.0  1.760655e+16      0.243829\n",
       "0.30         9.0  2.574811e+16      0.356913\n",
       "0.35        10.0  3.295785e+16      0.457054\n",
       "0.40        11.0  3.295785e+16      0.457054\n",
       "0.45        12.0  3.295785e+16      0.457054\n",
       "0.50        13.0  3.295785e+16      0.457054\n",
       "0.55        14.0  3.295785e+16      0.457054\n",
       "0.60        15.0  3.295785e+16      0.457054\n",
       "0.65        16.0  3.428236e+16      0.475451\n",
       "0.70        17.0  3.428236e+16      0.475451\n",
       "0.75        18.0  4.376616e+16      0.607178\n",
       "0.80        19.0  5.963416e+16      0.827580\n",
       "0.85        20.0  6.813966e+16      0.945719\n",
       "0.90        21.0  7.014065e+16      0.973512\n",
       "0.95        22.0  7.014065e+16      0.973512\n",
       "1.00        23.0  7.204767e+16      1.000000"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.quantile(np.linspace(0.0, 1.0, num=21))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot all data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GSE9PN44ePWoYhmEcPnw4EKV2GV/OecmSJcbWrVsNwzCML7/80njggQcCUWqX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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b630f5198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_all(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### plot one hour of a given day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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bLe87XPss4XPLA7WRLkGC8FW+Bz77zvzsO/TzhnWIGIaBw+EIvLbb7bS2tl50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\nRMQyhYiIiFimEBEREcsUIiIiYtn/A57za9AHy0G/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b16836550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_hour(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### one plot per day, overlayed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ETjKVTIiI7EP0bjKm2bqCUFTveNu6q+BqHYp+g5baromInDgKxCIi+xC8ZdI9Ihneqesa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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b168079e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_one_per_day_overlay(df)"
   ]
  }
 ],
 "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": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}