{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id !== undefined) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var element_id = msg.content.text.trim();\n",
       "            Bokeh.index[element_id].model.document.clear();\n",
       "            delete Bokeh.index[element_id];\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(`.${CLASS_NAME.split(' ')[0]}`);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[0].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[0].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[0]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        root._bokeh_is_loading--;\n",
       "        if (root._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.10.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n    }\n    finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.info(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(js_urls, callback) {\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = js_urls.length;\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var s = document.createElement('script');\n      s.src = url;\n      s.async = false;\n      s.onreadystatechange = s.onload = function() {\n        root._bokeh_is_loading--;\n        if (root._bokeh_is_loading === 0) {\n          console.log(\"Bokeh: all BokehJS libraries loaded\");\n          run_callbacks()\n        }\n      };\n      s.onerror = function() {\n        console.warn(\"failed to load library \" + url);\n      };\n      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.getElementsByTagName(\"head\")[0].appendChild(s);\n    }\n  };var element = document.getElementById(\"6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.12.10.min.js\"];\n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    \n    function(Bokeh) {\n      \n    },\n    function(Bokeh) {\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.10.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.10.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.12.10.min.css\");\n    }\n  ];\n\n  function run_inline_js() {\n    \n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"6f2a6a53-9ab3-470f-8a1d-39ced4bbc24a\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(js_urls, function() {\n      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "import pandas_datareader as pdr\n",
    "import os\n",
    "import numpy as np\n",
    "from bokeh.io import output_notebook\n",
    "from bokeh.plotting import figure, show\n",
    "from bokeh.palettes import Spectral8 # 色を考えなくても良い　地味に素敵 https://bokeh.pydata.org/en/latest/docs/reference/palettes.html\n",
    "from datetime import datetime\n",
    "from datetime import timedelta\n",
    "%matplotlib inline\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "start = datetime(2008, 9, 11)\n",
    "end = datetime(2018, 2, 9)\n",
    "mstar_spx = web.DataReader('SPX', 'morningstar', start, end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "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></th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SPX</th>\n",
       "      <th>2008-09-11</th>\n",
       "      <td>1249.0486</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-12</th>\n",
       "      <td>1251.7009</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-15</th>\n",
       "      <td>1192.7021</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-16</th>\n",
       "      <td>1213.5862</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-17</th>\n",
       "      <td>1156.3861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Close  High  Low  Open  Volume\n",
       "Symbol Date                                          \n",
       "SPX    2008-09-11  1249.0486   NaN  NaN   NaN       0\n",
       "       2008-09-12  1251.7009   NaN  NaN   NaN       0\n",
       "       2008-09-15  1192.7021   NaN  NaN   NaN       0\n",
       "       2008-09-16  1213.5862   NaN  NaN   NaN       0\n",
       "       2008-09-17  1156.3861   NaN  NaN   NaN       0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mstar_spx.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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></th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SPX</th>\n",
       "      <th>2018-02-05</th>\n",
       "      <td>2648.9391</td>\n",
       "      <td>2763.39</td>\n",
       "      <td>2638.17</td>\n",
       "      <td>2741.06</td>\n",
       "      <td>3205516825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-06</th>\n",
       "      <td>2695.1442</td>\n",
       "      <td>2701.04</td>\n",
       "      <td>2593.07</td>\n",
       "      <td>2614.78</td>\n",
       "      <td>3667048182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-07</th>\n",
       "      <td>2681.6601</td>\n",
       "      <td>2727.67</td>\n",
       "      <td>2681.33</td>\n",
       "      <td>2690.95</td>\n",
       "      <td>2559829157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-08</th>\n",
       "      <td>2580.9995</td>\n",
       "      <td>2685.27</td>\n",
       "      <td>2580.56</td>\n",
       "      <td>2685.01</td>\n",
       "      <td>2910724979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-09</th>\n",
       "      <td>2619.5456</td>\n",
       "      <td>2638.67</td>\n",
       "      <td>2532.69</td>\n",
       "      <td>2601.78</td>\n",
       "      <td>3437391201</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Close     High      Low     Open      Volume\n",
       "Symbol Date                                                        \n",
       "SPX    2018-02-05  2648.9391  2763.39  2638.17  2741.06  3205516825\n",
       "       2018-02-06  2695.1442  2701.04  2593.07  2614.78  3667048182\n",
       "       2018-02-07  2681.6601  2727.67  2681.33  2690.95  2559829157\n",
       "       2018-02-08  2580.9995  2685.27  2580.56  2685.01  2910724979\n",
       "       2018-02-09  2619.5456  2638.67  2532.69  2601.78  3437391201"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mstar_spx.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mstar_spx2 = web.DataReader('SPX', 'morningstar', '1900-01-01')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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></th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">SPX</th>\n",
       "      <th>1928-01-03</th>\n",
       "      <td>17.76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-04</th>\n",
       "      <td>17.72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-05</th>\n",
       "      <td>17.55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-06</th>\n",
       "      <td>17.66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1928-01-09</th>\n",
       "      <td>17.50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Close  High  Low  Open  Volume\n",
       "Symbol Date                                      \n",
       "SPX    1928-01-03  17.76   NaN  NaN   NaN       0\n",
       "       1928-01-04  17.72   NaN  NaN   NaN       0\n",
       "       1928-01-05  17.55   NaN  NaN   NaN       0\n",
       "       1928-01-06  17.66   NaN  NaN   NaN       0\n",
       "       1928-01-09  17.50   NaN  NaN   NaN       0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mstar_spx2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 株価以外のデータ・ソース\n",
    "* Enigma / https://public.enigma.com/    \n",
    "API KEYがいるみたいなのでパス   \n",
    "* FRED / https://fred.stlouisfed.org/   \n",
    "セントルイス連銀が出しているデータ\n",
    "* WORLD BANK / https://data.worldbank.org/\n",
    "* OECD / http://stats.oecd.org/\n",
    "* Eurostats / http://ec.europa.eu/eurostat/   \n",
    "   \n",
    "色々とあります。データありすぎ問題・・・"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# FRED のデータを取得してみる。注目されている米国金利 FF、２年、１０年、３０年\n",
    "start_f = datetime(1980,1,1)\n",
    "end_f = datetime(2018,2,9)\n",
    "# FF https://fred.stlouisfed.org/series/FF ２年 https://fred.stlouisfed.org/series/GS2\n",
    "# 10年　https://fred.stlouisfed.org/series/DGS10 30年 https://fred.stlouisfed.org/series/DGS30\n",
    "# Dがつくとdailyのよう。つけないとmonthly\n",
    "f_ff = web.DataReader('FF', 'fred', start_f, end_f) \n",
    "f_2 = web.DataReader('GS2', 'fred', start_f, end_f)\n",
    "f_10 = web.DataReader('GS10', 'fred', start_f, end_f)\n",
    "f_30 = web.DataReader('GS30', 'fred', start_f, end_f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1124ba748>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DU/ZdDuOzuz3esOrVCCFELCRFj33FrCwuWlY0LMfe4/EHdke4gT2Qiplcj726tRetYW7+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\nhEgx/x87UkhL25DkCAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111a9bf98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_2.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x111aeda58>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bKoQwSWAfB8k2Cw/cuJznv7KKixfnebb/1xULsFkGr/w4XrwnDE3PtmOzxJKR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\ntZE9p+LmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112b36518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_10.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x112c4ac88>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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W/v2cWTx68yrf9lUz0khx2/nLe8fGZcxCTCUS2CPo3qsW8/mzZvpm5UUZ8Zw7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\nDwvnAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112c5ec18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_30.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11242d128>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7Ai2nz8iyV5WrPFbL2xsORryOs0xqIngCVrKLNnOsgtV7jgPw7GId+qM6J00O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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111bc7fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_ff.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 負債の状況 自動車ローン https://fred.stlouisfed.org/series/MVLOAS\n",
    "f_car = web.DataReader('MVLOAS', 'fred', start_f, end_f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1127e3588>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kcHoCT320gQMHq3hpwiCSW8UGO6JISKj3kYJz7iHgIQDvkcJ9zrlrzexPwHjg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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11280b320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_car.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1129de6d8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9GWA6sMAqXwBcbS1PBxYZY6qMMfuBLGCkU6NWys01jJ/31f555QZa1EcvIr4i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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112a0e908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 不動産ローン\n",
    "f_re = web.DataReader('RHEACBW027SBOG', 'fred', start_f, end_f)\n",
    "f_re.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11310e9e8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ceWml3OpAQSmfbD/CkD7dWXrbZLp3a93o7X49g7g0sQ+/umwoGw8W8fq3Wa4N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\nSiml0GSglFIK+P+aeE2A/rD0vAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11312f9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 全産業ローン\n",
    "f_loan = web.DataReader('BUSLOANS', 'fred', start_f, end_f)\n",
    "f_loan.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1133ca198>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PqWqBqhZkZ2f35OMaE5Ye+/N2LvrPZQA2OjFhqServAR4BvhEVR/1K8/xq3Y9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\nsIRijDEmKCyhGGOMCQpLKMYYY4Li/wMwjliEYGt73wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d0e14e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# FED TOTAL ASSET \n",
    "f_fed_asset = web.DataReader('WALCL', 'fred', start_f, end_f)\n",
    "f_fed_asset.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1132a3cf8>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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rglg+3JVJQk45yfmVjLHGR8YN9cPD1YX//HAvLesxL540lJvOHsnNr2/nidWH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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1139500f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f_fed_asset['2014':].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1139add68>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Szx2jYojvGqIPZnIzR3JKuOG1DVTY7Lx313Cu6KVPXXVnOspLtQhbU/K4453N\nvPb1IYrLbWesf+e7Izy/ch9VVYaySjuz5idQZeDuy2P57Id0bnhtA3O/OuiCyNXZlFXaScoq4p75\nW7FXVfHxL0dpMmkGtIei3MqnO4+zZFsqb98xrM7eQmr+SSKD/ck/Wcm972+jsNTGuv3ZrN6byfPX\nX0JwgDfBAT4s3Z7GH5clAnDiZCX2KsO+jCLeuWMYY/tE8PPLu/GHxT/wn40pzB7bHV8vz6b4qOoc\nTlbYmPbSeg5nl+AhMO+u4fTs0NbVYal60ISi3Mpb3x5mZ2oB+zOL6NOx3Tm3+/ZgNre9tZlfXNGN\n7cdOkF9SyZLZoziSU8L9C7Yz5oV1BPh48vjUOJ5atocRsaH06diWeRtSALj90q6M7RMBQId2ftx5\nWQx3vLOFVYmZTBvYuUk+qzq7Z7/Yx5GcEp6YFsfQriF6n0kzoglFuY2juSfZmVoAOJ7Ad76Esnxn\nOgCvf3MYTw9h7k2D6Nc5iH6dg2gf6MvBrGJeWZvEo0t2ER0awGs/G0pIGx9mjIoho6CMYbGhp7V3\nRc9wIoP9+TAhVRNKI7BXGXanFdDWz4tu4YFsTcnjq71Z/H5Sbzw8BHuVYVdaAe98d4RPdhznzsti\nmDk61tVhqwbShKKcbs/xAjoH+RPSxqdB9T7b5UgS7QN9WJ+Uw88v73bW7exVhq/2ZnL1gI7EhLVh\neGwoY3pHnFo/slsYI7uFMTQ6hOdX7uPRq/ueiqVbeCDdwgPPaNPDQxjXJ4Il29OoqjI66que5n2f\nzL6MIv7ykwGnlVfaq1j+w3Em9+tIgI8XHyUc4+H/7gJgzvR+fLrjOAkp+cSGtaF9Wx/+/Pk+krKK\n8fH04IHxPZk9tocrPo66SJpQ1BmMMaTkniTmAmZwLSit5CevfM9PhkSd8UvmfGz2KhZvPcagLsEM\njArio4RUPtxyjEu7h9ElNACA4ydK+XhrKllF5eSWVHD1gE7n7U3EdW7HO3cOr3cMA6KCmL8xhSO5\nJXQ/S9JRZ3p/UwoHMou5+/LY0xL1hwnHeGzJbq4ekMm/bh3CqsRMIoP96RTkx/Mr91NUZsPf25NH\nluzCXmWIbd+Gv91wCWP7RBDawD9ElPvQUV7qDAu3HGPMC+vYfCSvwXVX7E6n3FbF5iO5Dar3/qaj\nHMou4Z4ru3NFz3BKK+384eMfuPu9BMptdo7lnWTC37/m718dYP7GFHy9PLjSyaN+BkQ6bpTbnVbg\n1HZbqrzP5O8ZAAAXbUlEQVSSCg5kFgPw0dbUU+XGGOZ9n0yAjyef78rgta8P892hHCb0jeC3k3pT\nVGbDx8uD92YOZ0BkEE/+KI6Vv76C64ZGaTJp5rSHok5T/csA4IWV+1n0i5ENujdj6fbjABzKLiG/\npOKsp72O5JTQNTSANfuyyD9ZwRW9wvn7qgNc1iOMyf06YAy89rOhFJRW8NDHu/jblweoqjKU26pY\n+esr8Pf2pKTCRls/b6d85mo9IwLx9fJgV2oB0wdFOrXtlqj6D47IYH8WbD7KvvRCfj2hFyUVNg5k\nFvPcdQNZsSeDZ1fsA2BsnwhGdgtlSr+ORIb4MywmlKWzL3PlR1BOpglFnSYhJZ99GUXEdw1hc3Ie\n6w5kM7bG9YnzOX6ilI1HcrmsRxjfJeWyNSX/jCfprdidzj3/2UZs+zYcySkBIDo0gHKbnT9e0x8R\nQQSm9O8IwK60At745jA+nh5cPaATvRpx+KiXpwd9O7XjB+2h1MvmI3n4ennw558M4Lcf7mTTkTye\n+GQ3nh5C+0AfrhnUmdE92zPx719jN4aR3cIQEV67bairQ1eNRE95qdMs2HSUtn5evDVjGDFhAcxZ\nlkhZpb1edT/deRxj4P+m9cPbU3j160PMeHsz+SUVgOM6yXMr9hMV4k+VMdw8rAtjeodzNO8kc67p\nT4+IM69bPPmjfozvE0GFvapJRv0MiAxiT1oBVVWm0ffVnJXb7KxPymZIdAhX9gon4fEJ/PGafvyQ\nWsD2oyd49Oq++Hl70jnYn7k3DeL/pvXDz1vv72nptIeiTimrtPNlomP0VFCAN3Om9+f2tzfzyrpD\n/GZiL3alFvD0Z4lMiutw1hFYS7enMTg6mN4d2zIgMoitKfkAvLjmII9c1ZfnVuzjcE4Jb9w2lEn9\nOp7a5+60AoZ2DTlrTN6eHrz6s6Ek55Y0au+k2rDYUOZvTGHD4Vwu69G+0ffnaiXlNtr41u/XQEpu\nCX/6bC9bkvMI8PEi7UQpz173vyT/kyFR/GdjCu38vfnx4P+dMqz+t1YtnyYUdcq3B3MoLrcx1Ro5\ndUWvcH48OJKX1xwkv6SCDzYfRYCE5DzC2/oSEuBDSt5JyirsiMC+jCLmTO8HwK8n9GL38QKOZJfw\nn40prErMJDW/lBvjo057wp6ftyfxMaFnC+cUHy+PJkkmAJPiOhAS4M38DSktPqG8vf4If/1iHx/c\nPaLOf4Nym51b/72JgtJKJvSNIKuonDnT+zG+xuN3PT2Ej+4ZhZeH6JxorZQmFHXKZz8cJzjAm1Hd\nw06VPXNtf3alFTB/YwqT4jrwx+n9+Om/N/HAwh1n1Pfx9GDqgE6AIxld0SucrMIyvj+US0xYG56e\n3v/U3enuys/bkxuHdeHNb4+QXlBKpyB/V4d0hmN5J9l2NJ+pAzpRWGbj76v2czCzmPkzR+DjVfdZ\n7D3HC9ifUcRfV+yjwl7F40t3s/z+0Xh5nl73h9QTJOee5EcDO/HBpqOknShl/szhXN7z3KPr6rN/\n1XJpQlEApJ0oZcWeDK4dFIl3jV8sbXy9eO+u4WxJzuNHAzvj4SF8/MtRbEnOI8jfm+iwANr4epF+\nogyDISzQ97R2I9r58d3D45r641yUnw7vyutfH2bJ9jTuHeNeN9j9a20SL3y5H2Pgyz2ZbDuaT3pB\nGQDfHcqpcwBF2olSrnv1e8oqq2gf6MMDE3rxxNLdLN6ayoCoIL5KzOJX43tQYa/il//ZRtqJUr7Y\nlc73hxyDLc6XTJTShKIAeNqaPPG+cWf+Au0c7H/aMNqQNj5nnBdv19G5Q3hdKTosgEu6BPP5rvTT\nEkpJuY0AH08OZRfz+a4MZl3RDT9vT8oq7RSWVhLRzq9R49p57AR/+3I/k+I60CUkgDfXHyGirS//\nvXcUt7+1mc9/SGfzkTyGx4Sesyf43Ip9GAMf3D2Cfp2CaOfvxfsbU3h/01ECd3ix4XAuV/Rqzw+p\nBaSdKGVM73C+2J3BsJgQ5kzv36ifTzV/mlBaqApbFR7iGAp74mQF9y/YTk5xBRPjOvDr8T3ZejSf\n/p2D8Pfx5Itd6azYk8HvJ/cmKiTA1aG7hWkDOvGnz/fy+a50Ku1VDIwK5pqX1tO3UztS8krILCxn\n29F8npgWx/0fbOdY3km++u2VdGikpFJus/O7j3YS0daP52+4hLa+XgyKDmZo1xA6BfkzoW8Ei7el\nYgx8F5XD2D4RfH0gm99/tJPgAG9mj+1BTFgbPtlxnPvH9WBU9/9dH7p5WBeesv6gAHjt60MkJOcz\nslso79wxjOJy59/zo1omMab1DI+Mj483CQkJrg6j0dmrDNe/9j0FpZU8c21/nl2xn73HCxkcHcym\nI3l0D2/DoewSfjw4kt9N7s3V//yWrmEBLL5nlJ4Dt6Tmn2T0s2tPvQ8O8MZeZbDZDV6ewoxLY3h5\nbRLguHYEcNWAjvzz5sH13kdZpZ2l29P4am8m3cMDmTEqhs7BZ79m88LK/by8NunUlPu1rdyTwS/m\nbyXI35uC0kqevrY/T36ym54RbfHwEA5lFzuSYW4J6x8aR2CNkV0nTlYw/M+r8RRhdM/2rErMxNfL\ng2X3j26ywRDKvYnIVmNMfF3baQ/FjXy+K534mBAi2l7cX7nzNySz/egJfLw8uPXfm/D39uTlWwcz\nMa4Dc1cd4F/rDhHfNYQl29NYn5SDvcrw4s2DNZnUEBUSwHVDojAYgvy9eff7ZF65dQgDooKwVxm6\nhrXhR5d05qu9mQzq4kjUL64+yJ2XxZ4x3fqxvJPsTiugS2gA/Tq3Y973yaQXlvH5rnSO5ZUSGezP\n1wey2ZKcx8e/HHXGCKnPfkjn1a8Pcd2QqHOeyhrfJ4I//bg/g7uEcPWL3/LE0t30jAjkv/eOorjc\nxvi/fc3OYyf4w5TepyUTgOAAH/4wuTd+3p7EdW7Huv1Z/N+P4jSZqAbTHoqbKCyrZOBTX3Lf2B78\nbnLvC25n7f4s7nt/G0O6hvDY1L6s3pvFTcO60L7GxfKySjvGwOR/fMPJChtv3zGMgVH6zInzKSit\nJMj/3Kd9isttXPqX1VzZK5yXbx1yqnzzkTxmvL2Z0ko7nh7CjwdHsnhrKp4eQo/wQB6f1pfRPdrz\nn01HeWLpbn42Mprvk3KZ//MR+Hh68NKag7y3IYVhMSG8dccw2tXj1NM1L6/nh9QCFs4aychujhF7\nHyYc44NNR3n/5yPqvO+kqKxST3Gp09S3h1JnQhGRt4FpQJYxpr9VFgosAmKAZOBGY0y+te4RYCZg\nB35ljFlplQ8F3gX8gc+BB4wxRkR8gfeAoUAucJMxJtmqMwN43ArlGWPMPKs8FlgIhAFbgduMMRV1\nfVh3TigHMouYNPcbpg7oxL9+6viFtC+jkF7WKYvzsVcZVuzOYOGWo6xPyqFvx3a8dUd8nUNe80oq\n8BDHX6jq4v358728tf4IE/pGnDqFNf5vXxPRzpfnr7+EPyzeyaHsEsb3ieDft8cjwqneSFmlnSue\nW0tWUTkAv5vUiy8TM0k8XsjNw7vw+NS4et9pvuFQLklZRdx2aUxjfVTVytQ3odTnHMe7wJRaZQ8D\nq40xPYHV1ntEJA64Gehn1XlFRKr/F7wK3A30tF7Vbc4E8o0xPYC5wLNWW6HAk8AIYDjwpIhU3079\nLDDXqpNvtdGsVQ/9rJ7fas/xAqb841tW78uqs+4d72xm9gfbSM4t4f5xPfn4l6Pqdf9EaBsfTSZO\nNGNUDB4CK/dk8vo3h3l5TRLF5TbevD2eoV1DeGvGMH42Mprnrh+IR62b//y8PXn62v7MuLQrg7oE\n8+9vj/BDagFPXdOPZ64d0KBpSy7tHqbJRLlEnQnFGPMNUHse8+nAPGt5HnBtjfKFxphyY8wRIAkY\nLiKdgHbGmI3G0SV6r1ad6rYWA+PF8T9tMrDKGJNn9X5WAVOsdeOsbWvvv9nKKCgFHNNbGGP4LikH\ngCM5xeetl1tczrcHc5g5OpZ1vxvLbyb2wt9H50xyhchgf1b8+go+mX0Z9irD/I0pXNYj7NRzQmLa\nt+GZawecca9Otcn9OvLH6f358eBICkoraefnxU+G6KzHqvm40KuwHYwx6dZyBlA9/0IkcKzGdqlW\nWaS1XLv8tDrGGBtQgONU1rnaCgNOWNvWbqvZqu6hlFTYyS4uZ9PhvNPKz2X70ROA45eRpz5l0OW6\nhwdySZdgLrWuXdwY36XBbVw1oCM+nh7cMiKaAB8dN6Oaj4v+tlrXQdz2yr6IzAJmAURHR7s4mnPL\nqJE4DmeXsDnZSignzp9Qth3Nx8tDGBgV1KjxqYa5f3wPfL09mHwBEyNGtPVj5YNXEHmOIcRKuasL\n7aFkWqexsH5Wn+hPA2r+SRZllaVZy7XLT6sjIl5AEI6L8+dqKxcItrat3dYZjDFvGGPijTHx4eHu\nO21EekEZwQGOkTUrdmdQVGbDQyDdOhV2LtuO5hPXuZ1ODe5mRnVvz7t3Dr/gf5fY9m10GLdqdi70\nG/spMMNangF8UqP8ZhHxtUZi9QQ2W6fHCkVkpHUN5PZadarbuh5YY11nWQlMEpEQ62L8JGCltW6t\ntW3t/TdbGQVlDIkOwctD+Nh6nOronuEcP88pL5u9ip3HChgSffap35VSqinVmVBEZAGwAegtIqki\nMhP4KzBRRA4CE6z3GGP2AB8CicAKYLYxpvrpTPcCb+K4UH8I+MIqfwsIE5Ek4DdYI8aMMXnA08AW\n6zXHKgN4CPiNVSfMasPllu08zuz3t1Fhq2pw3eMFpUSF+NMlNICichszLu3KkOhgcorLz9leQko+\npZX2cz5LRCmlmlKd11CMMbecY9X4c2z/J+BPZylPAM6YXc4YUwbccI623gbePkv5YRxDid3Gsp3H\n+dXC7RgDt1/alRHdwuquZCkut1FUZqNjkB/j+kSQmn+SJ6bF8d9taRgDmYVldAn93xxbn+48TmmF\njTX7sggO8GZC3w7naV0ppZqGDiFxkn98dYDeHdpyILOI7w7lNiihVF+Q7xzkf9rsth2DHFOwHD9R\neiqhlFXaeWzJLorKHIPc7h3TXYcJK6XcgiYUJ0g7Ucqh7BIen9qXZTuPs+FQDkzsVe/61QmlOoFU\n6xzseL90RxoLNh+lfaAv0WEBFJXZ6Ne5HUdySrhdb2BTSrkJTSj1UFxuw2avOudd5d8cyAYcTynM\nKa7gzW8Pc7LCVu97CJKyigDoGnb61PHVd7sv2HyMIH9vSspt2KoM0aEBLLtvNAWllYS00TvdlVLu\nQccl1sEYw73vb+OWf28it7j8tHU2exVbU/JZlZhJx3Z+9IwI5LIeYdiqDGv3ZfPvbw4zee43PLpk\nF0Vllefcx970IkICvOlY61kabXy9aOfnRVs/Lz771WjeuH0oPl4e3DayKx4eoslEKeVWtIdSBxHh\n56NjmTU/gRte38ALN1zCkOgQjuSU8MDC7fyQWgDAjfFRiAjDY0PpERHI40t3UVBaSWz7NizYfBRP\nEZ6+9uxPvNubUUjfTu3OmLYc4PFpcUSHBhAV4nhte2IibfSaiVLKDWkPpR6u6BXOvDuHU1Ju4yev\nfM9Lqw9y5zubOZp3kmeu7c/vJ/c+dTHd18uTF28eTEmFnaiQAD65bzR3jopl/sYU3l5/hMJaPRWb\nvYr9GUX07dTurPu+Mb7LqSnIAQJ9vc6aeJRSytW0h1JPI7qFsfq3Y/jD4p38bdUBPD2EBXePZHhs\n6BnbxnVux39/OYqwQB8Cfb347aRebD2az5zliSzacoxl948+dRd0cm4J5bYq4s6RUJRSqrnQhNIA\ngb5evHjzYCKD99GrQ9uzJpNq/SP/N7dWG18vlt47is92pXPfB9t545tD3DeuJ5mFZWw+kg9wzh6K\nUko1F5pQGsjL04PHpsY1uJ6IMG1gZz7flc4LXx7grfVHyD/pOP3l7Sn0iAh0dqhKKdWkNKE0sWev\nG8iQ6BAOZBbRM6ItBaWVhLbx0YkAlVLNniaUJtbWz5ufX97N1WEopZTT6Z/FSimlnEITilJKKafQ\nhKKUUsopNKEopZRyCk0oSimlnEITilJKKafQhKKUUsopNKEopZRyCjHGuDqGJiMi2UBKPTcPAgou\nYnfRwNELrHsx+77YuF25bz1mDeeqY3ax9fWYNZ+6AF2NMeF1bmWM0ddZXsAbF1k/2xX7dkLcrty3\nHrNmcsxc+bn1mDV93PV96Smvc1t2kfVPuGjfFxu3K/etx6zhXHXMLra+HrPmU7feWtUpr6YkIgnG\nmHhXx9Gc6DFrOD1mDafHrPFoD6XxvOHqAJohPWYNp8es4fSYNRLtoSillHIK7aEopZRyCk0o9SQi\nb4tIlojsrlF2iYhsEJFdIrJMRNpZ5T4i8o5VvlNExtSoc5OI/CAie0TkWRd8lCYjIl1EZK2IJFqf\n9wGrPFREVonIQetnSI06j4hIkojsF5HJZ2nz05r/Bi2NM49Za/muNfSYiUiYtX2xiLx8jjZb9Pes\nsWhCqb93gSm1yt4EHjbGDACWAL+3yu8GsMonAn8TEQ8RCQOeB8YbY/oBHUVkfFME7yI24LfGmDhg\nJDBbROKAh4HVxpiewGrrPda6m4F+OI71KyLiWd2YiPwEKG7aj9DknHLMWtl3rUHHDCgDngB+d7bG\nWsn3rFFoQqknY8w3QF6t4l7AN9byKuA6azkOWGPVy8IxTDEe6AYcNMZkW9t9VaNOi2OMSTfGbLOW\ni4C9QCQwHZhnbTYPuNZang4sNMaUG2OOAEnAcAARCQR+AzzTdJ+g6TnxmLWa71pDj5kxpsQYsx5H\nYjlNa/meNRZNKBdnD44vLcANQBdreSdwjYh4iUgsMNRalwT0FpEYEfHC8QXvQisgIjHAYGAT0MEY\nk26tygA6WMuRwLEa1VKtMoCngb8BJxs7VndxkcesVX7X6nnMzqfVfc+cSRPKxbkLuFdEtgJtgQqr\n/G0c/7ETgH8A3wN2Y0w+8EtgEfAtkAzYmzjmJmf91fcx8GtjTGHNdcYxzPC8Qw1FZBDQ3RizpPGi\ndC8Xe8xa43dNv2eu5+XqAJozY8w+YBKAiPQCplrlNuDB6u1E5HvggLVuGdZdqyIyi5b/n9wbx3/y\n940x/7WKM0WkkzEmXUQ6AVlWeRqn/xUdZZVdCsSLSDKO72yEiKwzxoxpis/Q1Jx0zFrVd62Bx+xc\nWtX3rDFoD+UiiEiE9dMDeBx4zXofICJtrOWJgM0Yk1irTghwL44L+y2SiAjwFrDXGPP3Gqs+BWZY\nyzOAT2qU3ywivtapwp7AZmPMq8aYzsaYGGA0cKCl/id31jGz2moV37ULOGZn1Zq+Z42mKSYMawkv\nYAGQDlTiOJ01E3gAR8/jAPBX/nejaAywH8fFwa9wzNRZs51E63Wzqz9XIx+z0ThOM/wA7LBeVwNh\nOEbdHLSOT2iNOo8Bh6zjd9VZ2owBdrv6szWHY9ZavmsXeMyScQyyKbb+P8e1pu9ZY730TnmllFJO\noae8lFJKOYUmFKWUUk6hCUUppZRTaEJRSinlFJpQlFJKOYUmFKUagYjYRWSHNfvtThH5rXW/Us1t\n/iEiadXlInKnVWeHiFSIY7bqHSLyVxG5Q0Sya6zfYU2AqJTb0GHDSjUCESk2xgRayxHAB8B3xpgn\nrTIP4AiOe5seMcasrVU/GYg3xuRY7++w3t/XZB9CqQbSHopSjcw4ZpyeBdxn3dUNMAbH5KKvAre4\nKDSlnEoTilJNwBhzGPAEIqyiW3Dcyb4EmGrNRVWXm2qd8vJvpHCVuiCaUJRqYiLig2NqkKXGMSvu\nJuCMp1OexSJjzKAar9JGDVSpBtLZhpVqAiLSDcdsv1nANCAY2GWdAQsASoHlLgtQKSfQhKJUIxOR\ncBwzUb9sjDEicgvwc2PMAmt9G+CIiAQYY/TBTqrZ0lNeSjUO/+phwzhmuv0S+KOIBOB49vtn1Rsa\nY0qA9cCP6miz9jWUUY0VvFIXQocNK6WUcgrtoSillHIKTShKKaWcQhOKUkopp9CEopRSyik0oSil\nlHIKTShKKaWcQhOKUkopp9CEopRSyin+H2E8dx+OgfL+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113a356d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# BOJ TOTAL ASSET\n",
    "f_boj = web.DataReader('JPNASSETS', 'fred', start_f, end_f)\n",
    "f_boj.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# World Bank\n",
    "from pandas_datareader import wb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mat = wb.search('elect')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "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>id</th>\n",
       "      <th>name</th>\n",
       "      <th>source</th>\n",
       "      <th>sourceNote</th>\n",
       "      <th>sourceOrganization</th>\n",
       "      <th>topics</th>\n",
       "      <th>unit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1.1_ACCESS.ELECTRICITY.TOT</td>\n",
       "      <td>Access to electricity (% of total population)</td>\n",
       "      <td>Sustainable Energy for All</td>\n",
       "      <td>Access to electricity is the percentage of pop...</td>\n",
       "      <td>b'World Bank Global Electrification Database 2...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1.2_ACCESS.ELECTRICITY.RURAL</td>\n",
       "      <td>Access to electricity (% of rural population)</td>\n",
       "      <td>Sustainable Energy for All</td>\n",
       "      <td>Access to electricity is the percentage of rur...</td>\n",
       "      <td>b'World Bank Global Electrification Database 2...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1.3_ACCESS.ELECTRICITY.URBAN</td>\n",
       "      <td>Access to electricity (% of urban population)</td>\n",
       "      <td>Sustainable Energy for All</td>\n",
       "      <td>Access to electricity is the percentage of tot...</td>\n",
       "      <td>b'World Bank Global Electrification Database 2...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2.0.cov.Ele</td>\n",
       "      <td>Coverage: Electricity</td>\n",
       "      <td>LAC Equity Lab</td>\n",
       "      <td>The coverage rate is the childhood access rate...</td>\n",
       "      <td>b'LAC Equity Lab tabulations of SEDLAC (CEDLAS...</td>\n",
       "      <td>Poverty</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2.0.hoi.Ele</td>\n",
       "      <td>HOI: Electricity</td>\n",
       "      <td>LAC Equity Lab</td>\n",
       "      <td>The Human Opportunities Index (HOI) is an econ...</td>\n",
       "      <td>b'LAC Equity Lab tabulations of SEDLAC (CEDLAS...</td>\n",
       "      <td>Poverty</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>4.1.1_TOTAL.ELECTRICITY.OUTPUT</td>\n",
       "      <td>Total electricity output (GWh)</td>\n",
       "      <td>Sustainable Energy for All</td>\n",
       "      <td>Total electricity output (GWh): Total number o...</td>\n",
       "      <td>b'World Bank and International Energy Agency (...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>4.1.2_REN.ELECTRICITY.OUTPUT</td>\n",
       "      <td>Renewable energy electricity output (GWh)</td>\n",
       "      <td>Sustainable Energy for All</td>\n",
       "      <td>Renewable energy electricity output (GWh): Tot...</td>\n",
       "      <td>b'World Bank and International Energy Agency (...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>4.1_SHARE.RE.IN.ELECTRICITY</td>\n",
       "      <td>Renewable electricity (% in total electricity ...</td>\n",
       "      <td>Sustainable Energy for All</td>\n",
       "      <td>Renewable electricity (% in total electricity ...</td>\n",
       "      <td>b'World Bank and International Energy Agency (...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4811</th>\n",
       "      <td>EG.ELC.ACCS.RU.ZS</td>\n",
       "      <td>Access to electricity, rural (% of rural popul...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>World Bank, Sustainable Energy for All (SE4ALL...</td>\n",
       "      <td>b'World Bank, Sustainable Energy for All (SE4A...</td>\n",
       "      <td>Agriculture &amp; Rural Development   ; Energy &amp; M...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4812</th>\n",
       "      <td>EG.ELC.ACCS.UR.ZS</td>\n",
       "      <td>Access to electricity, urban (% of urban popul...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Access to electricity, rural is the percentage...</td>\n",
       "      <td>b'World Bank, Sustainable Energy for All (SE4A...</td>\n",
       "      <td>Energy &amp; Mining  ; Urban Development</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4813</th>\n",
       "      <td>EG.ELC.ACCS.ZS</td>\n",
       "      <td>Access to electricity (% of population)</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Access to electricity is the percentage of pop...</td>\n",
       "      <td>b'World Bank, Sustainable Energy for All (SE4A...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Environment</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4814</th>\n",
       "      <td>EG.ELC.COAL.KH</td>\n",
       "      <td>Electricity production from coal sources (kWh)</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4815</th>\n",
       "      <td>EG.ELC.COAL.ZS</td>\n",
       "      <td>Electricity production from coal sources (% of...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Sources of electricity refer to the inputs use...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Infrastruc...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4816</th>\n",
       "      <td>EG.ELC.FOSL.ZS</td>\n",
       "      <td>Electricity production from oil, gas and coal ...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Sources of electricity refer to the inputs use...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Environment</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4817</th>\n",
       "      <td>EG.ELC.HOUS.ZS</td>\n",
       "      <td>Household electrification rate (% of households)</td>\n",
       "      <td>IDA Results Measurement System</td>\n",
       "      <td>Household electrification rate is defined as t...</td>\n",
       "      <td>b'Compiled by World Bank staff from household ...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4818</th>\n",
       "      <td>EG.ELC.HYRO.KH</td>\n",
       "      <td>Electricity production from hydroelectric sour...</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4819</th>\n",
       "      <td>EG.ELC.HYRO.ZS</td>\n",
       "      <td>Electricity production from hydroelectric sour...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Sources of electricity refer to the inputs use...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Infrastruc...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4820</th>\n",
       "      <td>EG.ELC.LOSS.KH</td>\n",
       "      <td>Electric power transmission and distribution l...</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4821</th>\n",
       "      <td>EG.ELC.LOSS.ZS</td>\n",
       "      <td>Electric power transmission and distribution l...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Electric power transmission and distribution l...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Infrastructure</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4822</th>\n",
       "      <td>EG.ELC.NGAS.KH</td>\n",
       "      <td>Electricity production from natural gas source...</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4823</th>\n",
       "      <td>EG.ELC.NGAS.ZS</td>\n",
       "      <td>Electricity production from natural gas source...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Sources of electricity refer to the inputs use...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Infrastruc...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4824</th>\n",
       "      <td>EG.ELC.NUCL.KH</td>\n",
       "      <td>Electricity production from nuclear sources (kWh)</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4825</th>\n",
       "      <td>EG.ELC.NUCL.ZS</td>\n",
       "      <td>Electricity production from nuclear sources (%...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Sources of electricity refer to the inputs use...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Infrastruc...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4826</th>\n",
       "      <td>EG.ELC.PETR.KH</td>\n",
       "      <td>Electricity production from oil sources (kWh)</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4827</th>\n",
       "      <td>EG.ELC.PETR.ZS</td>\n",
       "      <td>Electricity production from oil sources (% of ...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Sources of electricity refer to the inputs use...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Infrastruc...</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4828</th>\n",
       "      <td>EG.ELC.PROD.KH</td>\n",
       "      <td>Electricity production (kWh)</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4829</th>\n",
       "      <td>EG.ELC.RNEW.KH</td>\n",
       "      <td>Electricity production from renewable sources ...</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4830</th>\n",
       "      <td>EG.ELC.RNEW.ZS</td>\n",
       "      <td>Renewable electricity output (% of total elect...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Renewable electricity is the share of electrit...</td>\n",
       "      <td>b'World Bank, Sustainable Energy for All (SE4A...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Environment</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4831</th>\n",
       "      <td>EG.ELC.RNWX.KH</td>\n",
       "      <td>Electricity production from renewable sources,...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Electricity production from renewable sources,...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Environment</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4832</th>\n",
       "      <td>EG.ELC.RNWX.ZS</td>\n",
       "      <td>Electricity production from renewable sources,...</td>\n",
       "      <td>World Development Indicators</td>\n",
       "      <td>Electricity production from renewable sources,...</td>\n",
       "      <td>b'IEA Statistics  OECD/IEA 2014 (http://www.ie...</td>\n",
       "      <td>Energy &amp; Mining  ; Climate Change ; Environment</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6066</th>\n",
       "      <td>IC.GE.COST</td>\n",
       "      <td>Cost to get electricity(% of income per capita)</td>\n",
       "      <td>Doing Business</td>\n",
       "      <td>Cost to obtain an electricity connection (% of...</td>\n",
       "      <td>b'World Bank, Doing Business Project (http://w...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6067</th>\n",
       "      <td>IC.GE.NUM</td>\n",
       "      <td>Procedures required to connect to electricity ...</td>\n",
       "      <td>Doing Business</td>\n",
       "      <td>This indicator records the number of procedure...</td>\n",
       "      <td>b'World Bank, Doing Business Project (http://w...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6196</th>\n",
       "      <td>IN.ENRGY.ELEC.GEN</td>\n",
       "      <td>Total-Electricity Generated Gross (GWh)</td>\n",
       "      <td>Country Partnership Strategy for India (FY2013...</td>\n",
       "      <td>Total-Electricity Generated Gross (GWh). Inclu...</td>\n",
       "      <td>b'Source: Central Electricity Authority, Minis...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6201</th>\n",
       "      <td>IN.ENRGY.TOWNS.ELECTRFIED.NUM</td>\n",
       "      <td>Number of Towns Electrified (Per 2001 Census)</td>\n",
       "      <td>Country Partnership Strategy for India (FY2013...</td>\n",
       "      <td>Number of Towns Electrified (Per 2001 Census)</td>\n",
       "      <td>b'Source: Central Electricity Authority, Minis...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6202</th>\n",
       "      <td>IN.ENRGY.TOWNS.ELECTRFIED.PERCENT</td>\n",
       "      <td>Number of Towns Electrified (Percentage)</td>\n",
       "      <td>Country Partnership Strategy for India (FY2013...</td>\n",
       "      <td>Percentage of Towns in the State Electrified</td>\n",
       "      <td>b'Source: Central Electricity Authority, Minis...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6204</th>\n",
       "      <td>IN.ENRGY.VILLAG.ELECTRFIED</td>\n",
       "      <td>Number of Villages Electrified</td>\n",
       "      <td>Country Partnership Strategy for India (FY2013...</td>\n",
       "      <td>Number of Villages Electrified</td>\n",
       "      <td>b'Source: Central Electricity Authority, Minis...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6205</th>\n",
       "      <td>IN.ENRGY.VILLAG.ELECTRFIED.PERCENT</td>\n",
       "      <td>Number of Villages Electrified (Percentage)</td>\n",
       "      <td>Country Partnership Strategy for India (FY2013...</td>\n",
       "      <td>Percentage of Villages Electrified in the State</td>\n",
       "      <td>b'Source: Central Electricity Authority, Minis...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6333</th>\n",
       "      <td>IS.RRS.ELEC.KM</td>\n",
       "      <td>Rail lines, electric (km)</td>\n",
       "      <td>WDI Database Archives</td>\n",
       "      <td></td>\n",
       "      <td>b''</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7928</th>\n",
       "      <td>NV.IND.GELW.CD</td>\n",
       "      <td>Gas, electricity and water, value added (curre...</td>\n",
       "      <td>Africa Development Indicators</td>\n",
       "      <td>Value added in gas, electricity and water is d...</td>\n",
       "      <td>b'World Bank national accounts data, and OECD ...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7929</th>\n",
       "      <td>NV.IND.GELW.CN</td>\n",
       "      <td>Gas, electricity and water, value added (curre...</td>\n",
       "      <td>Africa Development Indicators</td>\n",
       "      <td>Value added in gas, electricity and water is d...</td>\n",
       "      <td>b'World Bank national accounts data, and OECD ...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7930</th>\n",
       "      <td>NV.IND.GELW.KN</td>\n",
       "      <td>Gas, electricity and water, value added (const...</td>\n",
       "      <td>Africa Development Indicators</td>\n",
       "      <td>Value added in gas, electricity and water is d...</td>\n",
       "      <td>b'World Bank national accounts data, and OECD ...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8777</th>\n",
       "      <td>SABER.GRVT.GOAL7.LVL3</td>\n",
       "      <td>SABER: (Engaging the Private Sector, Governmen...</td>\n",
       "      <td>Education Statistics</td>\n",
       "      <td>Data Interpretation: 1=Latent; 2=Emerging; 3=E...</td>\n",
       "      <td>b'Systems Approach for Better Education Result...</td>\n",
       "      <td>Education</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9266</th>\n",
       "      <td>SG.COK.ELEC.ZS</td>\n",
       "      <td>Main cooking fuel: electricity  (% of households)</td>\n",
       "      <td>Gender Statistics</td>\n",
       "      <td>Percentage of households who use electricity a...</td>\n",
       "      <td>b'Demographic and Health Surveys (DHS)'</td>\n",
       "      <td>Gender</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10175</th>\n",
       "      <td>SL.EMP.ELC</td>\n",
       "      <td>Number of people employed in electricity and u...</td>\n",
       "      <td>Indonesia Database for Policy and Economic Res...</td>\n",
       "      <td></td>\n",
       "      <td>b'BADAN PUSAT STATISTIK - Statistics Indonesia...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11207</th>\n",
       "      <td>UIS.AFR.SCHBSP.1.PU.WELEC</td>\n",
       "      <td>Africa Dataset: Percentage of primary schools ...</td>\n",
       "      <td>Education Statistics</td>\n",
       "      <td>Share of public primary schools with access to...</td>\n",
       "      <td>b'UNESCO Institute for Statistics'</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11208</th>\n",
       "      <td>UIS.AFR.SCHBSP.1.PU.WNIELEC</td>\n",
       "      <td>Africa Dataset: Percentage of primary schools ...</td>\n",
       "      <td>Education Statistics</td>\n",
       "      <td>Share of public primary schools where informat...</td>\n",
       "      <td>b'UNESCO Institute for Statistics'</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11211</th>\n",
       "      <td>UIS.AFR.SCHBSP.1.PU.WOELEC</td>\n",
       "      <td>Africa Dataset: Percentage of primary schools ...</td>\n",
       "      <td>Education Statistics</td>\n",
       "      <td>Share of public primary schools with no access...</td>\n",
       "      <td>b'UNESCO Institute for Statistics'</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <td>UIS.AFR.SCHBSP.2.PU.WELEC</td>\n",
       "      <td>Africa Dataset: Percentage of lower secondary ...</td>\n",
       "      <td>Education Statistics</td>\n",
       "      <td>Share of public lower secondary schools with a...</td>\n",
       "      <td>b'UNESCO Institute for Statistics'</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11219</th>\n",
       "      <td>UIS.AFR.SCHBSP.2.PU.WNIELEC</td>\n",
       "      <td>Africa Dataset: Percentage of lower secondary ...</td>\n",
       "      <td>Education Statistics</td>\n",
       "      <td>Share of public lower secondary schools where ...</td>\n",
       "      <td>b'UNESCO Institute for Statistics'</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11222</th>\n",
       "      <td>UIS.AFR.SCHBSP.2.PU.WOELEC</td>\n",
       "      <td>Africa Dataset: Percentage of lower secondary ...</td>\n",
       "      <td>Education Statistics</td>\n",
       "      <td>Share of public lower secondary schools with n...</td>\n",
       "      <td>b'UNESCO Institute for Statistics'</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12246</th>\n",
       "      <td>WP11633.1</td>\n",
       "      <td>Used electronic payments to make payments (% a...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12247</th>\n",
       "      <td>WP11633.10</td>\n",
       "      <td>Used electronic payments to make payments, rur...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12248</th>\n",
       "      <td>WP11633.2</td>\n",
       "      <td>Used electronic payments to make payments, mal...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12249</th>\n",
       "      <td>WP11633.3</td>\n",
       "      <td>Used electronic payments to make payments, fem...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12250</th>\n",
       "      <td>WP11633.4</td>\n",
       "      <td>Used electronic payments to make payments, you...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12251</th>\n",
       "      <td>WP11633.5</td>\n",
       "      <td>Used electronic payments to make payments, old...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12252</th>\n",
       "      <td>WP11633.6</td>\n",
       "      <td>Used electronic payments to make payments, pri...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12253</th>\n",
       "      <td>WP11633.7</td>\n",
       "      <td>Used electronic payments to make payments, sec...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12254</th>\n",
       "      <td>WP11633.8</td>\n",
       "      <td>Used electronic payments to make payments, inc...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12255</th>\n",
       "      <td>WP11633.9</td>\n",
       "      <td>Used electronic payments to make payments, inc...</td>\n",
       "      <td>Global Financial Inclusion</td>\n",
       "      <td>Denotes the percentage of respondents who used...</td>\n",
       "      <td>b'Demirguc-Kunt and Klapper, 2012'</td>\n",
       "      <td>Financial Sector</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>93 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       id  \\\n",
       "24             1.1_ACCESS.ELECTRICITY.TOT   \n",
       "39           1.2_ACCESS.ELECTRICITY.RURAL   \n",
       "40           1.3_ACCESS.ELECTRICITY.URBAN   \n",
       "42                            2.0.cov.Ele   \n",
       "67                            2.0.hoi.Ele   \n",
       "158        4.1.1_TOTAL.ELECTRICITY.OUTPUT   \n",
       "159          4.1.2_REN.ELECTRICITY.OUTPUT   \n",
       "172           4.1_SHARE.RE.IN.ELECTRICITY   \n",
       "4811                    EG.ELC.ACCS.RU.ZS   \n",
       "4812                    EG.ELC.ACCS.UR.ZS   \n",
       "4813                       EG.ELC.ACCS.ZS   \n",
       "4814                       EG.ELC.COAL.KH   \n",
       "4815                       EG.ELC.COAL.ZS   \n",
       "4816                       EG.ELC.FOSL.ZS   \n",
       "4817                       EG.ELC.HOUS.ZS   \n",
       "4818                       EG.ELC.HYRO.KH   \n",
       "4819                       EG.ELC.HYRO.ZS   \n",
       "4820                       EG.ELC.LOSS.KH   \n",
       "4821                       EG.ELC.LOSS.ZS   \n",
       "4822                       EG.ELC.NGAS.KH   \n",
       "4823                       EG.ELC.NGAS.ZS   \n",
       "4824                       EG.ELC.NUCL.KH   \n",
       "4825                       EG.ELC.NUCL.ZS   \n",
       "4826                       EG.ELC.PETR.KH   \n",
       "4827                       EG.ELC.PETR.ZS   \n",
       "4828                       EG.ELC.PROD.KH   \n",
       "4829                       EG.ELC.RNEW.KH   \n",
       "4830                       EG.ELC.RNEW.ZS   \n",
       "4831                       EG.ELC.RNWX.KH   \n",
       "4832                       EG.ELC.RNWX.ZS   \n",
       "...                                   ...   \n",
       "6066                           IC.GE.COST   \n",
       "6067                            IC.GE.NUM   \n",
       "6196                    IN.ENRGY.ELEC.GEN   \n",
       "6201        IN.ENRGY.TOWNS.ELECTRFIED.NUM   \n",
       "6202    IN.ENRGY.TOWNS.ELECTRFIED.PERCENT   \n",
       "6204           IN.ENRGY.VILLAG.ELECTRFIED   \n",
       "6205   IN.ENRGY.VILLAG.ELECTRFIED.PERCENT   \n",
       "6333                       IS.RRS.ELEC.KM   \n",
       "7928                       NV.IND.GELW.CD   \n",
       "7929                       NV.IND.GELW.CN   \n",
       "7930                       NV.IND.GELW.KN   \n",
       "8777                SABER.GRVT.GOAL7.LVL3   \n",
       "9266                       SG.COK.ELEC.ZS   \n",
       "10175                          SL.EMP.ELC   \n",
       "11207           UIS.AFR.SCHBSP.1.PU.WELEC   \n",
       "11208         UIS.AFR.SCHBSP.1.PU.WNIELEC   \n",
       "11211          UIS.AFR.SCHBSP.1.PU.WOELEC   \n",
       "11218           UIS.AFR.SCHBSP.2.PU.WELEC   \n",
       "11219         UIS.AFR.SCHBSP.2.PU.WNIELEC   \n",
       "11222          UIS.AFR.SCHBSP.2.PU.WOELEC   \n",
       "12246                           WP11633.1   \n",
       "12247                          WP11633.10   \n",
       "12248                           WP11633.2   \n",
       "12249                           WP11633.3   \n",
       "12250                           WP11633.4   \n",
       "12251                           WP11633.5   \n",
       "12252                           WP11633.6   \n",
       "12253                           WP11633.7   \n",
       "12254                           WP11633.8   \n",
       "12255                           WP11633.9   \n",
       "\n",
       "                                                    name  \\\n",
       "24         Access to electricity (% of total population)   \n",
       "39         Access to electricity (% of rural population)   \n",
       "40         Access to electricity (% of urban population)   \n",
       "42                                 Coverage: Electricity   \n",
       "67                                      HOI: Electricity   \n",
       "158                       Total electricity output (GWh)   \n",
       "159            Renewable energy electricity output (GWh)   \n",
       "172    Renewable electricity (% in total electricity ...   \n",
       "4811   Access to electricity, rural (% of rural popul...   \n",
       "4812   Access to electricity, urban (% of urban popul...   \n",
       "4813             Access to electricity (% of population)   \n",
       "4814      Electricity production from coal sources (kWh)   \n",
       "4815   Electricity production from coal sources (% of...   \n",
       "4816   Electricity production from oil, gas and coal ...   \n",
       "4817    Household electrification rate (% of households)   \n",
       "4818   Electricity production from hydroelectric sour...   \n",
       "4819   Electricity production from hydroelectric sour...   \n",
       "4820   Electric power transmission and distribution l...   \n",
       "4821   Electric power transmission and distribution l...   \n",
       "4822   Electricity production from natural gas source...   \n",
       "4823   Electricity production from natural gas source...   \n",
       "4824   Electricity production from nuclear sources (kWh)   \n",
       "4825   Electricity production from nuclear sources (%...   \n",
       "4826       Electricity production from oil sources (kWh)   \n",
       "4827   Electricity production from oil sources (% of ...   \n",
       "4828                        Electricity production (kWh)   \n",
       "4829   Electricity production from renewable sources ...   \n",
       "4830   Renewable electricity output (% of total elect...   \n",
       "4831   Electricity production from renewable sources,...   \n",
       "4832   Electricity production from renewable sources,...   \n",
       "...                                                  ...   \n",
       "6066     Cost to get electricity(% of income per capita)   \n",
       "6067   Procedures required to connect to electricity ...   \n",
       "6196             Total-Electricity Generated Gross (GWh)   \n",
       "6201       Number of Towns Electrified (Per 2001 Census)   \n",
       "6202            Number of Towns Electrified (Percentage)   \n",
       "6204                      Number of Villages Electrified   \n",
       "6205         Number of Villages Electrified (Percentage)   \n",
       "6333                           Rail lines, electric (km)   \n",
       "7928   Gas, electricity and water, value added (curre...   \n",
       "7929   Gas, electricity and water, value added (curre...   \n",
       "7930   Gas, electricity and water, value added (const...   \n",
       "8777   SABER: (Engaging the Private Sector, Governmen...   \n",
       "9266   Main cooking fuel: electricity  (% of households)   \n",
       "10175  Number of people employed in electricity and u...   \n",
       "11207  Africa Dataset: Percentage of primary schools ...   \n",
       "11208  Africa Dataset: Percentage of primary schools ...   \n",
       "11211  Africa Dataset: Percentage of primary schools ...   \n",
       "11218  Africa Dataset: Percentage of lower secondary ...   \n",
       "11219  Africa Dataset: Percentage of lower secondary ...   \n",
       "11222  Africa Dataset: Percentage of lower secondary ...   \n",
       "12246  Used electronic payments to make payments (% a...   \n",
       "12247  Used electronic payments to make payments, rur...   \n",
       "12248  Used electronic payments to make payments, mal...   \n",
       "12249  Used electronic payments to make payments, fem...   \n",
       "12250  Used electronic payments to make payments, you...   \n",
       "12251  Used electronic payments to make payments, old...   \n",
       "12252  Used electronic payments to make payments, pri...   \n",
       "12253  Used electronic payments to make payments, sec...   \n",
       "12254  Used electronic payments to make payments, inc...   \n",
       "12255  Used electronic payments to make payments, inc...   \n",
       "\n",
       "                                                  source  \\\n",
       "24                            Sustainable Energy for All   \n",
       "39                            Sustainable Energy for All   \n",
       "40                            Sustainable Energy for All   \n",
       "42                                        LAC Equity Lab   \n",
       "67                                        LAC Equity Lab   \n",
       "158                           Sustainable Energy for All   \n",
       "159                           Sustainable Energy for All   \n",
       "172                           Sustainable Energy for All   \n",
       "4811                        World Development Indicators   \n",
       "4812                        World Development Indicators   \n",
       "4813                        World Development Indicators   \n",
       "4814                               WDI Database Archives   \n",
       "4815                        World Development Indicators   \n",
       "4816                        World Development Indicators   \n",
       "4817                      IDA Results Measurement System   \n",
       "4818                               WDI Database Archives   \n",
       "4819                        World Development Indicators   \n",
       "4820                               WDI Database Archives   \n",
       "4821                        World Development Indicators   \n",
       "4822                               WDI Database Archives   \n",
       "4823                        World Development Indicators   \n",
       "4824                               WDI Database Archives   \n",
       "4825                        World Development Indicators   \n",
       "4826                               WDI Database Archives   \n",
       "4827                        World Development Indicators   \n",
       "4828                               WDI Database Archives   \n",
       "4829                               WDI Database Archives   \n",
       "4830                        World Development Indicators   \n",
       "4831                        World Development Indicators   \n",
       "4832                        World Development Indicators   \n",
       "...                                                  ...   \n",
       "6066                                      Doing Business   \n",
       "6067                                      Doing Business   \n",
       "6196   Country Partnership Strategy for India (FY2013...   \n",
       "6201   Country Partnership Strategy for India (FY2013...   \n",
       "6202   Country Partnership Strategy for India (FY2013...   \n",
       "6204   Country Partnership Strategy for India (FY2013...   \n",
       "6205   Country Partnership Strategy for India (FY2013...   \n",
       "6333                               WDI Database Archives   \n",
       "7928                       Africa Development Indicators   \n",
       "7929                       Africa Development Indicators   \n",
       "7930                       Africa Development Indicators   \n",
       "8777                                Education Statistics   \n",
       "9266                                   Gender Statistics   \n",
       "10175  Indonesia Database for Policy and Economic Res...   \n",
       "11207                               Education Statistics   \n",
       "11208                               Education Statistics   \n",
       "11211                               Education Statistics   \n",
       "11218                               Education Statistics   \n",
       "11219                               Education Statistics   \n",
       "11222                               Education Statistics   \n",
       "12246                         Global Financial Inclusion   \n",
       "12247                         Global Financial Inclusion   \n",
       "12248                         Global Financial Inclusion   \n",
       "12249                         Global Financial Inclusion   \n",
       "12250                         Global Financial Inclusion   \n",
       "12251                         Global Financial Inclusion   \n",
       "12252                         Global Financial Inclusion   \n",
       "12253                         Global Financial Inclusion   \n",
       "12254                         Global Financial Inclusion   \n",
       "12255                         Global Financial Inclusion   \n",
       "\n",
       "                                              sourceNote  \\\n",
       "24     Access to electricity is the percentage of pop...   \n",
       "39     Access to electricity is the percentage of rur...   \n",
       "40     Access to electricity is the percentage of tot...   \n",
       "42     The coverage rate is the childhood access rate...   \n",
       "67     The Human Opportunities Index (HOI) is an econ...   \n",
       "158    Total electricity output (GWh): Total number o...   \n",
       "159    Renewable energy electricity output (GWh): Tot...   \n",
       "172    Renewable electricity (% in total electricity ...   \n",
       "4811   World Bank, Sustainable Energy for All (SE4ALL...   \n",
       "4812   Access to electricity, rural is the percentage...   \n",
       "4813   Access to electricity is the percentage of pop...   \n",
       "4814                                                       \n",
       "4815   Sources of electricity refer to the inputs use...   \n",
       "4816   Sources of electricity refer to the inputs use...   \n",
       "4817   Household electrification rate is defined as t...   \n",
       "4818                                                       \n",
       "4819   Sources of electricity refer to the inputs use...   \n",
       "4820                                                       \n",
       "4821   Electric power transmission and distribution l...   \n",
       "4822                                                       \n",
       "4823   Sources of electricity refer to the inputs use...   \n",
       "4824                                                       \n",
       "4825   Sources of electricity refer to the inputs use...   \n",
       "4826                                                       \n",
       "4827   Sources of electricity refer to the inputs use...   \n",
       "4828                                                       \n",
       "4829                                                       \n",
       "4830   Renewable electricity is the share of electrit...   \n",
       "4831   Electricity production from renewable sources,...   \n",
       "4832   Electricity production from renewable sources,...   \n",
       "...                                                  ...   \n",
       "6066   Cost to obtain an electricity connection (% of...   \n",
       "6067   This indicator records the number of procedure...   \n",
       "6196   Total-Electricity Generated Gross (GWh). Inclu...   \n",
       "6201       Number of Towns Electrified (Per 2001 Census)   \n",
       "6202       Percentage of Towns in the State Electrified    \n",
       "6204                      Number of Villages Electrified   \n",
       "6205    Percentage of Villages Electrified in the State    \n",
       "6333                                                       \n",
       "7928   Value added in gas, electricity and water is d...   \n",
       "7929   Value added in gas, electricity and water is d...   \n",
       "7930   Value added in gas, electricity and water is d...   \n",
       "8777   Data Interpretation: 1=Latent; 2=Emerging; 3=E...   \n",
       "9266   Percentage of households who use electricity a...   \n",
       "10175                                                      \n",
       "11207  Share of public primary schools with access to...   \n",
       "11208  Share of public primary schools where informat...   \n",
       "11211  Share of public primary schools with no access...   \n",
       "11218  Share of public lower secondary schools with a...   \n",
       "11219  Share of public lower secondary schools where ...   \n",
       "11222  Share of public lower secondary schools with n...   \n",
       "12246  Denotes the percentage of respondents who used...   \n",
       "12247  Denotes the percentage of respondents who used...   \n",
       "12248  Denotes the percentage of respondents who used...   \n",
       "12249  Denotes the percentage of respondents who used...   \n",
       "12250  Denotes the percentage of respondents who used...   \n",
       "12251  Denotes the percentage of respondents who used...   \n",
       "12252  Denotes the percentage of respondents who used...   \n",
       "12253  Denotes the percentage of respondents who used...   \n",
       "12254  Denotes the percentage of respondents who used...   \n",
       "12255  Denotes the percentage of respondents who used...   \n",
       "\n",
       "                                      sourceOrganization  \\\n",
       "24     b'World Bank Global Electrification Database 2...   \n",
       "39     b'World Bank Global Electrification Database 2...   \n",
       "40     b'World Bank Global Electrification Database 2...   \n",
       "42     b'LAC Equity Lab tabulations of SEDLAC (CEDLAS...   \n",
       "67     b'LAC Equity Lab tabulations of SEDLAC (CEDLAS...   \n",
       "158    b'World Bank and International Energy Agency (...   \n",
       "159    b'World Bank and International Energy Agency (...   \n",
       "172    b'World Bank and International Energy Agency (...   \n",
       "4811   b'World Bank, Sustainable Energy for All (SE4A...   \n",
       "4812   b'World Bank, Sustainable Energy for All (SE4A...   \n",
       "4813   b'World Bank, Sustainable Energy for All (SE4A...   \n",
       "4814                                                 b''   \n",
       "4815   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4816   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4817   b'Compiled by World Bank staff from household ...   \n",
       "4818                                                 b''   \n",
       "4819   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4820                                                 b''   \n",
       "4821   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4822                                                 b''   \n",
       "4823   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4824                                                 b''   \n",
       "4825   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4826                                                 b''   \n",
       "4827   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4828                                                 b''   \n",
       "4829                                                 b''   \n",
       "4830   b'World Bank, Sustainable Energy for All (SE4A...   \n",
       "4831   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "4832   b'IEA Statistics  OECD/IEA 2014 (http://www.ie...   \n",
       "...                                                  ...   \n",
       "6066   b'World Bank, Doing Business Project (http://w...   \n",
       "6067   b'World Bank, Doing Business Project (http://w...   \n",
       "6196   b'Source: Central Electricity Authority, Minis...   \n",
       "6201   b'Source: Central Electricity Authority, Minis...   \n",
       "6202   b'Source: Central Electricity Authority, Minis...   \n",
       "6204   b'Source: Central Electricity Authority, Minis...   \n",
       "6205   b'Source: Central Electricity Authority, Minis...   \n",
       "6333                                                 b''   \n",
       "7928   b'World Bank national accounts data, and OECD ...   \n",
       "7929   b'World Bank national accounts data, and OECD ...   \n",
       "7930   b'World Bank national accounts data, and OECD ...   \n",
       "8777   b'Systems Approach for Better Education Result...   \n",
       "9266             b'Demographic and Health Surveys (DHS)'   \n",
       "10175  b'BADAN PUSAT STATISTIK - Statistics Indonesia...   \n",
       "11207                 b'UNESCO Institute for Statistics'   \n",
       "11208                 b'UNESCO Institute for Statistics'   \n",
       "11211                 b'UNESCO Institute for Statistics'   \n",
       "11218                 b'UNESCO Institute for Statistics'   \n",
       "11219                 b'UNESCO Institute for Statistics'   \n",
       "11222                 b'UNESCO Institute for Statistics'   \n",
       "12246                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12247                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12248                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12249                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12250                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12251                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12252                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12253                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12254                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "12255                 b'Demirguc-Kunt and Klapper, 2012'   \n",
       "\n",
       "                                                  topics unit  \n",
       "24                                                             \n",
       "39                                                             \n",
       "40                                                             \n",
       "42                                              Poverty        \n",
       "67                                              Poverty        \n",
       "158                                                            \n",
       "159                                                            \n",
       "172                                                            \n",
       "4811   Agriculture & Rural Development   ; Energy & M...       \n",
       "4812               Energy & Mining  ; Urban Development        \n",
       "4813    Energy & Mining  ; Climate Change ; Environment        \n",
       "4814                                                           \n",
       "4815   Energy & Mining  ; Climate Change ; Infrastruc...       \n",
       "4816                     Energy & Mining  ; Environment        \n",
       "4817                                                           \n",
       "4818                                                           \n",
       "4819   Energy & Mining  ; Climate Change ; Infrastruc...       \n",
       "4820                                                           \n",
       "4821                  Energy & Mining  ; Infrastructure        \n",
       "4822                                                           \n",
       "4823   Energy & Mining  ; Climate Change ; Infrastruc...       \n",
       "4824                                                           \n",
       "4825   Energy & Mining  ; Climate Change ; Infrastruc...       \n",
       "4826                                                           \n",
       "4827   Energy & Mining  ; Climate Change ; Infrastruc...       \n",
       "4828                                                           \n",
       "4829                                                           \n",
       "4830    Energy & Mining  ; Climate Change ; Environment        \n",
       "4831    Energy & Mining  ; Climate Change ; Environment        \n",
       "4832    Energy & Mining  ; Climate Change ; Environment        \n",
       "...                                                  ...  ...  \n",
       "6066                                                           \n",
       "6067                                                           \n",
       "6196                                                           \n",
       "6201                                                           \n",
       "6202                                                           \n",
       "6204                                                           \n",
       "6205                                                           \n",
       "6333                                                           \n",
       "7928                                                           \n",
       "7929                                                           \n",
       "7930                                                           \n",
       "8777                                          Education        \n",
       "9266                                              Gender       \n",
       "10175                                                          \n",
       "11207                                                          \n",
       "11208                                                          \n",
       "11211                                                          \n",
       "11218                                                          \n",
       "11219                                                          \n",
       "11222                                                          \n",
       "12246                                  Financial Sector        \n",
       "12247                                  Financial Sector        \n",
       "12248                                  Financial Sector        \n",
       "12249                                  Financial Sector        \n",
       "12250                                  Financial Sector        \n",
       "12251                                  Financial Sector        \n",
       "12252                                  Financial Sector        \n",
       "12253                                  Financial Sector        \n",
       "12254                                  Financial Sector        \n",
       "12255                                  Financial Sector        \n",
       "\n",
       "[93 rows x 7 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dat = wb.download(indicator='EG.ELC.ACCS.UR.ZS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>EG.ELC.ACCS.UR.ZS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Canada</th>\n",
       "      <th>2005</th>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Mexico</th>\n",
       "      <th>2005</th>\n",
       "      <td>99.605581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>99.390082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>99.579957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">United States</th>\n",
       "      <th>2005</th>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    EG.ELC.ACCS.UR.ZS\n",
       "country       year                   \n",
       "Canada        2005         100.000000\n",
       "              2004         100.000000\n",
       "              2003         100.000000\n",
       "Mexico        2005          99.605581\n",
       "              2004          99.390082\n",
       "              2003          99.579957\n",
       "United States 2005         100.000000\n",
       "              2004         100.000000\n",
       "              2003         100.000000"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eu = web.DataReader('teimf060', 'eurostat', start_f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>MATURITY</th>\n",
       "      <th>Maturity: 1 year</th>\n",
       "      <th>Maturity: 10 years</th>\n",
       "      <th>Maturity: 5 years</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BONDS</th>\n",
       "      <th>AAA rated euro area central government bonds</th>\n",
       "      <th>AAA rated euro area central government bonds</th>\n",
       "      <th>AAA rated euro area central government bonds</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CURV_TYP</th>\n",
       "      <th>Zero-coupon yield curve spot rate</th>\n",
       "      <th>Zero-coupon yield curve spot rate</th>\n",
       "      <th>Zero-coupon yield curve spot rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GEO</th>\n",
       "      <th>Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)</th>\n",
       "      <th>Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)</th>\n",
       "      <th>Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FREQ</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIME_PERIOD</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-02-01</th>\n",
       "      <td>-0.81</td>\n",
       "      <td>0.38</td>\n",
       "      <td>-0.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-01</th>\n",
       "      <td>-0.84</td>\n",
       "      <td>0.43</td>\n",
       "      <td>-0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-01</th>\n",
       "      <td>-0.80</td>\n",
       "      <td>0.32</td>\n",
       "      <td>-0.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-01</th>\n",
       "      <td>-0.73</td>\n",
       "      <td>0.44</td>\n",
       "      <td>-0.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-01</th>\n",
       "      <td>-0.71</td>\n",
       "      <td>0.37</td>\n",
       "      <td>-0.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-01</th>\n",
       "      <td>-0.69</td>\n",
       "      <td>0.58</td>\n",
       "      <td>-0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-01</th>\n",
       "      <td>-0.73</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-0.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-01</th>\n",
       "      <td>-0.76</td>\n",
       "      <td>0.45</td>\n",
       "      <td>-0.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-01</th>\n",
       "      <td>-0.77</td>\n",
       "      <td>0.48</td>\n",
       "      <td>-0.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-01</th>\n",
       "      <td>-0.78</td>\n",
       "      <td>0.43</td>\n",
       "      <td>-0.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-01</th>\n",
       "      <td>-0.80</td>\n",
       "      <td>0.42</td>\n",
       "      <td>-0.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>-0.66</td>\n",
       "      <td>0.61</td>\n",
       "      <td>-0.08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "MATURITY                                                                                 Maturity: 1 year  \\\n",
       "BONDS                                                        AAA rated euro area central government bonds   \n",
       "CURV_TYP                                                                Zero-coupon yield curve spot rate   \n",
       "GEO         Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)   \n",
       "FREQ                                                                                              Monthly   \n",
       "TIME_PERIOD                                                                                                 \n",
       "2017-02-01                                               -0.81                                              \n",
       "2017-03-01                                               -0.84                                              \n",
       "2017-04-01                                               -0.80                                              \n",
       "2017-05-01                                               -0.73                                              \n",
       "2017-06-01                                               -0.71                                              \n",
       "2017-07-01                                               -0.69                                              \n",
       "2017-08-01                                               -0.73                                              \n",
       "2017-09-01                                               -0.76                                              \n",
       "2017-10-01                                               -0.77                                              \n",
       "2017-11-01                                               -0.78                                              \n",
       "2017-12-01                                               -0.80                                              \n",
       "2018-01-01                                               -0.66                                              \n",
       "\n",
       "MATURITY                                                                               Maturity: 10 years  \\\n",
       "BONDS                                                        AAA rated euro area central government bonds   \n",
       "CURV_TYP                                                                Zero-coupon yield curve spot rate   \n",
       "GEO         Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)   \n",
       "FREQ                                                                                              Monthly   \n",
       "TIME_PERIOD                                                                                                 \n",
       "2017-02-01                                                0.38                                              \n",
       "2017-03-01                                                0.43                                              \n",
       "2017-04-01                                                0.32                                              \n",
       "2017-05-01                                                0.44                                              \n",
       "2017-06-01                                                0.37                                              \n",
       "2017-07-01                                                0.58                                              \n",
       "2017-08-01                                                0.45                                              \n",
       "2017-09-01                                                0.45                                              \n",
       "2017-10-01                                                0.48                                              \n",
       "2017-11-01                                                0.43                                              \n",
       "2017-12-01                                                0.42                                              \n",
       "2018-01-01                                                0.61                                              \n",
       "\n",
       "MATURITY                                                                                Maturity: 5 years  \n",
       "BONDS                                                        AAA rated euro area central government bonds  \n",
       "CURV_TYP                                                                Zero-coupon yield curve spot rate  \n",
       "GEO         Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)  \n",
       "FREQ                                                                                              Monthly  \n",
       "TIME_PERIOD                                                                                                \n",
       "2017-02-01                                               -0.43                                             \n",
       "2017-03-01                                               -0.35                                             \n",
       "2017-04-01                                               -0.42                                             \n",
       "2017-05-01                                               -0.31                                             \n",
       "2017-06-01                                               -0.34                                             \n",
       "2017-07-01                                               -0.18                                             \n",
       "2017-08-01                                               -0.29                                             \n",
       "2017-09-01                                               -0.31                                             \n",
       "2017-10-01                                               -0.28                                             \n",
       "2017-11-01                                               -0.32                                             \n",
       "2017-12-01                                               -0.27                                             \n",
       "2018-01-01                                               -0.08                                             "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "eu2 = web.DataReader('teimf050', 'eurostat', '1900')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th>INTRT</th>\n",
       "      <th colspan=\"21\" halign=\"left\">EMU convergence criterion bond yields</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GEO</th>\n",
       "      <th>Austria</th>\n",
       "      <th>Belgium</th>\n",
       "      <th>Bulgaria</th>\n",
       "      <th>Cyprus</th>\n",
       "      <th>Czech Republic</th>\n",
       "      <th>Germany (until 1990 former territory of the FRG)</th>\n",
       "      <th>Denmark</th>\n",
       "      <th>Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)</th>\n",
       "      <th>Estonia</th>\n",
       "      <th>Greece</th>\n",
       "      <th>...</th>\n",
       "      <th>Latvia</th>\n",
       "      <th>Malta</th>\n",
       "      <th>Netherlands</th>\n",
       "      <th>Poland</th>\n",
       "      <th>Portugal</th>\n",
       "      <th>Romania</th>\n",
       "      <th>Sweden</th>\n",
       "      <th>Slovenia</th>\n",
       "      <th>Slovakia</th>\n",
       "      <th>United Kingdom</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FREQ</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>...</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "      <th>Monthly</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIME_PERIOD</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>0.57</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1.77</td>\n",
       "      <td>3.45</td>\n",
       "      <td>0.47</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.37</td>\n",
       "      <td>1.10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.04</td>\n",
       "      <td>...</td>\n",
       "      <td>0.89</td>\n",
       "      <td>1.17</td>\n",
       "      <td>0.48</td>\n",
       "      <td>3.68</td>\n",
       "      <td>3.95</td>\n",
       "      <td>3.75</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.03</td>\n",
       "      <td>1.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-01</th>\n",
       "      <td>0.59</td>\n",
       "      <td>0.87</td>\n",
       "      <td>1.75</td>\n",
       "      <td>3.37</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.33</td>\n",
       "      <td>1.24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.52</td>\n",
       "      <td>...</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.32</td>\n",
       "      <td>0.49</td>\n",
       "      <td>3.81</td>\n",
       "      <td>4.04</td>\n",
       "      <td>3.96</td>\n",
       "      <td>0.66</td>\n",
       "      <td>1.01</td>\n",
       "      <td>1.09</td>\n",
       "      <td>1.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-01</th>\n",
       "      <td>0.59</td>\n",
       "      <td>0.87</td>\n",
       "      <td>1.73</td>\n",
       "      <td>3.34</td>\n",
       "      <td>0.87</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.19</td>\n",
       "      <td>1.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.17</td>\n",
       "      <td>...</td>\n",
       "      <td>0.94</td>\n",
       "      <td>1.55</td>\n",
       "      <td>0.49</td>\n",
       "      <td>3.66</td>\n",
       "      <td>3.99</td>\n",
       "      <td>3.99</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1.09</td>\n",
       "      <td>1.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-01</th>\n",
       "      <td>0.49</td>\n",
       "      <td>0.78</td>\n",
       "      <td>1.78</td>\n",
       "      <td>3.23</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.55</td>\n",
       "      <td>1.14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.70</td>\n",
       "      <td>...</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.43</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3.42</td>\n",
       "      <td>3.77</td>\n",
       "      <td>3.79</td>\n",
       "      <td>0.57</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.06</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-01</th>\n",
       "      <td>0.65</td>\n",
       "      <td>0.77</td>\n",
       "      <td>1.74</td>\n",
       "      <td>3.03</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.64</td>\n",
       "      <td>1.13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.86</td>\n",
       "      <td>...</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1.37</td>\n",
       "      <td>0.59</td>\n",
       "      <td>3.35</td>\n",
       "      <td>3.29</td>\n",
       "      <td>3.75</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.03</td>\n",
       "      <td>1.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-01</th>\n",
       "      <td>0.55</td>\n",
       "      <td>0.62</td>\n",
       "      <td>1.70</td>\n",
       "      <td>2.84</td>\n",
       "      <td>0.77</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.53</td>\n",
       "      <td>1.01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.76</td>\n",
       "      <td>...</td>\n",
       "      <td>0.85</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.50</td>\n",
       "      <td>3.19</td>\n",
       "      <td>2.97</td>\n",
       "      <td>3.67</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-01</th>\n",
       "      <td>0.73</td>\n",
       "      <td>0.83</td>\n",
       "      <td>1.65</td>\n",
       "      <td>2.57</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.67</td>\n",
       "      <td>1.18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.33</td>\n",
       "      <td>...</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.36</td>\n",
       "      <td>0.69</td>\n",
       "      <td>3.30</td>\n",
       "      <td>3.03</td>\n",
       "      <td>3.84</td>\n",
       "      <td>0.66</td>\n",
       "      <td>1.15</td>\n",
       "      <td>0.93</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-01</th>\n",
       "      <td>0.61</td>\n",
       "      <td>0.73</td>\n",
       "      <td>1.70</td>\n",
       "      <td>2.49</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.55</td>\n",
       "      <td>1.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.55</td>\n",
       "      <td>...</td>\n",
       "      <td>0.85</td>\n",
       "      <td>1.23</td>\n",
       "      <td>0.54</td>\n",
       "      <td>3.33</td>\n",
       "      <td>2.83</td>\n",
       "      <td>3.86</td>\n",
       "      <td>0.63</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.83</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-01</th>\n",
       "      <td>0.59</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1.66</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.51</td>\n",
       "      <td>1.06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.56</td>\n",
       "      <td>...</td>\n",
       "      <td>0.72</td>\n",
       "      <td>1.26</td>\n",
       "      <td>0.53</td>\n",
       "      <td>3.26</td>\n",
       "      <td>2.63</td>\n",
       "      <td>3.89</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.82</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-01</th>\n",
       "      <td>0.61</td>\n",
       "      <td>0.69</td>\n",
       "      <td>1.40</td>\n",
       "      <td>1.84</td>\n",
       "      <td>1.45</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.53</td>\n",
       "      <td>1.08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.59</td>\n",
       "      <td>...</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1.24</td>\n",
       "      <td>0.54</td>\n",
       "      <td>3.38</td>\n",
       "      <td>2.32</td>\n",
       "      <td>4.17</td>\n",
       "      <td>0.83</td>\n",
       "      <td>0.97</td>\n",
       "      <td>0.83</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-01</th>\n",
       "      <td>0.51</td>\n",
       "      <td>0.58</td>\n",
       "      <td>1.33</td>\n",
       "      <td>1.54</td>\n",
       "      <td>1.68</td>\n",
       "      <td>0.31</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.22</td>\n",
       "      <td>...</td>\n",
       "      <td>0.69</td>\n",
       "      <td>1.13</td>\n",
       "      <td>0.47</td>\n",
       "      <td>3.39</td>\n",
       "      <td>1.98</td>\n",
       "      <td>4.43</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.76</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-01</th>\n",
       "      <td>0.50</td>\n",
       "      <td>0.53</td>\n",
       "      <td>1.02</td>\n",
       "      <td>1.58</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.30</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.91</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.44</td>\n",
       "      <td>...</td>\n",
       "      <td>0.59</td>\n",
       "      <td>1.07</td>\n",
       "      <td>0.45</td>\n",
       "      <td>3.27</td>\n",
       "      <td>1.83</td>\n",
       "      <td>4.38</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.67</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "INTRT       EMU convergence criterion bond yields                           \\\n",
       "GEO                                       Austria Belgium Bulgaria  Cyprus   \n",
       "FREQ                                      Monthly Monthly  Monthly Monthly   \n",
       "TIME_PERIOD                                                                  \n",
       "2017-01-01                                   0.57    0.70     1.77    3.45   \n",
       "2017-02-01                                   0.59    0.87     1.75    3.37   \n",
       "2017-03-01                                   0.59    0.87     1.73    3.34   \n",
       "2017-04-01                                   0.49    0.78     1.78    3.23   \n",
       "2017-05-01                                   0.65    0.77     1.74    3.03   \n",
       "2017-06-01                                   0.55    0.62     1.70    2.84   \n",
       "2017-07-01                                   0.73    0.83     1.65    2.57   \n",
       "2017-08-01                                   0.61    0.73     1.70    2.49   \n",
       "2017-09-01                                   0.59    0.70     1.66    2.20   \n",
       "2017-10-01                                   0.61    0.69     1.40    1.84   \n",
       "2017-11-01                                   0.51    0.58     1.33    1.54   \n",
       "2017-12-01                                   0.50    0.53     1.02    1.58   \n",
       "\n",
       "INTRT                                                                        \\\n",
       "GEO         Czech Republic Germany (until 1990 former territory of the FRG)   \n",
       "FREQ               Monthly                                          Monthly   \n",
       "TIME_PERIOD                                                                   \n",
       "2017-01-01            0.47                                             0.25   \n",
       "2017-02-01            0.63                                             0.26   \n",
       "2017-03-01            0.87                                             0.35   \n",
       "2017-04-01            0.96                                             0.22   \n",
       "2017-05-01            0.74                                             0.34   \n",
       "2017-06-01            0.77                                             0.25   \n",
       "2017-07-01            0.90                                             0.46   \n",
       "2017-08-01            0.83                                             0.35   \n",
       "2017-09-01            0.97                                             0.35   \n",
       "2017-10-01            1.45                                             0.37   \n",
       "2017-11-01            1.68                                             0.31   \n",
       "2017-12-01            1.50                                             0.30   \n",
       "\n",
       "INTRT                \\\n",
       "GEO         Denmark   \n",
       "FREQ        Monthly   \n",
       "TIME_PERIOD           \n",
       "2017-01-01     0.37   \n",
       "2017-02-01     0.33   \n",
       "2017-03-01     0.19   \n",
       "2017-04-01     0.55   \n",
       "2017-05-01     0.64   \n",
       "2017-06-01     0.53   \n",
       "2017-07-01     0.67   \n",
       "2017-08-01     0.55   \n",
       "2017-09-01     0.51   \n",
       "2017-10-01     0.53   \n",
       "2017-11-01     0.44   \n",
       "2017-12-01     0.41   \n",
       "\n",
       "INTRT                                                                                                      \\\n",
       "GEO         Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)   \n",
       "FREQ                                                                                              Monthly   \n",
       "TIME_PERIOD                                                                                                 \n",
       "2017-01-01                                                1.10                                              \n",
       "2017-02-01                                                1.24                                              \n",
       "2017-03-01                                                1.27                                              \n",
       "2017-04-01                                                1.14                                              \n",
       "2017-05-01                                                1.13                                              \n",
       "2017-06-01                                                1.01                                              \n",
       "2017-07-01                                                1.18                                              \n",
       "2017-08-01                                                1.06                                              \n",
       "2017-09-01                                                1.06                                              \n",
       "2017-10-01                                                1.08                                              \n",
       "2017-11-01                                                0.95                                              \n",
       "2017-12-01                                                0.91                                              \n",
       "\n",
       "INTRT                            ...                                    \\\n",
       "GEO         Estonia  Greece      ...        Latvia   Malta Netherlands   \n",
       "FREQ        Monthly Monthly      ...       Monthly Monthly     Monthly   \n",
       "TIME_PERIOD                      ...                                     \n",
       "2017-01-01      NaN    7.04      ...          0.89    1.17        0.48   \n",
       "2017-02-01      NaN    7.52      ...          0.99    1.32        0.49   \n",
       "2017-03-01      NaN    7.17      ...          0.94    1.55        0.49   \n",
       "2017-04-01      NaN    6.70      ...          0.92    1.43        0.50   \n",
       "2017-05-01      NaN    5.86      ...          0.88    1.37        0.59   \n",
       "2017-06-01      NaN    5.76      ...          0.85    1.25        0.50   \n",
       "2017-07-01      NaN    5.33      ...          0.98    1.36        0.69   \n",
       "2017-08-01      NaN    5.55      ...          0.85    1.23        0.54   \n",
       "2017-09-01      NaN    5.56      ...          0.72    1.26        0.53   \n",
       "2017-10-01      NaN    5.59      ...          0.71    1.24        0.54   \n",
       "2017-11-01      NaN    5.22      ...          0.69    1.13        0.47   \n",
       "2017-12-01      NaN    4.44      ...          0.59    1.07        0.45   \n",
       "\n",
       "INTRT                                                                          \n",
       "GEO          Poland Portugal Romania  Sweden Slovenia Slovakia United Kingdom  \n",
       "FREQ        Monthly  Monthly Monthly Monthly  Monthly  Monthly        Monthly  \n",
       "TIME_PERIOD                                                                    \n",
       "2017-01-01     3.68     3.95    3.75    0.65     0.99     1.03           1.38  \n",
       "2017-02-01     3.81     4.04    3.96    0.66     1.01     1.09           1.24  \n",
       "2017-03-01     3.66     3.99    3.99    0.69     0.99     1.09           1.13  \n",
       "2017-04-01     3.42     3.77    3.79    0.57     1.00     1.06           1.00  \n",
       "2017-05-01     3.35     3.29    3.75    0.56     0.98     1.03           1.03  \n",
       "2017-06-01     3.19     2.97    3.67    0.46     0.86     0.86           0.98  \n",
       "2017-07-01     3.30     3.03    3.84    0.66     1.15     0.93            NaN  \n",
       "2017-08-01     3.33     2.83    3.86    0.63     1.09     0.83            NaN  \n",
       "2017-09-01     3.26     2.63    3.89    0.62     0.98     0.82            NaN  \n",
       "2017-10-01     3.38     2.32    4.17    0.83     0.97     0.83            NaN  \n",
       "2017-11-01     3.39     1.98    4.43    0.76     0.81     0.76            NaN  \n",
       "2017-12-01     3.27     1.83    4.38    0.72     0.69     0.67            NaN  \n",
       "\n",
       "[12 rows x 31 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eu2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MultiIndex(levels=[['EMU convergence criterion bond yields'], ['Austria', 'Belgium', 'Bulgaria', 'Croatia', 'Cyprus', 'Czech Republic', 'Denmark', 'Estonia', 'Euro area (EA11-2000, EA12-2006, EA13-2007, EA15-2008, EA16-2010, EA17-2013, EA18-2014, EA19)', 'European Union (27 countries)', 'European Union (28 countries)', 'Finland', 'France', 'Germany (until 1990 former territory of the FRG)', 'Greece', 'Hungary', 'Ireland', 'Italy', 'Latvia', 'Lithuania', 'Luxembourg', 'Malta', 'Netherlands', 'Poland', 'Portugal', 'Romania', 'Slovakia', 'Slovenia', 'Spain', 'Sweden', 'United Kingdom'], ['Monthly']],\n",
       "           labels=[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 2, 4, 5, 13, 6, 8, 7, 14, 28, 9, 10, 11, 12, 3, 15, 16, 17, 19, 20, 18, 21, 22, 23, 24, 25, 29, 27, 26, 30], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]],\n",
       "           names=['INTRT', 'GEO', 'FREQ'])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eu2.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## pandas_datareaderを使って分析を作ってみる\n",
    "* FRB議長が交代する時に、新議長を試すために市場が荒れることがよくあるそうな。\n",
    "* 幾つかの指標を使ってみてみます！\n",
    "* 参考　　wikipedia 連邦準備制度　https://ja.wikipedia.org/wiki/%E9%80%A3%E9%82%A6%E6%BA%96%E5%82%99%E5%88%B6%E5%BA%A6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "chair_p = {}\n",
    "chair_p = pd.DataFrame(chair_p)\n",
    "chair_p['name'] = ['Charles Hamlin', 'William Harding', 'Daniel Crissinger', 'Roy Young', 'Eugene Meyer', \\\n",
    "                  'Eugene Black', 'Marriner Eccles', 'Thomas McCabe', 'William Martin', 'Authur Burns', \\\n",
    "                  'William Miller', 'Paul Volker', 'Alan Greenspan', 'Ben Bernanke', 'Janet Yellen', 'Jerome Powell']\n",
    "chair_p['start'] = [datetime(1914,8,10), datetime(1916,8,10), datetime(1923,5,1), datetime(1927,10,4), \\\n",
    "                   datetime(1930,9,16), datetime(1933,5,19), datetime(1934,11,15), datetime(1948,4,15), \\\n",
    "                   datetime(1951,4,2), datetime(1970,2,2), datetime(1978,3,8), datetime(1979,8,6), \\\n",
    "                   datetime(1987,8,11), datetime(2006,2,1), datetime(2014,2,3), datetime(2018,2,5)]\n",
    "chair_p['end'] = [datetime(1916,8,10), datetime(1922,8,9), datetime(1927,9,15), datetime(1930,8,30), \\\n",
    "                 datetime(1933,5,10),datetime(1934,8,15), datetime(1948,1,31), datetime(1951,3,31), \\\n",
    "                 datetime(1970,1,31), datetime(1978,1,31), datetime(1979,8,6), datetime(1987,8,11), \\\n",
    "                 datetime(2006,1,31), datetime(2014,1,31), datetime(2018,2,5), '-']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>name</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Charles Hamlin</td>\n",
       "      <td>1914-08-10</td>\n",
       "      <td>1916-08-10 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>William Harding</td>\n",
       "      <td>1916-08-10</td>\n",
       "      <td>1922-08-09 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Daniel Crissinger</td>\n",
       "      <td>1923-05-01</td>\n",
       "      <td>1927-09-15 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Roy Young</td>\n",
       "      <td>1927-10-04</td>\n",
       "      <td>1930-08-30 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eugene Meyer</td>\n",
       "      <td>1930-09-16</td>\n",
       "      <td>1933-05-10 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Eugene Black</td>\n",
       "      <td>1933-05-19</td>\n",
       "      <td>1934-08-15 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Marriner Eccles</td>\n",
       "      <td>1934-11-15</td>\n",
       "      <td>1948-01-31 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Thomas McCabe</td>\n",
       "      <td>1948-04-15</td>\n",
       "      <td>1951-03-31 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>William Martin</td>\n",
       "      <td>1951-04-02</td>\n",
       "      <td>1970-01-31 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Authur Burns</td>\n",
       "      <td>1970-02-02</td>\n",
       "      <td>1978-01-31 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>William Miller</td>\n",
       "      <td>1978-03-08</td>\n",
       "      <td>1979-08-06 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Paul Volker</td>\n",
       "      <td>1979-08-06</td>\n",
       "      <td>1987-08-11 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Alan Greenspan</td>\n",
       "      <td>1987-08-11</td>\n",
       "      <td>2006-01-31 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Ben Bernanke</td>\n",
       "      <td>2006-02-01</td>\n",
       "      <td>2014-01-31 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>2014-02-03</td>\n",
       "      <td>2018-02-05 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Jerome Powell</td>\n",
       "      <td>2018-02-05</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 name      start                  end\n",
       "0      Charles Hamlin 1914-08-10  1916-08-10 00:00:00\n",
       "1     William Harding 1916-08-10  1922-08-09 00:00:00\n",
       "2   Daniel Crissinger 1923-05-01  1927-09-15 00:00:00\n",
       "3           Roy Young 1927-10-04  1930-08-30 00:00:00\n",
       "4        Eugene Meyer 1930-09-16  1933-05-10 00:00:00\n",
       "5        Eugene Black 1933-05-19  1934-08-15 00:00:00\n",
       "6     Marriner Eccles 1934-11-15  1948-01-31 00:00:00\n",
       "7       Thomas McCabe 1948-04-15  1951-03-31 00:00:00\n",
       "8      William Martin 1951-04-02  1970-01-31 00:00:00\n",
       "9        Authur Burns 1970-02-02  1978-01-31 00:00:00\n",
       "10     William Miller 1978-03-08  1979-08-06 00:00:00\n",
       "11        Paul Volker 1979-08-06  1987-08-11 00:00:00\n",
       "12     Alan Greenspan 1987-08-11  2006-01-31 00:00:00\n",
       "13       Ben Bernanke 2006-02-01  2014-01-31 00:00:00\n",
       "14       Janet Yellen 2014-02-03  2018-02-05 00:00:00\n",
       "15      Jerome Powell 2018-02-05                    -"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chair_p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "chair_p['before_365'] = 0\n",
    "chair_p['after_365'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(len(chair_p)):\n",
    "    a = chair_p.iloc[i, 1] - timedelta(days=365)\n",
    "    b = chair_p.iloc[i, 1] + timedelta(days=365)\n",
    "    chair_p.iloc[i, 3] = '{}-{}'.format(a.year, a.month)\n",
    "    chair_p.iloc[i, 4] = '{}-{}'.format(b.year, b.month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>name</th>\n",
       "      <th>start</th>\n",
       "      <th>end</th>\n",
       "      <th>before_365</th>\n",
       "      <th>after_365</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Charles Hamlin</td>\n",
       "      <td>1914-08-10</td>\n",
       "      <td>1916-08-10 00:00:00</td>\n",
       "      <td>1913-8</td>\n",
       "      <td>1915-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>William Harding</td>\n",
       "      <td>1916-08-10</td>\n",
       "      <td>1922-08-09 00:00:00</td>\n",
       "      <td>1915-8</td>\n",
       "      <td>1917-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Daniel Crissinger</td>\n",
       "      <td>1923-05-01</td>\n",
       "      <td>1927-09-15 00:00:00</td>\n",
       "      <td>1922-5</td>\n",
       "      <td>1924-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Roy Young</td>\n",
       "      <td>1927-10-04</td>\n",
       "      <td>1930-08-30 00:00:00</td>\n",
       "      <td>1926-10</td>\n",
       "      <td>1928-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Eugene Meyer</td>\n",
       "      <td>1930-09-16</td>\n",
       "      <td>1933-05-10 00:00:00</td>\n",
       "      <td>1929-9</td>\n",
       "      <td>1931-9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Eugene Black</td>\n",
       "      <td>1933-05-19</td>\n",
       "      <td>1934-08-15 00:00:00</td>\n",
       "      <td>1932-5</td>\n",
       "      <td>1934-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Marriner Eccles</td>\n",
       "      <td>1934-11-15</td>\n",
       "      <td>1948-01-31 00:00:00</td>\n",
       "      <td>1933-11</td>\n",
       "      <td>1935-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Thomas McCabe</td>\n",
       "      <td>1948-04-15</td>\n",
       "      <td>1951-03-31 00:00:00</td>\n",
       "      <td>1947-4</td>\n",
       "      <td>1949-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>William Martin</td>\n",
       "      <td>1951-04-02</td>\n",
       "      <td>1970-01-31 00:00:00</td>\n",
       "      <td>1950-4</td>\n",
       "      <td>1952-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Authur Burns</td>\n",
       "      <td>1970-02-02</td>\n",
       "      <td>1978-01-31 00:00:00</td>\n",
       "      <td>1969-2</td>\n",
       "      <td>1971-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>William Miller</td>\n",
       "      <td>1978-03-08</td>\n",
       "      <td>1979-08-06 00:00:00</td>\n",
       "      <td>1977-3</td>\n",
       "      <td>1979-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Paul Volker</td>\n",
       "      <td>1979-08-06</td>\n",
       "      <td>1987-08-11 00:00:00</td>\n",
       "      <td>1978-8</td>\n",
       "      <td>1980-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Alan Greenspan</td>\n",
       "      <td>1987-08-11</td>\n",
       "      <td>2006-01-31 00:00:00</td>\n",
       "      <td>1986-8</td>\n",
       "      <td>1988-8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Ben Bernanke</td>\n",
       "      <td>2006-02-01</td>\n",
       "      <td>2014-01-31 00:00:00</td>\n",
       "      <td>2005-2</td>\n",
       "      <td>2007-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>2014-02-03</td>\n",
       "      <td>2018-02-05 00:00:00</td>\n",
       "      <td>2013-2</td>\n",
       "      <td>2015-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Jerome Powell</td>\n",
       "      <td>2018-02-05</td>\n",
       "      <td>-</td>\n",
       "      <td>2017-2</td>\n",
       "      <td>2019-2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 name      start                  end before_365 after_365\n",
       "0      Charles Hamlin 1914-08-10  1916-08-10 00:00:00     1913-8    1915-8\n",
       "1     William Harding 1916-08-10  1922-08-09 00:00:00     1915-8    1917-8\n",
       "2   Daniel Crissinger 1923-05-01  1927-09-15 00:00:00     1922-5    1924-4\n",
       "3           Roy Young 1927-10-04  1930-08-30 00:00:00    1926-10   1928-10\n",
       "4        Eugene Meyer 1930-09-16  1933-05-10 00:00:00     1929-9    1931-9\n",
       "5        Eugene Black 1933-05-19  1934-08-15 00:00:00     1932-5    1934-5\n",
       "6     Marriner Eccles 1934-11-15  1948-01-31 00:00:00    1933-11   1935-11\n",
       "7       Thomas McCabe 1948-04-15  1951-03-31 00:00:00     1947-4    1949-4\n",
       "8      William Martin 1951-04-02  1970-01-31 00:00:00     1950-4    1952-4\n",
       "9        Authur Burns 1970-02-02  1978-01-31 00:00:00     1969-2    1971-2\n",
       "10     William Miller 1978-03-08  1979-08-06 00:00:00     1977-3    1979-3\n",
       "11        Paul Volker 1979-08-06  1987-08-11 00:00:00     1978-8    1980-8\n",
       "12     Alan Greenspan 1987-08-11  2006-01-31 00:00:00     1986-8    1988-8\n",
       "13       Ben Bernanke 2006-02-01  2014-01-31 00:00:00     2005-2    2007-2\n",
       "14       Janet Yellen 2014-02-03  2018-02-05 00:00:00     2013-2    2015-2\n",
       "15      Jerome Powell 2018-02-05                    -     2017-2    2019-2"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chair_p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "spx = web.DataReader('^SPX', 'stooq')\n",
    "spx = spx.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Open      1.782680e+03\n",
       "High      1.784830e+03\n",
       "Low       1.739660e+03\n",
       "Close     1.741890e+03\n",
       "Volume    7.444766e+08\n",
       "Name: 2014-02-03 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spx.loc['2014-02-03']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1789-05-01</th>\n",
       "      <td>0.51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1789-06-01</th>\n",
       "      <td>0.51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1789-07-01</th>\n",
       "      <td>0.50</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.50</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1789-08-01</th>\n",
       "      <td>0.50</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.51</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1789-09-01</th>\n",
       "      <td>0.51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.51</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Open  High   Low  Close  Volume\n",
       "Date                                       \n",
       "1789-05-01  0.51  0.51  0.51   0.51     NaN\n",
       "1789-06-01  0.51  0.51  0.51   0.51     NaN\n",
       "1789-07-01  0.50  0.50  0.50   0.50     NaN\n",
       "1789-08-01  0.50  0.51  0.50   0.51     NaN\n",
       "1789-09-01  0.51  0.51  0.50   0.51     NaN"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spx.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## S&P500指数の1941年からの算出なのになんてこった！！\n",
    "https://ja.wikipedia.org/wiki/S%26P_500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "spx = spx['1941':]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1941-01-02</th>\n",
       "      <td>10.52</td>\n",
       "      <td>10.58</td>\n",
       "      <td>10.46</td>\n",
       "      <td>10.48</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1941-01-03</th>\n",
       "      <td>10.61</td>\n",
       "      <td>10.74</td>\n",
       "      <td>10.57</td>\n",
       "      <td>10.72</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1941-01-04</th>\n",
       "      <td>10.69</td>\n",
       "      <td>10.78</td>\n",
       "      <td>10.69</td>\n",
       "      <td>10.72</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1941-01-06</th>\n",
       "      <td>10.71</td>\n",
       "      <td>10.81</td>\n",
       "      <td>10.71</td>\n",
       "      <td>10.74</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1941-01-07</th>\n",
       "      <td>10.73</td>\n",
       "      <td>10.79</td>\n",
       "      <td>10.69</td>\n",
       "      <td>10.75</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open   High    Low  Close  Volume\n",
       "Date                                          \n",
       "1941-01-02  10.52  10.58  10.46  10.48     NaN\n",
       "1941-01-03  10.61  10.74  10.57  10.72     NaN\n",
       "1941-01-04  10.69  10.78  10.69  10.72     NaN\n",
       "1941-01-06  10.71  10.81  10.71  10.74     NaN\n",
       "1941-01-07  10.73  10.79  10.69  10.75     NaN"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spx.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "spx7 = spx[chair_p.iloc[7,3]:chair_p.iloc[7,4]] / spx.loc[chair_p.iloc[7,1], 'Close'] * 100\n",
    "spx8 = spx[chair_p.iloc[8,3]:chair_p.iloc[8,4]] / spx.loc[chair_p.iloc[8,1], 'Close'] * 100\n",
    "spx9 = spx[chair_p.iloc[9,3]:chair_p.iloc[9,4]] / spx.loc[chair_p.iloc[9,1], 'Close'] * 100\n",
    "spx10 = spx[chair_p.iloc[10,3]:chair_p.iloc[10,4]] / spx.loc[chair_p.iloc[10,1], 'Close'] * 100\n",
    "spx11 = spx[chair_p.iloc[11,3]:chair_p.iloc[11,4]] / spx.loc[chair_p.iloc[11,1], 'Close'] * 100\n",
    "spx12 = spx[chair_p.iloc[12,3]:chair_p.iloc[12,4]] / spx.loc[chair_p.iloc[12,1], 'Close'] * 100\n",
    "spx13 = spx[chair_p.iloc[13,3]:chair_p.iloc[13,4]] / spx.loc[chair_p.iloc[13,1], 'Close'] * 100\n",
    "spx14 = spx[chair_p.iloc[14,3]:chair_p.iloc[14,4]] / spx.loc[chair_p.iloc[14,1], 'Close'] * 100\n",
    "spx15 = spx[chair_p.iloc[15,3]:chair_p.iloc[15,4]] / spx.loc[chair_p.iloc[15,1], 'Close'] * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "spx7.index = spx7.index - chair_p.iloc[7,1]\n",
    "spx8.index = spx8.index - chair_p.iloc[8,1]\n",
    "spx9.index = spx9.index - chair_p.iloc[9,1]\n",
    "spx10.index = spx10.index - chair_p.iloc[10,1]\n",
    "spx11.index = spx11.index - chair_p.iloc[11,1]\n",
    "spx12.index = spx12.index - chair_p.iloc[12,1]\n",
    "spx13.index = spx13.index - chair_p.iloc[13,1]\n",
    "spx14.index = spx14.index - chair_p.iloc[14,1]\n",
    "spx15.index = spx15.index - chair_p.iloc[15,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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       "    <div class=\"bk-plotdiv\" id=\"fe663196-7e32-4aed-bbd5-69df66fe4865\"></div>\n",
       "</div>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
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       "    var render_items = [{\"docid\":\"03e2f3f2-acbd-4ec1-b755-9de9bf94c94f\",\"elementid\":\"fe663196-7e32-4aed-bbd5-69df66fe4865\",\"modelid\":\"745c43f8-5236-4fe9-b170-5c6bfd2dd5ca\"}];\n",
       "\n",
       "    root.Bokeh.embed.embed_items(docs_json, render_items);\n",
       "  }\n",
       "\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        embed_document(root);\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "      attempts++;\n",
       "      if (attempts > 100) {\n",
       "        console.log(\"Bokeh: ERROR: Unable to embed document because BokehJS library is missing\")\n",
       "        clearInterval(timer);\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "745c43f8-5236-4fe9-b170-5c6bfd2dd5ca"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = figure(width=700, height = 500, title='FRB議長交代１年前後の株価の動き')\n",
    "\n",
    "p.line(spx7.index, spx7.Close, legend='McCabe', line_color=Spectral8[0])\n",
    "p.line(spx8.index, spx8.Close, legend='Martin', line_color=Spectral8[1])\n",
    "p.line(spx9.index, spx9.Close, legend='Burns', line_color=Spectral8[2])\n",
    "p.line(spx10.index, spx10.Close, legend='Miller', line_color=Spectral8[3])\n",
    "p.line(spx11.index, spx11.Close, legend='Volker', line_color=Spectral8[4])\n",
    "p.line(spx12.index, spx12.Close, legend='Greenspan', line_color=Spectral8[5])\n",
    "p.line(spx13.index, spx13.Close, legend='Bernanke',line_color=Spectral8[6])\n",
    "p.line(spx14.index, spx14.Close, legend='Yellen', line_color=Spectral8[7])\n",
    "p.line(spx15.index, spx15.Close, legend='Powell', line_color='black', line_width=3)\n",
    "\n",
    "p.legend.location = 'bottom_left'\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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