Tutorial.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Notebooks Tutorial\n",
    "\n",
    "Welcome to Notebooks.ai ❤️, a fully online 🤖, cloud-based ☁️ Data Science environment. All your work, analysis and datasets organized in the same place 🙌.\n",
    "\n",
    "##### Objective of this tutorial:\n",
    "\n",
    "> **Help you get started with Notebooks.ai for Data Science and Python programming.**\n",
    "\n",
    "_Need help? Create an [issue](https://github.com/notebooks-ai/notebooks-help)._\n",
    "\n",
    "## Jupyter Notebooks\n",
    "\n",
    "This document that you're currently reading is a \"Jupyter Notebook\", and you've probably heard about it before. It's like a text document, but you can run code on it! It can also display inline graphs, pull data from Databases or show excel spreadsheets live! Isn't it amazing? 😄 \n",
    "\n",
    "**Mildly interesting fact of the day:**\n",
    "\n",
    "> _Jupyter is a nod to 3 languages: Julia, Python, and R._ Source [@jakevdp](https://twitter.com/jakevdp/status/1033071052652302336).\n",
    "\n",
    "This is a really quick tutorial on how to get started with Jupyter notebooks (and lab). It shouldn't take more than 10 minutes and you'll be writing Python code right away.\n",
    "\n",
    "### Part 1: everything is a _cell_\n",
    "\n",
    "Jupyter Notebooks are organized as a set of _\"cells\"_. Each cell can contain different types of content: like Python code (or R, Julia, etc), images or even human readable text (markdown), like the one you're currently reading.\n",
    "\n",
    "I've left a couple of empty cells below for you to see them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is another cell containing Markdown (human readable) code. And below, another empty cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can edit these cells just by double clicking on them. Try editing the following cell:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**👉 Double click on me 👈**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you double click the cell, it should open an \"edit mode\", and you should see something similar to:\n",
    "\n",
    "![image](images/_1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you're seeing those asterisks, it's because you've correctly entered \"Edit Mode\". Once you've made the changes, you have to \"execute\", or \"run\" the cell to reflect the changes. To do that just click on the little _play_ button on the top menu bar:\n",
    "\n",
    "![image](images/_2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Jupyter notebooks are optimized for an efficient workflow. There are many keyboard shortcuts that will let you interact with your documents, run code and make other changes; mastering these shortcuts will speed up your work. For example, there are two shortcuts to execute a cell:\n",
    "\n",
    "1. `shift + return`: Run cell and advance to the next one.\n",
    "2. `ctrl  + return`: Run the cell but don't change focus.\n",
    "\n",
    "\n",
    "Try them with the following cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2 + 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can try executing these cells as many times as you want, it won't break anything"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### `ctrl + Return` effect:\n",
    "\n",
    "As you can see in the following animation, the code is correctly executed (it returns 4) and the focus (the blue line at the left side of the cell) stays in the same cell.\n",
    "\n",
    "![ctrl+enter effect](images/_3.gif)\n",
    "\n",
    "Now compare it to the next shortcut, `shift + return`:\n",
    "\n",
    "#### `shift + Return` effect:\n",
    "\n",
    "![shift+enter effect](images/_4.gif)\n",
    "\n",
    "As you can see, every time I execute code the focus changes to the cell below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 2: Working with code\n",
    "\n",
    "Jupyter notebooks have amazing features to include text and images and create beautiful, human readable documents as you've just seen. But their main benefit is working with code. Now we're going to import a few libraries and start experimenting with Python code. We've already done the simple `2 + 2` before, so let's do something a little bit more interesting. First, we need to import `numpy` and `matplotlib`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notebooks.ai include all the most popular Data Science and Deep Learning libraries already installed. And even if there's one missing, you can always install it in your own environment (more on that later). We've just imported these two libraries:\n",
    "* `numpy` the most popular Python library for array manipulation and numeric computing\n",
    "* `matplotlib` the most popular visualization library in the Python ecosystem.\n",
    "\n",
    "Let's now execute a few lines of code and generate some plots:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 10, 500)\n",
    "y = np.cumsum(np.random.randn(500, 6), 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7c0f8c6748>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 7))\n",
    "plt.plot(x, y)\n",
    "plt.legend('ABCDEF', ncol=2, loc='upper left')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But what is that 😱? Just random generated datapoints, but you can clearly see how simple is to do numeric processing and plotting with Notebooks.ai."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 3: Interacting with data\n",
    "\n",
    "Notebooks.ai and Jupyter Lab make it really simple to intereact with files in your local storage. These files are securely stored in the cloud and you can access them from anywhere in the world.\n",
    "\n",
    "To show you the full potential of Notebooks.ai, we're going to pull cryptocurrencies prices from a public API and download them as Excel files, pretty fancy 😎. I need to import two libraries first: `requests` (to pull data from the web) and `pandas` to process it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I have a predefined function that simplifies the process of importing data from [Cryptowatch](https://cryptowat.ch) (for reference, check [their docs](https://cryptowat.ch/docs/api#ohlc))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_historic_price(symbol, exchange='bitfinex', after='2018-09-01'):\n",
    "    url = 'https://api.cryptowat.ch/markets/{exchange}/{symbol}usd/ohlc'.format(\n",
    "        symbol=symbol, exchange=exchange)\n",
    "    resp = requests.get(url, params={\n",
    "        'periods': '3600',\n",
    "        'after': str(int(pd.Timestamp(after).timestamp()))\n",
    "    })\n",
    "    resp.raise_for_status()\n",
    "    data = resp.json()\n",
    "    df = pd.DataFrame(data['result']['3600'], columns=[\n",
    "        'CloseTime', 'OpenPrice', 'HighPrice', 'LowPrice', 'ClosePrice', 'Volume', 'NA'\n",
    "    ])\n",
    "    df['CloseTime'] = pd.to_datetime(df['CloseTime'], unit='s')\n",
    "    df.set_index('CloseTime', inplace=True)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I will now pull data from Bitcoin and Ether, two of the most popular cryptocurrencies, for the last 7 days:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2018-10-04 19:05:56.958797')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "last_week = (pd.Timestamp.now() - pd.offsets.Day(7))\n",
    "last_week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "btc = get_historic_price('btc', 'bitstamp', after=last_week)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "eth = get_historic_price('eth', 'bitstamp', after=last_week)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Bitcoin:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>OpenPrice</th>\n",
       "      <th>HighPrice</th>\n",
       "      <th>LowPrice</th>\n",
       "      <th>ClosePrice</th>\n",
       "      <th>Volume</th>\n",
       "      <th>NA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CloseTime</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>2018-10-04 19:00:00</th>\n",
       "      <td>6552.87</td>\n",
       "      <td>6572.03</td>\n",
       "      <td>6551.30</td>\n",
       "      <td>6557.04</td>\n",
       "      <td>177.172840</td>\n",
       "      <td>1162345.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 20:00:00</th>\n",
       "      <td>6557.04</td>\n",
       "      <td>6573.01</td>\n",
       "      <td>6557.04</td>\n",
       "      <td>6565.92</td>\n",
       "      <td>192.690520</td>\n",
       "      <td>1265504.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 21:00:00</th>\n",
       "      <td>6566.00</td>\n",
       "      <td>6572.98</td>\n",
       "      <td>6535.00</td>\n",
       "      <td>6545.05</td>\n",
       "      <td>206.450800</td>\n",
       "      <td>1351745.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 22:00:00</th>\n",
       "      <td>6545.05</td>\n",
       "      <td>6557.58</td>\n",
       "      <td>6517.39</td>\n",
       "      <td>6545.00</td>\n",
       "      <td>178.217800</td>\n",
       "      <td>1163628.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 23:00:00</th>\n",
       "      <td>6549.00</td>\n",
       "      <td>6563.98</td>\n",
       "      <td>6545.00</td>\n",
       "      <td>6554.20</td>\n",
       "      <td>62.939697</td>\n",
       "      <td>412657.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     OpenPrice  HighPrice  LowPrice  ClosePrice      Volume  \\\n",
       "CloseTime                                                                     \n",
       "2018-10-04 19:00:00    6552.87    6572.03   6551.30     6557.04  177.172840   \n",
       "2018-10-04 20:00:00    6557.04    6573.01   6557.04     6565.92  192.690520   \n",
       "2018-10-04 21:00:00    6566.00    6572.98   6535.00     6545.05  206.450800   \n",
       "2018-10-04 22:00:00    6545.05    6557.58   6517.39     6545.00  178.217800   \n",
       "2018-10-04 23:00:00    6549.00    6563.98   6545.00     6554.20   62.939697   \n",
       "\n",
       "                            NA  \n",
       "CloseTime                       \n",
       "2018-10-04 19:00:00  1162345.8  \n",
       "2018-10-04 20:00:00  1265504.5  \n",
       "2018-10-04 21:00:00  1351745.6  \n",
       "2018-10-04 22:00:00  1163628.1  \n",
       "2018-10-04 23:00:00   412657.6  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "btc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff3cc4322b0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "btc['ClosePrice'].plot(figsize=(15, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Ether:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>OpenPrice</th>\n",
       "      <th>HighPrice</th>\n",
       "      <th>LowPrice</th>\n",
       "      <th>ClosePrice</th>\n",
       "      <th>Volume</th>\n",
       "      <th>NA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CloseTime</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>2018-10-04 19:00:00</th>\n",
       "      <td>221.84</td>\n",
       "      <td>223.27</td>\n",
       "      <td>221.83</td>\n",
       "      <td>222.92</td>\n",
       "      <td>1555.00230</td>\n",
       "      <td>346043.220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 20:00:00</th>\n",
       "      <td>222.83</td>\n",
       "      <td>223.41</td>\n",
       "      <td>222.45</td>\n",
       "      <td>222.65</td>\n",
       "      <td>340.15000</td>\n",
       "      <td>75863.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 21:00:00</th>\n",
       "      <td>222.76</td>\n",
       "      <td>223.06</td>\n",
       "      <td>220.81</td>\n",
       "      <td>221.45</td>\n",
       "      <td>707.83680</td>\n",
       "      <td>156992.550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 22:00:00</th>\n",
       "      <td>221.45</td>\n",
       "      <td>221.54</td>\n",
       "      <td>218.55</td>\n",
       "      <td>220.59</td>\n",
       "      <td>1649.08060</td>\n",
       "      <td>362885.030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 23:00:00</th>\n",
       "      <td>220.54</td>\n",
       "      <td>222.32</td>\n",
       "      <td>220.25</td>\n",
       "      <td>221.17</td>\n",
       "      <td>228.63876</td>\n",
       "      <td>50586.176</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     OpenPrice  HighPrice  LowPrice  ClosePrice      Volume  \\\n",
       "CloseTime                                                                     \n",
       "2018-10-04 19:00:00     221.84     223.27    221.83      222.92  1555.00230   \n",
       "2018-10-04 20:00:00     222.83     223.41    222.45      222.65   340.15000   \n",
       "2018-10-04 21:00:00     222.76     223.06    220.81      221.45   707.83680   \n",
       "2018-10-04 22:00:00     221.45     221.54    218.55      220.59  1649.08060   \n",
       "2018-10-04 23:00:00     220.54     222.32    220.25      221.17   228.63876   \n",
       "\n",
       "                             NA  \n",
       "CloseTime                        \n",
       "2018-10-04 19:00:00  346043.220  \n",
       "2018-10-04 20:00:00   75863.090  \n",
       "2018-10-04 21:00:00  156992.550  \n",
       "2018-10-04 22:00:00  362885.030  \n",
       "2018-10-04 23:00:00   50586.176  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eth.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff3cc4175f8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "eth['ClosePrice'].plot(figsize=(15, 7))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, we're able to pull data from the internet with just a few lines, create a DataFrame and plot it all within Jupyter Lab."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>OpenPrice</th>\n",
       "      <th>HighPrice</th>\n",
       "      <th>LowPrice</th>\n",
       "      <th>ClosePrice</th>\n",
       "      <th>Volume</th>\n",
       "      <th>NA</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CloseTime</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>2018-10-04 19:00:00</th>\n",
       "      <td>221.84</td>\n",
       "      <td>223.27</td>\n",
       "      <td>221.83</td>\n",
       "      <td>222.92</td>\n",
       "      <td>1555.00230</td>\n",
       "      <td>346043.220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 20:00:00</th>\n",
       "      <td>222.83</td>\n",
       "      <td>223.41</td>\n",
       "      <td>222.45</td>\n",
       "      <td>222.65</td>\n",
       "      <td>340.15000</td>\n",
       "      <td>75863.090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 21:00:00</th>\n",
       "      <td>222.76</td>\n",
       "      <td>223.06</td>\n",
       "      <td>220.81</td>\n",
       "      <td>221.45</td>\n",
       "      <td>707.83680</td>\n",
       "      <td>156992.550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 22:00:00</th>\n",
       "      <td>221.45</td>\n",
       "      <td>221.54</td>\n",
       "      <td>218.55</td>\n",
       "      <td>220.59</td>\n",
       "      <td>1649.08060</td>\n",
       "      <td>362885.030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-10-04 23:00:00</th>\n",
       "      <td>220.54</td>\n",
       "      <td>222.32</td>\n",
       "      <td>220.25</td>\n",
       "      <td>221.17</td>\n",
       "      <td>228.63876</td>\n",
       "      <td>50586.176</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     OpenPrice  HighPrice  LowPrice  ClosePrice      Volume  \\\n",
       "CloseTime                                                                     \n",
       "2018-10-04 19:00:00     221.84     223.27    221.83      222.92  1555.00230   \n",
       "2018-10-04 20:00:00     222.83     223.41    222.45      222.65   340.15000   \n",
       "2018-10-04 21:00:00     222.76     223.06    220.81      221.45   707.83680   \n",
       "2018-10-04 22:00:00     221.45     221.54    218.55      220.59  1649.08060   \n",
       "2018-10-04 23:00:00     220.54     222.32    220.25      221.17   228.63876   \n",
       "\n",
       "                             NA  \n",
       "CloseTime                        \n",
       "2018-10-04 19:00:00  346043.220  \n",
       "2018-10-04 20:00:00   75863.090  \n",
       "2018-10-04 21:00:00  156992.550  \n",
       "2018-10-04 22:00:00  362885.030  \n",
       "2018-10-04 23:00:00   50586.176  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eth.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bonus: Dynamic plots with Bokeh\n",
    "\n",
    "We've also included [Bokeh](https://bokeh.pydata.org/) as part of this main distribution. Bokeh is a plotting library that generates interactive plots, that can be manipulated right within your browser.\n",
    "\n",
    "We first need to import the libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.plotting import figure, output_file, show\n",
    "from bokeh.io import output_notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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=\"32d5a772-20b1-45a3-8e00-621d014b4408\">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 != null && id in Bokeh.index) {\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 id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\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[toinsert.length - 1].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[toinsert.length - 1].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[toinsert.length - 1]);\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(\"32d5a772-20b1-45a3-8e00-621d014b4408\");\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(\"32d5a772-20b1-45a3-8e00-621d014b4408\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '32d5a772-20b1-45a3-8e00-621d014b4408' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.13.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.13.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.13.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.13.0.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-0.13.0.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.13.0.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.13.0.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.13.0.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.13.0.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.13.0.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(\"32d5a772-20b1-45a3-8e00-621d014b4408\")).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(\"32d5a772-20b1-45a3-8e00-621d014b4408\");\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(\"32d5a772-20b1-45a3-8e00-621d014b4408\");\n  if (element == null) {\n    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '32d5a772-20b1-45a3-8e00-621d014b4408' but no matching script tag was found. \")\n    return false;\n  }\n\n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.13.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.13.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.13.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-0.13.0.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-0.13.0.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.13.0.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.13.0.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.13.0.min.css\");\n      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-0.13.0.min.css\");\n      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-0.13.0.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(\"32d5a772-20b1-45a3-8e00-621d014b4408\")).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": [
    "output_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we generate the plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"2cd3145e-ade5-46c5-8bf9-3b29539beb09\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  var docs_json = 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Ticker\"},{\"attributes\":{\"data_source\":{\"id\":\"709ce31d-b64e-4a0c-8ce2-fae76d15e884\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"47f91594-dda7-4fbb-9684-0e8538dbef7e\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"56bfa6cb-59aa-487a-bd54-a793d89fbadb\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"3cc0a566-c1d1-4327-af9c-a2799f9edf9e\",\"type\":\"CDSView\"}},\"id\":\"1b794acb-e358-4c08-bdf9-78af1e683394\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null},\"id\":\"8fc1866e-2895-4ae0-9b47-5611128e29b7\",\"type\":\"DataRange1d\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"396e5f45-5432-40ef-bdf9-52c93e552e33\",\"type\":\"MonthsTicker\"},{\"attributes\":{},\"id\":\"5230829c-a7bf-4c57-bc0b-33433e2e1072\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"de735945-ef6a-40bf-b567-82894711212c\",\"type\":\"DaysTicker\"},{\"attributes\":{},\"id\":\"0fbc7bcf-e2fd-4f17-9dd2-c49e5bd497b8\",\"type\":\"YearsTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"8f571316-0579-4c7b-bb23-c052d5c69fdf\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"dimension\":1,\"grid_line_alpha\":{\"value\":0.3},\"plot\":{\"id\":\"6f7d4f6c-f9d8-4c9f-a019-5461ccb3b898\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"c22070bb-25fe-4a63-bd62-4f0811f3d674\",\"type\":\"BasicTicker\"}},\"id\":\"61432af1-312a-45ab-acce-6e7b9fbcfb27\",\"type\":\"Grid\"}],\"root_ids\":[\"6f7d4f6c-f9d8-4c9f-a019-5461ccb3b898\"]},\"title\":\"Bokeh Application\",\"version\":\"0.13.0\"}};\n",
       "  var render_items = [{\"docid\":\"57e27c1d-f74d-4c23-9b59-95ffdffcb807\",\"roots\":{\"6f7d4f6c-f9d8-4c9f-a019-5461ccb3b898\":\"2cd3145e-ade5-46c5-8bf9-3b29539beb09\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(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 run BokehJS code 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": "6f7d4f6c-f9d8-4c9f-a019-5461ccb3b898"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p1 = figure(x_axis_type=\"datetime\", title=\"Crypto Prices\")\n",
    "p1.grid.grid_line_alpha=0.3\n",
    "p1.xaxis.axis_label = 'Date'\n",
    "p1.yaxis.axis_label = 'Price'\n",
    "\n",
    "p1.line(btc.index, btc['ClosePrice'], color='#f2a900', legend='Bitcoin')\n",
    "p1.line(eth.index, eth['ClosePrice'], color='#A6CEE3', legend='Ether')\n",
    "\n",
    "p1.legend.location = \"top_left\"\n",
    "\n",
    "show(p1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "☝️ as you can see, the plot is interactive. Try zomming in and out, and scrolling in the plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 4: Exporting to Excel\n",
    "\n",
    "We're now ready to generate an Excel file from the downloaded prices. Working with Excel and other formats (like CSV or JSON) is extremely simple in Jupyter Lab (thanks to pandas and Python). Our first step will be to create an \"Excel writer\", a component from the `pandas` package:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "writer = pd.ExcelWriter('cryptos.xlsx')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll now write both our Bitcoin and Ether data as separate sheets:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "btc.to_excel(writer, sheet_name='Bitcoin')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "eth.to_excel(writer, sheet_name='Ether')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally, we can save the file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "writer.save()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once you've saved the file, you should see it in the left side navigation bar:\n",
    "\n",
    "![Excel file](images/_5.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Final words and how to get help\n",
    "\n",
    "That's it! It's your time now to start working and playing around with jupyter lab and Notebooks.ai. This product is in an early stage, so we'd love to receive all your feedback and suggestions. If you need help or ideas for us to implement, create an issue in the following replo: [https://github.com/notebooks-ai/notebooks-help](https://github.com/notebooks-ai/notebooks-help). It'll be highly appreciated!"
   ]
  }
 ],
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