Get Bitcoin Prices

gistfile1.txt

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<center><h2>Python Script that charts bitcoin prices in US dollars</h2></center>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt\n",
      "from matplotlib.dates import YearLocator, MonthLocator, WeekdayLocator, DayLocator, DateFormatter\n",
      "import dateutil\n",
      "from matplotlib.ticker import MultipleLocator\n",
      "from datetime import datetime\n",
      "from datetime import date\n",
      "import calendar\n",
      "\n",
      "# Data metadata:\n",
      "# CSV file where first column is string date in dd/mm/YYYY format and second column is the bitcoin price in US dollars\n",
      "# Pandas.read_csv has an awesome converters parameter that allows us to convert or modify a column's data on the fly!\n",
      "# Therefore, we can read the first column as an actual Python datetime object instead of as a string.\n",
      "bitcoin_data = pd.read_csv(\"http://blockchain.info/charts/market-price?showDataPoints=false&timespan=&show_header=true&daysAverageString=1&scale=0&format=csv&address=\",\n",
      "                 index_col=0, names=['price'], converters={0: lambda x: datetime.strptime(x, '%d/%m/%Y %H:%M:%S')})"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 40
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Let's view just the first 5 rows of the bitcoin data:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bitcoin_data.tail()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>price</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-01-09 18:15:05</th>\n",
        "      <td> 927.11829</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-10 18:15:05</th>\n",
        "      <td> 918.41811</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-11 18:15:05</th>\n",
        "      <td> 970.51160</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-12 18:15:05</th>\n",
        "      <td> 975.35750</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-13 14:54:31</th>\n",
        "      <td> 927.41733</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 41,
       "text": [
        "                         price\n",
        "2014-01-09 18:15:05  927.11829\n",
        "2014-01-10 18:15:05  918.41811\n",
        "2014-01-11 18:15:05  970.51160\n",
        "2014-01-12 18:15:05  975.35750\n",
        "2014-01-13 14:54:31  927.41733"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Now, let's plot the data.  Top chart will be all data available in monthly x-ticks intervals, bottom chart will be just last 2 calendar months of data, with daily x-ticks intervals."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, axes = plt.subplots(2, 1)  # Make 2 rows and 1 column of plots (2 plots total)\n",
      "\n",
      "# These are just time intervals we can use to format our X axis tick intervals\n",
      "year   = YearLocator()\n",
      "month  = MonthLocator(bymonth=range(1,13),  bymonthday=1, interval=1)\n",
      "week   = WeekdayLocator(byweekday=dateutil.rrule.MO)  # Every MOnday\n",
      "day    = DayLocator(bymonthday=range(1,32), interval=1)\n",
      "\n",
      "####################### Let's make the top plot ######################\n",
      "# Use trial and error to get the size you want\n",
      "axes[0] = fig.add_axes([0, 1.4, 1.5, 1])  # left, bottom, width, height\n",
      "\n",
      "# Format the x-axis, set tick labels as Month 'Yr format, turn on grid for major ticks\n",
      "monthsFmt = DateFormatter(\"%b '%y\")\n",
      "axes[0].xaxis.set_major_formatter(monthsFmt)\n",
      "axes[0].xaxis.set_major_locator(month)       # Make the x-axis tick interval to be monthly interval size\n",
      "axes[0].xaxis.grid(which='major')\n",
      "\n",
      "# Format the y-axis\n",
      "y_major_ticks = MultipleLocator(200)\n",
      "axes[0].yaxis.set_major_locator(y_major_ticks)\n",
      "axes[0].yaxis.set_ticks_position('right')   # Not sure why 'both' don't work\n",
      "axes[0].yaxis.set_label_position('right')\n",
      "axes[0].yaxis.grid(which='major')\n",
      "\n",
      "# Plot the data...\n",
      "axes[0].plot_date(bitcoin_data.index, bitcoin_data.values, 'r')\n",
      "axes[0].set_title(\"Bitcoin Value in US$\", weight=\"bold\")\n",
      "axes[0].set_xlabel(\"Month - Year\")\n",
      "axes[0].set_ylabel(\"US$\")\n",
      "plt.setp(axes[0].get_xticklabels(), rotation=-90)\n",
      "\n",
      "############# Let's get last 2 calendar months' worth of bitcoin prices ###########\n",
      "today = datetime.today()\n",
      "this_month = today.month\n",
      "if this_month==1:  # if month is January, then year will be one less than current year\n",
      "    last_year = today.year - 1  # if month is January, then previous month is Dec (12)\n",
      "    last_month = 12\n",
      "else:\n",
      "    last_year = today.year\n",
      "    last_month = this_month - 1  # last month will equal current month minus 1\n",
      "\n",
      "this_year = today.year\n",
      "\n",
      "# Now I will take advantage of Pandas partial string indexing described below to get just 2 months of data:\n",
      "# http://pandas.pydata.org/pandas-docs/stable/timeseries.html#partial-string-indexing\n",
      "last2months = bitcoin_data[str(last_month)+'-'+str(last_year):str(this_month)+'-'+str(this_year)]\n",
      "\n",
      "# Get the last date, convert it to a datetime.date, then make a string from it in mm/dd/YYYY format\n",
      "current_price = last2months[-1:].values[0][0]\n",
      "last_date = last2months[-1:].index\n",
      "current_date_unformatted = date(last_date.year[0], last_date.month[0], last_date.day[0])\n",
      "current_date = datetime.strftime(current_date_unformatted, \"%m/%d/%Y\")\n",
      "\n",
      "####################### Let's make the bottom plot ######################\n",
      "axes[1] = fig.add_axes([0, 0, 1.5, 1])   # left, bottom, width, height\n",
      "\n",
      "# Format the x-axis tick labels as mm/dd/YYYY format, turn on grid for major ticks\n",
      "dayFmt = DateFormatter(\"%b-%d-%Y\")\n",
      "axes[1].xaxis.set_major_locator(day)  # Make x-axis tick interval to be daily interval size\n",
      "axes[1].xaxis.set_major_formatter(dayFmt)\n",
      "axes[1].xaxis.grid(which='major')\n",
      "\n",
      "# Format the y-axis\n",
      "y_major_ticks = MultipleLocator(20)\n",
      "axes[1].yaxis.set_major_locator(y_major_ticks)\n",
      "axes[1].yaxis.set_ticks_position('right')  # Not sure why 'both' don't work\n",
      "axes[1].yaxis.set_label_position('right')\n",
      "axes[1].yaxis.grid(which='major')\n",
      "\n",
      "# Plot the data...\n",
      "axes[1].plot_date(last2months.index, last2months.values, 'r')\n",
      "axes[1].set_title(\"Current Value@\"+current_date+\": \"+str(current_price), weight=\"bold\", size=10)\n",
      "# MATPLOTLIB doesn't have a good way of creating a title with 2 rows of text with different font sizes\n",
      "# Below is a workaround(http://matplotlib.org/users/text_intro.html), sort of \"hackish\" and requires trial and error (x,y)\n",
      "axes[1].text(.22,1.07, \"Last 2 Calendar Months of Bitcoin Values in US$\", transform=axes[1].transAxes,\n",
      "             weight=\"bold\", size=14)\n",
      "axes[1].set_xlabel(\"Month - Day - Year\")\n",
      "axes[1].set_ylabel(\"US$\")\n",
      "plt.setp(axes[1].get_xticklabels(), rotation=-90, size=8)\n",
      "plt.setp(axes[1].get_yticklabels(), size=10)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAsEAAAMWCAYAAAAQ/VtXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nDMMwBgcPghmGYRiGYRiD4/8BhwVmPO9p6r8AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x6ef21d0>"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dates = [date for date in last2months.index]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 66
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "values = [value for value in last2months.values]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 67
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = zip(dates, values)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 68
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for value in data:\n",
      "    print(value)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(Timestamp('2013-12-01 18:15:05', tz=None), array([ 1150.08882]))\n",
        "(Timestamp('2013-12-02 18:15:05', tz=None), array([ 1024.7252]))\n",
        "(Timestamp('2013-12-03 18:15:05', tz=None), array([ 1107.06561]))\n",
        "(Timestamp('2013-12-04 18:15:05', tz=None), array([ 1170.46278]))\n",
        "(Timestamp('2013-12-05 18:15:05', tz=None), array([ 1091.62121]))\n",
        "(Timestamp('2013-12-06 18:15:05', tz=None), array([ 1042.7746]))\n",
        "(Timestamp('2013-12-07 18:15:05', tz=None), array([ 767.77696]))\n",
        "(Timestamp('2013-12-08 18:15:05', tz=None), array([ 726.58623]))\n",
        "(Timestamp('2013-12-09 18:15:05', tz=None), array([ 863.79314]))\n",
        "(Timestamp('2013-12-10 18:15:05', tz=None), array([ 935.89805]))\n",
        "(Timestamp('2013-12-11 18:15:05', tz=None), array([ 979.61901]))\n",
        "(Timestamp('2013-12-12 18:15:05', tz=None), array([ 889.63983]))\n",
        "(Timestamp('2013-12-13 18:15:05', tz=None), array([ 930.79973]))\n",
        "(Timestamp('2013-12-14 18:15:05', tz=None), array([ 911.20089]))\n",
        "(Timestamp('2013-12-15 18:15:05', tz=None), array([ 874.93158]))\n",
        "(Timestamp('2013-12-16 18:15:05', tz=None), array([ 868.14062]))\n",
        "(Timestamp('2013-12-17 18:15:05', tz=None), array([ 744.5032]))\n",
        "(Timestamp('2013-12-18 18:15:05', tz=None), array([ 584.0669]))\n",
        "(Timestamp('2013-12-19 18:15:05', tz=None), array([ 620.42169]))\n",
        "(Timestamp('2013-12-20 18:15:05', tz=None), array([ 724.59597]))\n",
        "(Timestamp('2013-12-21 18:15:05', tz=None), array([ 660.98483]))\n",
        "(Timestamp('2013-12-22 18:15:05', tz=None), array([ 659.59835]))\n",
        "(Timestamp('2013-12-23 18:15:05', tz=None), array([ 662.33077]))\n",
        "(Timestamp('2013-12-24 18:15:05', tz=None), array([ 698.43107]))\n",
        "(Timestamp('2013-12-25 18:15:05', tz=None), array([ 696.82096]))\n",
        "(Timestamp('2013-12-26 18:15:05', tz=None), array([ 749.74441]))\n",
        "(Timestamp('2013-12-27 18:15:05', tz=None), array([ 804.04208]))\n",
        "(Timestamp('2013-12-28 18:15:05', tz=None), array([ 772.1559]))\n",
        "(Timestamp('2013-12-29 18:15:05', tz=None), array([ 752.76039]))\n",
        "(Timestamp('2013-12-30 18:15:05', tz=None), array([ 795.20293]))\n",
        "(Timestamp('2013-12-31 18:15:05', tz=None), array([ 799.47647]))\n",
        "(Timestamp('2014-01-01 18:15:05', tz=None), array([ 807.8695]))\n",
        "(Timestamp('2014-01-02 18:15:05', tz=None), array([ 817.77549]))\n",
        "(Timestamp('2014-01-03 18:15:05', tz=None), array([ 862.98983]))\n",
        "(Timestamp('2014-01-04 18:15:05', tz=None), array([ 890.91951]))\n",
        "(Timestamp('2014-01-05 18:15:05', tz=None), array([ 954.12001]))\n",
        "(Timestamp('2014-01-06 18:15:05', tz=None), array([ 1026.49375]))\n",
        "(Timestamp('2014-01-07 18:15:05', tz=None), array([ 1005.67499]))\n",
        "(Timestamp('2014-01-08 18:15:05', tz=None), array([ 924.35554]))\n",
        "(Timestamp('2014-01-09 18:15:05', tz=None), array([ 927.11829]))\n",
        "(Timestamp('2014-01-10 18:15:05', tz=None), array([ 918.41811]))\n",
        "(Timestamp('2014-01-11 18:15:05', tz=None), array([ 970.5116]))\n",
        "(Timestamp('2014-01-12 18:15:05', tz=None), array([ 975.3575]))\n",
        "(Timestamp('2014-01-13 14:54:31', tz=None), array([ 927.41733]))\n"
       ]
      }
     ],
     "prompt_number": 69
    }
   ],
   "metadata": {}
  }
 ]
}