{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Quandl: US GDP, Implicit Price Deflator\n", "\n", "In this notebook, we'll take a look at data set , available on [Quantopian](https://www.quantopian.com/data). This dataset spans from 1961 through the current day. It contains the value for the United States' inflation rate, using the price deflator. We access this data via the API provided by [Quandl](https://www.quandl.com). [More details](https://www.quandl.com/data/UGID/INFL_USA-Inflation-GDP-deflator-United-States-of-America) on this dataset can be found on Quandl's website.\n", "\n", "### Blaze\n", "Before we dig into the data, we want to tell you about how you generally access Quantopian partner data sets. These datasets are available using the [Blaze](http://blaze.pydata.org) library. Blaze provides the Quantopian user with a convenient interface to access very large datasets.\n", "\n", "Some of these sets (though not this one) are many millions of records. Bringing that data directly into Quantopian Research directly just is not viable. So Blaze allows us to provide a simple querying interface and shift the burden over to the server side.\n", "\n", "To learn more about using Blaze and generally accessing Quantopian partner data, clone [this tutorial notebook](https://www.quantopian.com/clone_notebook?id=561827d21777f45c97000054).\n", "\n", "With preamble in place, let's get started:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# import the dataset\n", "from quantopian.interactive.data.quandl import ugid_infl_usa\n", "# Since this data is public domain and provided by Quandl for free, there is no _free version of this\n", "# data set, as found in the premium sets. This import gets you the entirety of this data set.\n", "\n", "# import data operations\n", "from odo import odo\n", "# import other libraries we will use\n", "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
asof_datevaluetimestamp
01961-12-311.229581961-12-31
11962-12-311.366491962-12-31
21963-12-311.059411963-12-31
31964-12-311.509051964-12-31
41965-12-311.878171965-12-31
51966-12-312.952821966-12-31
61967-12-313.096001967-12-31
71968-12-314.255661968-12-31
81969-12-314.732541969-12-31
91970-12-317.097381970-12-31
101971-12-315.082521971-12-31
" ], "text/plain": [ " asof_date value timestamp\n", "0 1961-12-31 1.22958 1961-12-31\n", "1 1962-12-31 1.36649 1962-12-31\n", "2 1963-12-31 1.05941 1963-12-31\n", "3 1964-12-31 1.50905 1964-12-31\n", "4 1965-12-31 1.87817 1965-12-31\n", "5 1966-12-31 2.95282 1966-12-31\n", "6 1967-12-31 3.09600 1967-12-31\n", "7 1968-12-31 4.25566 1968-12-31\n", "8 1969-12-31 4.73254 1969-12-31\n", "9 1970-12-31 7.09738 1970-12-31\n", "..." ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ugid_infl_usa.sort('asof_date')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data goes all the way back to 1961 and is updated annually.\n", "\n", "Blaze provides us with the first 10 rows of the data for display. Just to confirm, let's just count the number of rows in the Blaze expression:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "53" ], "text/plain": [ "53" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ugid_infl_usa.count()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's go plot it for fun. This data set is definitely small enough to just put right into a Pandas DataFrame" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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RUUpi2CEiIiIiopTEsENERERERCmJYYeIiIiIiFISww4REREREaUkhh0iIiIiIkpJDDtE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\nAWbr6QSopbMfLZ19Z/7e2tmPvPJWAMC+4zU4mFWHh5dG8oLvLOW1ncg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lcwN1YtmiqYkU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\nRERERPySwo6IiIiIiPil/wHfDAz61MU5RAAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "inf_df = odo(ugid_infl_usa, pd.DataFrame)\n", "\n", "inf_df.plot(x='asof_date', y='value')\n", "plt.xlabel(\"As Of Date (asof_date)\")\n", "plt.ylabel(\"Inflation Rate\")\n", "plt.title(\"US Inflation, Implicit Price Deflator\")\n", "plt.legend().set_visible(False)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.10" } }, "nbformat": 4, "nbformat_minor": 0 }