diff --git a/Forecasting a Time Series in Python.ipynb b/Forecasting a Time Series in Python.ipynb index e082305..5a9b665 100644 --- a/Forecasting a Time Series in Python.ipynb +++ b/Forecasting a Time Series in Python.ipynb @@ -27,18 +27,18 @@ "data": { "text/html": [ "
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" ] }, - "execution_count": 27, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "from plotly.plotly import plot_mpl\n", "from statsmodels.tsa.seasonal import seasonal_decompose\n", "result = seasonal_decompose(data, model='multiplicative')\n", "fig = result.plot()\n", - "plot_mpl(fig)" + "fig.set_size_inches((12, 8))\n", + "iplot_mpl(fig)" ] }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": true - }, + "execution_count": 11, + "metadata": {}, "outputs": [], "source": [ - "import plotly.plotly as ply\n", - "import cufflinks as cf\n", - "# Check the docs on setting up offline plotting" + "import cufflinks as cf" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.plotly.v1+json": { + "data": [ + { + "line": { + "color": "rgba(255, 153, 51, 1.0)", + "dash": "solid", + "shape": "linear", + 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Please use the pandas.tseries module instead.\n", - "\n" - ] - } - ], "source": [ "from pyramid.arima import auto_arima" ] @@ -494,38 +4853,39 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(0, 1, 1, 12); AIC=1782.527, BIC=1802.447, Fit time=0.866 seconds\n", - "Fit ARIMA: order=(0, 1, 0) seasonal_order=(0, 1, 0, 12); AIC=nan, BIC=nan, Fit time=nan seconds\n", - "Fit ARIMA: order=(1, 1, 0) seasonal_order=(1, 1, 0, 12); AIC=1942.040, BIC=1957.976, Fit time=0.238 seconds\n", - "Fit ARIMA: order=(0, 1, 1) seasonal_order=(0, 1, 1, 12); AIC=1837.289, BIC=1853.224, Fit time=0.361 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(1, 1, 1, 12); AIC=1783.875, BIC=1807.778, Fit time=1.434 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(0, 1, 0, 12); AIC=1920.884, BIC=1936.820, Fit time=0.451 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(0, 1, 2, 12); AIC=1784.212, BIC=1808.116, Fit time=3.491 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(1, 1, 2, 12); AIC=1781.900, BIC=1809.788, Fit time=3.586 seconds\n", - "Fit ARIMA: order=(0, 1, 1) seasonal_order=(1, 1, 2, 12); AIC=1837.164, BIC=1861.067, Fit time=1.287 seconds\n", - "Fit ARIMA: order=(2, 1, 1) seasonal_order=(1, 1, 2, 12); AIC=1782.648, BIC=1814.520, Fit time=4.348 seconds\n", - "Fit ARIMA: order=(1, 1, 0) seasonal_order=(1, 1, 2, 12); AIC=1852.587, BIC=1876.490, Fit time=1.008 seconds\n", - "Fit ARIMA: order=(1, 1, 2) seasonal_order=(1, 1, 2, 12); AIC=1781.940, BIC=1813.811, Fit time=4.222 seconds\n", - "Fit ARIMA: order=(0, 1, 0) seasonal_order=(1, 1, 2, 12); AIC=1864.184, BIC=1884.103, Fit time=1.035 seconds\n", - "Fit ARIMA: order=(2, 1, 2) seasonal_order=(1, 1, 2, 12); AIC=1782.722, BIC=1818.578, Fit time=5.144 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(2, 1, 2, 12); AIC=1772.539, BIC=1804.410, Fit time=4.551 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(2, 1, 1, 12); AIC=1771.295, BIC=1799.182, Fit time=2.270 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(1, 1, 0, 12); AIC=1870.049, BIC=1889.969, Fit time=0.974 seconds\n", - "Fit ARIMA: order=(0, 1, 1) seasonal_order=(2, 1, 1, 12); AIC=1825.210, BIC=1849.114, Fit time=0.999 seconds\n", - "Fit ARIMA: order=(2, 1, 1) seasonal_order=(2, 1, 1, 12); AIC=1772.010, BIC=1803.881, Fit time=3.391 seconds\n", - "Fit ARIMA: order=(1, 1, 0) seasonal_order=(2, 1, 1, 12); AIC=1842.551, BIC=1866.454, Fit time=0.808 seconds\n", - "Fit ARIMA: order=(1, 1, 2) seasonal_order=(2, 1, 1, 12); AIC=1771.612, BIC=1803.484, Fit time=4.359 seconds\n", - "Fit ARIMA: order=(0, 1, 0) seasonal_order=(2, 1, 1, 12); AIC=1855.606, BIC=1875.526, Fit time=0.641 seconds\n", - "Fit ARIMA: order=(2, 1, 2) seasonal_order=(2, 1, 1, 12); AIC=1773.049, BIC=1808.904, Fit time=5.352 seconds\n", - "Fit ARIMA: order=(1, 1, 1) seasonal_order=(2, 1, 0, 12); AIC=1813.388, BIC=1837.291, Fit time=3.069 seconds\n", - "Total fit time: 53.889 seconds\n" + "Fit ARIMA: order=(1, 1, 1) seasonal_order=(0, 1, 1, 12); AIC=1782.527, BIC=1802.280, Fit time=1.386 seconds\n", + "Fit ARIMA: order=(0, 1, 0) seasonal_order=(0, 1, 0, 12); AIC=2012.117, BIC=2020.018, Fit time=0.023 seconds\n", + "Fit ARIMA: order=(1, 1, 0) seasonal_order=(1, 1, 0, 12); AIC=1942.042, BIC=1957.844, Fit time=0.247 seconds\n", + "Fit ARIMA: order=(0, 1, 1) seasonal_order=(0, 1, 1, 12); AIC=1837.289, BIC=1853.091, Fit time=0.455 seconds\n", + "Fit ARIMA: order=(1, 1, 1) seasonal_order=(1, 1, 1, 12); AIC=1783.878, BIC=1807.582, Fit time=1.973 seconds\n", + "Fit ARIMA: order=(1, 1, 1) seasonal_order=(0, 1, 0, 12); AIC=1920.884, BIC=1936.687, Fit time=0.486 seconds\n", + "Fit ARIMA: order=(1, 1, 1) seasonal_order=(0, 1, 2, 12); AIC=1783.389, BIC=1807.093, Fit time=6.739 seconds\n", + "Fit ARIMA: order=(1, 1, 1) seasonal_order=(1, 1, 2, 12); AIC=1782.020, BIC=1809.675, Fit time=4.060 seconds\n", + "Fit ARIMA: order=(0, 1, 1) seasonal_order=(1, 1, 2, 12); AIC=1837.164, BIC=1860.868, Fit time=2.012 seconds\n", + "Fit ARIMA: order=(2, 1, 1) seasonal_order=(1, 1, 2, 12); AIC=1782.739, BIC=1814.344, Fit time=6.296 seconds\n", + "Fit ARIMA: order=(1, 1, 0) seasonal_order=(1, 1, 2, 12); AIC=1852.587, BIC=1876.291, Fit time=2.394 seconds\n", + "Fit ARIMA: order=(1, 1, 2) seasonal_order=(1, 1, 2, 12); AIC=1781.934, BIC=1813.539, Fit time=6.957 seconds\n", + "Fit ARIMA: order=(2, 1, 3) seasonal_order=(1, 1, 2, 12); AIC=1785.928, BIC=1825.434, Fit time=8.821 seconds\n", + "Fit ARIMA: order=(1, 1, 2) seasonal_order=(0, 1, 2, 12); AIC=1787.858, BIC=1815.513, Fit time=6.788 seconds\n", + "Fit ARIMA: order=(1, 1, 2) seasonal_order=(2, 1, 2, 12); AIC=1771.116, BIC=1806.671, Fit time=7.922 seconds\n", + "Fit ARIMA: order=(1, 1, 2) seasonal_order=(2, 1, 1, 12); AIC=1771.603, BIC=1803.209, Fit time=5.711 seconds\n", + "Fit ARIMA: order=(1, 1, 2) seasonal_order=(1, 1, 1, 12); AIC=1784.191, BIC=1811.846, Fit time=2.673 seconds\n", + "Fit ARIMA: order=(0, 1, 2) seasonal_order=(2, 1, 2, 12); AIC=1779.256, BIC=1810.861, Fit time=4.795 seconds\n", + "Fit ARIMA: order=(2, 1, 2) seasonal_order=(2, 1, 2, 12); AIC=1775.396, BIC=1814.903, Fit time=8.080 seconds\n", + "Fit ARIMA: order=(1, 1, 1) seasonal_order=(2, 1, 2, 12); AIC=1770.228, BIC=1801.833, Fit time=8.249 seconds\n", + "Fit ARIMA: order=(0, 1, 0) seasonal_order=(2, 1, 2, 12); AIC=1854.601, BIC=1878.305, Fit time=2.744 seconds\n", + "Fit ARIMA: order=(1, 1, 1) seasonal_order=(2, 1, 1, 12); AIC=1771.290, BIC=1798.945, Fit time=4.809 seconds\n", + "Fit ARIMA: order=(0, 1, 1) seasonal_order=(2, 1, 2, 12); AIC=1816.627, BIC=1844.282, Fit time=2.531 seconds\n", + "Fit ARIMA: order=(2, 1, 1) seasonal_order=(2, 1, 2, 12); AIC=1772.076, BIC=1807.632, Fit time=6.667 seconds\n", + "Fit ARIMA: order=(1, 1, 0) seasonal_order=(2, 1, 2, 12); AIC=1837.278, BIC=1864.933, Fit time=2.860 seconds\n", + "Total fit time: 105.685 seconds\n" ] } ], @@ -541,16 +4901,16 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "1771.2948217037836" + "1770.2279319649506" ] }, - "execution_count": 31, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -568,25 +4928,25 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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