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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pandas started out in the financial world, so naturally it has strong timeseries support.\n",
"\n",
"The first half of this post will look at pandas' capabilities for manipulating time series data.\n",
"The second half will discuss modelling time series data with statsmodels."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"\n",
"import numpy as np\n",
"import pandas as pd\n",
"import pandas_datareader.data as web\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"sns.set(style='ticks', context='talk')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"0\" 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",
" <th>Adj Close</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",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2006-01-03</th>\n",
" <td>126.699997</td>\n",
" <td>129.440002</td>\n",
" <td>124.230003</td>\n",
" <td>128.869995</td>\n",
" <td>6188700</td>\n",
" <td>114.660688</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-04</th>\n",
" <td>127.349998</td>\n",
" <td>128.910004</td>\n",
" <td>126.379997</td>\n",
" <td>127.089996</td>\n",
" <td>4861600</td>\n",
" <td>113.076954</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-05</th>\n",
" <td>126.000000</td>\n",
" <td>127.320000</td>\n",
" <td>125.610001</td>\n",
" <td>127.040001</td>\n",
" <td>3717400</td>\n",
" <td>113.032471</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-06</th>\n",
" <td>127.290001</td>\n",
" <td>129.250000</td>\n",
" <td>127.290001</td>\n",
" <td>128.839996</td>\n",
" <td>4319600</td>\n",
" <td>114.633997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-09</th>\n",
" <td>128.500000</td>\n",
" <td>130.619995</td>\n",
" <td>128.000000</td>\n",
" <td>130.389999</td>\n",
" <td>4723500</td>\n",
" <td>116.013096</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close Volume \\\n",
"Date \n",
"2006-01-03 126.699997 129.440002 124.230003 128.869995 6188700 \n",
"2006-01-04 127.349998 128.910004 126.379997 127.089996 4861600 \n",
"2006-01-05 126.000000 127.320000 125.610001 127.040001 3717400 \n",
"2006-01-06 127.290001 129.250000 127.290001 128.839996 4319600 \n",
"2006-01-09 128.500000 130.619995 128.000000 130.389999 4723500 \n",
"\n",
" Adj Close \n",
"Date \n",
"2006-01-03 114.660688 \n",
"2006-01-04 113.076954 \n",
"2006-01-05 113.032471 \n",
"2006-01-06 114.633997 \n",
"2006-01-09 116.013096 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs = web.DataReader(\"GS\", data_source='yahoo', start='2006-01-01',\n",
" end='2010-01-01')\n",
"gs.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We'll call any `DataFrame` or `Series` with a `DatetimeIndex` a timeseries.\n",
"There isn't a special data-container just for timeseries.\n",
"That said, `DataFrames` and `Series` with a `DatetiemIndex` do gain some special behaviors and additional methods."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Special Slicing"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Looking at the elements of `gs.index`, we see that `DatetimeIndex`es are made up of `pandas.Timestamp`s:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Timestamp('2006-01-03 00:00:00')"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.index[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A `Timestamp` is mostly compatible with the `datetime.datetime` class, but much amenable to storage in arrays.\n",
"\n",
"Working with `Timestamp`s can be a be awkward, so Series and DataFrames with `DatetimeIndexes` have some special slicing rules.\n",
"The first special case is *partial-string indexing*. Say we wanted to select all the days in 2006. Even with `Timestamp`'s convienient constructors, it's a pain."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"0\" 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",
" <th>Adj Close</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",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2006-01-03</th>\n",
" <td>126.699997</td>\n",
" <td>129.440002</td>\n",
" <td>124.230003</td>\n",
" <td>128.869995</td>\n",
" <td>6188700</td>\n",
" <td>114.660688</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-04</th>\n",
" <td>127.349998</td>\n",
" <td>128.910004</td>\n",
" <td>126.379997</td>\n",
" <td>127.089996</td>\n",
" <td>4861600</td>\n",
" <td>113.076954</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-05</th>\n",
" <td>126.000000</td>\n",
" <td>127.320000</td>\n",
" <td>125.610001</td>\n",
" <td>127.040001</td>\n",
" <td>3717400</td>\n",
" <td>113.032471</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-06</th>\n",
" <td>127.290001</td>\n",
" <td>129.250000</td>\n",
" <td>127.290001</td>\n",
" <td>128.839996</td>\n",
" <td>4319600</td>\n",
" <td>114.633997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-09</th>\n",
" <td>128.500000</td>\n",
" <td>130.619995</td>\n",
" <td>128.000000</td>\n",
" <td>130.389999</td>\n",
" <td>4723500</td>\n",
" <td>116.013096</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close Volume \\\n",
"Date \n",
"2006-01-03 126.699997 129.440002 124.230003 128.869995 6188700 \n",
"2006-01-04 127.349998 128.910004 126.379997 127.089996 4861600 \n",
"2006-01-05 126.000000 127.320000 125.610001 127.040001 3717400 \n",
"2006-01-06 127.290001 129.250000 127.290001 128.839996 4319600 \n",
"2006-01-09 128.500000 130.619995 128.000000 130.389999 4723500 \n",
"\n",
" Adj Close \n",
"Date \n",
"2006-01-03 114.660688 \n",
"2006-01-04 113.076954 \n",
"2006-01-05 113.032471 \n",
"2006-01-06 114.633997 \n",
"2006-01-09 116.013096 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.loc[pd.Timestamp('2006-01-01'):pd.Timestamp('2006-12-31')].head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Thanks to partial-string indexing, it's as simple as"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"<div>\n",
"<table border=\"0\" class=\"dataframe\">\n",
" <thead>\n",
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" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Volume</th>\n",
" <th>Adj Close</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",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2006-01-03</th>\n",
" <td>126.699997</td>\n",
" <td>129.440002</td>\n",
" <td>124.230003</td>\n",
" <td>128.869995</td>\n",
" <td>6188700</td>\n",
" <td>114.660688</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-04</th>\n",
" <td>127.349998</td>\n",
" <td>128.910004</td>\n",
" <td>126.379997</td>\n",
" <td>127.089996</td>\n",
" <td>4861600</td>\n",
" <td>113.076954</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-05</th>\n",
" <td>126.000000</td>\n",
" <td>127.320000</td>\n",
" <td>125.610001</td>\n",
" <td>127.040001</td>\n",
" <td>3717400</td>\n",
" <td>113.032471</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-06</th>\n",
" <td>127.290001</td>\n",
" <td>129.250000</td>\n",
" <td>127.290001</td>\n",
" <td>128.839996</td>\n",
" <td>4319600</td>\n",
" <td>114.633997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-09</th>\n",
" <td>128.500000</td>\n",
" <td>130.619995</td>\n",
" <td>128.000000</td>\n",
" <td>130.389999</td>\n",
" <td>4723500</td>\n",
" <td>116.013096</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close Volume \\\n",
"Date \n",
"2006-01-03 126.699997 129.440002 124.230003 128.869995 6188700 \n",
"2006-01-04 127.349998 128.910004 126.379997 127.089996 4861600 \n",
"2006-01-05 126.000000 127.320000 125.610001 127.040001 3717400 \n",
"2006-01-06 127.290001 129.250000 127.290001 128.839996 4319600 \n",
"2006-01-09 128.500000 130.619995 128.000000 130.389999 4723500 \n",
"\n",
" Adj Close \n",
"Date \n",
"2006-01-03 114.660688 \n",
"2006-01-04 113.076954 \n",
"2006-01-05 113.032471 \n",
"2006-01-06 114.633997 \n",
"2006-01-09 116.013096 "
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.loc['2006'].head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since label slicing is inclusive, this slice selects any observation where the year is 2006."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The second \"conveninece\" is `__getitem__` (squre-braket slicing) fallback indexing. I'm only going to mention it here, with the caveat that you should never use it.\n",
"DataFrame `__getitem__` typically looks in the column: `gs['2006']` would search `gs.columns` for `'2006'`, not find it, and raise a `KeyError`. But DataFrames with a `DatetimeIndex` catch that `KeyError` and try to slice the index.\n",
"If it succeeds in slicing the index, the result like `gs.loc['2006']` is returned.\n",
"If it fails, the `KeyError` is reraised.\n",
"This is confusing because in every other case `DataFrame.__getitem__` works on columns, and it's fragile becuase if you happened to have a column `'2006'` you *would* get just that column, and no fallback indexing would occur. Just use `gs.loc['2006']` when slicing DataFrame indexes."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Special Methods"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Resampling"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"Resampling is similar to a `groupby`: you split the time series into groups (5-day buckets below), apply a function to each group (`mean`), and combine the result (one row per group)."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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" <th>Open</th>\n",
" <th>High</th>\n",
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" <th>Close</th>\n",
" <th>Volume</th>\n",
" <th>Adj Close</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
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" <tbody>\n",
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" <th>2006-01-03</th>\n",
" <td>126.834999</td>\n",
" <td>128.730002</td>\n",
" <td>125.877501</td>\n",
" <td>127.959997</td>\n",
" <td>4771825</td>\n",
" <td>113.851027</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-08</th>\n",
" <td>130.349998</td>\n",
" <td>132.645000</td>\n",
" <td>130.205002</td>\n",
" <td>131.660000</td>\n",
" <td>4664300</td>\n",
" <td>117.143065</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-13</th>\n",
" <td>131.510002</td>\n",
" <td>133.395005</td>\n",
" <td>131.244995</td>\n",
" <td>132.924995</td>\n",
" <td>3258250</td>\n",
" <td>118.268581</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-18</th>\n",
" <td>132.210002</td>\n",
" <td>133.853333</td>\n",
" <td>131.656667</td>\n",
" <td>132.543335</td>\n",
" <td>4997766</td>\n",
" <td>118.001965</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-23</th>\n",
" <td>133.771997</td>\n",
" <td>136.083997</td>\n",
" <td>133.310001</td>\n",
" <td>135.153998</td>\n",
" <td>3968500</td>\n",
" <td>120.476883</td>\n",
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" </tbody>\n",
"</table>\n",
"</div>"
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"text/plain": [
" Open High Low Close Volume \\\n",
"Date \n",
"2006-01-03 126.834999 128.730002 125.877501 127.959997 4771825 \n",
"2006-01-08 130.349998 132.645000 130.205002 131.660000 4664300 \n",
"2006-01-13 131.510002 133.395005 131.244995 132.924995 3258250 \n",
"2006-01-18 132.210002 133.853333 131.656667 132.543335 4997766 \n",
"2006-01-23 133.771997 136.083997 133.310001 135.153998 3968500 \n",
"\n",
" Adj Close \n",
"Date \n",
"2006-01-03 113.851027 \n",
"2006-01-08 117.143065 \n",
"2006-01-13 118.268581 \n",
"2006-01-18 118.001965 \n",
"2006-01-23 120.476883 "
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.resample(\"5d\").mean().head()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
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" <th colspan=\"2\" halign=\"left\">High</th>\n",
" <th colspan=\"2\" halign=\"left\">Low</th>\n",
" <th colspan=\"2\" halign=\"left\">Close</th>\n",
" <th colspan=\"2\" halign=\"left\">Volume</th>\n",
" <th colspan=\"2\" halign=\"left\">Adj Close</th>\n",
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" <tr>\n",
" <th></th>\n",
" <th>mean</th>\n",
" <th>sum</th>\n",
" <th>mean</th>\n",
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" <th>mean</th>\n",
" <th>sum</th>\n",
" <th>mean</th>\n",
" <th>sum</th>\n",
" <th>mean</th>\n",
" <th>sum</th>\n",
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" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <th></th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>2006-01-08</th>\n",
" <td>126.834999</td>\n",
" <td>507.339996</td>\n",
" <td>128.730002</td>\n",
" <td>514.920006</td>\n",
" <td>125.877501</td>\n",
" <td>503.510002</td>\n",
" <td>127.959997</td>\n",
" <td>511.839988</td>\n",
" <td>4771825</td>\n",
" <td>19087300</td>\n",
" <td>113.851027</td>\n",
" <td>455.404110</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-15</th>\n",
" <td>130.684000</td>\n",
" <td>653.419998</td>\n",
" <td>132.848001</td>\n",
" <td>664.240006</td>\n",
" <td>130.544000</td>\n",
" <td>652.720001</td>\n",
" <td>131.979999</td>\n",
" <td>659.899994</td>\n",
" <td>4310420</td>\n",
" <td>21552100</td>\n",
" <td>117.427781</td>\n",
" <td>587.138903</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-22</th>\n",
" <td>131.907501</td>\n",
" <td>527.630005</td>\n",
" <td>133.672501</td>\n",
" <td>534.690003</td>\n",
" <td>131.389999</td>\n",
" <td>525.559998</td>\n",
" <td>132.555000</td>\n",
" <td>530.220000</td>\n",
" <td>4653725</td>\n",
" <td>18614900</td>\n",
" <td>117.994103</td>\n",
" <td>471.976414</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-29</th>\n",
" <td>133.771997</td>\n",
" <td>668.859986</td>\n",
" <td>136.083997</td>\n",
" <td>680.419983</td>\n",
" <td>133.310001</td>\n",
" <td>666.550003</td>\n",
" <td>135.153998</td>\n",
" <td>675.769989</td>\n",
" <td>3968500</td>\n",
" <td>19842500</td>\n",
" <td>120.476883</td>\n",
" <td>602.384416</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-02-05</th>\n",
" <td>140.900000</td>\n",
" <td>704.500000</td>\n",
" <td>142.467999</td>\n",
" <td>712.339996</td>\n",
" <td>139.937998</td>\n",
" <td>699.689988</td>\n",
" <td>141.618002</td>\n",
" <td>708.090011</td>\n",
" <td>3920120</td>\n",
" <td>19600600</td>\n",
" <td>126.238926</td>\n",
" <td>631.194630</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low \\\n",
" mean sum mean sum mean \n",
"Date \n",
"2006-01-08 126.834999 507.339996 128.730002 514.920006 125.877501 \n",
"2006-01-15 130.684000 653.419998 132.848001 664.240006 130.544000 \n",
"2006-01-22 131.907501 527.630005 133.672501 534.690003 131.389999 \n",
"2006-01-29 133.771997 668.859986 136.083997 680.419983 133.310001 \n",
"2006-02-05 140.900000 704.500000 142.467999 712.339996 139.937998 \n",
"\n",
" Close Volume Adj Close \\\n",
" sum mean sum mean sum mean \n",
"Date \n",
"2006-01-08 503.510002 127.959997 511.839988 4771825 19087300 113.851027 \n",
"2006-01-15 652.720001 131.979999 659.899994 4310420 21552100 117.427781 \n",
"2006-01-22 525.559998 132.555000 530.220000 4653725 18614900 117.994103 \n",
"2006-01-29 666.550003 135.153998 675.769989 3968500 19842500 120.476883 \n",
"2006-02-05 699.689988 141.618002 708.090011 3920120 19600600 126.238926 \n",
"\n",
" \n",
" sum \n",
"Date \n",
"2006-01-08 455.404110 \n",
"2006-01-15 587.138903 \n",
"2006-01-22 471.976414 \n",
"2006-01-29 602.384416 \n",
"2006-02-05 631.194630 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.resample(\"W\").agg(['mean', 'sum']).head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can upsample to convert to a higher frequency.\n",
"The new points are filled with NaNs."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"0\" 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",
" <th>Adj Close</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",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2006-01-03 00:00:00</th>\n",
" <td>126.699997</td>\n",
" <td>129.440002</td>\n",
" <td>124.230003</td>\n",
" <td>128.869995</td>\n",
" <td>6188700.0</td>\n",
" <td>114.660688</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-03 06:00:00</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-03 12:00:00</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-03 18:00:00</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-04 00:00:00</th>\n",
" <td>127.349998</td>\n",
" <td>128.910004</td>\n",
" <td>126.379997</td>\n",
" <td>127.089996</td>\n",
" <td>4861600.0</td>\n",
" <td>113.076954</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close \\\n",
"Date \n",
"2006-01-03 00:00:00 126.699997 129.440002 124.230003 128.869995 \n",
"2006-01-03 06:00:00 NaN NaN NaN NaN \n",
"2006-01-03 12:00:00 NaN NaN NaN NaN \n",
"2006-01-03 18:00:00 NaN NaN NaN NaN \n",
"2006-01-04 00:00:00 127.349998 128.910004 126.379997 127.089996 \n",
"\n",
" Volume Adj Close \n",
"Date \n",
"2006-01-03 00:00:00 6188700.0 114.660688 \n",
"2006-01-03 06:00:00 NaN NaN \n",
"2006-01-03 12:00:00 NaN NaN \n",
"2006-01-03 18:00:00 NaN NaN \n",
"2006-01-04 00:00:00 4861600.0 113.076954 "
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.resample(\"6H\").mean().head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Rolling / Expanding / EW"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These methods aren't unique to DatetimeIndexes, but they often make sense with timeseries, so I'll show them here."
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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RFK6f8zVsSZ34FG1/W/WBtmO6huEKjMfIGKJhS0OPFviSTAlRyzk/WFtJW0v4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\nuJ3hU6ew1J2jb/ceXD29+J1Ohk5UMnSiEkGtxlQ8g+y77iB+wXw58id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xVVlunfvQdvUzM9H27CdSCx95A5Nxf75EnkrFxB5tLFYnGBIRE+kdI5LhTl2Kmq66GlaxSCT6fD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\nW7M62fHeQ9g74nQ4WffhYQ7uVT8zTbtuMEGdnM8nrj16nZ7X5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hKsZ/ywfiREm7hp6iB3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\niYiIiIiIdFBK+ERERERERDqo/x/NP6y8AINmVgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1b2afae80>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gs.Close.plot(label='Raw')\n",
"gs.Close.rolling(28).mean().plot(label='28D MA')\n",
"gs.Close.expanding(7).mean().plot(label='7D EA')\n",
"gs.Close.ewm(alpha=0.03).mean().plot(label='EWMA($\\\\alpha=.03$)')\n",
"\n",
"plt.legend(bbox_to_anchor=(1.25, .5))\n",
"plt.tight_layout()\n",
"sns.despine()\n",
"plt.savefig('../output/images/ts-reew.svg', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Each of `.rolling`, `.expanding`, and `.ewm` return a deferred object, similar to a GroupBy."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Rolling [window=30,center=True,axis=0]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"roll = gs.Close.rolling(30, center=True)\n",
"roll"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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324XrdnciEZnLZLeLuXGnEWRH4jJ6LubPZtsc1RgZm1rRsRFCCFkZCrIJqbD+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\nsckmIiIiIpIZm2wiIiIiIpn9D/hjC//pQJTGAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1b2a14f28>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"m = roll.agg(['mean', 'std'])\n",
"ax = m['mean'].plot()\n",
"ax.fill_between(m.index, m['mean'] - m['std'], m['mean'] + m['std'],\n",
" alpha=.25)\n",
"plt.tight_layout()\n",
"sns.despine()\n",
"plt.savefig('../output/images/ts-roll.svg', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Grab Bag\n",
"\n",
"### Offsets\n",
"\n",
"These are similar to `dateutil.relativedelta`, but works with arrays."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"DatetimeIndex(['2006-04-01', '2006-04-02', '2006-04-03', '2006-04-04',\n",
" '2006-04-07', '2006-04-08', '2006-04-09', '2006-04-10',\n",
" '2006-04-11', '2006-04-15',\n",
" ...\n",
" '2010-03-15', '2010-03-16', '2010-03-19', '2010-03-20',\n",
" '2010-03-21', '2010-03-22', '2010-03-26', '2010-03-27',\n",
" '2010-03-28', '2010-03-29'],\n",
" dtype='datetime64[ns]', name='Date', length=1007, freq=None)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.index + pd.DateOffset(months=3, days=-2)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Holiday Calendars\n",
"\n",
"There are a whole bunch of special calendars, useful for traders probabaly."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from pandas.tseries.holiday import USColumbusDay"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"DatetimeIndex(['2015-10-12', '2016-10-10', '2017-10-09', '2018-10-08',\n",
" '2019-10-14'],\n",
" dtype='datetime64[ns]', freq='WOM-2MON')"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"USColumbusDay.dates('2015-01-01', '2020-01-01')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Timezones\n",
"\n",
"Pandas works with `pytz` for nice timezone-aware datetimes.\n",
"The typical workflow is\n",
"\n",
"1. localize timezone-naive timestamps to some timezone\n",
"2. convert to desired timezone\n",
"\n",
"If you already have timezone-aware Timestamps, there's no need for step one. "
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"0\" 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",
" <th>Adj Close</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",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2006-01-03 05:00:00+00:00</th>\n",
" <td>126.699997</td>\n",
" <td>129.440002</td>\n",
" <td>124.230003</td>\n",
" <td>128.869995</td>\n",
" <td>6188700</td>\n",
" <td>114.660688</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-04 05:00:00+00:00</th>\n",
" <td>127.349998</td>\n",
" <td>128.910004</td>\n",
" <td>126.379997</td>\n",
" <td>127.089996</td>\n",
" <td>4861600</td>\n",
" <td>113.076954</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-05 05:00:00+00:00</th>\n",
" <td>126.000000</td>\n",
" <td>127.320000</td>\n",
" <td>125.610001</td>\n",
" <td>127.040001</td>\n",
" <td>3717400</td>\n",
" <td>113.032471</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-06 05:00:00+00:00</th>\n",
" <td>127.290001</td>\n",
" <td>129.250000</td>\n",
" <td>127.290001</td>\n",
" <td>128.839996</td>\n",
" <td>4319600</td>\n",
" <td>114.633997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-09 05:00:00+00:00</th>\n",
" <td>128.500000</td>\n",
" <td>130.619995</td>\n",
" <td>128.000000</td>\n",
" <td>130.389999</td>\n",
" <td>4723500</td>\n",
" <td>116.013096</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close \\\n",
"Date \n",
"2006-01-03 05:00:00+00:00 126.699997 129.440002 124.230003 128.869995 \n",
"2006-01-04 05:00:00+00:00 127.349998 128.910004 126.379997 127.089996 \n",
"2006-01-05 05:00:00+00:00 126.000000 127.320000 125.610001 127.040001 \n",
"2006-01-06 05:00:00+00:00 127.290001 129.250000 127.290001 128.839996 \n",
"2006-01-09 05:00:00+00:00 128.500000 130.619995 128.000000 130.389999 \n",
"\n",
" Volume Adj Close \n",
"Date \n",
"2006-01-03 05:00:00+00:00 6188700 114.660688 \n",
"2006-01-04 05:00:00+00:00 4861600 113.076954 \n",
"2006-01-05 05:00:00+00:00 3717400 113.032471 \n",
"2006-01-06 05:00:00+00:00 4319600 114.633997 \n",
"2006-01-09 05:00:00+00:00 4723500 116.013096 "
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# tz naiive -> tz aware..... to desired UTC\n",
"gs.tz_localize('US/Eastern').tz_convert('UTC').head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Modeling Time Series\n",
"\n",
"The rest of this post will focus on time series in the econometric sense.\n",
"My indented reader for this section isn't all that clear, so I apologize upfront for any sudden shifts in complexity.\n",
"I'm roughly targeting material that could be presented in a first or second semester applied statisctics course.\n",
"What follows certainly isn't a replacement for that.\n",
"Any formality will be restricted to footnotes for the curious.\n",
"I've put a whole bunch of resources at the end for people earger to learn more.\n",
"\n",
"We'll focus on modelling Average Monthly Flights. Let's download the data.\n",
"If you've been following along in the series, you've seen most of this code before, so feel free to skip."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import os\n",
"import io\n",
"import glob\n",
"import zipfile\n",
"\n",
"import requests\n",
"import statsmodels.api as sm\n",
"\n",
"\n",
"def download_one(date):\n",
" '''\n",
" Download a single month's flights\n",
" '''\n",
" month = date.month\n",
" year = date.year\n",
" month_name = date.strftime('%B')\n",
" headers = {\n",
" 'Pragma': 'no-cache',\n",
" 'Origin': 'http://www.transtats.bts.gov',\n",
" 'Accept-Encoding': 'gzip, deflate',\n",
" 'Accept-Language': 'en-US,en;q=0.8',\n",
" 'Upgrade-Insecure-Requests': '1',\n",
" 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.87 Safari/537.36',\n",
" 'Content-Type': 'application/x-www-form-urlencoded',\n",
" 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',\n",
" 'Cache-Control': 'no-cache',\n",
" 'Referer': 'http://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236&DB_Short_Name=On-Time',\n",
" 'Connection': 'keep-alive',\n",
" 'DNT': '1',\n",
" }\n",
" os.makedirs('timeseries', exist_ok=True)\n",
" data = 'UserTableName=On_Time_Performance&DBShortName=On_Time&RawDataTable=T_ONTIME&sqlstr=+SELECT+FL_DATE%2CUNIQUE_CARRIER%2CCARRIER%2CTAIL_NUM%2CFL_NUM%2CORIGIN%2CDEST%2CCRS_DEP_TIME%2CDEP_TIME%2CTAXI_OUT%2CWHEELS_OFF%2CWHEELS_ON%2CTAXI_IN%2CCRS_ARR_TIME%2CARR_TIME%2CDISTANCE%2CCARRIER_DELAY%2CWEATHER_DELAY%2CNAS_DELAY%2CSECURITY_DELAY%2CLATE_AIRCRAFT_DELAY+FROM++T_ONTIME+WHERE+%28+DEST_STATE_NM%3D%27Illinois%27+OR+ORIGIN_STATE_NM+%3D%27Illinois%27+%29++AND+Month+%3D{month}+AND+YEAR%3D{year}&varlist=FL_DATE%2CUNIQUE_CARRIER%2CCARRIER%2CTAIL_NUM%2CFL_NUM%2CORIGIN%2CDEST%2CCRS_DEP_TIME%2CDEP_TIME%2CTAXI_OUT%2CWHEELS_OFF%2CWHEELS_ON%2CTAXI_IN%2CCRS_ARR_TIME%2CARR_TIME%2CDISTANCE%2CCARRIER_DELAY%2CWEATHER_DELAY%2CNAS_DELAY%2CSECURITY_DELAY%2CLATE_AIRCRAFT_DELAY&grouplist=&suml=&sumRegion=&filter1=title%3D&filter2=title%3D&geo=Illinois&time={month_name}&timename=Month&GEOGRAPHY=Illinois&XYEAR={year}&FREQUENCY={month}&VarDesc=Year&VarType=Num&VarDesc=Quarter&VarType=Num&VarDesc=Month&VarType=Num&VarDesc=DayofMonth&VarType=Num&VarDesc=DayOfWeek&VarType=Num&VarName=FL_DATE&VarDesc=FlightDate&VarType=Char&VarName=UNIQUE_CARRIER&VarDesc=UniqueCarrier&VarType=Char&VarDesc=AirlineID&VarType=Num&VarName=CARRIER&VarDesc=Carrier&VarType=Char&VarName=TAIL_NUM&VarDesc=TailNum&VarType=Char&VarName=FL_NUM&VarDesc=FlightNum&VarType=Char&VarDesc=OriginAirportID&VarType=Num&VarDesc=OriginAirportSeqID&VarType=Num&VarDesc=OriginCityMarketID&VarType=Num&VarName=ORIGIN&VarDesc=Origin&VarType=Char&VarDesc=OriginCityName&VarType=Char&VarDesc=OriginState&VarType=Char&VarDesc=OriginStateFips&VarType=Char&VarDesc=OriginStateName&VarType=Char&VarDesc=OriginWac&VarType=Num&VarDesc=DestAirportID&VarType=Num&VarDesc=DestAirportSeqID&VarType=Num&VarDesc=DestCityMarketID&VarType=Num&VarName=DEST&VarDesc=Dest&VarType=Char&VarDesc=DestCityName&VarType=Char&VarDesc=DestState&VarType=Char&VarDesc=DestStateFips&VarType=Char&VarDesc=DestStateName&VarType=Char&VarDesc=DestWac&VarType=Num&VarName=CRS_DEP_TIME&VarDesc=CRSDepTime&VarType=Char&VarName=DEP_TIME&VarDesc=DepTime&VarType=Char&VarDesc=DepDelay&VarType=Num&VarDesc=DepDelayMinutes&VarType=Num&VarDesc=DepDel15&VarType=Num&VarDesc=DepartureDelayGroups&VarType=Num&VarDesc=DepTimeBlk&VarType=Char&VarName=TAXI_OUT&VarDesc=TaxiOut&VarType=Num&VarName=WHEELS_OFF&VarDesc=WheelsOff&VarType=Char&VarName=WHEELS_ON&VarDesc=WheelsOn&VarType=Char&VarName=TAXI_IN&VarDesc=TaxiIn&VarType=Num&VarName=CRS_ARR_TIME&VarDesc=CRSArrTime&VarType=Char&VarName=ARR_TIME&VarDesc=ArrTime&VarType=Char&VarDesc=ArrDelay&VarType=Num&VarDesc=ArrDelayMinutes&VarType=Num&VarDesc=ArrDel15&VarType=Num&VarDesc=ArrivalDelayGroups&VarType=Num&VarDesc=ArrTimeBlk&VarType=Char&VarDesc=Cancelled&VarType=Num&VarDesc=CancellationCode&VarType=Char&VarDesc=Diverted&VarType=Num&VarDesc=CRSElapsedTime&VarType=Num&VarDesc=ActualElapsedTime&VarType=Num&VarDesc=AirTime&VarType=Num&VarDesc=Flights&VarType=Num&VarName=DISTANCE&VarDesc=Distance&VarType=Num&VarDesc=DistanceGroup&VarType=Num&VarName=CARRIER_DELAY&VarDesc=CarrierDelay&VarType=Num&VarName=WEATHER_DELAY&VarDesc=WeatherDelay&VarType=Num&VarName=NAS_DELAY&VarDesc=NASDelay&VarType=Num&VarName=SECURITY_DELAY&VarDesc=SecurityDelay&VarType=Num&VarName=LATE_AIRCRAFT_DELAY&VarDesc=LateAircraftDelay&VarType=Num&VarDesc=FirstDepTime&VarType=Char&VarDesc=TotalAddGTime&VarType=Num&VarDesc=LongestAddGTime&VarType=Num&VarDesc=DivAirportLandings&VarType=Num&VarDesc=DivReachedDest&VarType=Num&VarDesc=DivActualElapsedTime&VarType=Num&VarDesc=DivArrDelay&VarType=Num&VarDesc=DivDistance&VarType=Num&VarDesc=Div1Airport&VarType=Char&VarDesc=Div1AirportID&VarType=Num&VarDesc=Div1AirportSeqID&VarType=Num&VarDesc=Div1WheelsOn&VarType=Char&VarDesc=Div1TotalGTime&VarType=Num&VarDesc=Div1LongestGTime&VarType=Num&VarDesc=Div1WheelsOff&VarType=Char&VarDesc=Div1TailNum&VarType=Char&VarDesc=Div2Airport&VarType=Char&VarDesc=Div2AirportID&VarType=Num&VarDesc=Div2AirportSeqID&VarType=Num&VarDesc=Div2WheelsOn&VarType=Char&VarDesc=Div2TotalGTime&VarType=Num&VarDesc=Div2LongestGTime&VarType=Num&VarDesc=Div2WheelsOff&VarType=Char&VarDesc=Div2TailNum&VarType=Char&VarDesc=Div3Airport&VarType=Char&VarDesc=Div3AirportID&VarType=Num&VarDesc=Div3AirportSeqID&VarType=Num&VarDesc=Div3WheelsOn&VarType=Char&VarDesc=Div3TotalGTime&VarType=Num&VarDesc=Div3LongestGTime&VarType=Num&VarDesc=Div3WheelsOff&VarType=Char&VarDesc=Div3TailNum&VarType=Char&VarDesc=Div4Airport&VarType=Char&VarDesc=Div4AirportID&VarType=Num&VarDesc=Div4AirportSeqID&VarType=Num&VarDesc=Div4WheelsOn&VarType=Char&VarDesc=Div4TotalGTime&VarType=Num&VarDesc=Div4LongestGTime&VarType=Num&VarDesc=Div4WheelsOff&VarType=Char&VarDesc=Div4TailNum&VarType=Char&VarDesc=Div5Airport&VarType=Char&VarDesc=Div5AirportID&VarType=Num&VarDesc=Div5AirportSeqID&VarType=Num&VarDesc=Div5WheelsOn&VarType=Char&VarDesc=Div5TotalGTime&VarType=Num&VarDesc=Div5LongestGTime&VarType=Num&VarDesc=Div5WheelsOff&VarType=Char&VarDesc=Div5TailNum&VarType=Char'\n",
"\n",
" r = requests.post('http://www.transtats.bts.gov/DownLoad_Table.asp?Table_ID=236&Has_Group=3&Is_Zipped=0',\n",
" headers=headers, data=data.format(year=year, month=month, month_name=month_name),\n",
" stream=True)\n",
" fp = os.path.join('timeseries', '{}-{}.zip'.format(year, month))\n",
"\n",
" with open(fp, 'wb') as f:\n",
" for chunk in r.iter_content(chunk_size=1024): \n",
" if chunk:\n",
" f.write(chunk)\n",
" return fp\n",
" \n",
"def download_many(start, end):\n",
" months = pd.date_range(start, end=end, freq='M') \n",
" # We could easily parallelize this loop.\n",
" for i, month in enumerate(months):\n",
" download_one(month)\n",
" \n",
"def unzip_one(fp):\n",
" zf = zipfile.ZipFile(fp)\n",
" csv = zf.extract(zf.filelist[0])\n",
" return csv\n",
"\n",
"def time_to_datetime(df, columns):\n",
" '''\n",
" Combine all time items into datetimes.\n",
" \n",
" 2014-01-01,1149.0 -> 2014-01-01T11:49:00\n",
" '''\n",
" def converter(col):\n",
" timepart = (col.astype(str)\n",
" .str.replace('\\.0$', '') # NaNs force float dtype\n",
" .str.pad(4, fillchar='0'))\n",
" return pd.to_datetime(df['fl_date'] + ' ' +\n",
" timepart.str.slice(0, 2) + ':' +\n",
" timepart.str.slice(2, 4),\n",
" errors='coerce')\n",
" return datetime_part\n",
" df[columns] = df[columns].apply(converter)\n",
" return df\n",
"\n",
"\n",
"def read_one(fp):\n",
" df = (pd.read_csv(fp, encoding='latin1')\n",
" .rename(columns=str.lower)\n",
" .drop('unnamed: 21', axis=1)\n",
" .pipe(time_to_datetime, ['dep_time', 'arr_time', 'crs_arr_time',\n",
" 'crs_dep_time'])\n",
" .assign(fl_date=lambda x: pd.to_datetime(x['fl_date'])))\n",
" return df"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"download_many('2000-01-01', '2016-01-01')\n",
"\n",
"zips = glob.glob(os.path.join('timeseries', '*.zip'))\n",
"csvs = [unzip_one(fp) for fp in zips]\n",
"dfs = [read_one(fp) for fp in csvs]\n",
"df = pd.concat(dfs, ignore_index=True)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"fl_date datetime64[ns]\n",
"unique_carrier category\n",
"carrier category\n",
"tail_num category\n",
"fl_num int64\n",
"origin category\n",
"dest category\n",
"crs_dep_time datetime64[ns]\n",
"dep_time datetime64[ns]\n",
"taxi_out float64\n",
"wheels_off float64\n",
"wheels_on float64\n",
"taxi_in float64\n",
"crs_arr_time datetime64[ns]\n",
"arr_time datetime64[ns]\n",
"distance float64\n",
"carrier_delay float64\n",
"weather_delay float64\n",
"nas_delay float64\n",
"security_delay float64\n",
"late_aircraft_delay float64\n",
"dtype: object\n"
]
}
],
"source": [
"with pd.option_context('display.max_rows', 100):\n",
" print(df.dtypes)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cat_cols = ['unique_carrier', 'carrier', 'tail_num', 'origin', 'dest']\n",
"\n",
"df[cat_cols] = df[cat_cols].apply(pd.Categorical)\n",
"\n",
"df.to_hdf('ts.hdf5', 'ts', format='table')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"df = pd.read_hdf('ts.hdf5', 'ts')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can calculate the historical values with a resample."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"2000-01-01 1882.387097\n",
"2000-02-01 1926.896552\n",
"2000-03-01 1951.000000\n",
"2000-04-01 1944.400000\n",
"2000-05-01 1957.967742\n",
"Freq: MS, Name: fl_date, dtype: float64"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"daily = df.fl_date.value_counts().sort_index()\n",
"y = daily.resample('MS').mean()\n",
"y.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that I use the `\"MS\"` frequency code there.\n",
"Pandas defaults to end of month (or end of year).\n",
"Append an `'S'` to get the start."
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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RjIbkFDNEz2HvoAMFZnkqub62DCeaBzAw7ITPL2kuYxMRZQOWeonG6eofQ8+AnJ0TK1zC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\n/AiCIAiCIEYJ/z+1PA/eMBrvygAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1b24e26d8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"y.plot()\n",
"sns.despine()\n",
"plt.savefig('../output/images/ts-y.svg', transparent=True)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import statsmodels.formula.api as smf\n",
"import statsmodels.tsa.api as smt\n",
"import statsmodels.api as sm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Think back to a typical regression problem, ignoring anything to do wtih time series for now.\n",
"The usual task is to predict some value $y$ using some a linear combination of features in $X$.\n",
"\n",
"$$y = \\beta_0 + \\beta_1 X_1 + \\ldots + \\beta_p X_p + \\epsilon$$\n",
"\n",
"When working with time series, some of the most important (and sometimes *only*) features are the previous, or *lagged*, values of $y$.\n",
"\n",
"We'll start by doing just that: running a regression of `y` on lagged values of itself.\n",
"We'll see that this regression suffers from a few problems: multicolinearity, autocorrelation, non-stationarity, and seasonality.\n",
"Once we touch on each of those problems, we'll use a second model, seasonal ARIMA, which handles those problems for us.\n",
"\n",
"First, let's create a dataframe with our lagged values of `y` using the `.shift` method, which shifts the index `i` periods, so it lines up with that observation."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"0\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>y</th>\n",
" <th>L1</th>\n",
" <th>L2</th>\n",
" <th>L3</th>\n",
" <th>L4</th>\n",
" <th>L5</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2000-06-01</th>\n",
" <td>1976.133333</td>\n",
" <td>1957.967742</td>\n",
" <td>1944.400000</td>\n",
" <td>1951.000000</td>\n",
" <td>1926.896552</td>\n",
" <td>1882.387097</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-07-01</th>\n",
" <td>1937.032258</td>\n",
" <td>1976.133333</td>\n",
" <td>1957.967742</td>\n",
" <td>1944.400000</td>\n",
" <td>1951.000000</td>\n",
" <td>1926.896552</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-08-01</th>\n",
" <td>1960.354839</td>\n",
" <td>1937.032258</td>\n",
" <td>1976.133333</td>\n",
" <td>1957.967742</td>\n",
" <td>1944.400000</td>\n",
" <td>1951.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-09-01</th>\n",
" <td>1900.533333</td>\n",
" <td>1960.354839</td>\n",
" <td>1937.032258</td>\n",
" <td>1976.133333</td>\n",
" <td>1957.967742</td>\n",
" <td>1944.400000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-10-01</th>\n",
" <td>1931.677419</td>\n",
" <td>1900.533333</td>\n",
" <td>1960.354839</td>\n",
" <td>1937.032258</td>\n",
" <td>1976.133333</td>\n",
" <td>1957.967742</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" y L1 L2 L3 L4 \\\n",
"2000-06-01 1976.133333 1957.967742 1944.400000 1951.000000 1926.896552 \n",
"2000-07-01 1937.032258 1976.133333 1957.967742 1944.400000 1951.000000 \n",
"2000-08-01 1960.354839 1937.032258 1976.133333 1957.967742 1944.400000 \n",
"2000-09-01 1900.533333 1960.354839 1937.032258 1976.133333 1957.967742 \n",
"2000-10-01 1931.677419 1900.533333 1960.354839 1937.032258 1976.133333 \n",
"\n",
" L5 \n",
"2000-06-01 1882.387097 \n",
"2000-07-01 1926.896552 \n",
"2000-08-01 1951.000000 \n",
"2000-09-01 1944.400000 \n",
"2000-10-01 1957.967742 "
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X = (pd.concat([y.shift(i) for i in range(6)], axis=1,\n",
" keys=['y'] + ['L%s' % i for i in range(1, 6)])\n",
" .dropna())\n",
"X.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can fit the lagged model using statsmodels (which uses [patsy](http://patsy.readthedocs.org) to translate the formula string to a design matrix)."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"simpletable\">\n",
"<caption>OLS Regression Results</caption>\n",
"<tr>\n",
" <th>Dep. Variable:</th> <td>y</td> <th> R-squared: </th> <td> 0.881</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Model:</th> <td>OLS</td> <th> Adj. R-squared: </th> <td> 0.877</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td> 221.7</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Date:</th> <td>Fri, 13 May 2016</td> <th> Prob (F-statistic):</th> <td>2.40e-80</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Time:</th> <td>16:14:16</td> <th> Log-Likelihood: </th> <td> -1076.6</td>\n",
"</tr>\n",
"<tr>\n",
" <th>No. Observations:</th> <td> 187</td> <th> AIC: </th> <td> 2167.</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Df Residuals:</th> <td> 180</td> <th> BIC: </th> <td> 2190.</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Df Model:</th> <td> 6</td> <th> </th> <td> </td> \n",
"</tr>\n",
"<tr>\n",
" <th>Covariance Type:</th> <td>nonrobust</td> <th> </th> <td> </td> \n",
"</tr>\n",
"</table>\n",
"<table class=\"simpletable\">\n",
"<tr>\n",
" <td></td> <th>coef</th> <th>std err</th> <th>t</th> <th>P>|t|</th> <th>[0.025</th> <th>0.975]</th> \n",
"</tr>\n",
"<tr>\n",
" <th>Intercept</th> <td> 208.2440</td> <td> 65.495</td> <td> 3.180</td> <td> 0.002</td> <td> 79.008</td> <td> 337.480</td>\n",
"</tr>\n",
"<tr>\n",
" <th>trend</th> <td> -0.1123</td> <td> 0.106</td> <td> -1.055</td> <td> 0.293</td> <td> -0.322</td> <td> 0.098</td>\n",
"</tr>\n",
"<tr>\n",
" <th>L1</th> <td> 1.0489</td> <td> 0.075</td> <td> 14.052</td> <td> 0.000</td> <td> 0.902</td> <td> 1.196</td>\n",
"</tr>\n",
"<tr>\n",
" <th>L2</th> <td> -0.0001</td> <td> 0.108</td> <td> -0.001</td> <td> 0.999</td> <td> -0.213</td> <td> 0.213</td>\n",
"</tr>\n",
"<tr>\n",
" <th>L3</th> <td> -0.1450</td> <td> 0.108</td> <td> -1.346</td> <td> 0.180</td> <td> -0.358</td> <td> 0.068</td>\n",
"</tr>\n",
"<tr>\n",
" <th>L4</th> <td> -0.0393</td> <td> 0.109</td> <td> -0.361</td> <td> 0.719</td> <td> -0.254</td> <td> 0.175</td>\n",
"</tr>\n",
"<tr>\n",
" <th>L5</th> <td> 0.0506</td> <td> 0.074</td> <td> 0.682</td> <td> 0.496</td> <td> -0.096</td> <td> 0.197</td>\n",
"</tr>\n",
"</table>\n",
"<table class=\"simpletable\">\n",
"<tr>\n",
" <th>Omnibus:</th> <td>55.872</td> <th> Durbin-Watson: </th> <td> 2.009</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Prob(Omnibus):</th> <td> 0.000</td> <th> Jarque-Bera (JB): </th> <td> 322.488</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Skew:</th> <td> 0.956</td> <th> Prob(JB): </th> <td>9.39e-71</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Kurtosis:</th> <td> 9.142</td> <th> Cond. No. </th> <td>5.97e+04</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<class 'statsmodels.iolib.summary.Summary'>\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: y R-squared: 0.881\n",
"Model: OLS Adj. R-squared: 0.877\n",
"Method: Least Squares F-statistic: 221.7\n",
"Date: Fri, 13 May 2016 Prob (F-statistic): 2.40e-80\n",
"Time: 16:14:16 Log-Likelihood: -1076.6\n",
"No. Observations: 187 AIC: 2167.\n",
"Df Residuals: 180 BIC: 2190.\n",
"Df Model: 6 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [0.025 0.975]\n",
"------------------------------------------------------------------------------\n",
"Intercept 208.2440 65.495 3.180 0.002 79.008 337.480\n",
"trend -0.1123 0.106 -1.055 0.293 -0.322 0.098\n",
"L1 1.0489 0.075 14.052 0.000 0.902 1.196\n",
"L2 -0.0001 0.108 -0.001 0.999 -0.213 0.213\n",
"L3 -0.1450 0.108 -1.346 0.180 -0.358 0.068\n",
"L4 -0.0393 0.109 -0.361 0.719 -0.254 0.175\n",
"L5 0.0506 0.074 0.682 0.496 -0.096 0.197\n",
"==============================================================================\n",
"Omnibus: 55.872 Durbin-Watson: 2.009\n",
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 322.488\n",
"Skew: 0.956 Prob(JB): 9.39e-71\n",
"Kurtosis: 9.142 Cond. No. 5.97e+04\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
"[2] The condition number is large, 5.97e+04. This might indicate that there are\n",
"strong multicollinearity or other numerical problems.\n",
"\"\"\""
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mod_lagged = smf.ols('y ~ trend + L1 + L2 + L3 + L4 + L5',\n",
" data=X.assign(trend=np.arange(len(X))))\n",
"res_lagged = mod_lagged.fit()\n",
"res_lagged.summary()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are a few problems with this approach though.\n",
"Since our lagged values are highly correlated with each other, our regression suffers from multicollinearity.\n",
"That ruins our estimates of the slopes."
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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AAMvYgG6iMgUAAGADlSkAAGAZhSkTyRQAALAsjmwqhDYfAACADVSmAACAZWxAN4WtTHV0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\nIOcz0/8AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10e372278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.heatmap(X.corr())\n",
"plt.savefig('../output/images/ts-corr.svg', transparent=True);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Seoncd, we'd intuitively expect the $\\beta_i$s to gradually decline to zero.\n",
"The immediately preceding period should be most important ($\\beta_1$ is the largest coefficient in absolute value), followed by $\\beta_2$, and $\\beta_3$...\n",
"Looking at the regression summary and the bar graph below, this isn't the case (the cause is related to multicolinearity)."
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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AIAckn3E86aSTYsGCBfHxxx/HP/zDP8Szzz4bHTp0iPvuuy8GDx7cnDMCAJADks84RkQc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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1b2b207f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"res_lagged.params.drop(['Intercept', 'trend']).plot.bar(rot=0)\n",
"plt.ylabel('Coefficeint')\n",
"sns.despine()\n",
"plt.savefig('../output/images/ts-lagged-coef.svg', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally, our degrees of freedom drop since we lose two for each variable (one for estimating the coefficient, one for the lost observation as a result of the `shift`).\n",
"At least in (macro)econometrics, each observation is precious and we're loath to throw them away, though sometimes that's unavoidable."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Autocorrelation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another problem our lagged model suffered from is autocorrelation (also know as serial correlation).\n",
"Roughly speaking, autocorrelation is when there's a clear pattern in the residuals.\n",
"Let's fit a simple model of $y = \\beta_0 + \\beta_1 T + \\epsilon$, where `T` is the time trend (`np.arange(len(y))`)."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# `Results.resid` is a Series of residuals: y - ŷ\n",
"mod_trend = sm.OLS.from_formula(\n",
" 'y ~ trend', data=y.to_frame(name='y')\n",
" .assign(trend=np.arange(len(y))))\n",
"res_trend = mod_trend.fit()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Residuals (the observed minus the expected, or $\\hat{e_t} = y_t - \\hat{y_t}$) are supposed to be [white noise](https://en.wikipedia.org/wiki/White_noise).\n",
"That's [one of the assumptions](https://en.wikipedia.org/wiki/Gauss–Markov_theorem) many of the properties of linear regression are founded upon.\n",
"In this case there's a correlation between one residual and the next: if the residual at time $t$ was above expecation, then the residual at time $t + 1$ is *much* more likely to be above average as well ($e_t > 0 \\implies E_t[e_{t+1}] > 0$).\n",
"\n",
"We'll define a helper function to plot the residuals time series, and some diagnostics about them."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def tsplot(y, lags=None, figsize=(10, 8)):\n",
" fig = plt.figure(figsize=figsize)\n",
" layout = (2, 2)\n",
" ts_ax = plt.subplot2grid(layout, (0, 0), colspan=2)\n",
" acf_ax = plt.subplot2grid(layout, (1, 0))\n",
" pacf_ax = plt.subplot2grid(layout, (1, 1))\n",
" \n",
" y.plot(ax=ts_ax)\n",
" smt.graphics.plot_acf(y, lags=lags, ax=acf_ax)\n",
" smt.graphics.plot_pacf(y, lags=lags, ax=pacf_ax)\n",
" [ax.set_xlim(1.5) for ax in [acf_ax, pacf_ax]]\n",
" sns.despine()\n",
" plt.tight_layout()\n",
" return ts_ax, acf_ax, pacf_ax"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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q7698DhS8ALB0RgFaOgx487Nz+PJwk3D5jQtLIIkBT2xRTjIuNvXGZOMaWRpi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\nokOgL5LS8hDc0kfp4ZAVeXs4I7eguEoZ3gCT3sJKeHZSZ6RkFCiaaa4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CRYsWKT2MCnEO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\nRERJjQkvERERESW1/w/hM7rBDKeQtwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1b2a1fd68>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"tsplot(res_trend.resid, lags=36)\n",
"plt.savefig('../output/images/ts-res-trend-tsplot.svg', transparent=True);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The top subplot shows the time series of our residuals $e_t$.\n",
"The bottom left is the [autocorrelation](https://www.otexts.org/fpp/2/2#autocorrelation) of the residuals.\n",
"It measures the correlation between a a value and it's lagged self, e.g. $corr(e_t, e_{t-1}), corr(e_t, e_{t-2}), \\ldots$.\n",
"I won't really go into partial autocorrelation, but it's a similar concept.\n",
"\n",
"Autocorelation is a problem in regular regressions like above, but we'll use it to our advantage when we setup an ARIMA model below."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Stationarity\n",
"\n",
"It's important that your dataset be stationary, otherwise you run the risk of finding [spurious correlations](http://www.tylervigen.com/spurious-correlations).\n",
"Granger and Newbold (1974) as well.\n",
"The typical way to handle non-stationarity is to difference the non-stationary variable until is is stationary."
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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vT44yXSI4wJfQID+vr0/QOr4+avpHB3G5tJ5LpXVMGtWvu5ckEAh6ISLtK+g2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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1b26aa0f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"y.to_frame(name='y').assign(Δy=lambda x: x.y.diff()).plot(subplots=True)\n",
"sns.despine()\n",
"plt.savefig('../output/images/ts-y-deltay.svg', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Our original series actually doesn't look *that* bad.\n",
"But we have more rigorous methods for detetcing whether a series is non-stationary.\n",
"One example is the Augmented Dickey-Fuller test.\n",
"It's a statistical hypothesis test that says:\n",
"\n",
"$H_0$ (null hypothesis): $y$ is non-stationary\n",
"\n",
"$H_A$ (alternative hypothesis): $y$ is stationary\n",
"\n",
"\n",
"$$y_t^\\prime = \\phi y_{t-1} + \\beta_1 y_{t-1}^\\prime + \\beta_2 y_{t-2}^\\prime + \\ldots + \\beta_k y_{t-k}^\\prime$$\n",
"\n",
"This is implemented in statsmodels as `smt.adfuller`. The return type is a bit busy for me, so we'll wrap it in a `namedtuple`."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from collections import namedtuple\n",
"\n",
"ADF = namedtuple(\"ADF\", \"adf pvalue usedlag nobs critical icbest\")"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"ADF(adf=-1.9904608794641487, pvalue=0.29077127047555601, usedlag=15, nobs=176, critical={'1%': -3.4680615871598537, '10%': -2.5756015922004134, '5%': -2.8781061899535128}, icbest=1987.6605732826176)"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ADF(*smt.adfuller(y))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So we failed to reject the null hypothesis that the original series was non-stationary.\n",
"Let's difference it."
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"ADF(adf=-3.5862361055645211, pvalue=0.0060296818910968268, usedlag=14, nobs=176, critical={'1%': -3.4680615871598537, '10%': -2.5756015922004134, '5%': -2.8781061899535128}, icbest=1979.6445486427308)"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ADF(*smt.adfuller(y.diff().dropna()))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This looks better.\n",
"It's not statistically significant at the 5% level, but who cares what statisticins say anyway.\n",
"\n",
"We'll fit another OLS model of $\\Delta y = \\beta_0 + \\beta_1 L \\Delta y_{t-1} + e_t$"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"data = (y.to_frame(name='y')\n",
" .assign(Δy=lambda df: df.y.diff())\n",
" .assign(LΔy=lambda df: df.Δy.shift()))\n",
"mod_stationary = smf.ols('Δy ~ LΔy', data=data.dropna())\n",
"res_stationary = mod_stationary.fit()"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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0EARBEASRLCR4TUTv6OozvUT3qBleC3VpIAiCIAjCNEjwmoje4aU+vImhtiWzUZcGgiAI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\nU5ChEp3c0FuYefgAHxtxF4NFJ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KGamho99thjrrgWvduOV3LfMbvteKXhx+zGHt5MibmS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\n0Uh4AQAA4GgkvAAAAHC0/w+Ov/2Anz7TswAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10dacac50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"tsplot(res_stationary.resid, lags=24)\n",
"plt.savefig('../output/images/ts-stationary.svg', transparent=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So we've taken care of multicolinearity, autocorelation, and stationarity, but we still aren't done."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Seasonality"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Our last issue to deal with is seasonality: we have strong monthly seasonality."
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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dIQ/H5HDxsoJ8eZVwhhH8rfnwh1jOJBYQ7OdKeO/OhAV0wtbaor2HdddRrVRT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O655/DKK6/Y1M8GgF27dmHBggW0d3rx4sX46KOPsGjRIuzevRu33norRo+2xOS+9NJLmDJlCpqa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KzuXX4w/vn8HGD87CwLOy+++j1/CrV4/gd++eRE5xI6dKFo3eYGRyiWdPHc3kEgsEAvz2kSkY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\nRK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1b2859198>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"smt.seasonal_decompose(y).plot()\n",
"plt.savefig('../output/images/ts-decompose.svg', transparent=True);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are a few ways to handle seasonality. We'll just rely on the `SARIMAX` method to do it for us. For now, recognize that it's a problem."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## ARIMA\n",
"\n",
"So, we've sketched the problems with regular old regression: multicolinearity, autocorrelation, non-stationarity, and seasonality.\n",
"Our tool of choice, `smt.SARIMAX`, which stands for Seasonal ARIMA with eXogenous regressors, can handle all these.\n",
"We'll walk through the components in pieces."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"ARIMA stands for AutoRegressive Integrated Moving Average, and it's a relatively simple way of modeling univariate time series.\n",
"It's made up of three components, and is typically written as $\\mathrm{ARIMA}(p, d, q)$."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### [AutoRegressive](https://www.otexts.org/fpp/8/3)\n",
"\n",
"The idea is to predict a variable by a linear combination of its lagged values (*auto*-regressive as in regressing a value on its past *self*).\n",
"An AR(p), where $p$ repgresents the number of past values used, is written as\n",
"\n",
"$$y_t = c + \\phi_1 y_{t-1} + \\phi_2 y_{t-2} + \\ldots + \\phi_p y_{t-p} + e_t$$\n",
"\n",
"$c$ is a constant and $e_t$ is white noise. Other than that this is quite similar to a linear regression model with multiple predictors, but the predictors happen to be lagged values of $y$ (though they are estimated differently)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Integrated\n",
"\n",
"Integrated is like the opposite of differencing, and is the part that deals with stationarity.\n",
"If you have to difference your dataset 1 time to get it stationary, then $d=1$.\n",
"We'll introduce one bit of notation for differencing: $\\Delta y_t = y_t - y_{t-1}$ for $d=1$."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### [Moving Average](https://www.otexts.org/fpp/8/4)\n",
"\n",
"MA models look somewhat similar to the AR component, but it's dealing with different values.\n",
"\n",
"$$y_t = c + e_t + \\theta_1 e_{t-1} + \\theta_2 e_{t-2} + \\ldots + \\theta_q e_{t-q}$$\n",
"\n",
"$c$ again is a constant and $e_t$ again is white noise.\n",
"But now the coefficients are the *residuals* from previous predictions."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Combining\n",
"\n",
"Putting that together, we have an ARIMA(1, 1, 1) proces is written as\n",
"\n",
"$$\\Delta y_t = c + \\phi_1 \\Delta y_{t-1} + \\theta_t e_{t-1} + e_t$$ \n",
"\n",
"Using *lag notation*, where $L y_t = y_{t-1}$, i.e. `y.shift()` in pandas, we can rewrite that as\n",
"\n",
"$$(1 - \\phi_1 L) (1 - L)y_t = c + (1 + \\theta L)e_t$$\n",
"\n",
"For our ARIMA(1, 1, 1) model. In general that becomes\n",
"\n",
"$$(1 - \\phi_1 L - \\ldots - \\phi_p L^p) (1 - L)^d y_t = c + (1 + \\theta L + \\ldots + \\theta_q L^q)e_t$$"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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jNW08of6caB1e8SJ/ppkWagw0WgwXxVRmwYnzi5PqgHWgDlyP1ylT3J2+UK8K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\n/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R6btesSjev2RwEvsckXX3yBnj17Ys6cOZLH9+7di82bN+PatWsAYNHHsaE7VR8fH4tF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\nSHeypnjKPqk+J9w0bGXv3r3y+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"text/plain": [
"<matplotlib.figure.Figure at 0x1b26ee978>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mod = smt.SARIMAX(y, trend='c', order=(1, 1, 1))\n",
"res = mod.fit()\n",
"tsplot(res.resid[2:], lags=24)\n",
"plt.savefig('../output/images/ts-arima.svg', transparent=True);"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"simpletable\">\n",
"<caption>Statespace Model Results</caption>\n",
"<tr>\n",
" <th>Dep. Variable:</th> <td>fl_date</td> <th> No. Observations: </th> <td>192</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Model:</th> <td>SARIMAX(1, 1, 1)</td> <th> Log Likelihood </th> <td>-1104.663</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Date:</th> <td>Fri, 13 May 2016</td> <th> AIC </th> <td>2217.326</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Time:</th> <td>16:16:27</td> <th> BIC </th> <td>2230.356</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Sample:</th> <td>01-01-2000</td> <th> HQIC </th> <td>2222.603</td> \n",
"</tr>\n",
"<tr>\n",
" <th></th> <td>- 12-01-2015</td> <th> </th> <td> </td> \n",
"</tr>\n",
"<tr>\n",
" <th>Covariance Type:</th> <td>opg</td> <th> </th> <td> </td> \n",
"</tr>\n",
"</table>\n",
"<table class=\"simpletable\">\n",
"<tr>\n",
" <td></td> <th>coef</th> <th>std err</th> <th>z</th> <th>P>|z|</th> <th>[0.025</th> <th>0.975]</th> \n",
"</tr>\n",
"<tr>\n",
" <th>intercept</th> <td> 0.7993</td> <td> 4.959</td> <td> 0.161</td> <td> 0.872</td> <td> -8.921</td> <td> 10.519</td>\n",
"</tr>\n",
"<tr>\n",
" <th>ar.L1</th> <td> 0.3515</td> <td> 0.564</td> <td> 0.623</td> <td> 0.533</td> <td> -0.754</td> <td> 1.457</td>\n",
"</tr>\n",
"<tr>\n",
" <th>ma.L1</th> <td> -0.2310</td> <td> 0.577</td> <td> -0.400</td> <td> 0.689</td> <td> -1.361</td> <td> 0.899</td>\n",
"</tr>\n",
"<tr>\n",
" <th>sigma2</th> <td> 6181.2832</td> <td> 350.439</td> <td> 17.639</td> <td> 0.000</td> <td> 5494.435</td> <td> 6868.131</td>\n",
"</tr>\n",
"</table>\n",
"<table class=\"simpletable\">\n",
"<tr>\n",
" <th>Ljung-Box (Q):</th> <td>209.30</td> <th> Jarque-Bera (JB): </th> <td>424.36</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Prob(Q):</th> <td>0.00</td> <th> Prob(JB): </th> <td>0.00</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Heteroskedasticity (H):</th> <td>0.86</td> <th> Skew: </th> <td>1.15</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Prob(H) (two-sided):</th> <td>0.54</td> <th> Kurtosis: </th> <td>9.93</td> \n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<class 'statsmodels.iolib.summary.Summary'>\n",
"\"\"\"\n",
" Statespace Model Results \n",
"==============================================================================\n",
"Dep. Variable: fl_date No. Observations: 192\n",
"Model: SARIMAX(1, 1, 1) Log Likelihood -1104.663\n",
"Date: Fri, 13 May 2016 AIC 2217.326\n",
"Time: 16:16:27 BIC 2230.356\n",
"Sample: 01-01-2000 HQIC 2222.603\n",
" - 12-01-2015 \n",
"Covariance Type: opg \n",
"==============================================================================\n",
" coef std err z P>|z| [0.025 0.975]\n",
"------------------------------------------------------------------------------\n",
"intercept 0.7993 4.959 0.161 0.872 -8.921 10.519\n",
"ar.L1 0.3515 0.564 0.623 0.533 -0.754 1.457\n",
"ma.L1 -0.2310 0.577 -0.400 0.689 -1.361 0.899\n",
"sigma2 6181.2832 350.439 17.639 0.000 5494.435 6868.131\n",
"===================================================================================\n",
"Ljung-Box (Q): 209.30 Jarque-Bera (JB): 424.36\n",
"Prob(Q): 0.00 Prob(JB): 0.00\n",
"Heteroskedasticity (H): 0.86 Skew: 1.15\n",
"Prob(H) (two-sided): 0.54 Kurtosis: 9.93\n",
"===================================================================================\n",
"\n",
"Warnings:\n",
"[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
"\"\"\""
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res.summary()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Things are looking better, but we still haven't accounted for seasonality.\n",
"\n",
"A seasonal ARIMA model is written as $\\mathrm{ARIMA}(p,d,q)×(P,D,Q)_s$.\n",
"Lowercase letters are for the non-seasonal component, just like before. Upper-case letters are a similar specification for the seasonal component, where $s$ is the periodicity (4 for quarterly, 12 for monthly).\n",
"\n",
"It's like we have two processes, one for non-seasonal component and one for seasonal components, and we mulitply them together.\n",
"\n",
"The general form of that looks like (quoting the statsmodels docs here)\n",
"\n",
"$$\\phi_p(L)\\tilde{\\phi}_P(L^S)\\Delta^d\\Delta_s^D y_t = A(t) + \\theta_q(L)\\tilde{\\theta}_Q(L^s)e_t$$\n",
"\n",
"where\n",
"\n",
"- $\\phi_p(L)$ is the non-seasonal autoregressive lag polynomial\n",
"- $\\tilde{\\phi}_P(L^S)$ is the seasonal autoregressive lag polynomial\n",
"- $\\Delta^d\\Delta_s^D$ is the time series, differenced $d$ times, and seasonally differenced $D$ times.\n",
"- $A(t)$ is the trend polynomial (including the intercept)\n",
"- $\\theta_q(L)$ is the non-seasonal moving average lag polynomial\n",
"- $\\tilde{\\theta}_Q(L^s)$ is the seasonal moving average lag polynomial\n",
"\n",
"I don't find that to be very clear, but maybe an example will help. We'll fit a seasonal ARIMA$(2,0,1)×(1, 1, 1)_{12}$.\n",
"\n",
"So the nonseasonal component is\n",
"\n",
"- $p=2$: period autoregressive: use $y_{t-1}$ and $y_{t-2}$\n",
"- $d=0$: no first-differencing of the data\n",
"- $q=1$: use the previous non-seasonal residual, $e_{t-1}$, to forecast\n",
"\n",
"And the seasonal component is\n",
"\n",
"- $P=1$: use the previous seasonal value: $y_{t-12}$\n",
"- $D=1$: Difference the series 12 periods back: `y.diff(12)`\n",
"- $Q=1$: Use the previous seasonal residual, $e{t-12}$"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"mod_seasonal = smt.SARIMAX(y, trend='c',\n",
" order=(1, 1, 2), seasonal_order=(0, 1, 2, 12),\n",
" simple_differencing=False)\n",
"res_seasonal = mod_seasonal.fit()"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"simpletable\">\n",
"<caption>Statespace Model Results</caption>\n",
"<tr>\n",
" <th>Dep. Variable:</th> <td>fl_date</td> <th> No. Observations: </th> <td>192</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Model:</th> <td>SARIMAX(1, 1, 2)x(0, 1, 2, 12)</td> <th> Log Likelihood </th> <td>-992.148</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Date:</th> <td>Fri, 13 May 2016</td> <th> AIC </th> <td>1998.297</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Time:</th> <td>16:16:31</td> <th> BIC </th> <td>2021.099</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Sample:</th> <td>01-01-2000</td> <th> HQIC </th> <td>2007.532</td>\n",
"</tr>\n",
"<tr>\n",
" <th></th> <td>- 12-01-2015</td> <th> </th> <td> </td> \n",
"</tr>\n",
"<tr>\n",
" <th>Covariance Type:</th> <td>opg</td> <th> </th> <td> </td> \n",
"</tr>\n",
"</table>\n",
"<table class=\"simpletable\">\n",
"<tr>\n",
" <td></td> <th>coef</th> <th>std err</th> <th>z</th> <th>P>|z|</th> <th>[0.025</th> <th>0.975]</th> \n",
"</tr>\n",
"<tr>\n",
" <th>intercept</th> <td> 0.7824</td> <td> 5.279</td> <td> 0.148</td> <td> 0.882</td> <td> -9.564</td> <td> 11.129</td>\n",
"</tr>\n",
"<tr>\n",
" <th>ar.L1</th> <td> -0.9880</td> <td> 0.374</td> <td> -2.639</td> <td> 0.008</td> <td> -1.722</td> <td> -0.254</td>\n",
"</tr>\n",
"<tr>\n",
" <th>ma.L1</th> <td> 0.9905</td> <td> 0.437</td> <td> 2.265</td> <td> 0.024</td> <td> 0.133</td> <td> 1.847</td>\n",
"</tr>\n",
"<tr>\n",
" <th>ma.L2</th> <td> 0.0041</td> <td> 0.091</td> <td> 0.045</td> <td> 0.964</td> <td> -0.174</td> <td> 0.182</td>\n",
"</tr>\n",
"<tr>\n",
" <th>ma.S.L12</th> <td> -0.7869</td> <td> 0.066</td> <td> -11.972</td> <td> 0.000</td> <td> -0.916</td> <td> -0.658</td>\n",
"</tr>\n",
"<tr>\n",
" <th>ma.S.L24</th> <td> 0.2121</td> <td> 0.063</td> <td> 3.366</td> <td> 0.001</td> <td> 0.089</td> <td> 0.336</td>\n",
"</tr>\n",
"<tr>\n",
" <th>sigma2</th> <td> 3645.3299</td> <td> 219.296</td> <td> 16.623</td> <td> 0.000</td> <td> 3215.518</td> <td> 4075.142</td>\n",
"</tr>\n",
"</table>\n",
"<table class=\"simpletable\">\n",
"<tr>\n",
" <th>Ljung-Box (Q):</th> <td>47.28</td> <th> Jarque-Bera (JB): </th> <td>464.42</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Prob(Q):</th> <td>0.20</td> <th> Prob(JB): </th> <td>0.00</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Heteroskedasticity (H):</th> <td>0.29</td> <th> Skew: </th> <td>-1.30</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Prob(H) (two-sided):</th> <td>0.00</td> <th> Kurtosis: </th> <td>10.45</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<class 'statsmodels.iolib.summary.Summary'>\n",
"\"\"\"\n",
" Statespace Model Results \n",
"==========================================================================================\n",
"Dep. Variable: fl_date No. Observations: 192\n",
"Model: SARIMAX(1, 1, 2)x(0, 1, 2, 12) Log Likelihood -992.148\n",
"Date: Fri, 13 May 2016 AIC 1998.297\n",
"Time: 16:16:31 BIC 2021.099\n",
"Sample: 01-01-2000 HQIC 2007.532\n",
" - 12-01-2015 \n",
"Covariance Type: opg \n",
"==============================================================================\n",
" coef std err z P>|z| [0.025 0.975]\n",
"------------------------------------------------------------------------------\n",
"intercept 0.7824 5.279 0.148 0.882 -9.564 11.129\n",
"ar.L1 -0.9880 0.374 -2.639 0.008 -1.722 -0.254\n",
"ma.L1 0.9905 0.437 2.265 0.024 0.133 1.847\n",
"ma.L2 0.0041 0.091 0.045 0.964 -0.174 0.182\n",
"ma.S.L12 -0.7869 0.066 -11.972 0.000 -0.916 -0.658\n",
"ma.S.L24 0.2121 0.063 3.366 0.001 0.089 0.336\n",
"sigma2 3645.3299 219.296 16.623 0.000 3215.518 4075.142\n",
"===================================================================================\n",
"Ljung-Box (Q): 47.28 Jarque-Bera (JB): 464.42\n",
"Prob(Q): 0.20 Prob(JB): 0.00\n",
"Heteroskedasticity (H): 0.29 Skew: -1.30\n",
"Prob(H) (two-sided): 0.00 Kurtosis: 10.45\n",
"===================================================================================\n",
"\n",
"Warnings:\n",
"[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
"\"\"\""
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res_seasonal.summary()"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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6UNzW2eM/4CU+3uoGI/JO1GLD50XUD3mzqPD02twkhGpVcHKBq83F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\n4OQF3sJC/LsEoj6Kp0y6PLzS9fcHK6dg4wtL+63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e5P/tsfEEIM7odG/GG7CxrEEul+Ev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xjTe/bsiYKCAqxZs8bsRhHHjx/H0KFD0bdvX+HejL+3pozrln5folvDDC/dts8++wwqlQpDhw5t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\nAFsj4QUAAICt/X+Cy7tYrPXUJgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10e43b940>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"tsplot(res_seasonal.resid[12:], lags=24)\n",
"plt.savefig('../output/images/ts-seasonal.svg', transparent=True);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Things look much better now.\n",
"\n",
"One thing I didn't really talk about is order selection. How to choose $p, d, q, P, D$ and $Q$.\n",
"R's forecast package does have a handy `auto.arima` function that does this for you."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Forecasting"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can use the results to make one-step-ahead forecasts.\n",
"At each point, we take the history up to that point and make a forecast for the next month."
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"pred = res_seasonal.get_prediction(start='2001-03-01')\n",
"pred_ci = pred.conf_int()"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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+tuOhq9e27ZL2NH4v0cJ/9rxGwizsgn11Z5xfP9NBZ9/RWwjZGBL2ujK9h/V4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\n13Vqa2vp6+sbdlL2exSUTDl4eunJDK/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aDX+2PBcsOK+i0Z/42bYdO4dhiZ+sAj579ixm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Zdxs3k3fN2g5KZer8fmgTfrt/BG/Ub4czVC/IpaPnEjJBQ/CqK4WG9YmDdXwr9JUjEs8avUTFy5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\n4FKbB5uHlHLinOVRm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EF7Y7AD4BhIMITrEKx6i4V5HcdBt5u9p8x4FwCOdZra98wSv+rv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
@nateGeorge
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Hey I think some of your links are broken, e.g. https://tomaugspurger.github.io/author/modern-6-visualization.html . I get a 404

@emunsing
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It seems like the flight API that you're calling has changed, and no longer yields data. If you're able to post the file ts.hdf5 somewhere that could make this future-proof!

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