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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"*JM: This is a modified version of Tom's original ipynb. Most changes are to copy more of his [helpful article text](http://tomaugspurger.github.io/modern-7-timeseries.html) to be inline, here, and to add some exploratory cells investigating the many `pandas` tricks.*\n",
"\n",
"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": "markdown",
"metadata": {},
"source": [
"Let's grab some stock data for Goldman Sachs using the `pandas-datareader` package, which spun off of pandas:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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>113.747787</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>112.176662</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>112.132533</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>113.721309</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>115.089427</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",
"2006-01-03 113.747787 \n",
"2006-01-04 112.176662 \n",
"2006-01-05 112.132533 \n",
"2006-01-06 113.721309 \n",
"2006-01-09 115.089427 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs = web.DataReader(\"GS\", \n",
" data_source='yahoo', \n",
" 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": [
"DatetimeIndex(['2006-01-03', '2006-01-04', '2006-01-05', '2006-01-06',\n",
" '2006-01-09', '2006-01-10', '2006-01-11', '2006-01-12',\n",
" '2006-01-13', '2006-01-17',\n",
" ...\n",
" '2009-12-17', '2009-12-18', '2009-12-21', '2009-12-22',\n",
" '2009-12-23', '2009-12-24', '2009-12-28', '2009-12-29',\n",
" '2009-12-30', '2009-12-31'],\n",
" dtype='datetime64[ns]', name='Date', length=1007, freq=None)"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.index"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Timestamp('2006-01-03 00:00:00')"
]
},
"execution_count": 4,
"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": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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>113.747787</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>112.176662</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>112.132533</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>113.721309</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>115.089427</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",
"2006-01-03 113.747787 \n",
"2006-01-04 112.176662 \n",
"2006-01-05 112.132533 \n",
"2006-01-06 113.721309 \n",
"2006-01-09 115.089427 "
]
},
"execution_count": 5,
"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": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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",
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" <th></th>\n",
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" </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>113.747787</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>112.176662</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>112.132533</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>113.721309</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>115.089427</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",
"2006-01-03 113.747787 \n",
"2006-01-04 112.176662 \n",
"2006-01-05 112.132533 \n",
"2006-01-06 113.721309 \n",
"2006-01-09 115.089427 "
]
},
"execution_count": 6,
"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 (and partial-string indexing isn't limited to just years)."
]
},
{
"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": "markdown",
"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": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" <thead>\n",
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" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
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" <th>Volume</th>\n",
" <th>Adj Close</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
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" <th></th>\n",
" <th></th>\n",
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" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <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>112.944573</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>116.210400</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>117.326954</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>117.062463</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",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"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",
"2006-01-03 112.944573 \n",
"2006-01-08 116.210400 \n",
"2006-01-13 117.326954 \n",
"2006-01-18 117.062463 \n",
"2006-01-23 119.517678 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.resample(\"5d\").mean().head()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
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" <th colspan=\"3\" halign=\"left\">High</th>\n",
" <th colspan=\"3\" halign=\"left\">Low</th>\n",
" <th colspan=\"3\" halign=\"left\">Close</th>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <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>4</td>\n",
" <td>128.730002</td>\n",
" <td>514.920006</td>\n",
" <td>4</td>\n",
" <td>125.877501</td>\n",
" <td>503.510002</td>\n",
" <td>4</td>\n",
" <td>127.959997</td>\n",
" <td>511.839988</td>\n",
" <td>4</td>\n",
" <td>4771825</td>\n",
" <td>19087300</td>\n",
" <td>4</td>\n",
" <td>112.944573</td>\n",
" <td>451.778291</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-15</th>\n",
" <td>130.684000</td>\n",
" <td>653.419998</td>\n",
" <td>5</td>\n",
" <td>132.848001</td>\n",
" <td>664.240006</td>\n",
" <td>5</td>\n",
" <td>130.544000</td>\n",
" <td>652.720001</td>\n",
" <td>5</td>\n",
" <td>131.979999</td>\n",
" <td>659.899994</td>\n",
" <td>5</td>\n",
" <td>4310420</td>\n",
" <td>21552100</td>\n",
" <td>5</td>\n",
" <td>116.492848</td>\n",
" <td>582.464241</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-22</th>\n",
" <td>131.907501</td>\n",
" <td>527.630005</td>\n",
" <td>4</td>\n",
" <td>133.672501</td>\n",
" <td>534.690003</td>\n",
" <td>4</td>\n",
" <td>131.389999</td>\n",
" <td>525.559998</td>\n",
" <td>4</td>\n",
" <td>132.555000</td>\n",
" <td>530.220000</td>\n",
" <td>4</td>\n",
" <td>4653725</td>\n",
" <td>18614900</td>\n",
" <td>4</td>\n",
" <td>117.054663</td>\n",
" <td>468.218654</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-29</th>\n",
" <td>133.771997</td>\n",
" <td>668.859986</td>\n",
" <td>5</td>\n",
" <td>136.083997</td>\n",
" <td>680.419983</td>\n",
" <td>5</td>\n",
" <td>133.310001</td>\n",
" <td>666.550003</td>\n",
" <td>5</td>\n",
" <td>135.153998</td>\n",
" <td>675.769989</td>\n",
" <td>5</td>\n",
" <td>3968500</td>\n",
" <td>19842500</td>\n",
" <td>5</td>\n",
" <td>119.517678</td>\n",
" <td>597.588391</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-02-05</th>\n",
" <td>140.900000</td>\n",
" <td>704.500000</td>\n",
" <td>5</td>\n",
" <td>142.467999</td>\n",
" <td>712.339996</td>\n",
" <td>5</td>\n",
" <td>139.937998</td>\n",
" <td>699.689988</td>\n",
" <td>5</td>\n",
" <td>141.618002</td>\n",
" <td>708.090011</td>\n",
" <td>5</td>\n",
" <td>3920120</td>\n",
" <td>19600600</td>\n",
" <td>5</td>\n",
" <td>125.233845</td>\n",
" <td>626.169226</td>\n",
" <td>5</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High \\\n",
" mean sum count mean sum count \n",
"Date \n",
"2006-01-08 126.834999 507.339996 4 128.730002 514.920006 4 \n",
"2006-01-15 130.684000 653.419998 5 132.848001 664.240006 5 \n",
"2006-01-22 131.907501 527.630005 4 133.672501 534.690003 4 \n",
"2006-01-29 133.771997 668.859986 5 136.083997 680.419983 5 \n",
"2006-02-05 140.900000 704.500000 5 142.467999 712.339996 5 \n",
"\n",
" Low Close \\\n",
" mean sum count mean sum count \n",
"Date \n",
"2006-01-08 125.877501 503.510002 4 127.959997 511.839988 4 \n",
"2006-01-15 130.544000 652.720001 5 131.979999 659.899994 5 \n",
"2006-01-22 131.389999 525.559998 4 132.555000 530.220000 4 \n",
"2006-01-29 133.310001 666.550003 5 135.153998 675.769989 5 \n",
"2006-02-05 139.937998 699.689988 5 141.618002 708.090011 5 \n",
"\n",
" Volume Adj Close \n",
" mean sum count mean sum count \n",
"Date \n",
"2006-01-08 4771825 19087300 4 112.944573 451.778291 4 \n",
"2006-01-15 4310420 21552100 5 116.492848 582.464241 5 \n",
"2006-01-22 4653725 18614900 4 117.054663 468.218654 4 \n",
"2006-01-29 3968500 19842500 5 119.517678 597.588391 5 \n",
"2006-02-05 3920120 19600600 5 125.233845 626.169226 5 "
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.resample(\"W\").agg(['mean', 'sum', 'count']).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": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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>113.747787</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>112.176662</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 6188700.0 113.747787 \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 4861600.0 112.176662 "
]
},
"execution_count": 9,
"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": 10,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
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8+Vp63iQycxICr6ltszsTqd7dyra11Tz2qw/obB+90mAhhBBCHB8k4BNilDW1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\nRaQyJydER0j9QyJ8kuALp3QGHUtL0qcAcCpGhA8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8+qu3jBjhi6zpaxcl4TYzYyrpppQx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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10b1315f8>"
]
},
"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": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Rolling [window=30,center=True,axis=0]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"roll = gs.Close.rolling(30, center=True)\n",
"roll"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>mean</th>\n",
" <th>std</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2006-01-03</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-04</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-05</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-06</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-09</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-10</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-11</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-12</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-13</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-17</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-18</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-19</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-20</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-23</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-24</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-25</th>\n",
" <td>135.744999</td>\n",
" <td>5.159806</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-26</th>\n",
" <td>136.287333</td>\n",
" <td>5.266226</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-27</th>\n",
" <td>136.914333</td>\n",
" <td>5.253174</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-30</th>\n",
" <td>137.530999</td>\n",
" <td>5.138666</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-31</th>\n",
" <td>138.017999</td>\n",
" <td>4.976346</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" mean std\n",
"Date \n",
"2006-01-03 NaN NaN\n",
"2006-01-04 NaN NaN\n",
"2006-01-05 NaN NaN\n",
"2006-01-06 NaN NaN\n",
"2006-01-09 NaN NaN\n",
"2006-01-10 NaN NaN\n",
"2006-01-11 NaN NaN\n",
"2006-01-12 NaN NaN\n",
"2006-01-13 NaN NaN\n",
"2006-01-17 NaN NaN\n",
"2006-01-18 NaN NaN\n",
"2006-01-19 NaN NaN\n",
"2006-01-20 NaN NaN\n",
"2006-01-23 NaN NaN\n",
"2006-01-24 NaN NaN\n",
"2006-01-25 135.744999 5.159806\n",
"2006-01-26 136.287333 5.266226\n",
"2006-01-27 136.914333 5.253174\n",
"2006-01-30 137.530999 5.138666\n",
"2006-01-31 138.017999 4.976346"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m = roll.agg(['mean', 'std'])\n",
"m.head(20)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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CK4kxKqVZi65m7Y5AIJxCerFWW09aMmN84spcdBBCCClUUpB9/Phx3H///Th8+DCOHj2K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\nrkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x112966438>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = m['mean'].plot()\n",
"ax.fill_between(m.index, \n",
" m['mean'] - m['std'], \n",
" 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": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"DatetimeIndex(['2006-01-03', '2006-01-04', '2006-01-05', '2006-01-06',\n",
" '2006-01-09', '2006-01-10', '2006-01-11', '2006-01-12',\n",
" '2006-01-13', '2006-01-17',\n",
" ...\n",
" '2009-12-17', '2009-12-18', '2009-12-21', '2009-12-22',\n",
" '2009-12-23', '2009-12-24', '2009-12-28', '2009-12-29',\n",
" '2009-12-30', '2009-12-31'],\n",
" dtype='datetime64[ns]', name='Date', length=1007, freq=None)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gs.index"
]
},
{
"cell_type": "code",
"execution_count": 15,
"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": 15,
"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": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from pandas.tseries.holiday import USColumbusDay"
]
},
{
"cell_type": "code",
"execution_count": 17,
"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": 17,
"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": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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>113.747787</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>112.176662</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>112.132533</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>113.721309</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>115.089427</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",
"2006-01-03 113.747787 \n",
"2006-01-04 112.176662 \n",
"2006-01-05 112.132533 \n",
"2006-01-06 113.721309 \n",
"2006-01-09 115.089427 "
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# tz-naive\n",
"gs.head()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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 00:00:00-05:00</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>113.747787</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-04 00:00:00-05:00</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>112.176662</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-05 00:00:00-05:00</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>112.132533</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-06 00:00:00-05:00</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>113.721309</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006-01-09 00:00:00-05:00</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>115.089427</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close \\\n",
"Date \n",
"2006-01-03 00:00:00-05:00 126.699997 129.440002 124.230003 128.869995 \n",
"2006-01-04 00:00:00-05:00 127.349998 128.910004 126.379997 127.089996 \n",
"2006-01-05 00:00:00-05:00 126.000000 127.320000 125.610001 127.040001 \n",
"2006-01-06 00:00:00-05:00 127.290001 129.250000 127.290001 128.839996 \n",
"2006-01-09 00:00:00-05:00 128.500000 130.619995 128.000000 130.389999 \n",
"\n",
" Volume Adj Close \n",
"Date \n",
"2006-01-03 00:00:00-05:00 6188700 113.747787 \n",
"2006-01-04 00:00:00-05:00 4861600 112.176662 \n",
"2006-01-05 00:00:00-05:00 3717400 112.132533 \n",
"2006-01-06 00:00:00-05:00 4319600 113.721309 \n",
"2006-01-09 00:00:00-05:00 4723500 115.089427 "
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# pin to EST (note \"-05:00\")\n",
"gs.tz_localize('US/Eastern').head()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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>113.747787</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>112.176662</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>112.132533</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>113.721309</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>115.089427</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 113.747787 \n",
"2006-01-04 05:00:00+00:00 4861600 112.176662 \n",
"2006-01-05 05:00:00+00:00 3717400 112.132533 \n",
"2006-01-06 05:00:00+00:00 4319600 113.721309 \n",
"2006-01-09 05:00:00+00:00 4723500 115.089427 "
]
},
"execution_count": 20,
"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": 21,
"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": [
"# note: this takes a while (10-15 minutes?)\n",
"download_many('2000-01-01', '2016-01-01')"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# this also takes a while\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": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"fl_date datetime64[ns]\n",
"unique_carrier object\n",
"carrier object\n",
"tail_num object\n",
"fl_num int64\n",
"origin object\n",
"dest object\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": 30,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"cat_cols = ['unique_carrier', 'carrier', 'tail_num', 'origin', 'dest']\n",
"\n",
"df[cat_cols] = df[cat_cols].apply(pd.Categorical)"
]
},
{
"cell_type": "raw",
"metadata": {
"collapsed": true
},
"source": [
"# can't get hdf5 to work on my os x\n",
"# - tried installing hdf5 via brew + tables via pip\n",
"df.to_hdf('ts.hdf5', 'ts', format='table')\n",
"df = pd.read_hdf('ts.hdf5', 'ts')"
]
},
{
"cell_type": "raw",
"metadata": {},
"source": [
"# verrry slow\n",
"df.to_csv('ts.csv.gz', compression='gzip')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can calculate the historical values with a resample."
]
},
{
"cell_type": "code",
"execution_count": 32,
"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": 32,
"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": 33,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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86meUh3zMLD9CiN5Q+JG8IlMZfkDovt5cDXGm8BvPtMrEQpyF8KupsKKs2BLy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Szn+MnHNXay9wua6CUIgiAmEazU62E9fiOU4acWc7YPQARahjczLp1XgUvnVfCvjUZ5o8e5rqGo\n46cUflmY6gVkQXqua4g7fl5fEF0RYUqOH0EQBDEZiDp+saVeinJJzqRz/Ow2M6aU2JP/oAawSJcL\nPbnr+Ck3jWgZak0QBEEQ2cI+arjDPUzhzWqZdMJv+hSnbgMM1aMiXVh4pMGQnQBnACjhIc6y48fK\nvA67me/yJQiCIIiJjN3KhF8QkiTh8wtuAFFDhkjM5BN+lfqtJGMPsM5Rjl+23D4AKBu1tk052EET\nvQRBEMRkgPX4SRIw4g3is/YBAMD8maXZPKwJwaQTftMqdBR+kXy/rr4RhEJhhfDLnsBiIc69brnU\nS6vaCIIgiMkG6/EDgNNtvTxHd+7Mkmwd0oRh0gm/6VP0d/xCYQkX+z281JtVxy9SznUP+/Hvz59E\n63n5UxANdhAEQRCTBdbjBwAnP+0GABQ5rahSLFwg4jPphJ+ear8qJstvhOf4ZVP4Laqfwq3uo2+1\noqvPA4CEH0EQBDF5UDp+7396EQAwb2YptTSpYNIJPz1Fl91q5lO0Hb3DvNSbjXVtDLPJiJ/ccgWu\n2zA/ZsCESr0EQRDEZKFA4fix/r55M6jMq4ZJmeOnJ9XlTvQN+nD+4jAqSwsAAJYsCj8AsJiNuPZr\nDbhs8VQ8/cqHqCgpQEXk2AiCIAhiomOzRuWLFNmWOpcGO1RBwi9DZk8vxum2XnzQ0o3VS2oAAGZz\nbljNddOKcf/Oldk+DIIgCILQFJPRAKvZCL9iVeo8En6qmHSlXr1ZGtnm8cnZfvRHQpNNRrqsBEEQ\nBCES5YDH1HInipy0tUMNpFAyZPGcKTAZDZAk4PjpTgDZW9dGEARBEPmCUvhRjIt6SKFkiMNuwYK6\nMgDA5x1yZl62e/wIgiAIYrJToJjspTKvekihaMCy+ZUxX5uyGOBMEARBEPmA0vGbN4OEn1pI+GnA\naOGXzRw/giAIgsgHWJaf0WjA7JriLB/NxIEUigbUTStGicvGvybhRxAEQRBisUciXWZNLYLNYkry\n0wSDFIoGGI0GLJlfwb/O5q5egiAIgsgHplXIK1pZugahDsrx04hl8yvx+jvnAJDjRxAEQRCi+c7X\nG7BkXgUumV2e7UOZUJDw04il86J9fhTnQhAEQRBisVlMY3rsieSQQtGIkkIbZk+Xm0spzoUgCIIg\niFyEFIqGfGvdHFSUFmBV47RsHwpBEARBEMQYqNSrIWuW1mDN0ppsHwZBEARBEERcyPEjCIIgCILI\nE0j4EQRBEARB5Akk/AiCIAiCIPIEEn4EQRAEQRB5Agk/giAIgiCIPIGEH0EQBEEQRJ5Awo8gCIIg\nCCJPIOFHEARBEASRJ5DwIwiCIAiCyBNI+BEEQRAEQeQJJPwIgiAIgiDyhJSE38mTJ7F69Wr+dVdX\nF26++WasWLECq1evxsGDB2N+/sCBA1i5ciWamprw0EMPQZIkftvTTz+NNWvWYPny5bjnnnvg9Xoz\nPBWCIAiCIAhiPFQLv+eeew47duxAMBjk33vggQcwa9Ys/PWvf8Vzzz2HV155BS+99BIAoLm5GW++\n+SaOHj2KV199Fe+88w6efPJJAMBrr72Gp556Cs3NzXj99dfR39+PRx55RONTIwiCIAiCIJSoEn5H\njhxBc3Mz9uzZE/P91tZWBINBBINBSJIEk8mEgoICAMDLL7+MG264AeXl5SgvL8fu3bvxwgsv8Nu2\nbNmCmTNnwuVyYe/evXjppZdiHEGCIAiCIAhCW1QJvy1btuDFF1/EokWLYr5/00034dlnn8XSpUux\nbt06LFu2DBs2bAAAtLS0YM6cOfxn6+rq0Nraym+rr6+PuW1kZASdnZ0ZnxBBEARBEAQRH1XCb8qU\nKXG/L0kSbr75Zrz77rs4evQojh8/jmeffRYA4PF4YLfb+c/a7XaEw2H4/X54PB7uDALg/+3xeNI+\nEYIgCIIgCGJ8zOn+YldXF/bv34+3334bFosF9fX12LlzJ5555hls3boVdrs9ZmDD6/XCZDLBarWO\nuY0JPofDoepv9/X1ob+/P+Z77e3tAICOjo50T4kgCIIgCGJSUF1dDbN5rMxLW/h1d3cjGAwiEAjA\nYrEAAEwmE//v+vp6tLa2orGxEUBseZfdxmhpaUFRURGqqqpU/e3m5mYcOnQo7m3f+c530j0lgiAI\ngiCIScF///d/o6amZsz30xZ+c+bMQVVVFR555BH84Ac/QFdXF5566ils3boVALBp0yY88cQTuOyy\ny2AymfD444/j6quv5rft378fGzZsQHV1NR577DFs2rRJ9d/etm0brrzyypjv+f1+/PjHP8aDDz4I\nk8mU7mlpytmzZ7F9+3Y8/fTTmDFjRrYPBwDw4IMP4gc/+EG2DwNAbl4fgK6RGugaJYeuUXLoGiWH\nrtH45NL1AXLrGlVXV8f9ftrCz2q14vHHH8dDDz2E1atXw+l0YuvWrbj++usBANdddx16enqwZcsW\nBAIBbN68Gdu3bwcArFu3Du3t7di1axeGhoawdu1a3H333ar/dmlpKUpLS8d8v6qqCrW1temekuYE\nAgEA8sWPp7qzgcPhyJljycXrA9A1UgNdo+TQNUoOXaPk0DUan1y6PkBuXqPRpCT8VqxYgWPHjvGv\n6+vr8cQTT8T9WaPRiL1792Lv3r1xb9+2bRu2bduWyp9PCpsoJhJD1yg5dI2SQ9coOXSNkkPXKDl0\njcaHrk/qTKqVbV/72teyfQg5D12j5NA1Sg5do+TQNUoOXaPk0DUaH7o+qTOphB9BEARBEASRGNP+\n/fv3Z/sgJjN2ux0rVqyIyS0kotD1SQ5do+TQNUoOXaPk0DVKDl2j5OT6NTJItCeNIAiCIAgiL6BS\nL0EQBEEQRJ5Awo8gCIIgCCJPIOFHEARBEASRJ5DwIwiCIAiCyBNI+BEEQRAEQeQJJPwIgiAIgiDy\nBBJ+BEEQBEEQeQIJvxQ4fvw4tm7diuXLl2PDhg145plnAAButxu33norli9fjvXr1+O5557jv+P3\n+3HvvfeiqakJV1xxBY4cOTLmfiVJwq233opf/vKXup2LCLS+Pm63G3fccQeamprQ1NSEffv2YWho\nSPfz0hIRj6GlS5di2bJl/P937dql6zlpjdbX6Morr8SyZcv4/xobG7FgwQJcvHhR93PTCq2vkcfj\nwX333YdVq1bhiiuuwIEDBxAKhXQ/Ly1J5xoxfD4frrnmGrzxxhtx7/v+++/Hz372M6HHrwdaXyO/\n34/9+/dj5cqV+NKXvoRbbrkFnZ2dup2PCEQ8jjZu3IglS5bw1+2rrrpKl3PhSIQqBgYGpBUrVkhH\njx6VJEmSTp06Ja1YsUL685//LN12223SPffcI/n9funEiRPSihUrpBMnTkiSJEkPP/yw9L3vfU8a\nGhqS2trapPXr10u//e1v+f22t7dLO3fulBoaGqTm5uasnJsWiLg+d911l3TnnXdKXq9XGhkZkXbs\n2CE9/PDDWTvHTBFxjdra2qRly5Zl7Zy0RtTzTMn1118vPfroo7qdk9aIuEb33Xef9K1vfUvq7OyU\nBgcHpZtuukn66U9/mrVzzJR0r5EkSdKZM2eka665RmpoaJBef/31mPvt6emR7rrrLqmhoUE6cOCA\nruekNSKu0cGDB6Xvfve7ktvtlgKBgPT9739fuu2223Q/N60QcY28Xq90ySWXSH19fbqfD4McP5Wc\nP38ea9euxcaNGwEACxcuRFNTE95991388Y9/xO233w6LxYLGxkZcddVVePHFFwEAv/nNb3DzzTfD\n6XSitrYW27ZtwwsvvAAACAQC+OY3v4mGhgYsXbo0a+emBSKuz8MPP4yHH34YNpsNbrcbIyMjKC0t\nzdo5ZoqIa/Thhx+ioaEha+ekNSKukZKnn34aQ0NDuP3223U9Ly0RcY1+//vf44477kBlZSVcLhdu\nu+02PP/881k7x0xJ9xqdP38eN9xwA77+9a9j6tSpY+732muvRUFBAb7yla/oej4iEHGN9u7di1/8\n4hcoLCzE4OAghoaG8vI1e7xrdObMGUyZMgUlJSW6nw+DhJ9KGhoa8Mgjj/CvBwYGcPz4cQCA2WzG\n9OnT+W11dXVoaWmB2+1Gd3c36uvrx9zGfu/VV1/FnXfeCZPJpNOZiEHE9TGZTLBYLPj+97+PtWvX\nYmhoCN/+9rd1OiPtEXGNTp8+DbfbjauvvhqrVq3C3r17J3RpRcQ1Yrjdbhw+fBj33XcfDAaD4DMR\nh4hrFAqFYLPZ+G0GgwH9/f1wu92iT0cI6VwjACgtLcXvf/97bN++Pe79Njc340c/+hHsdru4g9cJ\nEdfIYDDAarXi0KFDWLVqFU6ePImdO3eKPRGBiLhGp0+fhslkwre//W2sXLkSO3bswGeffSb2REZB\nwi8NBgcHsWfPHixevBhNTU0xL5iAvKDZ6/XC4/Hwr5W3se8bDAaUl5frd+A6odX1Ydx///14++23\nUVdXh1tuuUX8CeiAVtfIarVi6dKlePLJJ/G73/0ODodjQrtZSrR+HP3yl7/EkiVL0NjYKP7gdUKr\na7R+/XocPnwYPT09GBgY4P1/Pp9PpzMRh9prBAAFBQVwuVwJ76uiokLosWYLLa8RAOzatQsnTpzA\nV7/6VezYsWPC94sC2l6jxsZGHDx4EG+88QYWLVqEXbt2we/3Cz1+JST8UuTs2bO49tprUVpaisce\newwOh2PMi6PX64XD4eAvssrbvV4vnE6nrsesJyKuj9Vqhcvlwt1334233357wroQDC2v0a233oof\n/ehHKCsrg8vlwr59+3DixAl0d3frd0ICEPE4euGFF3DttdeKP3id0PIa3XvvvZg2bRo2bdqE6667\nDmvXrgUAFBUV6XMygkjlGuUrIq6R1WqF1WrFPffcg/b2dnz88cdaH7auaHmNrrnmGhw8eBBTp06F\n1WrFHXfcgYGBAZw+fVrU4Y+BhF8KnDp1Ctdccw1Wr16Nw4cPw2q1ora2FsFgEB0dHfznWltbUV9f\nj+LiYpSXl8eUnNhtkxGtr8+OHTvGTIyZzWYUFBTod1Iao/U1evzxx/Hhhx/y23w+HwwGw5hPoxMJ\nEc+zzz77DD09PVizZo2u5yIKra/RxYsXsW/fPrz11lt45ZVXUFVVhVmzZuXV4ygf0foa3XvvvfjV\nr37Fvw4GgwCAwsJC7Q9eJ7S+Rs8++yyOHTvGvw4GgwgGg7o+10j4qaS7uxs7d+7EjTfeiH379vHv\nO51OrF+/HgcOHIDX68XJkydx9OhRbNq0CQCwadMmHDp0CAMDA2hra0NzczOuvvrqbJ2GMERcn4UL\nF+Lf/u3f0Nvbi4GBAfz0pz/F5s2bYbFYsnKOmSLiGrW2tuKRRx5Bf38/BgcH8dBDD+ErX/nKhH2h\nFfU8O3HiBBYuXAiz2az7OWmNiGv0i1/8Ag888AACgQDOnTuHn/3sZxPaHU31Gukep5EDiLhGjY2N\neOqpp9De3g6Px4MHH3wQy5cvR01NjchTEYaIa9TV1YWHHnoIHR0d8Hq9ePjhhzF79mx9h/SyNk88\nwThy5IjU0NAgLV26VFqyZIm0ZMkSaenSpdLBgwelgYEBae/evdKKFSukdevWSc8//zz/Pa/XK913\n333SypUrpcsvv1z693//97j3/93vfndCx7mIuD4+n0964IEHpFWrVkmrV6+WfvzjH0sejycbp6cJ\nIq7R0NCQ9P3vf1+67LLLpOXLl0t33XWX5Ha7s3F6miDqefav//qv0p133qn36QhBxDXq6+uT9uzZ\nIy1fvlxas2aNdOTIkWycmmake42UrF+/fkycC+Ouu+6a8HEuoq7R4cOHpdWrV0srV66U7rrrrqzG\nlmSKiGsUDAalhx9+WLr88sulZcuWSbt375YuXLig1ylJkiRJBkmSJP1kJkEQBEEQBJEtqNRLEARB\nEASRJ5DwIwiCIAiCyBNI+BEEQRAEQeQJJPwIgiAIgiDyBBJ+BEEQBEEQeQIJP4IgCIIgiDyBhB9B\nEARBEESeQMKPIAiCIAgiTyDhRxAEQRAEkSf8/0J5zGzWrz7PAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1181f82b0>"
]
},
"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": 52,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import statsmodels.formula.api as smf\n",
"import statsmodels.tsa.api as smt\n",
"import statsmodels.tsa.statespace.sarimax as sms\n",
"import statsmodels.api as sm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"One note of warning: I'm using the development version of statsmodels (commit `de15ec8` to be precise). Not all of the items I've shown here are available in the currently-released version. (JM: I used `pip install statsmodel==0.8.0rc1`)\n",
"\n",
"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": 35,
"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",
"2000-06-01 1976.133333\n",
"2000-07-01 1937.032258\n",
"2000-08-01 1960.354839\n",
"2000-09-01 1900.533333\n",
"2000-10-01 1931.677419\n",
"Freq: MS, Name: fl_date, dtype: float64"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"2000-01-01 NaN\n",
"2000-02-01 1882.387097\n",
"2000-03-01 1926.896552\n",
"2000-04-01 1951.000000\n",
"2000-05-01 1944.400000\n",
"Freq: MS, Name: fl_date, dtype: float64"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y.shift(1).head()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" 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": 37,
"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": 38,
"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>Thu, 01 Sep 2016</td> <th> Prob (F-statistic):</th> <td>2.40e-80</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Time:</th> <td>14:58:40</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: Thu, 01 Sep 2016 Prob (F-statistic): 2.40e-80\n",
"Time: 14:58:40 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": 38,
"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](https://en.wikipedia.org/wiki/Multicollinearity).\n",
"That ruins our estimates of the slopes."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x118a9d978>"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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LzS1UpAAAAAxRkQIAALZRkLKQSAEAANtiyKQk0doDAAAwRkUKAADYxmJzS9iKVGNjo558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\nAQAAGPq/mKnleLVEKDUAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117803fd0>"
]
},
"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": 40,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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sWbOia9eucffdd0d+fn6MGzcuTj/99Bg/fnycddZZsX79+hg/fnxs3bo1Bg4c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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117832b38>"
]
},
"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](https://en.wikipedia.org/wiki/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": 41,
"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> 0.002</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Model:</th> <td>OLS</td> <th> Adj. R-squared: </th> <td> -0.004</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td> 0.3188</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Date:</th> <td>Thu, 01 Sep 2016</td> <th> Prob (F-statistic):</th> <td> 0.573</td> \n",
"</tr>\n",
"<tr>\n",
" <th>Time:</th> <td>14:59:00</td> <th> Log-Likelihood: </th> <td> -1314.3</td>\n",
"</tr>\n",
"<tr>\n",
" <th>No. Observations:</th> <td> 192</td> <th> AIC: </th> <td> 2633.</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Df Residuals:</th> <td> 190</td> <th> BIC: </th> <td> 2639.</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Df Model:</th> <td> 1</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> 2326.1917</td> <td> 32.848</td> <td> 70.817</td> <td> 0.000</td> <td> 2261.398</td> <td> 2390.985</td>\n",
"</tr>\n",
"<tr>\n",
" <th>trend</th> <td> -0.1680</td> <td> 0.297</td> <td> -0.565</td> <td> 0.573</td> <td> -0.755</td> <td> 0.419</td>\n",
"</tr>\n",
"</table>\n",
"<table class=\"simpletable\">\n",
"<tr>\n",
" <th>Omnibus:</th> <td>13.337</td> <th> Durbin-Watson: </th> <td> 0.121</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Prob(Omnibus):</th> <td> 0.001</td> <th> Jarque-Bera (JB): </th> <td> 5.448</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Skew:</th> <td>-0.107</td> <th> Prob(JB): </th> <td> 0.0656</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Kurtosis:</th> <td> 2.203</td> <th> Cond. No. </th> <td> 220.</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<class 'statsmodels.iolib.summary.Summary'>\n",
"\"\"\"\n",
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: y R-squared: 0.002\n",
"Model: OLS Adj. R-squared: -0.004\n",
"Method: Least Squares F-statistic: 0.3188\n",
"Date: Thu, 01 Sep 2016 Prob (F-statistic): 0.573\n",
"Time: 14:59:00 Log-Likelihood: -1314.3\n",
"No. Observations: 192 AIC: 2633.\n",
"Df Residuals: 190 BIC: 2639.\n",
"Df Model: 1 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [0.025 0.975]\n",
"------------------------------------------------------------------------------\n",
"Intercept 2326.1917 32.848 70.817 0.000 2261.398 2390.985\n",
"trend -0.1680 0.297 -0.565 0.573 -0.755 0.419\n",
"==============================================================================\n",
"Omnibus: 13.337 Durbin-Watson: 0.121\n",
"Prob(Omnibus): 0.001 Jarque-Bera (JB): 5.448\n",
"Skew: -0.107 Prob(JB): 0.0656\n",
"Kurtosis: 2.203 Cond. No. 220.\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
"\"\"\""
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"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()\n",
"res_trend.summary()"
]
},
{
"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": 42,
"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": "markdown",
"metadata": {},
"source": [
"Calling it on the residuals from the linear trend:"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"(<matplotlib.axes._subplots.AxesSubplot at 0x1128f94e0>,\n",
" <matplotlib.axes._subplots.AxesSubplot at 0x11527d710>,\n",
" <matplotlib.axes._subplots.AxesSubplot at 0x113e72b00>)"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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AhkvtGCZ0n9HWI1R4i3NThr1eIZfhoVsWoiQvWbpsUkk6ppSGdks4XJSKtoZY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\nrtvx9t6TePPvl8gcFVFskDThv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"text/plain": [
"<matplotlib.figure.Figure at 0x118a832b0>"
]
},
"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 etet, which should be white noise (but it isn't). The bottom shows the [autocorrelation](https://www.otexts.org/fpp/2/2#autocorrelation) of the residuals as a correlogram. It measures the correlation between a value and it's lagged self, $corr(e_t, e_{t-1}), corr(e_t, e_{t-2}), \\ldots$. The partial autocorrelation plot in the bottom-right shows a similar concept. It's partial in the sense that the value for $corr(e_t,e_{t−k})corr(e_t,e_{t−k})$ is the correlation between those two periods, after controlling for the values at all shorter lags.\n",
"\n",
"Autocorrelation is a problem in regular regressions like above, but we'll use it to our advantage when we setup an ARIMA model below. The basic idea is pretty sensible: if your regression residuals have a clear pattern, then there's clearly some structure in the data that you aren't taking advantage of. If a positive residual today means you'll likely have a positive residual tomorrow, why not incorporate that information into your forecast, and lower your forecasted value for tomorrow? That's pretty much what ARIMA does."
]
},
{
"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). A common example is the relationship between number of TVs per person and life expectancy. It's not likely that there's an actual causal relationship there. Rather, there could be a third variable that's driving both (wealth, say). Granger and Newbold (1974) had some stern words for the econometrics literature on this.\n",
"\n",
"> We find it very curious that whereas virtually every textbook on econometric methodology contains explicit warnings of the dangers of autocorrelated errors, this phenomenon crops up so frequently in well-respected applied work.\n",
"\n",
"(:fire:), but in that academic passive-aggressive way.\n",
"\n",
"The typical way to handle non-stationarity is to difference the non-stationary variable until is is stationary."
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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jcsQvZfDl0dU4wmnkbGq0UlDm+xReQVktj7zwFY+88BWllQ3K48eyDHxzpEgR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\n2sO1wcNT5LRzdJi+y524coOHt7z8cou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+W8Ob5s2tIfuuXSipwezBNBFzo1Uxum6rWaYr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\nRp7pjfYBmI18gdnIPQaDwem1Hjl+OTk5ePPNNzFp0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MaPHx/iTxMYmI28w2zkhhBHHIPG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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x117841748>"
]
},
"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. It doesn't look like nominal GDP say, where there's a clearly rising trend. But we have more rigorous methods for detecting whether a series is non-stationary than simply plotting and squinting at it. One popular method is the Augmented Dickey-Fuller test. It's a statistical hypothesis test that roughly 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",
"I don't want to get into the weeds on exactly what the test statistic is, and what the distribution looks like. 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": 45,
"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": 46,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"OrderedDict([('adf', -1.990460879464149),\n",
" ('pvalue', 0.29077127047555601),\n",
" ('usedlag', 15),\n",
" ('nobs', 176),\n",
" ('critical',\n",
" {'1%': -3.4680615871598537,\n",
" '10%': -2.5756015922004134,\n",
" '5%': -2.8781061899535128}),\n",
" ('icbest', 1987.6605732826176)])"
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ADF(*smt.adfuller(y))._asdict()"
]
},
{
"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": 47,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"OrderedDict([('adf', -3.5862361055645193),\n",
" ('pvalue', 0.0060296818910968528),\n",
" ('usedlag', 14),\n",
" ('nobs', 176),\n",
" ('critical',\n",
" {'1%': -3.4680615871598537,\n",
" '10%': -2.5756015922004134,\n",
" '5%': -2.8781061899535128}),\n",
" ('icbest', 1979.6445486427308)])"
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ADF(*smt.adfuller(y.diff().dropna()))._asdict()"
]
},
{
"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": 48,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>y</th>\n",
" <th>Δy</th>\n",
" <th>LΔy</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2000-01-01</th>\n",
" <td>1882.387097</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-02-01</th>\n",
" <td>1926.896552</td>\n",
" <td>44.509455</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-03-01</th>\n",
" <td>1951.000000</td>\n",
" <td>24.103448</td>\n",
" <td>44.509455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-04-01</th>\n",
" <td>1944.400000</td>\n",
" <td>-6.600000</td>\n",
" <td>24.103448</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-05-01</th>\n",
" <td>1957.967742</td>\n",
" <td>13.567742</td>\n",
" <td>-6.600000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-06-01</th>\n",
" <td>1976.133333</td>\n",
" <td>18.165591</td>\n",
" <td>13.567742</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-07-01</th>\n",
" <td>1937.032258</td>\n",
" <td>-39.101075</td>\n",
" <td>18.165591</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-08-01</th>\n",
" <td>1960.354839</td>\n",
" <td>23.322581</td>\n",
" <td>-39.101075</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-09-01</th>\n",
" <td>1900.533333</td>\n",
" <td>-59.821505</td>\n",
" <td>23.322581</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2000-10-01</th>\n",
" <td>1931.677419</td>\n",
" <td>31.144086</td>\n",
" <td>-59.821505</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" y Δy LΔy\n",
"2000-01-01 1882.387097 NaN NaN\n",
"2000-02-01 1926.896552 44.509455 NaN\n",
"2000-03-01 1951.000000 24.103448 44.509455\n",
"2000-04-01 1944.400000 -6.600000 24.103448\n",
"2000-05-01 1957.967742 13.567742 -6.600000\n",
"2000-06-01 1976.133333 18.165591 13.567742\n",
"2000-07-01 1937.032258 -39.101075 18.165591\n",
"2000-08-01 1960.354839 23.322581 -39.101075\n",
"2000-09-01 1900.533333 -59.821505 23.322581\n",
"2000-10-01 1931.677419 31.144086 -59.821505"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = (y.to_frame(name='y')\n",
" .assign(Δy=lambda df: df.y.diff())\n",
" .assign(LΔy=lambda df: df.Δy.shift()))\n",
"data.head(10) "
]
},
{
"cell_type": "code",
"execution_count": 49,
"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": 50,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(<matplotlib.axes._subplots.AxesSubplot at 0x11524f320>,\n",
" <matplotlib.axes._subplots.AxesSubplot at 0x1149ee748>,\n",
" <matplotlib.axes._subplots.AxesSubplot at 0x115edc048>)"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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ei0vObnKIrcdYNwZaQY0gCIIgiFQgsZsm9JYHpiWDk0NsPUYxBoIgCIIg0gGJ3TSh5+IG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\nAAAAy/r/+E4L8n25JO0AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116773d68>"
]
},
"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": [
"This is better, but we still see a regular cycle in the residuals. The cause is seasonality.\n",
"\n",
"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": 51,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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lFQKwZHKPBnOwjdwud/qpsZ0Y3N2H/Wdv8HtMOiXlBtWPhwYEMuWBUBxsLRvUjpqQSiU8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hk/5eObY0WYOyke08dGIzE6wKmQDZPJhPwyBQ6cK8PJ7Cq6pL1ULMTdM5Iwf9pgiH1c7z3nin5/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\nIBAIBAKBYGT+H9/M8KYY64SqAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118a8f828>"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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lFQKwZHKPBnOwjdwud/qpsZ0Y3N2H/Wdv8HtMOiXlBtWPhwYEMuWBUBxsLRvUjpqQSiU8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hk/5eObY0WYOyke08dGIzE6wKmQDZPJhPwyBQ6cK8PJ7Cq6pL1ULMTdM5Iwf9pgiH1c7z3nin5/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\nIBAIBAKBYGT+H9/M8KYY64SqAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118a8f828>"
]
},
"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 to be solved."
]
},
{
"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 $d=1$, and your series is integrated of order 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. But now the coefficients are the residuals from previous predictions, not the actual (or differenced) values."
]
},
{
"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",
"That was for our specific ARIMA(1,1,1)ARIMA(1,1,1) model. For the general ARIMA(p,d,q)ARIMA(p,d,q), that becomes\n",
"\n",
"$$(1 - \\phi_1 L - \\ldots - \\phi_p L^p) (1 - L)^d y_t = c + (1 + \\theta L + \\ldots + \\theta_q L^q)e_t$$\n",
"\n",
"We went through that extremely quickly, so don't feel bad if things aren't clear. Fortunately, the model is pretty easy to use with statsmodels."
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(<matplotlib.axes._subplots.AxesSubplot at 0x117728358>,\n",
" <matplotlib.axes._subplots.AxesSubplot at 0x118ad1080>,\n",
" <matplotlib.axes._subplots.AxesSubplot at 0x1177e8fd0>)"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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E7iA5u0ddHu7mV8+dpjzWjaaW7rivbRFiDD2+0KDkilmMgZ2DBUqMIaUCtdNJ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ElbjiGxzhnHUK1WQ61W48EHH8TFixfxyy+/OHqzPYojj+H06dOxbt06dO7cGWq1Gvfeey9KS0tx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