{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Seasonality, Trend and Noise\n", "> You will go beyond summary statistics by learning about autocorrelation and partial autocorrelation plots. You will also learn how to automatically detect seasonality, trend and noise in your time series data. This is the Summary of lecture \"Visualizing Time-Series data in Python\", via datacamp.\n", "\n", "- toc: true \n", "- badges: true\n", "- comments: true\n", "- author: Chanseok Kang\n", "- categories: [Python, Datacamp, Time_Series_Analysis, Visualization]\n", "- image: images/trend_seasonal.png" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "plt.rcParams['figure.figsize'] = (10, 5)\n", "plt.style.use('fivethirtyeight')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Autocorrelation and Partial autocorrelation\n", "- Autocorrelation in time series data\n", " - Autocorrelation is measured as the correlation between a time series and a delayed copy of itself\n", " - For example, an autocorrelation of order 3 returns the correlation between a time series at points($t_1, t_2, t_3$) and its own values lagged by 3 time points. ($t_4, t_5, t_6$)\n", " - It is used to find repetitive paterns or periodic signal it time series\n", "- Partial autocorrelation in time series data\n", " - Contrary to autocorrelation, partial autocorrelation removes the effect of previous time points\n", " - For example, a partial autocorrelatio nfunction of order 3 returns the correlation between out time series ($t_1, t_2, t_3$) and lagged values of itself by 3 time points ($t_4, t_5, t_6$), but only after removing all effects attributable to lags 1 and 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Autocorrelation in time series data\n", "In the field of time series analysis, autocorrelation refers to the correlation of a time series with a lagged version of itself. For example, an autocorrelation of order 3 returns the correlation between a time series and its own values lagged by 3 time points.\n", "\n", "It is common to use the autocorrelation (ACF) plot, also known as self-autocorrelation, to visualize the autocorrelation of a time-series. The ```plot_acf()``` function in the statsmodels library can be used to measure and plot the autocorrelation of a time series." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "co2_levels = pd.read_csv('./dataset/ch2_co2_levels.csv')\n", "co2_levels.set_index('datestamp', inplace=True)\n", "co2_levels = co2_levels.fillna(method='bfill')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from statsmodels.graphics import tsaplots\n", "\n", "# Display \n", "fig = tsaplots.plot_acf(co2_levels['co2'], lags= 24);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Interpret autocorrelation plots\n", "If autocorrelation values are close to 0, then values between consecutive observations are not correlated with one another. Inversely, autocorrelations values close to 1 or -1 indicate that there exists strong positive or negative correlations between consecutive observations, respectively.\n", "\n", "In order to help you asses how trustworthy these autocorrelation values are, the ```plot_acf()``` function also returns confidence intervals (represented as blue shaded regions). If an autocorrelation value goes beyond the confidence interval region, you can assume that the observed autocorrelation value is statistically significant." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Partial autocorrelation in time series data\n", "Like autocorrelation, the partial autocorrelation function (PACF) measures the correlation coefficient between a time-series and lagged versions of itself. However, it extends upon this idea by also removing the effect of previous time points. For example, a partial autocorrelation function of order 3 returns the correlation between our time series ($t_1, t_2, t_3, \\dots$) and its own values lagged by 3 time points ($t_4, t_5, t_6, \\dots$), but only after removing all effects attributable to lags 1 and 2.\n", "\n", "The ```plot_pacf()``` function in the statsmodels library can be used to measure and plot the partial autocorrelation of a time series." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Display the partial autocorrelation plot of your time series\n", "fig = tsaplots.plot_pacf(co2_levels['co2'], lags=24);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Interpret partial autocorrelation plots\n", "If partial autocorrelation values are close to 0, then values between observations and lagged observations are not correlated with one another. Inversely, partial autocorrelations with values close to 1 or -1 indicate that there exists strong positive or negative correlations between the lagged observations of the time series.\n", "\n", "The ```.plot_pacf()``` function also returns confidence intervals, which are represented as blue shaded regions. If partial autocorrelation values are beyond this confidence interval regions, then you can assume that the observed partial autocorrelation values are statistically significant." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Seasonality, trend and noise in time series data\n", "- The properties of time series\n", " - Seasonality: does the data display a clear periodic pattern?\n", " - Trend: does the data follow a consistent upwards or downwards slope?\n", " - Noise: are there any outlier points or missing values that are not consistent with the rest of the data?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Time series decomposition\n", "You can rely on a method known as time-series decomposition to automatically extract and quantify the structure of time-series data. The statsmodels library provides the ```seasonal_decompose()``` function to perform time series decomposition out of the box.\n", "```python\n", "decomposition = sm.tsa.seasonal_decompose(time_series)\n", "```\n", "You can extract a specific component, for example seasonality, by accessing the seasonal attribute of the ```decomposition``` object." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "co2_levels.index = pd.to_datetime(co2_levels.index)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "datestamp\n", "1958-03-29 1.028042\n", "1958-04-05 1.235242\n", "1958-04-12 1.412344\n", "1958-04-19 1.701186\n", "1958-04-26 1.950694\n", " ... \n", "2001-12-01 -0.525044\n", "2001-12-08 -0.392799\n", "2001-12-15 -0.134838\n", "2001-12-22 0.116056\n", "2001-12-29 0.285354\n", "Name: seasonal, Length: 2284, dtype: float64\n" ] } ], "source": [ "import statsmodels.api as sm\n", "\n", "# Perform time series decomposition\n", "decomposition = sm.tsa.seasonal_decompose(co2_levels)\n", "\n", "# Print the seasonality component\n", "print(decomposition.seasonal)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot individual components\n", "It is also possible to extract other inferred quantities from your time-series decomposition object. The following code shows you how to extract the observed, trend and noise (or residual, ```resid```) components.\n", "```python\n", "observed = decomposition.observed\n", "trend = decomposition.trend\n", "residuals = decomposition.resid\n", "```\n", "You can then use the extracted components and plot them individually." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Extract the trend component\n", "trend = decomposition.trend\n", "\n", "# Plot the values of the trend\n", "ax = trend.plot(figsize=(12, 6), fontsize=10);\n", "\n", "# Specify axis labels\n", "ax.set_xlabel('Date', fontsize=10);\n", "ax.set_title('Seasonal component the CO2 time-series', fontsize=10);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A quick review\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Visualize the airline dataset\n", "You will now review the contents of chapter 1. You will have the opportunity to work with a new dataset that contains the monthly number of passengers who took a commercial flight between January 1949 and December 1960." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "airline = pd.read_csv('./dataset/ch3_airline_passengers.csv', parse_dates=['Month'], index_col='Month')" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "DatetimeIndex: 144 entries, 1949-01-01 to 1960-12-01\n", "Data columns (total 1 columns):\n", " # Column Non-Null Count Dtype\n", "--- ------ -------------- -----\n", " 0 AirPassengers 144 non-null int64\n", "dtypes: int64(1)\n", "memory usage: 2.2 KB\n" ] } ], "source": [ "airline.info()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot the time series in your dataframe\n", "ax = airline.plot(color='blue', fontsize=12);\n", "\n", "# Add a red vertical line at the date 1955-12-01\n", "ax.axvline('1955-12-01', color='red', linestyle='--');\n", "\n", "# Specify the labels in your plot\n", "ax.set_xlabel('Date', fontsize=12);\n", "ax.set_title('Number of Monthly Airline Passengers', fontsize=12);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Analyze the airline dataset\n", "In Chapter 2 you learned:\n", "\n", "- How to check for the presence of missing values, and how to collect summary statistics of time series data contained in a pandas DataFrame.\n", "- To generate boxplots of your data to quickly gain insight in your data.\n", "- Display aggregate statistics of your data using groupby()." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "AirPassengers 0\n", "dtype: int64\n", " AirPassengers\n", "count 144.000000\n", "mean 280.298611\n", "std 119.966317\n", "min 104.000000\n", "25% 180.000000\n", "50% 265.500000\n", "75% 360.500000\n", "max 622.000000\n" ] } ], "source": [ "# Print out the number of missing values\n", "print(airline.isnull().sum())\n", "\n", "# Print out summary statistics of the airline DataFrame\n", "print(airline.describe())" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Display boxplot of airline values\n", "ax = airline.boxplot();\n", "\n", "# Specify the title of your plot\n", "ax.set_title('Boxplot of Monthly Airline\\nPassengers Count', fontsize=20);" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Get month for each dates from the index of airline\n", "index_month = airline.index.month\n", "\n", "# Compute the mean number of passengers for each month of the year\n", "mean_airline_by_month = airline.groupby(index_month).mean()\n", "\n", "# Plot the mean number of passengers for each month of the year\n", "mean_airline_by_month.plot();\n", "plt.legend(fontsize=20);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Time series decomposition of the airline dataset\n", "In this exercise, you will apply time series decomposition to the ```airline``` dataset, and visualize the ```trend``` and ```seasonal``` componenets." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# Perform time series decomposition\n", "decomposition = sm.tsa.seasonal_decompose(airline)\n", "\n", "# Extract the trend and seasonal components\n", "trend = decomposition.trend\n", "seasonal = decomposition.seasonal" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "airline_decomposed = pd.concat([trend, seasonal], axis=1)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " trend seasonal\n", "Month \n", "1949-01-01 NaN -24.748737\n", "1949-02-01 NaN -36.188131\n", "1949-03-01 NaN -2.241162\n", "1949-04-01 NaN -8.036616\n", "1949-05-01 NaN -4.506313\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Print the first 5 rows of airline_decomposed\n", "print(airline_decomposed.head(5))\n", "\n", "# Plot the values of the airline_decomposed DataFrame\n", "ax = airline_decomposed.plot(figsize=(12, 6), fontsize=15);\n", "\n", "# Specify axis labels\n", "ax.set_xlabel('Date', fontsize=15);\n", "plt.legend(fontsize=15);\n", "plt.savefig('../images/trend_seasonal.png')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }