<spanid="pyfts-data-common-module"></span><h2>pyFTS.data.common module<aclass="headerlink"href="#module-pyFTS.data.common"title="Permalink to this headline">¶</a></h2>
<codeclass="descclassname">pyFTS.data.common.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><em>filename</em>, <em>url</em>, <em>sep=';'</em>, <em>compression='infer'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.common.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="artificial-and-synthetic-data-generators"></span><h2>Artificial and synthetic data generators<aclass="headerlink"href="#module-pyFTS.data.artificial"title="Permalink to this headline">¶</a></h2>
<p>Facilities to generate synthetic stochastic processes</p>
<emclass="property">class </em><codeclass="descclassname">pyFTS.data.artificial.</code><codeclass="descname">SignalEmulator</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.SignalEmulator"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">blip</code><spanclass="sig-paren">(</span><em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.SignalEmulator.blip"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">incremental_gaussian</code><spanclass="sig-paren">(</span><em>mu</em>, <em>sigma</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.SignalEmulator.incremental_gaussian"title="Permalink to this definition">¶</a></dt>
<li><strong>sigma</strong>– increment on variance</li>
<li><strong>start</strong>– lag index to start this signal, the default value is 0</li>
<li><strong>it</strong>– Number of iterations, the default value is 1</li>
<li><strong>length</strong>– Number of samples generated on each iteration, the default value is 100</li>
<li><strong>vmin</strong>– Lower bound value of generated data, the default value is None</li>
<li><strong>vmax</strong>– Upper bound value of generated data, the default value is None</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">the current SignalEmulator instance, for method chaining</p>
<codeclass="descname">periodic_gaussian</code><spanclass="sig-paren">(</span><em>type</em>, <em>period</em>, <em>mu_min</em>, <em>sigma_min</em>, <em>mu_max</em>, <em>sigma_max</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.SignalEmulator.periodic_gaussian"title="Permalink to this definition">¶</a></dt>
<li><strong>type</strong>–‘linear’ or ‘sinoidal’</li>
<li><strong>period</strong>– the period of recurrence</li>
<li><strong>mu</strong>– increment on mean</li>
<li><strong>sigma</strong>– increment on variance</li>
<li><strong>start</strong>– lag index to start this signal, the default value is 0</li>
<li><strong>it</strong>– Number of iterations, the default value is 1</li>
<li><strong>length</strong>– Number of samples generated on each iteration, the default value is 100</li>
<li><strong>vmin</strong>– Lower bound value of generated data, the default value is None</li>
<li><strong>vmax</strong>– Upper bound value of generated data, the default value is None</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">the current SignalEmulator instance, for method chaining</p>
<codeclass="descname">run</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.SignalEmulator.run"title="Permalink to this definition">¶</a></dt>
<codeclass="descname">stationary_gaussian</code><spanclass="sig-paren">(</span><em>mu</em>, <em>sigma</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.SignalEmulator.stationary_gaussian"title="Permalink to this definition">¶</a></dt>
<li><strong>additive</strong>– If False it cancels the previous signal and start this one, if True
this signal is added to the previous one</li>
<li><strong>start</strong>– lag index to start this signal, the default value is 0</li>
<li><strong>it</strong>– Number of iterations, the default value is 1</li>
<li><strong>length</strong>– Number of samples generated on each iteration, the default value is 100</li>
<li><strong>vmin</strong>– Lower bound value of generated data, the default value is None</li>
<li><strong>vmax</strong>– Upper bound value of generated data, the default value is None</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">the current SignalEmulator instance, for method chaining</p>
<codeclass="descclassname">pyFTS.data.artificial.</code><codeclass="descname">random_walk</code><spanclass="sig-paren">(</span><em>n=500</em>, <em>type='gaussian'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.random_walk"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.artificial.</code><codeclass="descname">white_noise</code><spanclass="sig-paren">(</span><em>n=500</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.artificial.white_noise"title="Permalink to this definition">¶</a></dt>
<spanid="airpassengers-dataset"></span><h2>AirPassengers dataset<aclass="headerlink"href="#module-pyFTS.data.AirPassengers"title="Permalink to this headline">¶</a></h2>
<p>Monthly totals of a airline passengers from USA, from January 1949 through December 1960.</p>
<p>Source: Hyndman, R.J., Time Series Data Library, <aclass="reference external"href="http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/">http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/</a>.</p>
<codeclass="descclassname">pyFTS.data.AirPassengers.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.AirPassengers.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.AirPassengers.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.AirPassengers.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.Bitcoin.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='AVG'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Bitcoin.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.Bitcoin.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Bitcoin.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="dowjones-dataset"></span><h2>DowJones dataset<aclass="headerlink"href="#module-pyFTS.data.DowJones"title="Permalink to this headline">¶</a></h2>
<p>DJI - Dow Jones</p>
<p>Daily averaged index, by business day, from 1985 to 2017.</p>
<codeclass="descclassname">pyFTS.data.DowJones.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='AVG'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.DowJones.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.DowJones.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.DowJones.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="enrollments-dataset"></span><h2>Enrollments dataset<aclass="headerlink"href="#module-pyFTS.data.Enrollments"title="Permalink to this headline">¶</a></h2>
<codeclass="descclassname">pyFTS.data.Enrollments.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Enrollments.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.Enrollments.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Enrollments.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="ethereum-dataset"></span><h2>Ethereum dataset<aclass="headerlink"href="#module-pyFTS.data.Ethereum"title="Permalink to this headline">¶</a></h2>
<p>Ethereum to USD quotations</p>
<p>Daily averaged index, by business day, from 2016 to 2018.</p>
<codeclass="descclassname">pyFTS.data.Ethereum.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='AVG'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Ethereum.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.Ethereum.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Ethereum.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.EURGBP.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='avg'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.EURGBP.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.EURGBP.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.EURGBP.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.EURUSD.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='avg'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.EURUSD.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.EURUSD.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.EURUSD.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.GBPUSD.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='avg'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.GBPUSD.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.GBPUSD.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.GBPUSD.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.INMET.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.INMET.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="malaysia-dataset"></span><h2>Malaysia dataset<aclass="headerlink"href="#module-pyFTS.data.Malaysia"title="Permalink to this headline">¶</a></h2>
<p>Hourly Malaysia eletric load and tempeature</p>
<codeclass="descclassname">pyFTS.data.Malaysia.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='load'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Malaysia.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.Malaysia.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.Malaysia.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.NASDAQ.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field='avg'</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.NASDAQ.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.NASDAQ.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.NASDAQ.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.SONDA.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>field</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.SONDA.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.SONDA.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.SONDA.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="s-p-500-dataset"></span><h2>S&P 500 dataset<aclass="headerlink"href="#module-pyFTS.data.SP500"title="Permalink to this headline">¶</a></h2>
<codeclass="descclassname">pyFTS.data.SP500.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.SP500.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.SP500.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.SP500.get_dataframe"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.TAIEX.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.TAIEX.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.TAIEX.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.TAIEX.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="henon-chaotic-time-series"></span><h2>Henon chaotic time series<aclass="headerlink"href="#module-pyFTS.data.henon"title="Permalink to this headline">¶</a></h2>
<codeclass="descclassname">pyFTS.data.henon.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>var, a=1.4, b=0.3, initial_values=[1, 1], iterations=1000</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.henon.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.henon.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><em>a=1.4, b=0.3, initial_values=[1, 1], iterations=1000</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.henon.get_dataframe"title="Permalink to this definition">¶</a></dt>
<spanid="logistic-map-chaotic-time-series"></span><h2>Logistic_map chaotic time series<aclass="headerlink"href="#module-pyFTS.data.logistic_map"title="Permalink to this headline">¶</a></h2>
<codeclass="descclassname">pyFTS.data.logistic_map.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><em>r=4</em>, <em>initial_value=0.3</em>, <em>iterations=100</em><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.logistic_map.get_data"title="Permalink to this definition">¶</a></dt>
<spanid="lorentz-chaotic-time-series"></span><h2>Lorentz chaotic time series<aclass="headerlink"href="#module-pyFTS.data.lorentz"title="Permalink to this headline">¶</a></h2>
<li><strong>dt</strong>– Time differential for continuous time integration. Default value: 0.01</li>
<li><strong>initial_values</strong>– numpy array with the initial values of x,y and z. Default: [0.1, 0, 0]</li>
<li><strong>iterations</strong>– number of iterations. Default: 1000</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">Panda dataframe with the x, y and z values</p>
<spanid="mackey-glass-chaotic-time-series"></span><h2>Mackey-Glass chaotic time series<aclass="headerlink"href="#module-pyFTS.data.mackey_glass"title="Permalink to this headline">¶</a></h2>
<spanid="rossler-chaotic-time-series"></span><h2>Rossler chaotic time series<aclass="headerlink"href="#module-pyFTS.data.rossler"title="Permalink to this headline">¶</a></h2>
<li><strong>dt</strong>– Time differential for continuous time integration. Default value: 0.01</li>
<li><strong>initial_values</strong>– numpy array with the initial values of x,y and z. Default: [0.001, 0.001, 0.001]</li>
<li><strong>iterations</strong>– number of iterations. Default: 5000</li>
</ul>
</td>
</tr>
<trclass="field-even field"><thclass="field-name">Returns:</th><tdclass="field-body"><pclass="first last">Panda dataframe with the x, y and z values</p>
<spanid="sunspots-dataset"></span><h2>Sunspots dataset<aclass="headerlink"href="#module-pyFTS.data.sunspots"title="Permalink to this headline">¶</a></h2>
<codeclass="descclassname">pyFTS.data.sunspots.</code><codeclass="descname">get_data</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.sunspots.get_data"title="Permalink to this definition">¶</a></dt>
<codeclass="descclassname">pyFTS.data.sunspots.</code><codeclass="descname">get_dataframe</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink"href="#pyFTS.data.sunspots.get_dataframe"title="Permalink to this definition">¶</a></dt>