Search code examples
pythonmatplotlibmachine-learningtime-seriesstatsmodels

seasonal decompose in python


I have a CSV file that contains the average temperature over almost 5 years. After decomposition using seasonal_decompose function from statsmodels.tsa.seasonal, I got the following results. Indeed, the results do not show any seasonal! However, I see a clear sin in the trend! I am wondering why is that and how can I correct it? Thank you.

nresult = seasonal_decompose(nseries, model='additive', freq=1)
nresult.plot()
plt.show()

enter image description here


Solution

  • It looks like your freq is off.

    import numpy as np
    import pandas as pd
    from statsmodels.tsa.seasonal import seasonal_decompose
    
    # Generate some data
    np.random.seed(0)
    n = 1500
    dates = np.array('2005-01-01', dtype=np.datetime64) + np.arange(n)
    data = 12*np.sin(2*np.pi*np.arange(n)/365) + np.random.normal(12, 2, 1500)
    df = pd.DataFrame({'data': data}, index=dates)
    
    # Reproduce the example in OP
    seasonal_decompose(df, model='additive', freq=1).plot()
    

    enter image description here

    # Redo the same thing, but with the known frequency
    seasonal_decompose(df, model='additive', freq=365).plot()
    

    enter image description here