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Seasonal decomposition

In the last exercise, you identified some repetitive patterns in the traffic data with both visual inspection and using an autocorrelation plot.

You'll now dissect this data further by splitting it into it's components.

The data has been loaded for you into traffic.

Este ejercicio forma parte del curso

Analyzing IoT Data in Python

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Instrucciones del ejercicio

  • Import statsmodels.api as sm.
  • Perform seasonal decomposition on the time series "vehicles" column from the DataFrame traffic and assign the result to res.
  • Print the seasonal component to screen.
  • Plot the time series decomposition result.

Ejercicio interactivo práctico

Prueba este ejercicio y completa el código de muestra.

# Import modules
____

# Perform decompositon 
res = sm.tsa.____(____[____])

# Print the seasonal component
____

# Plot the result
____

# Show the plot
plt.show()
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