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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 exercício faz parte do curso

Analyzing IoT Data in Python

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Instruções do exercício

  • 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.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# Import modules
____

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

# Print the seasonal component
____

# Plot the result
____

# Show the plot
plt.show()
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