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Visualize forward fill imputation

To visualize time-series imputations, we can create two plots with the plot of original DataFrame overlapping the imputed DataFrame. Additionally, changing the linestyle, color and marker for the imputed DataFrame, helps to clearly distinguish the non-missing values and the imputed values. The imputed DataFrames can be plotted using the .plot() method.

In this exercise, you will first impute and then plot the time-series plot of forward filled DataFrame. The airquality DataFrame has been loaded for you.

Questo esercizio fa parte del corso

Dealing with Missing Data in Python

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Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Impute airquality DataFrame with ffill method
ffill_imputed = ___
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