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  3. Dealing with Missing Data in Python

Exercise

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.

Instructions 1/3

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  • Impute airquality DataFrame with the frontward fill method.