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.
This exercise is part of the course
Dealing with Missing Data in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Impute airquality DataFrame with ffill method
ffill_imputed = ___