Replace NA values with forward fill including a factor in Python
This Python tutorial shows how to simply forward fill NA/NaN values with the previous number including a specific multiplication factor in pandas DataFrame in Python. With the factor, the NA values are not replaced by the previous number, but with the previous number times the factor. This allows, to increase or decrease the following numbers by replacing the NA value. This methodology to get rid of NA values in a DataFrame is an easy and powerful method to clean the data for time series data. The video shows an example with a factor of 0.9 for positive and negative values before NA values but also the case, if there is a different factor based on the sign of the value before the NA values. With the forward fill method, we make sure for time-series data that we only incorporate information that is available at a certain point in time. Thanks for watching and in case you got value out of the video, please leave a like and subscribe the channel for more useful Python content.
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