Handling Missing Values in Data Frames | ZORBA CONSULTING
fillna() function of Pandas conveniently handles missing values. Using fillna(), missing values can be replaced by a special value or an aggregate value such as mean, median. Furthermore, missing values can be replaced with the value before or after it which is pretty useful for time-series datasets.
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