Data Science | Machine learning | Data Cleaning
Question
How to handle missing values in the huge dataset?
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Answer ( 1 )
Data cleaning is a very important process before analysis of data because if any type of irregularity is present in the dataset, then it loses information, so data cleaning is necessary before analysis. There are various methods to handle missing values first is we can simply drop those missing values but it is responsible for missing important information. Second, we can replace those missing values with the statistics concepts like Mean, Median, and Mode.
Mean -> Missing values can be replaced by the average value of the Feature.
Median -> Missing values can be replaced by the median value of the feature.
Mode -> Missing values can be replaced by the most repeated value of the feature.