Don't let missing values ruin your analysis output, Deal with them!

Missing values or their replacement values can lead to huge errors in your analysis output wheter it is a machine learning model, KPIs or a report. Missing values or their replacement values can lead to huge errors in your analysis output wheter it is a machine learning model, KPIs or a report. Often analysts deal with missing values just like there is only one type of them. It is not the case, there is three types of missing values and there is ways of dealing with0 each one of them. Missing at random (MAR): The presence of a null value in a variable is not random but rather dependent of a known or unknown characteristic of the record.