Datasets are also prone to missing information. This is very common in datasets that require user input, for example, in surveys where the user might not have entered all the information in the respective fields. Also, sometimes the data might not even be available or due to restrictions could not be included in the respective dataset.
There are multiple techniques that have been devised to fill in missing values. The methods include simple procedures such as using the mean or median of the columns to more advanced methods in fields such as survey statistics.
A few of the common methods to impute, that is, fill in missing values, have been provided as follows:
- Imputation using statistical measures of central tendency: This means ...
