Dimensionality reduction with missing values imputation

For about thirty years, data analysis methods have largely demonstrated their effectiveness in the processing of data in many fields. Data reduction is one of these methods and part of the descriptive (or exploratory) statistics. It tries to summarize a sample of data using graphs or numerical characteristics. The main interpretation of data reduction is reducing the number of dimensions. This implies that data reduction is part of the multivariate exploratory statistics which seek to reduce the number of data dimensions by extracting a number of factors, dimensions, clusters, etc., which explain the dispersion of (multidimensional) data.