Performing Analysis of a Factor in R Programming - factanal() Function Last Updated : 12 Jul, 2025 Comments Improve Suggest changes Like Article Like Report Factor Analysis also known as Exploratory Factor Analysis is a statistical technique used in R programming to identify the inactive relational structure and further, narrowing down a pool of variables to few variables. The main motive to use this technique is to find out which factor is most responsible for influence in the categorization of weights. Syntax: factanal(x, factors) Parameters: x: represents dataset factors: specifies number of factors to be fitted Example: Let us suppose, there are number of food available in the dataset with their food texture data points such as Oil, Density, Crispy, Fracture, and Hardness. Python3 # Reading csv file of food textures food_textures <- read.csv("https://userpage.fu-berlin.de/soga/300/30100_data_sets/food-texture.csv") food_textures <- food_textures[, 2:6] factor_analysis <- factanal(food_textures, factors = 2) print(factor_analysis) # Output to be present as PNG file png(file = "factorAnalysisGFG.png") # Plot factor 1 by factor 2 load <- factor_analysis$loadings[, 1:2] # Plot graph plot(load, type = "n") text(load, labels = names(food_textures), cex = .9) # Saving the file dev.off() Output: Call: factanal(x = food_textures, factors = 2) Uniquenesses: Oil Density Crispy Fracture Hardness 0.334 0.156 0.042 0.256 0.407 Loadings: Factor1 Factor2 Oil -0.816 Density 0.919 Crispy -0.745 0.635 Fracture 0.645 -0.573 Hardness 0.764 Factor1 Factor2 SS loadings 2.490 1.316 Proportion Var 0.498 0.263 Cumulative Var 0.498 0.761 Test of the hypothesis that 2 factors are sufficient. The chi-square statistic is 0.27 on 1 degree of freedom. The p-value is 0.603 Comment More infoAdvertise with us Next Article R Programming Language - Introduction U utkarsh_kumar Follow Improve Article Tags : R Language R-Factors R Factor-Function Similar Reads R Tutorial | Learn R Programming Language R is an interpreted programming language widely used for statistical computing, data analysis and visualization. R language is open-source with large community support. R provides structured approach to data manipulation, along with decent libraries and packages like Dplyr, Ggplot2, shiny, Janitor a 4 min read IntroductionR Programming Language - IntroductionR is a programming language and software environment that has become the first choice for statistical computing and data analysis. Developed in the early 1990s by Ross Ihaka and Robert Gentleman, R was built to simplify complex data manipulation and create clear, customizable visualizations. 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