With the development of the smart grid, power grid enterprises have accumulated a large amount of business data, visualization has become an effective way for big data mining. The operating data in power grid has the characteristics of sequential, multidimensional and fast.Monitoring data of wind turbines is one part of it.The current monitoring data visualization of wind turbines suffers from poor interactivity and less intuitiveness. In this paper, a visualization method based on random forest is proposed.Firstly, random forest was used for feature transformation on monitoring data, which enhanced the separability in the new feature space. Then ,the principal component analysis (PCA) is adopted to reduce the dimension of transformed data , by which the relationship between the multidimensional data information is transformed into low dimensional space for human visual perception.Finally, the data in low dimensional space using a scatter diagram and parallel coordinates figure is displayed. The experimental results shows that the condition monitoring data of wind turbines processed with the random forest,has a good visual effect and it’s easy for the wind turbines manager to figure out the data characteristics, distribution, development trend and the relationship between attributes on the whole grasp.It’s of great significance to improve the running reliability of wind turbines.