用R语言中的psych包做PCA分析，测试数据中包含较多0，导致测试结果中提示了一些信息，请问一下黄色字体部分是什么意思？做PCA分析时遇到原始数据中包含较多0时该如何处理？初学，谢谢！
测试结果：

>fa.parallel(EL_Data_Frame[,c(4,5,6,7,9)],fa="pc",n.iter = 100,show.legend= FALSE,main = "ATL PCA")

In smc, the correlation matrix was notinvertible, smc's returned as 1s

In smc, the correlation matrix was notinvertible, smc's returned as 1s

In factor.stats, the correlation matrix issingular, an approximation is used

In factor.scores, the correlation matrix issingular, an approximation is used

I was unable to calculate the factor scoreweights, factor loadings used instead

Parallel analysis suggests that the numberof factors =  NA  and the number of components =  2

>pc<-principal(EL_Data_Frame[,c(4,5,6,7,9)],nfactors = 2)

In factor.stats, the correlation matrix issingular, an approximation is used

In factor.scores, the correlation matrix issingular, an approximation is used

I was unable to calculate the factor scoreweights, factor loadings used instead

测试数据:

    S1 S2 S3 S4 S6

1  2020 30  0 30

2  3020 50  0 0

3  1515 40  0 30

4  1010 50  0 30

5  5  5 60  0 30

6   020 50  0 30

7 20  0 50  0 30

8  2020 30 30  0

9  2020 60  0 0

10 30 20 50 0  0

11 15 15 40 0 30

12 10 10 50 0 30

13 5  5 60  0 30

14  020 50  0 30

15 20 0 50  0 30

16 20 20 30 30  0

17 20 20 60 0  0

18 20 20 60 0  0

19 20 20 30 0 30

20 20 20 30 0 30

21 20 20 30 0 30

22 20 20 30 0 30

23 20 20 30 0 30

24 20 20 30 0 30

25 20 20 30 0 30

26 20 20 30 0 30

27 20 20 30 0 30

28 20 20 30 0 30

29 20 20 30 0 30

30 20 20 30 0 30

31 20 20 30 0 30

32 20 20 30 0 30

33 20 20 30 0 30

34 20 20 30 0 30

35 20 20 30 0 30

36 20 20 30 0 30

37 20 20 30 0 30

38 20 20 30 0 30

39 20 20 30 0 30

40 20 20 30 0 30