approxfun中的错误，需要至少两个非NA值来进行插值。

huangapple
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英文:

Error in approxfun, need at least two non-NA values to interpolate

问题

我试图使用approxfun来计算插值来填充缺失值：

  1. column_name <- colnames(vndusd_merged);
  3. lapply(column_name, function(x){
  4.   if(x != "Date"){ 
  5.     interpl <- approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], vndusd_merged$x[!is.na(vndusd_merged$x)]);
  6.     vndusd_merged$x <- interpl(vndusd_merged$Date);  
  7.   }
  8. })

我一直收到这个错误：

  1. Error in approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], vndusd_merged$x[!is.na(vndusd_merged$x)]) : 
  2.   need at least two non-NA values to interpolate 
  3. 4.
  4. stop("need at least two non-NA values to interpolate") 
  5. 3.
  6. approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], vndusd_merged$x[!is.na(vndusd_merged$x)]) 
  7. 2.
  8. FUN(X[[i]], ...) 
  9. 1.
  10. lapply(column_name, function(x) {
  11.     if (x != "Date") {
  12.         interpl <- approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], 
  13.             vndusd_merged$x[!is.na(vndusd_merged$x)]) ...

以下是<code>vndusd_merged</code>的前20行示例。列"Date"没有任何N/A：

  1.          Date Ask.Close Bid.Close
  2. 1  01/01/2014     21115     21075
  3. 2  02/01/2014     21160     21060
  4. 3  03/01/2014     21115     21075
  5. 4  04/01/2014        NA        NA
  6. 5  05/01/2014        NA        NA
  7. 6  06/01/2014     21120     21080
  8. 7  07/01/2014     21115     21075
  9. 8  08/01/2014     21120     21080
  10. 9  09/01/2014     21115     21075
  11. 10 10/01/2014     21110     21072
  12. 11 11/01/2014        NA        NA
  13. 12 12/01/2014        NA        NA
  14. 13 13/01/2014     21120     21060
  15. 14 14/01/2014     21110     21072
  16. 15 15/01/2014     21110     21070
  17. 16 16/01/2014     21120     21080
  18. 17 17/01/2014     21110     21070
  19. 18 18/01/2014        NA        NA
  20. 19 19/01/2014        NA        NA
  21. 20 20/01/2014     21110     21070

我尝试手动插入列名运行它，但仍然收到相同的错误：

  1. interpl <- aproxfun(vndusd_merged$Date[!is.na(vndusd_merged$Ask.Close)], vndusd_merged$Ask.Close[!is.na(vndusd_merged$Ask.Close)]);

我该如何解决这个问题？

英文:

I'm trying to use approxfun to calculate missing value using interpolate:

  1. column_name &lt;- colnames(vndusd_merged);
  3. lapply(column_name, function(x){
  4.   if(x != &quot;Date&quot;){ 
  5.     interpl &lt;- approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], vndusd_merged$x[!is.na(vndusd_merged$x)]);
  6.     vndusd_merged$x &lt;- interpl(vndusd_merged$Date);  
  7.   }
  8. })

I keep getting this error:

  1. Error in approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], vndusd_merged$x[!is.na(vndusd_merged$x)]) : 
  2.   need at least two non-NA values to interpolate 
  3. 4.
  4. stop(&quot;need at least two non-NA values to interpolate&quot;) 
  5. 3.
  6. approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], vndusd_merged$x[!is.na(vndusd_merged$x)]) 
  7. 2.
  8. FUN(X[[i]], ...) 
  9. 1.
  10. lapply(column_name, function(x) {
  11.     if (x != &quot;Date&quot;) {
  12.         interpl &lt;- approxfun(vndusd_merged$Date[!is.na(vndusd_merged$x)], 
  13.             vndusd_merged$x[!is.na(vndusd_merged$x)]) ...

Here are the sample of the first 20 row of <code>vndusd_merged</code>. The column "Date" does not have any N/A

  1.          Date Ask.Close Bid.Close
  2. 1  01/01/2014     21115     21075
  3. 2  02/01/2014     21160     21060
  4. 3  03/01/2014     21115     21075
  5. 4  04/01/2014        NA        NA
  6. 5  05/01/2014        NA        NA
  7. 6  06/01/2014     21120     21080
  8. 7  07/01/2014     21115     21075
  9. 8  08/01/2014     21120     21080
  10. 9  09/01/2014     21115     21075
  11. 10 10/01/2014     21110     21072
  12. 11 11/01/2014        NA        NA
  13. 12 12/01/2014        NA        NA
  14. 13 13/01/2014     21120     21060
  15. 14 14/01/2014     21110     21072
  16. 15 15/01/2014     21110     21070
  17. 16 16/01/2014     21120     21080
  18. 17 17/01/2014     21110     21070
  19. 18 18/01/2014        NA        NA
  20. 19 19/01/2014        NA        NA
  21. 20 20/01/2014     21110     21070

I tried to run it by inserting the column name manually but I still got the same error.

  1. interpl &lt;- aproxfun(vndusd_merged$Date[!is.na(vndusd_merged$Ask.Close)], vndusd_merged$Ask.Close[!is.na(vndusd_merged$Ask.Close)]);

How can I solve this problem?

答案1

得分: 1

你可以更加简洁地使用 approx 函数来实现相同的效果。

  1. ip <- sapply(vndusd_merged[-1], function(x) with(vndusd_merged, approx(Date, x, xout=Date)$y))
  2. cbind(vndusd_merged[1], ip)
  3. #          Date Ask.Close Bid.Close
  4. # 1  01/01/2014  21115.00  21075.00
  5. # 2  02/01/2014  21160.00  21060.00
  6. # 3  03/01/2014  21115.00  21075.00
  7. # 4  04/01/2014  21116.67  21076.67
  8. # 5  05/01/2014  21118.33  21078.33
  9. # 6  06/01/2014  21120.00  21080.00
  10. # 7  07/01/2014  21115.00  21075.00
  11. # 8  08/01/2014  21120.00  21080.00
  12. # 9  09/01/2014  21115.00  21075.00
  13. # 10 10/01/2014  21110.00  21072.00
  14. # 11 11/01/2014  21113.33  21068.00
  15. # 12 12/01/2014  21116.67  21064.00
  16. # 13 13/01/2014  21120.00  21060.00
  17. # 14 14/01/2014  21110.00  21072.00
  18. # 15 15/01/2014  21110.00  21070.00
  19. # 16 16/01/2014  21120.00  21080.00
  20. # 17 17/01/2014  21110.00  21070.00
  21. # 18 18/01/2014  21110.00  21070.00
  22. # 19 19/01/2014  21110.00  21070.00
  23. # 20 20/01/2014  21110.00  21070.00

数据：

  1. vndusd_merged <- structure(list(Date = structure(1:20, .Label = c("01/01/2014", 
  2. "02/01/2014", "03/01/2014", "04/01/2014", "05/01/2014", "06/01/2014", 
  3. "07/01/2014", "08/01/2014", "09/01/2014", "10/01/2014", "11/01/2014", 
  4. "12/01/2014", "13/01/2014", "14/01/2014", "15/01/2014", "16/01/2014", 
  5. "17/01/2014", "18/01/2014", "19/01/2014", "20/01/2014"), class = "factor"), 
  6.         Ask.Close = c(21115L, 21160L, 21115L, NA, NA, 21120L, 21115L, 
  7.         21120L, 21115L, 21110L, NA, NA, 21120L, 21110L, 21110L, 21120L, 
  8.         21110L, NA, NA, 21110L), Bid.Close = c(21075L, 21060L, 21075L, 
  9.         NA, NA, 21080L, 21075L, 21080L, 21075L, 21072L, NA, NA, 21060L, 
  10.         21072L, 21070L, 21080L, 21070L, NA, NA, 21070L)), class = "data.frame", row.names = c("1", 
  11.     "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
  12.     "14", "15", "16", "17", "18", "19", "20"))
英文:

You could do the same a little more concise using approx.

  1. ip &lt;- sapply(vndusd_merged[-1], function(x) with(vndusd_merged, approx(Date, x, xout=Date)$y))
  2. cbind(vndusd_merged[1], ip)
  3. #          Date Ask.Close Bid.Close
  4. # 1  01/01/2014  21115.00  21075.00
  5. # 2  02/01/2014  21160.00  21060.00
  6. # 3  03/01/2014  21115.00  21075.00
  7. # 4  04/01/2014  21116.67  21076.67
  8. # 5  05/01/2014  21118.33  21078.33
  9. # 6  06/01/2014  21120.00  21080.00
  10. # 7  07/01/2014  21115.00  21075.00
  11. # 8  08/01/2014  21120.00  21080.00
  12. # 9  09/01/2014  21115.00  21075.00
  13. # 10 10/01/2014  21110.00  21072.00
  14. # 11 11/01/2014  21113.33  21068.00
  15. # 12 12/01/2014  21116.67  21064.00
  16. # 13 13/01/2014  21120.00  21060.00
  17. # 14 14/01/2014  21110.00  21072.00
  18. # 15 15/01/2014  21110.00  21070.00
  19. # 16 16/01/2014  21120.00  21080.00
  20. # 17 17/01/2014  21110.00  21070.00
  21. # 18 18/01/2014  21110.00  21070.00
  22. # 19 19/01/2014  21110.00  21070.00
  23. # 20 20/01/2014  21110.00  21070.00

Data:

  1. vndusd_merged &lt;- structure(list(Date = structure(1:20, .Label = c(&quot;01/01/2014&quot;, 
  2. &quot;02/01/2014&quot;, &quot;03/01/2014&quot;, &quot;04/01/2014&quot;, &quot;05/01/2014&quot;, &quot;06/01/2014&quot;, 
  3. &quot;07/01/2014&quot;, &quot;08/01/2014&quot;, &quot;09/01/2014&quot;, &quot;10/01/2014&quot;, &quot;11/01/2014&quot;, 
  4. &quot;12/01/2014&quot;, &quot;13/01/2014&quot;, &quot;14/01/2014&quot;, &quot;15/01/2014&quot;, &quot;16/01/2014&quot;, 
  5. &quot;17/01/2014&quot;, &quot;18/01/2014&quot;, &quot;19/01/2014&quot;, &quot;20/01/2014&quot;), class = &quot;factor&quot;), 
  6.     Ask.Close = c(21115L, 21160L, 21115L, NA, NA, 21120L, 21115L, 
  7.     21120L, 21115L, 21110L, NA, NA, 21120L, 21110L, 21110L, 21120L, 
  8.     21110L, NA, NA, 21110L), Bid.Close = c(21075L, 21060L, 21075L, 
  9.     NA, NA, 21080L, 21075L, 21080L, 21075L, 21072L, NA, NA, 21060L, 
  10.     21072L, 21070L, 21080L, 21070L, NA, NA, 21070L)), class = &quot;data.frame&quot;, row.names = c(&quot;1&quot;, 
  11. &quot;2&quot;, &quot;3&quot;, &quot;4&quot;, &quot;5&quot;, &quot;6&quot;, &quot;7&quot;, &quot;8&quot;, &quot;9&quot;, &quot;10&quot;, &quot;11&quot;, &quot;12&quot;, &quot;13&quot;, 
  12. &quot;14&quot;, &quot;15&quot;, &quot;16&quot;, &quot;17&quot;, &quot;18&quot;, &quot;19&quot;, &quot;20&quot;))

答案2

得分: 0

以下代码执行了问题所要求的操作。

  1. vndusd_merged$Date <- as.Date(vndusd_merged$Date, "%d/%m/%Y")
  3. vndusd_merged[-1] <- lapply(vndusd_merged[-1], function(x){
  4.   i <- !is.na(x)
  5.   f <- approxfun(vndusd_merged$Date[i], x[i])
  6.   y <- f(vndusd_merged$Date)
  7.   y
  8. })
  10. vndusd_merged
  11. #         Date Ask.Close Bid.Close
  12. #1  2014-01-01  21115.00  21075.00
  13. #2  2014-01-02  21160.00  21060.00
  14. #3  2014-01-03  21115.00  21075.00
  15. #4  2014-01-04  21116.67  21076.67
  16. #5  2014-01-05  21118.33  21078.33
  17. #6  2014-01-06  21120.00  21080.00
  18. #7  2014-01-07  21115.00  21075.00
  19. #8  2014-01-08  21120.00  21080.00
  20. #9  2014-01-09  21115.00  21075.00
  21. #10 2014-01-10  21110.00  21072.00
  22. #11 2014-01-11  21113.33  21068.00
  23. #12 2014-01-12  21116.67  21064.00
  24. #13 2014-01-13  21120.00  21060.00
  25. #14 2014-01-14  21110.00  21072.00
  26. #15 2014-01-15  21110.00  21070.00
  27. #16 2014-01-16  21120.00  21080.00
  28. #17 2014-01-17  21110.00  21070.00
  29. #18 2014-01-18  21110.00  21070.00
  30. #19 2014-01-19  21110.00  21070.00
  31. #20 2014-01-20  21110.00  21070.00

如果要使用不等于 "Date" 的列名向量，可以使用上面的代码，但应用于不同的子数据框。

  1. column_name <- colnames(vndusd_merged)
  2. column_name <- column_name[column_name != "Date"]
  4. vndusd_merged[column_name] <- lapply(vndusd_merged[column_name], function(x){
  5.   #与上面的代码相同
  6. })
英文:

The following code does what the question asks for.

  1. vndusd_merged$Date &lt;- as.Date(vndusd_merged$Date, &quot;%d/%m/%Y&quot;)
  3. vndusd_merged[-1] &lt;- lapply(vndusd_merged[-1], function(x){
  4.   i &lt;- !is.na(x)
  5.   f &lt;- approxfun(vndusd_merged$Date[i], x[i])
  6.   y &lt;- f(vndusd_merged$Date)
  7.   y
  8. })
  10. vndusd_merged
  11. #         Date Ask.Close Bid.Close
  12. #1  2014-01-01  21115.00  21075.00
  13. #2  2014-01-02  21160.00  21060.00
  14. #3  2014-01-03  21115.00  21075.00
  15. #4  2014-01-04  21116.67  21076.67
  16. #5  2014-01-05  21118.33  21078.33
  17. #6  2014-01-06  21120.00  21080.00
  18. #7  2014-01-07  21115.00  21075.00
  19. #8  2014-01-08  21120.00  21080.00
  20. #9  2014-01-09  21115.00  21075.00
  21. #10 2014-01-10  21110.00  21072.00
  22. #11 2014-01-11  21113.33  21068.00
  23. #12 2014-01-12  21116.67  21064.00
  24. #13 2014-01-13  21120.00  21060.00
  25. #14 2014-01-14  21110.00  21072.00
  26. #15 2014-01-15  21110.00  21070.00
  27. #16 2014-01-16  21120.00  21080.00
  28. #17 2014-01-17  21110.00  21070.00
  29. #18 2014-01-18  21110.00  21070.00
  30. #19 2014-01-19  21110.00  21070.00
  31. #20 2014-01-20  21110.00  21070.00

If you want to use a vector of column names, in this case not equal to &quot;Date&quot;, use code above but applied to a different sub-dataframe.

  1. column_name &lt;- colnames(vndusd_merged)
  2. column_name &lt;- column_name[column_name != &quot;Date&quot;]
  4. vndusd_merged[column_name] &lt;- lapply(vndusd_merged[column_name], function(x){
  5.   #same code as above
  6. })

huangapple
  • 本文由 发表于 2020年1月6日 15:05:42
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