必填结果

Question

我有一个CSV文件，大约有800列，不同的编号。数据和我正在计算每列的幅度和一些其他参数。但是当我在csv文件中写入数据时，它会附加在一个列中，我希望将数据列明智地附加到另一个文件中。

假设：以下是数据。

col_1       col_2       col_3    col_4       col_5                      
1.1612      0.3067    -1.1993    0.2182     -0.9918   
2.0096     -0.0519    -1.0422    0.0748      0.0259
1.6678      1.1963    -0.1755    0.0198     -0.2106
0.4608      0.676     -0.7721    0.6531      0.5783
0.5463      0.7111    -0.7782    0.4303     -0.3082
-0.1022     0.9064    -0.6317    0.5188     -1.2695
0.4211      0.5859     0.1846    0.1434     -0.4181
1.2848     -0.5249     1.1307   -0.5768      0.0336
0.7813      0.6989              -0.0885     -0.5295
0.4288      1.0056               0.2213    
            0.8469               0.9048

脚本：

i=1
for(i in 1:5){
  readfile <- read.csv("test.CSV" , header = FALSE,  skip = 1)[,i]
  readfile
  colnm <- na.omit(readfile)
  colnm
  arr_colmn <- array(colnm)
  arr_colmn
  no._of_rows <- nrow(arr_colmn)   ### For single column row count
  no._of_rows
##other calculation not mentioned
  AMP <-  abs(fft(arr_colmn,inverse = FALSE))
  YY <- data.frame(AMP) 
  write.table(YY, "test_1.csv", append = TRUE,col.names = TRUE, row.names = FALSE, sep = ",")
   i=i+1
}`

必填结果

Col_1_Result   col_2_Result      Col_3_Result............
8.3432          3.000             0.611
17.2494         14.42             0.8412
7.72650         15.76
.               . 
.               .
.               .
.               .

Answer 1

我真的不明白你如何生成输出表，你提供的代码似乎没有重现表;不幸的是，你的其他评论也没有真正帮助。

除此之外，我认为你想为不同长度的列计算某种形式的汇总统计数据。

在以下示例中，我为每列计算mean和sd，并将结果存储在dataframe中。请注意，for的每一列都不需要lapply循环，只需dataframe个函数。

# Your sample data
data <- structure(list(V1 = c(1.1612, 2.0096, 1.6678, 0.4608, 0.5463,
-0.1022, 0.4211, 1.2848, 0.7813, 0.4288, -0.3342, 0.2777, 0.8392,
-0.5539, -0.8286, -0.9506, -1.1383, -1.7395, -0.7492), V2 = c(0.3067,
-0.0519, 1.1963, 0.676, 0.7111, 0.9064, 0.5859, -0.5249, 0.6989,
1.0056, 0.8469, 1.1276, 2.3087, -0.8514, -1.1398, NA, NA, NA,
NA), V3 = c(-1.1993, -1.0422, -0.1755, -0.7721, -0.7782, -0.6317,
0.1846, 1.1307, -0.5127, -0.6622, 0.3677, 0.2151, -0.0458, -1.7883,
-0.9445, 0.5524, -0.9857, -0.9644, -1.6342), V4 = c(0.2182, 0.0748,
0.0198, 0.6531, 0.4303, 0.5188, 0.1434, -0.5768, -0.0885, 0.2213,
0.9048, -0.0305, -1.3046, -0.4242, 0.1053, 0.9766, -0.5783, 0.7462,
NA), V5 = c(-0.9918, 0.0259, -0.2106, 0.5783, -0.3082, -1.2695,
-0.4181, 0.0336, -0.5295, -0.415, 1.2634, 0.769, -0.1862, -0.7126,
-0.2716, -0.3479, 1.1002, NA, NA)), .Names = c("V1", "V2", "V3",
"V4", "V5"), class = "data.frame", row.names = c(NA, -19L))

# Calculate mean and sd for every column; ignore NA's
df  <- do.call(rbind.data.frame, lapply(d, function(x)
    c(mean(x, na.rm = TRUE), sd(x, na.rm = TRUE))));
colnames(df) <- c("mean", "sd");
df;
#    mean        sd
#1  0.1832684 1.0095877
#2  0.5201400 0.8748568
#3 -0.5098053 0.7594946
#4  0.1116500 0.5779139
#5 -0.1112118 0.6902565

# Write to file
write.csv(df, file = "output.csv", row.names = FALSE, quote = FALSE);

Answer 2

使用此方法，您可以从列中读取列数据，并将数据附加到新CSV的列中。

readfile <- read.csv("DATA.csv" , header = TRUE, check.names = FALSE)   # Read the file

    R <- nrow(readfile)  ##No. of Total Rows
    C <- ncol(readfile)  ##No. of Columns

    datalist <- NULL   # CReating a Null Dataframe
    i=1
    for (i in 1:C) {
      l <-na.omit(readfile[[i]])     # NO. of Rows Of ith Column
      Amp <- abs((array(l))    ###Any calculation: i have taken ABS
      combine_df <- data.frame(Amp)
      datalist[[i]] <- combine_df  ## Adding data to NULL df
      i=i+1
    }
    Data_Final_1 = do.call(data.frame,datalist)  ###Extracting the final Data  
    write.csv(Data_Final, "DATA_1.csv",row.names = FALSE, na = "")

在写入新的csv

必填结果

2 个答案: