数据挖掘 - R中的数据框突变 - 吾爱随笔录

我有以下格式的数据框：
符号日期时间利润
$BANKNIFTY 4/1/2010 9:55:00 -1.18% <br>$ 银行财报 2010 年 4 月 1 日 12:30:00 -2.84%
$BANKNIFTY 4/1/2010 12:45:00 7.17% <br>$ 银行 5/1/2010 11:40:00 -7.11%
泽尔 26/6/2012 13:50:00 24.75%
泽尔 27/6/2012 15:15:00 -1.90%
泽尔 28/6/2012 9:45 :00 37.58%
泽尔 28/6/2012 14:55:00 23.95%
泽尔 29/6/2012 14:20:00 -4.65%
泽尔 29/6/2012 14:30:00 -6.01%
泽尔 29/6/ 2012 14:55:00 -12.23%
泽尔 29/6/2012 15:15:00 35.13%

我想要实现的是将该数据框转换为一个数据框，其中包含行名称的日期、列的符号名称以及每天的百分比利润总和。如下所示：

日期 BankNifty ZEEL
4/1/2010 3.15% 0 5/1/2010
-7.11% 0
26/6/2012 0 24.75%
27/6/2012 0 -1.90%
28/6/2012 0 61.53%
29/6/2012 0 12.24%

我怎样才能在 R 中实现这一点？dplyr突变或一些应用功能？

我是 R 编程的初学者。提前致谢。

R中的数据是

structure(list(Symbol = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L), .Label = c("BANKNIFTY", "ZEEL"), class = "factor"), 
    Date = structure(c(5L, 5L, 5L, 6L, 1L, 2L, 3L, 3L, 4L, 4L, 
    4L, 4L), .Label = c("26/6/2012", "27/6/2012", "28/6/2012", 
    "29/6/2012", "4/1/2010", "5/1/2010"), class = "factor"), 
    Time = structure(c(10L, 2L, 3L, 1L, 4L, 8L, 9L, 7L, 5L, 6L, 
    7L, 8L), .Label = c("11:40:00", "12:30:00", "12:45:00", "13:50:00", 
    "14:20:00", "14:30:00", "14:55:00", "15:15:00", "9:45:00", 
    "9:55:00"), class = "factor"), Profit = structure(c(1L, 4L, 
    12L, 7L, 9L, 2L, 11L, 8L, 5L, 6L, 3L, 10L), .Label = c("-1.18%", 
    "-1.90%", "-12.23%", "-2.84%", "-4.65%", "-6.01%", "-7.11%", 
    "23.95%", "24.75%", "35.13%", "37.58%", "7.17%"), class = "factor")), .Names = c("Symbol", 
"Date", "Time", "Profit"), class = "data.frame", row.names = c(NA, 
-12L))

require(data.table) data <- data.table(data) # Remove the percentage from your file and convert the field to numeric. data[, Profit := as.numeric(gsub("%", "", Profit))] data ## Symbol Date Time Profit ## 1: BANKNIFTY 4/1/2010 9:55:00 -1.18 ## 2: BANKNIFTY 4/1/2010 12:30:00 -2.84 ## 3: BANKNIFTY 4/1/2010 12:45:00 7.17 ## 4: BANKNIFTY 5/1/2010 11:40:00 -7.11 ## 5: ZEEL 26/6/2012 13:50:00 24.75 ## 6: ZEEL 27/6/2012 15:15:00 -1.90 ## 7: ZEEL 28/6/2012 9:45:00 37.58 ## 8: ZEEL 28/6/2012 14:55:00 23.95 ## 9: ZEEL 29/6/2012 14:20:00 -4.65 ## 10: ZEEL 29/6/2012 14:30:00 -6.01 ## 11: ZEEL 29/6/2012 14:55:00 -12.23 ## 12: ZEEL 29/6/2012 15:15:00 35.13 # Melt the data so that we can easily dcast afterwards. molten_data <- melt(data[, list(Symbol, Date, Profit)] # Create a summary by date and Symbol. dcast(molten_data, id = c("Symbol", "Date")), Date ~ variable + Symbol, fun = sum) ## Date Profit_BANKNIFTY Profit_ZEEL ## 1: 26/6/2012 0.00 24.75 ## 2: 27/6/2012 0.00 -1.90 ## 3: 28/6/2012 0.00 61.53 ## 4: 29/6/2012 0.00 12.24 ## 5: 4/1/2010 3.15 0.00 ## 6: 5/1/2010 -7.11 0.00