Q:

Data frame mutation in R

I have a data frame of the following format:
Symbol  Date    Time    Profit
$BANKNIFTY 4/1/2010 9:55:00 -1.18%
<br>$BANKNIFTY   4/1/2010    12:30:00    -2.84%
$BANKNIFTY 4/1/2010 12:45:00 7.17%
<br>$BANKNIFTY   5/1/2010    11:40:00    -7.11%
ZEEL    26/6/2012   13:50:00    24.75%
ZEEL    27/6/2012   15:15:00    -1.90%
ZEEL    28/6/2012   9:45:00 37.58%
ZEEL    28/6/2012   14:55:00    23.95%
ZEEL    29/6/2012   14:20:00    -4.65%
ZEEL    29/6/2012   14:30:00    -6.01%
ZEEL    29/6/2012   14:55:00    -12.23%
ZEEL    29/6/2012   15:15:00    35.13%
What I'd like to achieve is convert that data frame into a data frame which has dates for row names, symbol names for columns and sum of percentage profit for each day. Like in the following:
Date    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%
How can I achieve that in R? dplyr mutation or some apply function?
I'm a beginner in R programming. 
Thanks in advance.
The data in R is
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))

A:

The fastest way would be,
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

