R: from long to wide

While preparing data for Multiple Linear Regression, I have faced an interesting problem of conversion data from "long" format into "wide" format.

Input data format:

date	term	value
2012-01-01	term1	3
2012-01-01	term2	4
2012-01-01	term4	5
2012-01-01	term5	6
2012-01-01	term6	7
2012-01-02	term1	3
2012-01-02	term2	4
2012-01-02	term3	5
2012-01-02	term5	7
2012-01-02	term6	8
2012-01-03	term3	4
2012-01-03	term4	3

Desired output format:

date	term1	term2	term3	term4	term5	term6
2012-01-01	3	4	0	5	6	7
2012-01-02	3	4	5	0	7	8
2012-01-03	0	0	4	3	0	0

Instructions:
# first of all, let's import data from CSV file
> value_per_term <- read.csv("~/value_per_term.csv")


First with reshape function from base package:
# now, the tricky part - reshaping; let's review parameters one-by-one
# data=value_per_term: defines structure to work with

# timevar="term": defines column in long format whose values will serve as 

# column names in wide format; in our case its "term"

# idvar="date": defines grouping criteria - in our case this is date

# direction="wide": either "long" or "wide"; in our case its "wide"

> wide_by_reshape = reshape(data=value_per_term, timevar="term", idvar="date", direction="wide")

# replace NA with 0
> wide_by_reshape[is.na(wide_by_reshape)] <- 0

Let's redo the same with cast function from reshape package:

# import the package

> library("reshape")

# reshape with "cast" method

# data=value_per_term: defines structure to work with
# formula=date~term: row names are taken from column "date", 
# while column names are taken from column "term"
# value="value": column containing data to aggregate
# fun.aggregate=sum: name of the function to perform aggregation
# fill=0: defining filling in cases data is missing. NA was used in example above
> wide_by_cast = cast(data=clicks_per_keyword, formula=date~term, value="value", fun.aggregate=sum, fill=0)

Summary: though, both methods allow reshaping data, I see cast as more preferable and flexible.