我有一个很长的数据集我想扩大,我很好奇是否有一种方法可以使用R中的reshape2或tidyr包一步完成所有这些操作.
数据框df如下所示:
id type transactions amount
20 income 20 100
20 expense 25 95
30 income 50 300
30 expense 45 250
我想谈谈这个问题:
id income_transactions expense_transactions income_amount expense_amount
20 20 25 100 95
30 50 45 300 250
我知道我可以通过reshape2来获得部分路径,例如:
dcast(df, id ~ type, value.var="transactions")
但有没有办法一次性重塑整个df,同时解决"交易"和"金额"变量？理想情况下,新的更合适的列名称？
这是一个普遍公认的事实,R的基本重塑命令是快速而强大的,但具有悲惨的语法.因此,我已经编写了一个快速包装器,我将把它放到taRifx包的下一个版本中.然而,在我这样做之前,我想要求改进.
这是我的版本,来自@RichieCotton的更新:
# reshapeasy: Version of reshape with way, way better syntax
# Written with the help of the StackOverflow R community
# x is a data.frame to be reshaped
# direction is "wide" or "long"
# vars are the names of the (stubs of) the variables to be reshaped (if omitted, defaults to everything not in id or vary)
# id are the names of the variables that identify unique observations
# vary is the variable that …我正在努力使用reshape包寻找一种方法"强制转换"数据帧,但在"value.var"中有两个(或更多)值.
这是我想要实现的一个例子.
df <- data.frame( StudentID = c("x1", "x10", "x2",
"x3", "x4", "x5", "x6", "x7", "x8", "x9"),
StudentGender = c('F', 'M', 'F', 'M', 'F', 'M', 'F', 'M', 'M', 'M'),
ExamenYear = c('2007','2007','2007','2008','2008','2008','2008','2009','2009','2009'),
Exam = c('algebra', 'stats', 'bio', 'algebra', 'algebra', 'stats', 'stats', 'algebra', 'bio', 'bio'),
participated = c('no','yes','yes','yes','no','yes','yes','yes','yes','yes'),
passed = c('no','yes','yes','yes','no','yes','yes','yes','no','yes'),
stringsAsFactors = FALSE)
从df我可以创建以下数据帧:
tx <- ddply(df, c('ExamenYear','StudentGender'), summarize,
participated = sum(participated == "yes"),
passed = sum(passed == "yes"))
在重塑逻辑中,我有两个"值变量"参与并通过
我正在寻找在一个数据帧中组合以下信息的方法:
dcast(tx, formula = ExamenYear ~ StudentGender, value.var …