我使用函数聚合来创建一个长格式的数据框架,但是同事需要在Excel中使用它。我发现很难转换成宽格式。我需要将列“变量”和“类型”分成几个列,每个列包含成员(额叶、顶叶和枕骨)和(α、β、伽马、三角洲和θ)。
dput(head(aggdata))
structure(list(Time = c(1, 2, 3, 4, 5, 6), Type = structure(c(1L,
1L, 1L, 1L, 1L, 1L), .Label = c("alpha", "beta", "gamma", "delta",
"theta"), class = c("ordered", "factor")), Group = structure(c(1L,
1L, 1L, 1L, 1L, 1L), .Label = c("C", "N"), class = "factor"),
variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Frontal",
"Parietal", "Occipital"), class = "factor"), Condition = c(1,
1, 1, 1, 1, 1), value = c(0.0947259533333333, 0.0489575420666667,
0.0686301660666667, 0.0754647909333333, 0.0708219834666667,
0.0644100006)), .Names = c("Time", "Type", "Group", "variable",
"Condition", "value"), row.names = c(NA, 6L), class = "data.frame")发布于 2017-06-07 09:15:33
您可能需要检查reshape2包,以及dcast和熔融函数。这里有一个很好的熔融数据集,你想要铸造它。
让我先修改一下你的样本数据,因为它不会给出几个变量来传播。
agg_data <- rbind(agg_data,head(agg_data,1))
agg_data$variable[7] <- "Parietal"
agg_data$value[7] <- 0.0686301660666667
agg_data
# Time Type Group variable Condition value
# 1 1 alpha C Frontal 1 0.09472595
# 2 2 alpha C Frontal 1 0.04895754
# 3 3 alpha C Frontal 1 0.06863017
# 4 4 alpha C Frontal 1 0.07546479
# 5 5 alpha C Frontal 1 0.07082198
# 6 6 alpha C Frontal 1 0.06441000
# 7 1 alpha C Parietal 1 0.06863017我觉得你想要的是:
dcast(agg_data, Time + Type + Group + Condition ~ variable)
# Time Type Group Condition Frontal Parietal
# 1 1 alpha C 1 0.09472595 0.06863017
# 2 2 alpha C 1 0.04895754 NA
# 3 3 alpha C 1 0.06863017 NA
# 4 4 alpha C 1 0.07546479 NA
# 5 5 alpha C 1 0.07082198 NA
# 6 6 alpha C 1 0.06441000 NA在左侧,您将您想要聚合的数据放在其中,在右侧,您将您要扩展的变量放在您要扩展的变量上,您也可以在右侧放置一个变量之和,以便在多个变量上进行扩展,例如:
dcast(agg_data, Time + Group + Condition ~ variable + Type)
# Time Group Condition Frontal_alpha Parietal_alpha
# 1 1 C 1 0.09472595 0.06863017
# 2 2 C 1 0.04895754 NA
# 3 3 C 1 0.06863017 NA
# 4 4 C 1 0.07546479 NA
# 5 5 C 1 0.07082198 NA
# 6 6 C 1 0.06441000 NAhttps://stackoverflow.com/questions/44407661
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