我的目标和背景
我在R中有一个数据框架，我想使用reshape2库熔化。有两个原因。
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我想使用ggplot在条形图中绘制每个用户对每个问题的得分。
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我想把这些数据放入Excel中，这样我就可以看到，每个用户，他们的情绪，得分，动机，态度等混合。我的意图是使用melt，然后cast将数据转换为宽格式，以便于Excel导入。
当我尝试运行melt时，我得到一个警告，并最终在我得到的熔融数据帧中得到NAs。
Warning messages:
1: In `[<-.factor`(`*tmp*`, ri, value = c(0.148024, 0.244452, -0.00421, :
invalid factor level, NAs generated
2: In `[<-.factor`(`*tmp*`, ri, value = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, :
invalid factor level, NAs generated
我最终在我的结果融化的数据框架中有大量的NAs。我想这是因为我在同一列中同时使用了字符和数字。
<标题>我的问题结果我有两个问题。
问题1:在R中是否有解决这个问题的方法?
问题2:我是否有更好的方法来构建我的数据来避免这个问题?
<标题> 代码这是我创建数据帧的代码。
words <- data.frame(read.delim("sentiments-test-subset-no-text.txt", header=FALSE))
names(words) <- c("level", "question", "user", "sentiment", "score", "mixed")
words$user <- as.factor(words$user)
words.m <- melt(words, id.vars=c("user", "level"), measure.vars=c("sentiment", "score", "mixed"))
我对重塑和融化很陌生，但我认为这就是我想要的最后一行。
<标题> 数据人类可读格式的数据是这样的。
experimental motivated 1 positive 0.148024 0
experimental motivated 2 positive 0.244452 0
experimental motivated 3 negative -0.004210 0
experimental motivated 4 unknown 0.000000 0
experimental attitudeBefore 1 negative -0.241500 0
experimental attitudeBefore 2 neutral 0.000000 0
experimental attitudeBefore 3 neutral 0.000000 0
experimental attitudeBefore 4 unknown 0.000000 0
dput如下。
structure(list(level = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), .Label = "experimental", class = "factor"), question = structure(c(2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L), .Label = c("attitudeBefore", "motivated"
), class = "factor"), user = structure(c(1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L), .Label = c("1", "2", "3", "4"), class = "factor"),
sentiment = structure(c(3L, 3L, 1L, 4L, 1L, 2L, 2L, 4L), .Label = c("negative",
"neutral", "positive", "unknown"), class = "factor"), score = c(0.148024,
0.244452, -0.00421, 0, -0.2415, 0, 0, 0), mixed = c(0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("level", "question",
"user", "sentiment", "score", "mixed"), row.names = c(NA, -8L
), class = "data.frame")
看起来您可能只是使用了错误的库。reshape和reshape2不是一回事。
library(reshape2)
words.m <- melt(words, id.vars=c("user", "level"), measure.vars=c("sentiment", "score", "mixed"))
# no problem
detach(package:reshape2)
# using reshape instead of reshape2
library(reshape)
words.m <- melt(words, id.vars=c("user", "level"), measure.vars=c("sentiment", "score", "mixed"))
# Warning messages:
# 1: In `[<-.factor`(`*tmp*`, ri, value = c(3L, 3L, 1L, 4L, 1L, 2L, 2L, :
# invalid factor level, NAs generated
# 2: In `[<-.factor`(`*tmp*`, ri, value = c(3L, 3L, 1L, 4L, 1L, 2L, 2L, :
# invalid factor level, NAs generated
如果reshape2在您的系统中不可用，您可以从CRAN
install.packages("reshape2")