【发布时间】:2016-12-15 18:05:55
【问题描述】:
我有一个名为“游戏”的值数据框,其中包含几列数字。原始的 csv 文件有一些缺失的值,当我读入它们时它们变成了 NA。我试图用行中位数(已经存储为数据框的列)替换这些 NA。我无法让原始 NA 从字符强制转换为数字。
我首先找到了缺失值的索引。
ng <- which(is.na(games), arr.ind = TRUE)
然后我尝试用“linemedian”列中的值替换 NA。
games[ng] <- games[ng[,1], "linemedian"]
games[ng]
[1] " -3.25" " 9.98" " -9.1" " -9.1" " 14.0" " -3.25" " 9.98" " -3.25" " 9.98" " 2.30" " 13.75" "-24.00" " 3.71" " 15.94" " 14.25" " -9.83" " 13.75" " -4.88"
用任意数字替换 NA 也不起作用。
games[is.na(games)] <- 0
[1] " 0.0" " 0.0" " 0" " 0" " 0" " 0.0" " 0.0" " 0.0" " 0.0" " 0.00" " 0.00" " 0.00" " 0" " 0" " 0.00" " 0.00" " 0.00" " 0.00"
我认为删除空格可能会改变结果,但事实并非如此。
games[ng] <- as.numeric(trimws(games[ng[,1], "linemedian"]))
[1] "-3.25" "9.98" "-9.1" "-9.1" "14" "-3.25" "9.98" "-3.25" "9.98" "2.3" "13.75" "-24" "3.71" "15.94" "14.25" "-9.83" "13.75" "-4.88"
其他无效的尝试:
games[ng] <- type.convert(games[ng]) # using type.convert()
games[, -c(1,2)] <- as.numeric(games[, -c(1,2)]) # first two columns are metadata
Error: (list) object cannot be coerced to type 'double'
games[, -c(1,2)] <- as.numeric(unlist(games[, -c(1,2)]))
games[ng] <- as.numeric(as.character(trimws(games[ng[,1], "linemedian"])))
# New Addition from Answer
games[, sapply(games, is.numeric)][ng] <- games[, sapply(games, is.numeric)][ng[,1], "linemedian"]
我确定我分配给 games[ng] 的值是一个数字。
games[ng[,1], "linemedian"]
[1] -3.25 9.98 -9.10 -9.10 14.00 -3.25 9.98 -3.25 9.98 2.30 13.75 -24.00 3.71 15.94 14.25 -9.83 13.75 -4.88
typeof(games[ng[,1], "linemedian"])
[1] "double"
我在 Stack Overflow 板上的任何地方,显而易见的答案应该是 games[is.na(games)]
如果你想复制,这里是完整的代码:
## Download Raw Files
download.file("http://www.thepredictiontracker.com/ncaa2016.csv",
"data/ncaa2016.csv")
download.file("http://www.thepredictiontracker.com/ncaapredictions.csv",
"data/ncaapredictions.csv")
## Create Training and Prediction Data Sets
games <- read.csv("data/ncaa2016.csv", header = TRUE, stringsAsFactors = FALSE,
colClasses=c(rep("character",2),rep("numeric",72)))
preds <- read.csv("data/ncaapredictions.csv", header = TRUE, stringsAsFactors = TRUE)
colnames(preds)[colnames(preds) == "linebillings"] <- "linebill"
colnames(preds)[colnames(preds) == "linebillings2"] <- "linebill2"
colnames(preds)[colnames(preds) == "home"] <- "Home"
colnames(preds)[colnames(preds) == "road"] <- "Road"
## Remove Columns with too many missing values
rm <- unique(c(names(games[, sapply(games, function(z) sum(is.na(z))) > 50]), # Games and predictions
names(preds[, sapply(preds, function(z) sum(is.na(z))) > 10]))) # with missing data
games <- games[, !(names(games) %in% rm)] # Remove games with no prediction data
preds <- preds[, !(names(preds) %in% rm)] # Remove predictions with no game data
## Replace NAs with Prediction Median
ng <- which(is.na(games), arr.ind = TRUE)
games[ng] <- games[ng[,1], "linemedian"]
另外,我不能发布整个 dput() 输出,但这里有一些数据集只是为了显示结构。
dput(head(games[1:6]))
structure(list(Home = c("Alabama", "Arizona", "Arkansas", "Arkansas St.",
"Auburn", "Boston College"), Road = c("USC", "BYU", "Louisiana Tech",
"Toledo", "Clemson", "Georgia Tech"), line = c("12", "-2", "24.5",
"4", "-8.5", "-3"), linesag = c(12.19, 0.97, 24.26, -2.07, -4.78,
-2.74), linepayne = c(12, -0.81, 12.53, -0.86, -10.72, -3.87),
linemassey = c(19.15, -2.1, 21.07, -8.68, -5.45, -6.76)), .Names = c("Home",
"Road", "line", "linesag", "linepayne", "linemassey"), row.names = c(NA,
6L), class = "data.frame")
最后,我在 x86_64-w64-mingw32 上运行 R 版本 3.2.1。
【问题讨论】:
-
您需要在
games的合适子集上发布调用dput的结果,以便人们可以看到数据结构是什么。 -
我认为我们都将该输出误解为表示
games中的值是字符。我会发布一些调试代码。
标签: r