list 防止 unlist 删除 NULL 值
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Prevent unlist to drop NULL values
提问by nico
I have a vector of lists and I use unliston them. Some of the elements in the vectors are NULLand unlistseems to be dropping them.
我有一个列表向量，并unlist在它们上使用。向量中的一些元素正在NULL并且unlist似乎正在删除它们。
How can I prevent this?
我怎样才能防止这种情况？
Here's a simple (non) working example showing this unwanted featureof unlist
下面是一个简单的（非）工作表示本实例不需要的功能的unlist
a = c(list("p1"=2, "p2"=5),
list("p1"=3, "p2"=4),
list("p1"=NULL, "p2"=NULL),
list("p1"=4, "p2"=5))
unlist(a)
p1 p2 p1 p2 p1 p2
2 5 3 4 4 5
采纳答案by Fojtasek
The issue here is that you can't have NULLin the middle of a vector. For example:
这里的问题是你不能NULL在向量中间。例如：
> c(1,NULL,3)
[1] 1 3
You can have NA in the middle though. You could could convert it to character and then back to numeric, which automatically converts the NULL values to NA (with a warning):
不过，您可以在中间放置 NA。您可以将其转换为字符，然后再转换回数字，这会自动将 NULL 值转换为 NA（带有警告）：
> b <- as.numeric(as.character(a))
Warning message:
NAs introduced by coercion
then put the names back in, because they've been dropped by the previous operation:
然后把名字放回去，因为它们已经被上一个操作删除了：
> names(b) <- names(a)
> b
p1 p2 p1 p2 p1 p2 p1 p2
2 5 3 4 NA NA 4 5 `
回答by Marek
In this case (one level depth list) this should works too:
在这种情况下（一级深度列表）这也应该有效：
a[sapply(a, is.null)] <- NA
unlist(a)
# p1 p2 p1 p2 p1 p2 p1 p2
# 2 5 3 4 NA NA 4 5
回答by elmaroto10
If you are dealing with a long complex JSON with several levels you should give this a try:
如果您正在处理具有多个级别的长而复杂的 JSON，您应该尝试一下：
I extracted game log data from nba.com/stats web site. The problem is, some players have a NULL value for 3 point free throws (mostly centers) and jsonlite::fromJSON seems to handle NULL values very well:
我从 nba.com/stats 网站提取了游戏日志数据。问题是，有些球员的 3 分罚球（主要是中锋）有一个 NULL 值，而 jsonlite::fromJSON 似乎可以很好地处理 NULL 值：
#### Player game logs URL: one record per player per game played ####
gameLogsURL <- paste("http://stats.nba.com/stats/leaguegamelog?Counter=1000&Direction=DESC&LeagueID=00&PlayerOrTeam=P&Season=2016-17&SeasonType=Regular+Season&Sorter=PTS")
#### Import game logs data from JSON ####
# use jsonlite::fromJSON to handle NULL values
gameLogsData <- jsonlite::fromJSON(gameLogsURL, simplifyDataFrame = TRUE)
# Save into a data frame and add column names
gameLogs <- data.frame(gameLogsData$resultSets$rowSet)
colnames(gameLogs) <- gameLogsData$resultSets$headers[[1]]
回答by George Dontas
The correct way to indicate a missing value is NA (not NULL). Here is another version that is working:
指示缺失值的正确方法是 NA（非 NULL）。这是另一个正在运行的版本：
a = c(list("p1"=2, "p2"=5),
list("p1"=3, "p2"=4),
list("p1"=NA, "p2"=NA),
list("p1"=4, "p2"=5))
unlist(a)
p1 p2 p1 p2 p1 p2 p1 p2
2 5 3 4 NA NA 4 5
