R 创建NA行的子集数据
我一直在处理这个大型数据集(19个变量,包含int、字符串和float的任意组合,包含完整的观察值和包含空变量的观察值)。我已经根据日期将它们分为不同的数据帧,并且得到了一些意想不到的结果。我迄今为止的工作:R 创建NA行的子集数据,r,R,我一直在处理这个大型数据集(19个变量,包含int、字符串和float的任意组合,包含完整的观察值和包含空变量的观察值)。我已经根据日期将它们分为不同的数据帧,并且得到了一些意想不到的结果。我迄今为止的工作: # reading in data; at this point there are no rows that are completely # full of na values Data <- read.csv("Data.csv", stringsAsFactors
# reading in data; at this point there are no rows that are completely
# full of na values
Data <- read.csv("Data.csv", stringsAsFactors = FALSE)
# removing data I don't want to look at; I'm sure this isn't the
# most efficient way to do this but it works
Data2 <- Data[!(Data$Event.Clearance.Group=="TRAFFIC RELATED CALLS") &
!(Data$Event.Clearance.Group=="FALSE ALARMS") &
!(Data$Event.Clearance.Group=="FALSE ALACAD") &
!(Data$Event.Clearance.Group=="HARBOR CALLS") &
!(Data$Event.Clearance.Group=="NULL"),]
# reformatting the date into new col to easily subset
Data2$Date <- as.Date(as.character(Data2$Event.Clearance.Date), "%m/%d/%Y")
# Subsetting Data into years; after I do this the subsets suddenly have
# tons of NA values. I do this for each year from 2011 - 2015
Data2011 <- Data2[Data2$Date >= as.Date("2011-01-01") &
Data2$Date <as.Date("2012-01-01"),]
#读取数据;此时,没有完全相同的行
#充满na值
Data您的Data2$Date是否有NA值?
结果如何
sum(is.na(Data2$Date >= as.Date("2011-01-01") &
Data2$Date <as.Date("2012-01-01")))
sum(is.na(Data2$Date>=截止日期(“2011-01-01”)&
Data2$Date您的Data2$Date是否有NA值?
结果如何
sum(is.na(Data2$Date >= as.Date("2011-01-01") &
Data2$Date <as.Date("2012-01-01")))
sum(is.na(Data2$Date>=截止日期(“2011-01-01”)&
Data2$Date可能会使用运行良好的myYearList,谢谢。显然,我只是用我的其他方法每次生成14198个空行……但我的问题仍然是,为什么会生成这些空行?可能会使用运行良好的myYearList,谢谢。显然,我只是每次使用我的另一个方法…我的问题仍然存在,为什么要生成这些空行?