按生成 NA 的日期合并数据帧

Question

我正在学习 R，目前正在尝试填充缺少日期和 NA 值的数据框。

数据样本：

Date <- c("23-01-19", "24-01-19", "25-01-19",  "30-01-19", "31-01-19" )
Open <- c("69.849998", "69.440002", "69.540001", "70.32", "69.559998")
High <- c("69.849998", "69.440002", "69.540001", "70.32", "69.559998")
Low <- c("69.849998", "69.440002", "69.540001", "70.32", "69.559998")
Close <- c("69.849998", "69.440002", "69.540001", "70.32", "69.559998")
Adj_Close <- c("69.849998", "69.440002", "69.540001", "70.32", "69.559998")
Volume <- c("0", "0", "0", "0","0")

InvescoDf <- data.frame(Date, Open, High, Low, Close, Adj_Close, Volume)

我正在尝试：

library(tidyverse)
library(zoo)

df <- InvescoDf
df$Date <- as.Date(df$Date, "%d-%m-%y")                    # assign as Date
df$Date<-as.POSIXlt(df$Date,format="%Y-%m-%d")             # assign as POSIXlt
df1.zoo<-zoo(df[,-1],df[,1])                               # assign Date as index
df2.zoo<-zoo(,seq(start(df1.zoo),end(df1.zoo),by="day"))   # create data sequence
df2 <- merge(df1.zoo,df2.zoo, all=TRUE)                    # merge

Error : Warning message: In merge.zoo(df1.zoo, df2.zoo, all = TRUE) : Index vectors are of different classes: POSIXlt POSIXct

显然 seq() 创建了一个 POSIXct，但我只需要天数而不是小时数。我不太了解 zoo 对象，可能是有错误。请帮助并告诉我您需要什么进一步的信息。

编辑：

现在我正在尝试遍历多个 dfs，有人可以帮忙吗？

OssiamDf <- InvescoDf
new_list <- list(InvescoDf, OssiamDf)
new_list <- lapply(new_list, function(dat) {
# change all to date
  dat[[1]] <- as.Date(dat3[[1]], "%d-%m-%y")
# change the other variables to num 
  dat[-1] <- lapply(dat[-1],  function(x) as.numeric(as.character(x)))
# complete the dates?
  dat[[1]] <- lapply(dat[[1]], complete(dat[[1]], 
Date = seq(min(dat[[1]]), max(dat[[1]]), by = "day")))
  dat
})

我不知道如何把complete状态变成lapply 请帮助。

Answer 1

您可以将 Date 转换为日期对象，然后使用 tidyr 中的 complete 来填充缺失的日期。

library(dplyr)
library(tidyr)

InvescoDf %>%
  mutate(Date = as.Date(Date, "%d-%m-%y")) %>%
  complete(Date = seq(min(Date), max(Date), by = "day"))

#  Date        Open  High   Low Close Adj_Close Volume
#  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>  <int>
#1 2019-01-23  69.8  69.8  69.8  69.8      69.8      0
#2 2019-01-24  69.4  69.4  69.4  69.4      69.4      0
#3 2019-01-25  69.5  69.5  69.5  69.5      69.5      0
#4 2019-01-26  NA    NA    NA    NA        NA       NA
#5 2019-01-27  NA    NA    NA    NA        NA       NA
#6 2019-01-28  NA    NA    NA    NA        NA       NA
#7 2019-01-29  NA    NA    NA    NA        NA       NA
#8 2019-01-30  70.3  70.3  70.3  70.3      70.3      0
#9 2019-01-31  69.6  69.6  69.6  69.6      69.6      0

要对列表中的多个数据帧执行此操作，我们可以这样做

new_list <- lapply(new_list, function(dat) {
    dat[[1]] <- as.Date(dat[[1]], "%d-%m-%y")
    # change the other variables to num 
    dat[-1] <- lapply(dat[-1],  function(x) as.numeric(as.character(x)))
    # complete the dates?
    dat <- complete(dat, Date = seq(min(Date), max(Date), by = "day"))
    #OR
    #dat <- complete(dat, Date = seq(min(dat[[1]]), max(dat[[1]]), by = "day"))
    dat
 })

数据

InvescoDf <- type.convert(InvescoDf)

按生成 NA 的日期合并数据帧

Merge data frames by date generating NA

merge

r

date

zoo

posixlt