我有一个大数据集,下面是一个示例:
df <- data.frame(stringsAsFactors=FALSE,
Date = c("2015-10-26", "2015-10-26", "2015-10-26", "2015-10-26",
"2015-10-27", "2015-10-27", "2015-10-27"),
Ticker = c("ANZ", "CBA", "NAB", "WBC", "ANZ", "CBA", "WBC"),
Open = c(29.11, 77.89, 32.69, 31.87, 29.05, 77.61, 31.84),
High = c(29.17, 77.93, 32.76, 31.92, 29.08, 78.1, 31.95),
Low = c(28.89, 77.37, 32.42, 31.71, 28.9, 77.54, 31.65),
Close = c(28.9, 77.5, 32.42, 31.84, 28.94, 77.74, 31.77),
Volume = c(6350170L, 2251288L, 3804239L, 5597684L, 5925519L, 2424679L,
5448863L)
)
Date Ticker Open High Low Close Volume
有关如何执行此操作的任何想法?
我已经尝试
gather
+ spread
失败了 最佳答案
tidyr::complete
和tidyr::fill
专门针对这种情况而构建:
library(tidyverse)
df %>%
complete(Date,Ticker) %>%
arrange(Ticker) %>%
fill(names(.)) %>%
arrange(Date)
#
# # A tibble: 8 x 7
# Date Ticker Open High Low Close Volume
# <chr> <chr> <dbl> <dbl> <dbl> <dbl> <int>
# 1 2015-10-26 ANZ 29.11 29.17 28.89 28.90 6350170
# 2 2015-10-26 CBA 77.89 77.93 77.37 77.50 2251288
# 3 2015-10-26 NAB 32.69 32.76 32.42 32.42 3804239
# 4 2015-10-26 WBC 31.87 31.92 31.71 31.84 5597684
# 5 2015-10-27 ANZ 29.05 29.08 28.90 28.94 5925519
# 6 2015-10-27 CBA 77.61 78.10 77.54 77.74 2424679
# 7 2015-10-27 NAB 32.69 32.76 32.42 32.42 3804239
# 8 2015-10-27 WBC 31.84 31.95 31.65 31.77 5448863
关于r - 填补缺失的行,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/49308251/