我有一個看起來像這樣的資料集：

Date,Open,High,Low,Close,Adjusted_close,Volume
2020-10-28,1384,1384,1384,1384,1384,0
2020-10-29,1297,1297,1297,1297,1297,0
2020-10-30,1283,1283,1283,1283,1283,0
2020-11-02,1284,1284,1284,1284,1284,0
2020-11-03,1263,1263,1263,1263,1263,0
2020-11-04,1224,1224,1224,1224,1224,0
2020-11-05,1194,1194,1194,1194,1194,0
2020-11-06,1196,1196,1196,1196,1196,0
2020-11-09,1207,1207,1207,1207,1207,0
2020-11-10,1200,1200,1200,1200,1200,0

我想填寫 10-31 和 11-1 的值，以包含前一個交易日 (10-30) 的值。這在 R 中如何輕松實作？我覺得圖書館（tidyr）似乎完全適合這張照片？

預期代表將是：

Date,Open,High,Low,Close,Adjusted_close,Volume
2020-10-28,1384,1384,1384,1384,1384,0
2020-10-29,1297,1297,1297,1297,1297,0
2020-10-30,1283,1283,1283,1283,1283,0
2020-10-31,1283,1283,1283,1283,1283,0
2020-11-01,1283,1283,1283,1283,1283,0
2020-11-02,1284,1284,1284,1284,1284,0
2020-11-03,1263,1263,1263,1263,1263,0
2020-11-04,1224,1224,1224,1224,1224,0
2020-11-05,1194,1194,1194,1194,1194,0
2020-11-06,1196,1196,1196,1196,1196,0
2020-11-07,1196,1196,1196,1196,1196,0
2020-11-08,1196,1196,1196,1196,1196,0
2020-11-09,1207,1207,1207,1207,1207,0
2020-11-10,1200,1200,1200,1200,1200,0

請求的 dput 輸出

structure(list(Date = c("2020-10-28", "2020-10-29", "2020-10-30", 
"2020-11-02", "2020-11-03", "2020-11-04", "2020-11-05", "2020-11-06", 
"2020-11-09", "2020-11-10"), Open = c(1384L, 1297L, 1283L, 1284L, 
1263L, 1224L, 1194L, 1196L, 1207L, 1200L), High = c(1384L, 1297L, 
1283L, 1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L), Low = c(1384L, 
1297L, 1283L, 1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L
), Close = c(1384L, 1297L, 1283L, 1284L, 1263L, 1224L, 1194L, 
1196L, 1207L, 1200L), Adjusted_close = c(1384L, 1297L, 1283L, 
1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L), Volume = c(0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(NA, 10L), class = "data.frame")

uj5u.com熱心網友回復：

第一個日期必須是日期格式

df$Date = as.Date(df$Date)

df %>% 
  full_join(data.frame(Date = seq(min(df$Date), max(df$Date), by = "days")),by = "Date") %>% 
  arrange(Date) %>% 
  fill(everything())

然后與僅包含資料庫中整個日期序列的資料進行連接，我們對其進行排序并使用填充函式來填充它們

uj5u.com熱心網友回復：

解決方案

這是中的一個解決方案tidyverse，它利用該tidyr::fill()函式來填充較早行的值：

library(tidyverse)


# ...
# Code to generate 'my_data'.
# ...


my_data %>%
  # Ensure 'Date' column is proper datatype.
  mutate(Date = as.Date(Date)) %>%
  # Link to full range of dates, with blank rows for missing dates.
  right_join(
    # A temporary dataset with the full range of 'Date's.
    tibble(Date = seq(from = min(.$Date), to = max(.$Date), by = "days")),
    by = "Date"
  ) %>%
  # Sort for filling: earlier above later.
  arrange(Date) %>%
  # Fill blank rows with values above.
  fill(everything(), .direction = "down")

結果

鑒于my_data像data.frame這里轉載

my_data <- structure(
  list(
    Date = c(
      "2020-10-28", "2020-10-29", "2020-10-30", "2020-11-02", "2020-11-03",
      "2020-11-04", "2020-11-05", "2020-11-06", "2020-11-09", "2020-11-10"
    ),
    Open = c(
      1384L, 1297L, 1283L, 1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L
    ),
    High = c(
      1384L, 1297L, 1283L, 1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L
    ),
    Low = c(
      1384L, 1297L, 1283L, 1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L
    ),
    Close = c(
      1384L, 1297L, 1283L, 1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L
    ),
    Adjusted_close = c(
      1384L, 1297L, 1283L, 1284L, 1263L, 1224L, 1194L, 1196L, 1207L, 1200L
    ),
    Volume = c(
      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
    )
  ),
  row.names = c(NA, 10L),
  class = "data.frame"
)

這個解決方案應該產生data.frame這樣的：

         Date Open High  Low Close Adjusted_close Volume
1  2020-10-28 1384 1384 1384  1384           1384      0
2  2020-10-29 1297 1297 1297  1297           1297      0
3  2020-10-30 1283 1283 1283  1283           1283      0
4  2020-10-31 1283 1283 1283  1283           1283      0
5  2020-11-01 1283 1283 1283  1283           1283      0
6  2020-11-02 1284 1284 1284  1284           1284      0
7  2020-11-03 1263 1263 1263  1263           1263      0
8  2020-11-04 1224 1224 1224  1224           1224      0
9  2020-11-05 1194 1194 1194  1194           1194      0
10 2020-11-06 1196 1196 1196  1196           1196      0
11 2020-11-07 1196 1196 1196  1196           1196      0
12 2020-11-08 1196 1196 1196  1196           1196      0
13 2020-11-09 1207 1207 1207  1207           1207      0
14 2020-11-10 1200 1200 1200  1200           1200      0

uj5u.com熱心網友回復：

1）使用（這也轉換為類）轉換為zoo類系列，然后將所有日期與. 使用填充缺失值，最后使用轉換回資料框。如果結果是動物園物件沒問題，則省略該部分。zread.zooDateDatezna.locffortify.zoofortify.zoo

library(zoo)

z <- read.zoo(dat)
out1 <- merge(z, zoo(, seq(start(z), end(z), "day"))) |> 
  na.locf() |>
  fortify.zoo(name = "Date")

# check - target is defined in Note at the end
identical(out1, transform(target, Date = as.Date(Date)))
## [1] TRUE

2）在這個替代方案中，我們使用以下管道。而不是使用merge.zoo，如上所述，這轉換為 ts 類并回傳以擴展日期。

轉換dat為zoo類，這也將索引轉換為Date類。
然后將其轉換為ts類。由于該類僅支持規則間隔的系列，因此轉換將用 NA 填充與缺失日期相對應的值。
na.locf 然后將填寫那些 NA。
用于fortify.zoo將其轉換回資料框。
由于tsclass 不支持 Date 索引，因此此時 Date 列只是數字，因此將它們轉換回Dateclass。

library(zoo)

out2 <- dat |> 
  read.zoo() |>
  as.ts() |>
  na.locf() |>
  fortify.zoo(name = "Date") |>
  transform(Date = as.Date(Date))

# check - target is defined in Note at the end    
identical(out2, transform(target, Date = as.Date(Date)))
## [1] TRUE

筆記

可重現形式的輸入dat和輸出target假定為：

Lines <- "Date,Open,High,Low,Close,Adjusted_close,Volume
2020-10-28,1384,1384,1384,1384,1384,0
2020-10-29,1297,1297,1297,1297,1297,0
2020-10-30,1283,1283,1283,1283,1283,0
2020-10-31,1283,1283,1283,1283,1283,0
2020-11-01,1283,1283,1283,1283,1283,0
2020-11-02,1284,1284,1284,1284,1284,0
2020-11-03,1263,1263,1263,1263,1263,0
2020-11-04,1224,1224,1224,1224,1224,0
2020-11-05,1194,1194,1194,1194,1194,0
2020-11-06,1196,1196,1196,1196,1196,0
2020-11-07,1196,1196,1196,1196,1196,0
2020-11-08,1196,1196,1196,1196,1196,0
2020-11-09,1207,1207,1207,1207,1207,0
2020-11-10,1200,1200,1200,1200,1200,0"
dat <- read.csv(text = Lines, strip.white = TRUE)

Lines2 <- "Date,Open,High,Low,Close,Adjusted_close,Volume
2020-10-28,1384,1384,1384,1384,1384,0
2020-10-29,1297,1297,1297,1297,1297,0
2020-10-30,1283,1283,1283,1283,1283,0
2020-10-31,1283,1283,1283,1283,1283,0
2020-11-01,1283,1283,1283,1283,1283,0
2020-11-02,1284,1284,1284,1284,1284,0
2020-11-03,1263,1263,1263,1263,1263,0
2020-11-04,1224,1224,1224,1224,1224,0
2020-11-05,1194,1194,1194,1194,1194,0
2020-11-06,1196,1196,1196,1196,1196,0
2020-11-07,1196,1196,1196,1196,1196,0
2020-11-08,1196,1196,1196,1196,1196,0
2020-11-09,1207,1207,1207,1207,1207,0
2020-11-10,1200,1200,1200,1200,1200,0"
target <- read.csv(text = Lines2, strip.white = TRUE)

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標籤：r 数据框数据集

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根據R中的前一天填寫值

解決方案

結果

筆記