我试图建立一个数据框架，显示每天所有交易的高潮(不使用for循环)

Question

对于每一天，我希望看到当天发生的所有事务的最终结果(使用As_Of_Dt作为当天的指标)。例如，在第一天(1/1/22)，只有一个交易，因此期望看到As_Of_Dt的一行。第二天(2022年1月2日)，有两个交易，所以预计会看到As_Of_Dt的三个交易(来自1/2/22的两个交易，加上来自1/1/22的一个交易)，等等，在未来的所有日子里。

下面是一个数据集的例子，我能够使用for循环来做到这一点，但是我的真实数据集要大得多，我正在寻找一个更快的解决方案(可能使用apply家族?)

df <- data.frame(TradeDate = c("2022-01-01","2022-01-02","2022-01-02", "2022-01-03","2022-01-04"),
Ticker = c("AAPL", "AMZN", "META", "AAPL","TSLA"),
Type = c("Buy", "Buy", "Buy", "Buy","Buy"),
Shares = c(10, 12, 5, 15, 20))
df1 <- df[0, ]
dtStart <- as_date("2022-01-01")
dtEnd <- as_date("2022-01-04")
dtRng <- interval(dtStart, dtEnd) %/% days(1) + 1

for(i in 1:dtRng){
df2 <- df %>%
filter(TradeDate <= (dtStart + i - 1)) %>%
mutate(As_Of_Dt = as_date(dtStart) + i - 1)
df1 <- bind_rows(df1, df2)
}

<表类>TradeDate股票型股票As_Of_Dttbody><<tr>2022-01-01apple买102022-01-012022-01-01apple买102022-01-022022-01-02amazon买122022-01-022022-01-02元买52022-01-022022-01-01apple买102022-01-032022-01-02amazon买122022-01-032022-01-02元买52022-01-032022-01-03apple买152022-01-032022-01-01apple买102022-01-042022-01-02amazon买122022-01-042022-01-02元买52022-01-042022-01-03apple买152022-01-042022-01-04厂商买202022-01-04

我希望这比您的循环更有效，但不如非相等连接有效。

library(dplyr)
df %>%
distinct(as_of = TradeDate) %>%
left_join(df, by = character()) %>%
filter(TradeDate <= as_of)

或者使用dplyr的开发版本，该版本引入了非对等连接

devtools::install_github("tidyverse/dplyr")
df %>% 
distinct(as_of = TradeDate) %>%
left_join(df, join_by(as_of >= TradeDate))

结果

as_of  TradeDate Ticker Type Shares
1  2022-01-01 2022-01-01   AAPL  Buy     10
2  2022-01-02 2022-01-01   AAPL  Buy     10
3  2022-01-02 2022-01-02   AMZN  Buy     12
4  2022-01-02 2022-01-02   META  Buy      5
5  2022-01-03 2022-01-01   AAPL  Buy     10
6  2022-01-03 2022-01-02   AMZN  Buy     12
7  2022-01-03 2022-01-02   META  Buy      5
8  2022-01-03 2022-01-03   AAPL  Buy     15
9  2022-01-04 2022-01-01   AAPL  Buy     10
10 2022-01-04 2022-01-02   AMZN  Buy     12
11 2022-01-04 2022-01-02   META  Buy      5
12 2022-01-04 2022-01-03   AAPL  Buy     15
13 2022-01-04 2022-01-04   TSLA  Buy     20