我有一个tsibble矩阵，它每天从传入的数据中增长 32 行，我只想在我的绘图函数中绘制过去 5 天，这需要我对底部行的 (32*5) 160 行进行子集化。随着新的每日数据的出现，每行的日期每 32 行更改一次。
例如
library(tsibble)
library(lubridate)
df <- data.frame(ticker = c("UST10Y", "UST2Y", "AAPL", "SPX", "BNO"),
buy_price = c(62.00, 68.00, 37.00, 55.00, 41.00),
sale_price = c(64.00, 71.00, 42.00, 60.00, 45.00),
close_price = c(63.00, 70.00, 38.00, 56.00, 43.00),
date = mdy(c("April 29th, 2021", "April 29th, 2021", "April 29th, 2021", "April 29th, 2021", "April 29th, 2021")))
df2 <- data.frame(ticker = c("UST10Y", "UST2Y", "AAPL", "SPX", "BNO"),
buy_price = c(63.00, 69.00, 38.00, 53.00, 44.00),
sale_price = c(66.00, 77.00, 47.00, 63.00, 48.00),
close_price = c(65.00, 74.00, 39.00, 55.00, 45.00),
date = mdy(c("April 30th, 2021", "April 30th, 2021", "April 30th, 2021", "April 30th, 2021", "April 30th, 2021")))
df3 <- data.frame(ticker = c("UST10Y", "UST2Y", "AAPL", "SPX", "BNO"),
buy_price = c(63.00, 69.00, 38.00, 53.00, 44.00),
sale_price = c(66.00, 77.00, 47.00, 63.00, 48.00),
close_price = c(65.00, 74.00, 39.00, 55.00, 45.00),
date = mdy(c("May 1st, 2021", "May 1st, 2021", "May 1st, 2021", "May 1st, 2021", "May 1st, 2021")))
final_df <- rbind(df,df2, df3)
as_tsibble(final_df, index = date, key = ticker, regular = T)
我只能用函数检索最后 5 行
final_df %>%
slice_tail(n = 5)
tail(final_df, 5)
虽然我应该让n = 6我得到这个错误。
Error: Can't obtain the interval due to the mismatched index class.
i Please see `vignette("FAQ")` for details.
关于如何解决这个问题的任何见解或想法？
OG数据
rr_master_tsibble_rep <-
structure(
list(
DATE = structure(
c(
18751,
18752,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18751,
18750,
18751,
18750,
18751,
18750,
18751,
18750,
18751,
18750,
18751,
18750,
18751,
18750,
18751,
18750,
18751
),
class = "Date"
),
TICKER = c(
"AAPL ",
"AAPL ",
"AMZN ",
"CAD/USD ",
"COMPQ ",
"COPPER ",
"DAX ",
"EUR/USD ",
"FB ",
"GBP/USD ",
"GOLD ",
"GOOGL ",
"MSFT ",
"NATGAS ",
"NFLX ",
"NIKK ",
"NYXBT ",
"RUT ",
"SILVER ",
"SPX ",
"SSEC ",
"TSLA ",
"USD ",
"USD/CHF ",
"USD/JPY ",
"UST10Y ",
"UST10Y ",
"UST2Y ",
"UST2Y ",
"VIX ",
"VIX ",
"WTIC ",
"WTIC ",
"XLE ",
"XLE ",
"XLF ",
"XLF ",
"XLK ",
"XLK ",
"XLU ",
"XLU "
),
BUY.TRADE = c(
131,
127,
3335,
0.79,
13801,
4.26,
15106,
1.198,
310,
1.38,
1753,
2310,
248,
2.72,
483,
28431,
50209,
2227,
25.75,
4140,
3407,
657,
90.3,
0.9,
107.45,
1.71,
1.72,
0.19,
0.18,
15.74,
15.8,
62.04,
62.2,
46.73,
46.75,
35.03,
35.22,
139.22,
138.45,
65.24,
65.29
),
SELL.TRADE = c(
136,
137,
3521,
0.82,
14204,
4.62,
15463,
1.216,
334,
1.401,
1797,
2407,
264,
3.06,
520,
29840,
60982,
2339,
27.09,
4229,
3498,
745,
91.43,
0.92,
109.74,
1.57,
1.56,
0.15,
0.15,
19.12,
18.98,
65.16,
65.7,
50.99,
51.91,
36.9,
37.01,
144.08,
144.46,
67.88,
67.45
),
PREV.CLOSE = c(
132,
127,
3386,
0.81,
13895,
4.53,
15236,
1.206,
322,
1.391,
1791,
2343,
251,
2.97,
509,
28812,
58035,
2277,
26.96,
4192,
3446,
684,
90.93,
0.91,
109.07,
1.65,
1.63,
0.16,
0.16,
18.61,
18.31,
63.58,
64.49,
49.39,
50.75,
36.26,
36.44,
139.7,
139.31,
66.72,
66.71
),
TREND = structure(
c(
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
1L,
2L,
2L,
2L,
1L,
2L,
2L,
2L,
2L,
2L,
1L,
1L,
1L,
1L,
2L,
2L,
2L,
2L,
2L,
1L,
1L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
3L,
3L
),
.Label = c("BEARISH", "BULLISH",
"NEUTRAL"),
class = "factor"
)
),
row.names = c(NA,-41L),
key = structure(
list(
TICKER = c(
"AAPL ",
"AMZN ",
"CAD/USD ",
"COMPQ ",
"COPPER ",
"DAX ",
"EUR/USD ",
"FB ",
"GBP/USD ",
"GOLD ",
"GOOGL ",
"MSFT ",
"NATGAS ",
"NFLX ",
"NIKK ",
"NYXBT ",
"RUT ",
"SILVER ",
"SPX ",
"SSEC ",
"TSLA ",
"USD ",
"USD/CHF ",
"USD/JPY ",
"UST10Y ",
"UST2Y ",
"VIX ",
"WTIC ",
"XLE ",
"XLF ",
"XLK ",
"XLU "
),
.rows = structure(
list(
1:2,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L,
16L,
17L,
18L,
19L,
20L,
21L,
22L,
23L,
24L,
25L,
26:27,
28:29,
30:31,
32:33,
34:35,
36:37,
38:39,
40:41
),
ptype = integer(0),
class = c("vctrs_list_of",
"vctrs_vctr", "list")
)
),
row.names = c(NA, 32L),
class = c("tbl_df",
"tbl", "data.frame"),
.drop = TRUE
),
index = structure("DATE", ordered = TRUE),
index2 = "DATE",
interval = structure(
list(
year = 0,
quarter = 0,
month = 0,
week = 0,
day = 1,
hour = 0,
minute = 0,
second = 0,
millisecond = 0,
microsecond = 0,
nanosecond = 0,
unit = 0
),
.regular = TRUE,
class = c("interval",
"vctrs_rcrd", "vctrs_vctr")
),
class = c("tbl_ts", "tbl_df", "tbl",
"data.frame"))
所以日期是这样分组的，而不是按股票交替和分组。