将年度插值到每月，然后将长数据更改为宽数据，R

Question

我有一个大的 csv 数据文件，数据示例如下。

name                  year            value
China                 1997            481970
Japan                 1997            8491480
Germany               1997            4678022
China                 1998            589759
Japan                 1998            7912546
Germany               1998            5426582

经过几次尝试都没有成功，我想将我的数据插入到每月，然后将数据的格式更改为如下示例，

date             China       Japan        Germany       
1997-01-31       40164.17    707623.33    389835.17
1997-02-28       80328.33    1415246.67   779670.33
1997-03-30       1204925     2122870      1169505.50
1997-04-30       160656.67   2830493.33   1559340.67  
1997-05-31       200820.83   3538116.67   1949175.83
    .               .           .              .
    .               .           .              .
    .               .           .              .
1997-12-31       481970       8491480      4678022

1998-01-31       49146.58     659378.83    452215.17
1998-02-28       98293.17     1318757.67   904430.33
1998-03-30       147439.75    1978136.5    1356645.5 
1998-04-30       196586.33    2637515.33   1808860.67
1998-05-31       245732.97    3296894.17   2261075.83
    .               .           .              .
    .               .           .              .
    .               .           .              .
1998-12-31        589759      7912546      5426582

有人建议How to pivot a dataframe，尽管事实证明我很难达到预期的结果。可能我python没那么好。

我想用 R 来做。 想法？

Answer 1

假设在最后的注释中可重现地显示输入，将其转换为动物园对象z，通过指定split=，它也会同时将其转换为宽格式。然后使用merge 扩展它并使用na.approx 使用线性插值。或者将na.approx 替换为na.spline。最后将时间索引转换为Date类。结果是一个动物园对象m。如果您需要数据框，请使用fortify.zoo(m)。

library(zoo)

z <- read.zoo(DF, split = 1, index = 2, FUN = as.numeric)

m <- na.approx(merge(z, zoo(, c(kronecker(time(z), 0:11/12, "+")))))
time(m) <- as.Date(as.yearmon(time(m)), frac = 1)
m

给予：

              China Germany   Japan
1997-01-31 481970.0 4678022 8491480
1997-02-28 490952.4 4740402 8443236
1997-03-31 499934.8 4802782 8394991
1997-04-30 508917.2 4865162 8346747
1997-05-31 517899.7 4927542 8298502
1997-06-30 526882.1 4989922 8250257
1997-07-31 535864.5 5052302 8202013
1997-08-31 544846.9 5114682 8153769
1997-09-30 553829.3 5177062 8105524
1997-10-31 562811.8 5239442 8057280
1997-11-30 571794.2 5301822 8009035
1997-12-31 580776.6 5364202 7960790
1998-01-31 589759.0 5426582 7912546

注意

Lines <- "name                  year            value
China                 1997            481970
Japan                 1997            8491480
Germany               1997            4678022
China                 1998            589759
Japan                 1998            7912546
Germany               1998            5426582"
DF <- read.table(text = Lines, header = TRUE, as.is = TRUE)

Answer 2

使用data.table的选项：

DT[, date := as.IDate(paste0(year, "-12-31"))][,
    c("y0", "y1") := .(value, shift(value, -1L, fill=value[.N])), name]

longDT <- DT[, {
    eom <- seq(min(date)+1L, max(date)+1L, by="1 month") - 1L
    v <- unlist(mapply(function(a, d) a + (0:11) * d, y0, (y1 - y0)/12, SIMPLIFY=FALSE))
    .(eom, v=v[seq_along(eom)])
}, name]

dcast(longDT, eom ~ name, sum, value.var="v")

输出：

           eom     China   Germany     Japan
 1: 1996-12-31  40164.17  389835.2  707623.3
 2: 1997-01-31  76981.32  747184.1 1356278.1
 3: 1997-02-28 113798.48 1104533.0 2004932.8
 4: 1997-03-31 150615.63 1461881.9 2653587.5
 5: 1997-04-30 187432.78 1819230.8 3302242.2
 6: 1997-05-31 224249.93 2176579.7 3950896.9
 7: 1997-06-30 261067.09 2533928.6 4599551.7
 8: 1997-07-31 297884.24 2891277.5 5248206.4
 9: 1997-08-31 334701.39 3248626.4 5896861.1
10: 1997-09-30 371518.54 3605975.3 6545515.8
11: 1997-10-31 408335.70 3963324.2 7194170.6
12: 1997-11-30 445152.85 4320673.1 7842825.3
13: 1997-12-31 481970.00 4678022.0 8491480.0
14: 1998-01-31 490952.42 4740402.0 8443235.5
15: 1998-02-28 499934.83 4802782.0 8394991.0
16: 1998-03-31 508917.25 4865162.0 8346746.5
17: 1998-04-30 517899.67 4927542.0 8298502.0
18: 1998-05-31 526882.08 4989922.0 8250257.5
19: 1998-06-30 535864.50 5052302.0 8202013.0
20: 1998-07-31 544846.92 5114682.0 8153768.5
21: 1998-08-31 553829.33 5177062.0 8105524.0
22: 1998-09-30 562811.75 5239442.0 8057279.5
23: 1998-10-31 571794.17 5301822.0 8009035.0
24: 1998-11-30 580776.58 5364202.0 7960790.5
25: 1998-12-31 589759.00 5426582.0 7912546.0
           eom     China   Germany     Japan

数据：

library(data.table)
DT <- fread("name     year            value
China                 1996            40164.17
Japan                 1996            707623.33
Germany               1996            389835.17
China                 1997            481970
Japan                 1997            8491480
Germany               1997            4678022
China                 1998            589759
Japan                 1998            7912546
Germany               1998            5426582")

我冒昧地添加了 1996 年的数据。