所以我的数据集非常糟糕,不允许更改。我想选择“ Draw_CashFlow”列,并在其自己的列中仅添加某些值。另外,我需要将变量全部设置为一列(句号)(如果可以的话,应整整排成Tidy)。
在下面的数据集中,我们有一列(Draw_CashFlow),该列以所讨论的变量开头,后跟ID列表,然后对下一个变量重复。有些变量可能具有NA条目。
structure(list(Draw_CashFlow = c("Principal", "R01",
"R02", "R03", "Workout Recovery Principal",
"Prepaid Principal", "R01", "R02", "R03",
"Interest", "R01", "R02"), `PERIOD 1` = c(NA,
834659.51, 85800.18, 27540.31, NA, NA, 366627.74, 0, 0, NA, 317521.73,
29175.1), `PERIOD 2` = c(NA, 834659.51, 85800.18, 27540.31, NA,
NA, 306125.98, 0, 0, NA, 302810.49, 28067.8), `PERIOD 3` = c(NA,
834659.51, 85800.18, 27540.31, NA, NA, 269970.12, 0, 0, NA, 298529.92,
27901.36), `PERIOD 4` = c(NA, 834659.51, 85800.18, 27540.31,
NA, NA, 307049.06, 0, 0, NA, 293821.89, 27724.4)), row.names = c(NA,
-12L), class = c("tbl_df", "tbl", "data.frame"))
现在它是所需变量的有限列表(委托人,锻炼恢复委托人,预付委托人和利息),因此我尝试制作一个循环,在该循环中查看其是否存在然后收集,但这是不正确的。
将变量与Draw_CashFlow分开设置后,我希望它看起来像这样(前四行,忽略变量缩写)。
ID Period Principal Wrk_Reco_Principal Prepaid_Principal Interest
R01 1 834659.51 NA 366627.74 317521.73
R02 1 85800.18 NA 0.00 29175.10
R03 1 27540.31 NA 0.00 NA
R01 2 834659.51 NA 306125.98 302810.49
注意:Wrl_Reco_Principal是NA,因为此Draw_CashFlow中没有此变量的ID。请记住,它应该可以抵抗任何数量的ID,但是Draw_CashFlow列中的变量名将始终相同。
答案 0 :(得分:1)
这是一种假设以R
开头的Draw_CashFlow值是ID号的方法。如果这种方法无法解决问题,则可能需要其他方法(例如!Draw_CashFlow %in% LIST_OF_VARIABLES
)。
df %>%
# create separate columns for ID and Variable
mutate(ID = if_else(Draw_CashFlow %>% str_starts("R"),
Draw_CashFlow, NA_character_),
Variable = if_else(!Draw_CashFlow %>% str_starts("R"),
Draw_CashFlow, NA_character_)) %>%
fill(Variable) %>% # Fill down Variable in NA rows from above
select(-Draw_CashFlow) %>%
gather(Period, value, -c(ID, Variable)) %>% # Gather into long form
drop_na() %>%
spread(Variable, value, fill = 0) %>% # Spread based on Variable
mutate(Period = parse_number(Period))
# A tibble: 12 x 5
ID Period Interest `Prepaid Principal` Principal
<chr> <dbl> <dbl> <dbl> <dbl>
1 R01 1 317522. 366628. 834660.
2 R01 2 302810. 306126. 834660.
3 R01 3 298530. 269970. 834660.
4 R01 4 293822. 307049. 834660.
5 R02 1 29175. 0 85800.
6 R02 2 28068. 0 85800.
7 R02 3 27901. 0 85800.
8 R02 4 27724. 0 85800.
9 R03 1 0 0 27540.
10 R03 2 0 0 27540.
11 R03 3 0 0 27540.
12 R03 4 0 0 27540.