r - 不带组的data.table线性内插NA值

Question

我想在不带组的data.table中填充一些NA值。请考虑以下data.table提取物，该数据代表时间和距离：

library(data.table)
df <- data.frame(time = seq(7173, 7195, 1), dist = c(31091.33, NA, 31100.00, 31103.27, NA, NA, NA, NA, 31124.98, NA,31132.81, NA, NA, NA, NA, 31154.19, NA, 31161.47, NA, NA, NA, NA, 31182.97))
DT<- data.table(df)

我想要在DT data.table中，使用取决于之前/之后的非NA值的函数来填充NA值。例如，在j中编写一个函数来替换每条指令

DT[2, dist := (31091.33 + (31100-31091.33) / 2)]

然后

DT[5:8, dist := (31103.27 + "something" * (31124.98 - 31103.27) / 5)]

等等...

Answer 1

内联代码说明。例如，您可以使用df[,dist_before := NULL]删除临时列。

library(data.table)
df=data.table(time=seq(7173,7195,1),dist=c(31091.33,NA,31100.00,31103.27,NA,NA,NA,
NA,31124.98,NA,31132.81,NA,NA,NA,NA,31154.19,NA,31161.47,NA,NA,NA,NA,31182.97))
df
#>     time     dist
#>  1: 7173 31091.33
#>  2: 7174       NA
#>  3: 7175 31100.00
#>  4: 7176 31103.27
#>  5: 7177       NA
#>  6: 7178       NA
#>  7: 7179       NA
#>  8: 7180       NA
#>  9: 7181 31124.98
#> 10: 7182       NA
#> 11: 7183 31132.81
#> 12: 7184       NA
#> 13: 7185       NA
#> 14: 7186       NA
#> 15: 7187       NA
#> 16: 7188 31154.19
#> 17: 7189       NA
#> 18: 7190 31161.47
#> 19: 7191       NA
#> 20: 7192       NA
#> 21: 7193       NA
#> 22: 7194       NA
#> 23: 7195 31182.97
#>     time     dist
# Carry forward the last non-missing observation
df[,dist_before := nafill(dist, "locf")]
# Bring back the next non-missing dist
df[,dist_after := nafill(dist, "nocb")]
# rleid will create groups based on run-lengths of values within the data.
# This means 4 NA's in a row will be grouped together, for example.
# We then count the missings and add 1, because we want the 
# last NA before the next non-missing to be less than the non-missing value.
df[, rle := rleid(dist)][,missings := max(.N +  1 , 2), by = rle][]
#>     time     dist dist_before dist_after rle missings
#>  1: 7173 31091.33    31091.33   31091.33   1        2
#>  2: 7174       NA    31091.33   31100.00   2        2
#>  3: 7175 31100.00    31100.00   31100.00   3        2
#>  4: 7176 31103.27    31103.27   31103.27   4        2
#>  5: 7177       NA    31103.27   31124.98   5        5
#>  6: 7178       NA    31103.27   31124.98   5        5
#>  7: 7179       NA    31103.27   31124.98   5        5
#>  8: 7180       NA    31103.27   31124.98   5        5
#>  9: 7181 31124.98    31124.98   31124.98   6        2
#> 10: 7182       NA    31124.98   31132.81   7        2
#> 11: 7183 31132.81    31132.81   31132.81   8        2
#> 12: 7184       NA    31132.81   31154.19   9        5
#> 13: 7185       NA    31132.81   31154.19   9        5
#> 14: 7186       NA    31132.81   31154.19   9        5
#> 15: 7187       NA    31132.81   31154.19   9        5
#> 16: 7188 31154.19    31154.19   31154.19  10        2
#> 17: 7189       NA    31154.19   31161.47  11        2
#> 18: 7190 31161.47    31161.47   31161.47  12        2
#> 19: 7191       NA    31161.47   31182.97  13        5
#> 20: 7192       NA    31161.47   31182.97  13        5
#> 21: 7193       NA    31161.47   31182.97  13        5
#> 22: 7194       NA    31161.47   31182.97  13        5
#> 23: 7195 31182.97    31182.97   31182.97  14        2
#>     time     dist dist_before dist_after rle missings
# .SD[,.I] will get us the row number relative to the group it is in. 
# For example, row 5 dist is calculated as
# dist_before + 1 * (dist_after - dist_before)/5
df[is.na(dist), dist := dist_before + .SD[,.I] *
                     (dist_after - dist_before)/(missings), by = rle]
df[]
#>     time     dist dist_before dist_after rle missings
#>  1: 7173 31091.33    31091.33   31091.33   1        2
#>  2: 7174 31095.67    31091.33   31100.00   2        2
#>  3: 7175 31100.00    31100.00   31100.00   3        2
#>  4: 7176 31103.27    31103.27   31103.27   4        2
#>  5: 7177 31107.61    31103.27   31124.98   5        5
#>  6: 7178 31111.95    31103.27   31124.98   5        5
#>  7: 7179 31116.30    31103.27   31124.98   5        5
#>  8: 7180 31120.64    31103.27   31124.98   5        5
#>  9: 7181 31124.98    31124.98   31124.98   6        2
#> 10: 7182 31128.90    31124.98   31132.81   7        2
#> 11: 7183 31132.81    31132.81   31132.81   8        2
#> 12: 7184 31137.09    31132.81   31154.19   9        5
#> 13: 7185 31141.36    31132.81   31154.19   9        5
#> 14: 7186 31145.64    31132.81   31154.19   9        5
#> 15: 7187 31149.91    31132.81   31154.19   9        5
#> 16: 7188 31154.19    31154.19   31154.19  10        2
#> 17: 7189 31157.83    31154.19   31161.47  11        2
#> 18: 7190 31161.47    31161.47   31161.47  12        2
#> 19: 7191 31165.77    31161.47   31182.97  13        5
#> 20: 7192 31170.07    31161.47   31182.97  13        5
#> 21: 7193 31174.37    31161.47   31182.97  13        5
#> 22: 7194 31178.67    31161.47   31182.97  13        5
#> 23: 7195 31182.97    31182.97   31182.97  14        2
#>     time     dist dist_before dist_after rle missings