根据现有的行和列计算 r 数据框 r 中的新行

debugcn 发表于 Dev

史蒂芬

我很想知道哪个命令用于以下内容：我想计算“名称”列中城市和“年”列中每年的人口估计值。“增长”列提供了增长率。所以作为公式，它会是这样的：

Population[Lucknow,2030] = Population[Lucknow, 2020] * growth[2030]

等等。以下df：

df <- data.frame(YEAR=c(2020,2020,2020,2030,2040,2050), NAME=c("Lucknow","Delhi","Hyderadabad",NA,NA,NA), POPULATION=c(3704, 29274,10275,NA,NA,NA), growth=c(1.0,1.0,1.0,1.10,1.18,1.24))
Year                Name           Population        growth
2020             Lucknow                 3704     1.0000000
2020               Delhi                29274     1.0000000
2020           Hyderabad                10275     1.0000000
2030                <NA>                   NA   <NA> 1.10
2040                <NA>                   NA   <NA> 1.18
2050                <NA>                   NA   <NA> 1.24

编辑：按照 Dom（谢谢！）在下面写的内容，输入将是：

df <- tibble( year = rep(c(2020,2030,2040,2050), each = 3), city =rep(c("Lucknow","Delhi","Hyderadabad"), times = 4), pop = c(3704, 29274,10275, rep(NA_integer_, times = 9)), growth = rep(c(1.0, 1.10, 1.18, 1.24), each = 3) )
    year city          pop growth
   <dbl> <chr>       <dbl>  <dbl>
 1  2020 Lucknow      3704   1   
 2  2020 Delhi       29274   1   
 3  2020 Hyderadabad 10275   1   
 4  2030 Lucknow        NA   1.1 
 5  2030 Delhi          NA   1.1 
 6  2030 Hyderadabad    NA   1.1 
 7  2040 Lucknow        NA   1.18
 8  2040 Delhi          NA   1.18
 9  2040 Hyderadabad    NA   1.18
10  2050 Lucknow        NA   1.24
11  2050 Delhi          NA   1.24
12  2050 Hyderadabad    NA   1.24

输出应如下所示：

Year                Name           Population        growth
2020             Lucknow                 3704     1.0000000
2020               Delhi                29274     1.0000000
2020           Hyderabad                10275     1.0000000
2030             Lucknow               4074.4     1.1000000
2030               Delhi              32201.4     1.1000000
2030           Hyderabad              11302.5     1.1000000
....

如何在tibble中填充NA？

我对合并和 dplyr::mutate 进行了各种尝试，但由于这是一个向量操作，因此无法确定我需要在这里做什么。我很乐意为正确的命令提供任何线索来执行这样的基本操作。

谢谢！

sindri_baldur

使用dplyr：

library(dplyr)
df %>%
  arrange(city, year) %>%
  group_by(city) %>%
  mutate(pop = pop[1] * growth)

# A tibble: 12 x 4
# Groups:   city [3]
    year city           pop growth
   <dbl> <chr>        <dbl>  <dbl>
 1  2020 Delhi       29274    1   
 2  2030 Delhi       32201.   1.1 
 3  2040 Delhi       34543.   1.18
 4  2050 Delhi       36300.   1.24
 5  2020 Hyderadabad 10275    1   
 6  2030 Hyderadabad 11303.   1.1 
 7  2040 Hyderadabad 12124.   1.18
 8  2050 Hyderadabad 12741    1.24
 9  2020 Lucknow      3704    1   
10  2030 Lucknow      4074.   1.1 
11  2040 Lucknow      4371.   1.18
12  2050 Lucknow      4593.   1.24

使用基础R：

df <- df[order(df[["city"]], df[["year"]]), ]
df[["pop"]] <-
  unlist(
    lapply(
      unique(df[["city"]]), 
      function(x) with(df[df[["city"]] == x, ], pop[1] * growth)
    )
  )

使用data.table：

library(data.table)
setDT(df)[order(city, year), pop := pop[1] * growth, city]

数据：

df <- tibble(
  year   = rep(c(2020, 2030, 2040, 2050), each = 3), 
  city   = rep(c("Lucknow", "Delhi", "Hyderadabad"), times = 4), 
  pop    = c(3704, 29274, 10275, rep(NA, times = 9)), 
  growth = rep(c(1.0, 1.10, 1.18, 1.24), each = 3)
)

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