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获取字符串中的最小数字

string r

DTYK · 技术社区 · 7 年前

我有一个数据框架,由捕捉不同事件的列组成。受访者填写他们经历这些事件的年龄。对于他们经历过多次的任何给定事件,他们用一个分号来分隔经历过的年龄(例如,如果他们在5、6、7岁时经历过,他们将在该特定列中输入5、6、7)。对于他们没有经历过的事件,受访者会将其留空。

因为有20多列,所以我将所有列连接在一起,形成一个单列,形成一个字符列。我想提取那个字符串中最小的数字。我无法将列强制为数字数据类型,因为某些事件将被受访者多次经历,并且被R解释为字符串(例如“5;6;7”)。

我的数据如下所示:

df <- data.frame(ID = c("001", "002", "003", "004"),
             concatenated = c("NA_NA_NA_NA_5; 6_NA_4_NA_NA_NA",
                              "3_3_NA_NA_NA_3; 4; 5; 6_NA_NA_NA_NA",
                              "NA_5_4_2_NA_NA_NA_NA_6; 7; 8; 9; 10_NA",
                              "NA_NA_11_12_11_NA_4; 5; 6_NA_NA_9"))

df$concatenated <- as.character(df$concatenated)

我想要得到的最终结果是:

ID                           concatenated smallest_number
1 001         NA_NA_NA_NA_5; 6_NA_4_NA_NA_NA               4
2 002    3_3_NA_NA_NA_3; 4; 5; 6_NA_NA_NA_NA               3
3 003 NA_5_4_2_NA_NA_NA_NA_6; 7; 8; 9; 10_NA               2
4 004      NA_NA_11_12_11_NA_4; 5; 6_NA_NA_9               4

谢谢!非常感谢!

4 回复 | 直到 7 年前

Hugh 7 年前

假设您的数据结构如下:

DF <- data.frame(ID = 1:4,
                 age = c("5", "5;6;7", "20;15;12", "2;4"),
                 stringsAsFactors = FALSE)

你可以使用 strsplit 将每个年龄段划分为一个数字,然后按照通常的方式取最小值:

DF$min_age <- vapply(strsplit(DF$age, split = "[^0-9]"),
                     function(x) min(as.numeric(x), na.rm = TRUE),
                     double(1))

如果数字有时不出现,只需排除这些行

i <- grep("[0-9]", DF$age)  # rows with numbers somewhere
DF$min_age <- NA_character_
DF$min_age[i] <- vapply(strsplit(DF$age[i], split = "[^0-9]"),
                        function(x) min(as.numeric(x), na.rm = TRUE),
                        double(1))

moodymudskipper 7 年前

我们可以用 gsub 为每个项使用一个下划线分隔的字符串,然后使用 scan 和 min 在他们身上。

df$smallest_number <- sapply(df$concatenated, function(x){
  min(scan(text=gsub("; ","_",x), what = numeric(), sep="_"),na.rm=TRUE)})
df
#    ID                           concatenated smallest_number
# 1 001         NA_NA_NA_NA_5; 6_NA_4_NA_NA_NA               4
# 2 002    3_3_NA_NA_NA_3; 4; 5; 6_NA_NA_NA_NA               3
# 3 003 NA_5_4_2_NA_NA_NA_NA_6; 7; 8; 9; 10_NA               2
# 4 004      NA_NA_11_12_11_NA_4; 5; 6_NA_NA_9               4

s_baldur 7 年前

library(stringr)
df$smallest_number <- sapply(
  str_extract_all(df$concatenated, "[0-9]+"),
  function(x) min(as.integer(x))
)
df
   ID                           concatenated smallest_number
1 001         NA_NA_NA_NA_5; 6_NA_4_NA_NA_NA               4
2 002    3_3_NA_NA_NA_3; 4; 5; 6_NA_NA_NA_NA               3
3 003 NA_5_4_2_NA_NA_NA_NA_6; 7; 8; 9; 10_NA               2
4 004      NA_NA_11_12_11_NA_4; 5; 6_NA_NA_9               4

tmfmnk 7 年前

用 tidyverse 和 splitstackshape 你可以做到:

df %>%
 mutate(temp = gsub(";", "_", concatenated),
        temp = gsub(" ", "", temp)) %>%
 cSplit("temp", sep = "_") %>%
 gather(var, val, -c(concatenated, ID)) %>%
 group_by(ID) %>%
 mutate(res = min(val, na.rm = TRUE)) %>%
 spread(var, val) %>%
 select(ID, concatenated, res)

  ID    concatenated                             res
  <fct> <chr>                                  <dbl>
1 001   NA_NA_NA_NA_5; 6_NA_4_NA_NA_NA            4.
2 002   3_3_NA_NA_NA_3; 4; 5; 6_NA_NA_NA_NA       3.
3 003   NA_5_4_2_NA_NA_NA_NA_6; 7; 8; 9; 10_NA    2.
4 004   NA_NA_11_12_11_NA_4; 5; 6_NA_NA_9         4.

首先,它取代了 ; 具有 _ 并根据 γ . 其次,它将数据从宽格式转换为长格式,并按“id”列分组。最后,它评估最小值并将数据返回到宽格式。

或者只是 时髦诗 :

df %>% 
 mutate(temp = gsub(";", "_", concatenated),
        temp = gsub(" ", "", temp),
        temp = strsplit(temp, "_")) %>%
 unnest(temp) %>%
 group_by(ID) %>%
 mutate_if(is.character, as.numeric) %>%
 mutate(res = min(temp, na.rm = TRUE),
        rowid = row_number()) %>%
 spread(rowid, temp) %>%
 select(ID, concatenated , res)

  ID    concatenated                             res
  <fct> <fct>                                  <dbl>
1 001   NA_NA_NA_NA_5; 6_NA_4_NA_NA_NA            4.
2 002   3_3_NA_NA_NA_3; 4; 5; 6_NA_NA_NA_NA       3.
3 003   NA_5_4_2_NA_NA_NA_NA_6; 7; 8; 9; 10_NA    2.
4 004   NA_NA_11_12_11_NA_4; 5; 6_NA_NA_9         4.