使用R将单个列分成多个观察 [英] Splitting a single column into multiple observation using R

问题描述

我正在处理HCUP数据，这在一个单独的列中需要分割成多个列的值的范围。以下是HCUP数据框架供参考：

I am working on HCUP data and this has range of values in one single column that needs to be split into multiple columns. Below is the HCUP data frame for reference :

code            label
61000-61003     excision of CNS
0169T-0169T     ventricular shunt

所需输出应为：

code            label
61000           excision of CNS
61001           excision of CNS
61002           excision of CNS
61003           excision of CNS
0169T           ventricular shunt

我的方法是使用包 splitstackshape 并使用此代码

My approach to this problem is using the package splitstackshape and using this code

library(data.table)
library(splitstackshape)

cSplit(hcup, "code", "-")[, list(code = code_1:code_2, by = label)]

b $ b

这种方法会导致内存问题。是否有更好的方法解决这个问题？

This approach leads to memory issues. Is there a better approach to this problem?

一些注释：

• 数据除了T外还有许多字母。


• 字母可以在前面或最后，但不能在两个数字之间。

• The data has many letters apart from "T".
• The letter can be either in the front or at the very end but not in between two numbers.
• There is no change of letter from "T" to "U" in one single range

推荐答案

这里有一个使用 dplyr 和 all.is.numeric Hmisc ：

library(dplyr)
library(Hmisc)
library(tidyr)
dat %>% separate(code, into=c("code1", "code2")) %>%
        rowwise %>%
        mutate(lists = ifelse(all.is.numeric(c(code1, code2)),
                         list(as.character(seq(from = as.numeric(code1), to = as.numeric(code2)))),
                         list(code1))) %>%
        unnest(lists) %>%
        select(code = lists, label)

Source: local data frame [5 x 2]

   code             label
  (chr)            (fctr)
1 61000   excision of CNS
2 61001   excision of CNS
3 61002   excision of CNS
4 61003   excision of CNS
5 0169T ventricular shunt

使用字符值修正范围的编辑。提升简单性：

An edit to fix ranges with character values. Brings down the simplicity a little:

dff %>% mutate(row = row_number()) %>%
        separate(code, into=c("code1", "code2")) %>%
        group_by(row) %>%
        summarise(lists = if(all.is.numeric(c(code1, code2)))
                              {list(str_pad(as.character(
                                   seq(from = as.numeric(code1), to = as.numeric(code2))),
                                         nchar(code1), pad="0"))}
                          else if(grepl("^[0-9]", code1))
                              {list(str_pad(paste0(as.character(
                                   seq(from = extract_numeric(code1), to = extract_numeric(code2))),
                                      strsplit(code1, "[0-9]+")[[1]][2]),
                                         nchar(code1), pad = "0"))}
                          else
                              {list(paste0(
                                      strsplit(code1, "[0-9]+")[[1]],
                                      str_pad(as.character(
                                    seq(from = extract_numeric(code1), to = extract_numeric(code2))),
                                         nchar(gsub("[^0-9]", "", code1)), pad="0")))},
                   label = first(label)) %>%
        unnest(lists) %>%
        select(-row)
Source: local data frame [15 x 2]

               label lists
               (chr) (chr)
1    excision of CNS 61000
2    excision of CNS 61001
3    excision of CNS 61002
4  ventricular shunt 0169T
5  ventricular shunt 0170T
6  ventricular shunt 0171T
7    excision of CNS 01000
8    excision of CNS 01001
9    excision of CNS 01002
10    some procedure A2543
11    some procedure A2544
12    some procedure A2545
13    some procedure A0543
14    some procedure A0544
15    some procedure A0545

data：

dff <- structure(list(code = c("61000-61002", "0169T-0171T", "01000-01002", 
"A2543-A2545", "A0543-A0545"), label = c("excision of CNS", "ventricular shunt", 
"excision of CNS", "some procedure", "some procedure")), .Names = c("code", 
"label"), row.names = c(NA, 5L), class = "data.frame")

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