识别模式并将它们作为新列

Question

我在一个项目中工作，其中包含大量存储在 HTML 中的表。在抓取的过程中，我不得不处理以下问题。

Some of the tables that I am scraping look like this

在我导入 DF 时，我必须在此代码中为那些合并单元格的行（“鸡”和“没有骨头的鸡”）输入 fill = TRUE 参数：

read_html(link) %>%
    html_nodes(node) %>%
    html_table(fill = T, header = T, dec = ",")

但这为我生成了这样的表格：

   df <- data.frame(year = c("chicken",2000,2001,2002,"chicken without bones",2003,2004,2005, "chicken without bones and feet", 2006, 2007, 2008), 
                 weight = c("chicken",5,6,4,"chicken without bones",2,1,3,"chicken without bones and feet", 1, 1.5, 2)
                 )

试图找到一种方法让我的表格看起来像这样：

df2 <- data.frame(year = c(2000,2001,2002, 2003, 2004, 2005,2006,2007, 2008), number = c(5,6,4,2,1,3,1,1.5, 2), 
                 new_variable = c("chicken","chicken","chicken","chicken without bones","chicken without bones",
                                  "chicken without bones","chicken without bones and feet","chicken without bones and feet","chicken without bones and feet" )
                 )

我在 R 上苦苦挣扎，但仍然不知道如何在我的 1.028.974 表被刮掉的情况下做到这一点。 Obs.：这些表没有这种发生的模式；因此，我需要一个代码来识别填充节点，将它们的值作为字符获取并将其转换为新的列值，直到下一次填充发生。

感谢关注！！

Answer 1

你可以试试这个-

library(dplyr)
library(zoo)

df %>%
  mutate_if(is.factor, as.character) %>%
  mutate(new_variable = ifelse(grepl("\\D+", year), year, NA),
         new_variable = na.locf(new_variable)) %>%
  filter(!grepl("\\D+", year))

输出为：

  year weight                   new_variable
1 2000      5                        chicken
2 2001      6                        chicken
3 2002      4                        chicken
4 2003      2          chicken without bones
5 2004      1          chicken without bones
6 2005      3          chicken without bones
7 2006      1 chicken without bones and feet
8 2007    1.5 chicken without bones and feet
9 2008      2 chicken without bones and feet

样本数据：

df <- structure(list(year = structure(c(10L, 1L, 2L, 3L, 11L, 4L, 5L, 
6L, 12L, 7L, 8L, 9L), .Label = c("2000", "2001", "2002", "2003", 
"2004", "2005", "2006", "2007", "2008", "chicken", "chicken without bones", 
"chicken without bones and feet"), class = "factor"), weight = structure(c(8L, 
6L, 7L, 5L, 9L, 3L, 1L, 4L, 10L, 1L, 2L, 3L), .Label = c("1", 
"1.5", "2", "3", "4", "5", "6", "chicken", "chicken without bones", 
"chicken without bones and feet"), class = "factor")), class = "data.frame", row.names = c(NA, 
-12L))

#                             year                         weight
#1                         chicken                        chicken
#2                            2000                              5
#3                            2001                              6
#4                            2002                              4
#5           chicken without bones          chicken without bones
#6                            2003                              2
#7                            2004                              1
#8                            2005                              3
#9  chicken without bones and feet chicken without bones and feet
#10                           2006                              1
#11                           2007                            1.5
#12                           2008                              2