R：ifelse语句：比较data.frames

问题描述

我有2个数据框，其中im尝试将其中的值与另一个
进行比较。如果值在表1和2中匹配，则表2中的第三个值被插入到表1中。

示例表我的DF

 字数
 1 it 1 
 2为2 
 3 3 
 4 LTD数量4 
 5结束5 
 6 6 6 
 7冬天7 
  

表x.sub

  lev_dist Var1 Var2 
 31 1 LTD数量有限公司数量
  

我想说的是，如果x.sub中的Var1等于MyDF中的单词，然后在mydf中的单词旁边的第三列中插入x.sub.lev_dist

我的尝试是在下面，但是在结果中生成3，而不是lev_value

  mydf $ lev_dist<  -  ifelse（test =（mydf $ words == x.sub $ Var1），x.sub $ Var1,0）
  

结果：

 字数lev_dist 
 1 it 1 0 
 2为2 0 
 3 3 0 
 4 LTD数量4 3 
 5 zh d 5 0 
 6/6 0 
 7冬季7 0 
  

帮助

解决方案

x.sub $ Var1 是一个 factor 列。所以，当我们执行 ifelse 时，我们得到这个因子的数值级别。在 x.sub $ Var1 与 as.character（x.sub $ Var1） > ifelse

  mydf $ lev_dist<  -  ifelse（mydf $ words == as.character xsub $ Var1）），
 x.sub $ lev_dist，0）
  

如果列是字符类，可以避免。使用 stringsAsFactors = FALSE 在 read.csv / read.table 或 data.frame 将确保所有字符列都是字符类。

I have 2 dataframes where im trying to compare the value in one with anotherIf the value matches in both table 1 and 2, then a third value from table 2 is inserted into Table one.

Example Table My DF

    words number
 1      it      1
 2     was      2
 3     the      3
 4     LTD QTY  4
 5     end      5
 6      of      6
 7  winter      7

Table x.sub

   lev_dist    Var1    Var2
31        1 LTD QTY LTD QTY

What i want to say is, if Var1 in x.sub is equal to words in MyDF then insert x.sub.lev_dist in a third column next to the word in mydf

My attempt is below but keeps producing 3 in the results instead of the lev_value

mydf$lev_dist <- ifelse(test = (mydf$words == x.sub$Var1),x.sub$Var1,0)

Results:

    words number lev_dist
1      it      1        0
2     was      2        0
3     the      3        0
4 LTD QTY      4        3
5     end      5        0
6      of      6        0
7  winter      7        0

Can anyone help

解决方案

The x.sub$Var1 is a factor column. So, when we do the ifelse, we get the numeric levels of the factor. Replace x.sub$Var1 with as.character(x.sub$Var1) in the ifelse

 mydf$lev_dist <- ifelse(mydf$words == as.character(x.sub$Var1)),
                        x.sub$lev_dist,0)

This could have avoided if the columns were of character class. Using stringsAsFactors=FALSE in the read.csv/read.table or data.frame would ensure that all the character columns are of character class.

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