根据条件更改列中所有字符串的值 [英] Change value of all strings in column based on condition

问题描述

R的新手，我对数据清理有疑问。

New-ish to R, I have a question about data cleaning.

我有一个列，其中包含汽车的驱动类型-四轮，全轮，2轮等

I have a column that contains what type of drive a car is - four wheel, all wheel, 2 wheel etc

问题是没有标准化，因此某些行具有4 WHEEL驱动器，4wd，4WD，四轮驱动器等

The problem is there is no standardization, so some rows have 4 WHEEL drive, 4wd, 4WD, Four - Wheel - Drive, etc

第一步很容易，这就是大写内容，但我遇到的困难是将每个值更改为4WD之类的标准，而不必重新编码每个唯一的驱动器。

The first step is easy, which is to uppercase everything but the step I'm having trouble with is changing each value to a standard, like 4WD, without having to recode each unique drive.

如果值LIKE / CONTAINS的 FOUR更改为 4WD，则类似于For列中的每个值。

Something like For Each value in column, if value LIKE/CONTAINS "FOUR" change to "4WD".

我已经研究了recode以及stringdist和mutate，但我找不到合适的方法。当我键入它时，听起来好像需要循环，但不确定确切的语法。

I've researched recode and stringdist and mutate but I can't find a fit. When I typed it out it sounds like I need a loop but not sure the exact syntax.

如果该解决方案可以与tidyverse一起使用，那就太好了！

If the solution could work with the tidyverse that would be great!

推荐答案

欢迎使用StackOverflow！我已经回答了您的问题，但是将来，请提供一小部分数据样本，以便我们更轻松地解决您的问题。值得深思：如何制作可重复的例子

Welcome to StackOverflow! I've answered your question, but in the future, please include a small sample of your data so it's easier for us to solve your problem. Food for thought: How to make a reproducible example

require(plyr)
require(dplyr)


# Since you haven't provided a data sample, I'm going to assume your dataframe is named "DF" and your column's name is "Drive"

# Set everything to lowercase to pare down uniqueness
DF <- mutate(DF, Drive = replace(Drive, Drive, tolower(Drive)))


# You'll need one line like this for each replacement.  Of the following form:
#     <column_name> = replace(<column_name>, <condition>, <new value>)
DF <- mutate(DF, Drive = replace(Drive, Drive == "4 wheel drive", "4WD"))

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