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在R和summary()函数中创建因子水平

[英]Create factor levels in R and summary() function

So, I am learning R. I am following this tutorial here: https://www.datacamp.com/courses/introduction-to-r/chapter-4-factors?ex=4 因此,我正在学习R。我在这里关注此教程: https : //www.datacamp.com/courses/introduction-to-r/chapter-4-factors?ex=4

Thats what I put in: 那就是我输入的内容:

survey_vector <- c("M","F","F","M","M")
factor_survey_vector <- factor(survey_vector)

# Your code here
levels(factor_survey_vector) <- c("Female","Male")

factor_survey_vector
summary(factor_survey_vector)

And thats what it prompts out in R 这就是R中提示的内容

> factor_survey_vector
[1] Male   Female Female Male   Male  
Levels: Female Male
> summary(factor_survey_vector)
Female   Male 
     2      3 

While I understand the prompt of factor_survey_vector I do not understand the prompt of the summary(factor_survey_vector) . 虽然我了解factor_survey_vector的提示, factor_survey_vector我不了解summary(factor_survey_vector)的提示。 How does R know, that there are 2 Females and 3 Males? R怎么知道有2个雌性和3个雄性? I only assigned the vector c("Female","Male") to levels(factor_survey_vector) . 我只将向量c("Female","Male")分配给levels(factor_survey_vector) How can it interpret, that each M is a Male and each F a Female? 如何解释每个M是男性,每个F是女性? I guess I am overseeing something very trivial here?! 我想我正在监督一些非常琐碎的事情?!

You can use str() to look at the underlying structure: 您可以使用str()查看底层结构:

> survey_vector <- c("M","F","F","M","M")
> factor_survey_vector <- factor(survey_vector)
> 
> 
> str(factor_survey_vector)
 Factor w/ 2 levels "F","M": 2 1 1 2 2

So factor_survey_vector is a 2 1 1 2 2 with level 1 being "F" and level 2 "M" 因此factor_survey_vector是2 1 1 2 2 2,级别1为“ F”,级别2为“ M”

> levels(factor_survey_vector) <- c("Female","Male")
> str(factor_survey_vector)
 Factor w/ 2 levels "Female","Male": 2 1 1 2 2

Here the only difference is the level labels have changed. 唯一的区别是级别标签已更改。 Now 1 is Female, 2 is Male. 现在1是女性,2是男性。

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