r语言min-max归一化_如何在R中使用min（）和max（）

爱被打了一巴掌 2023-02-28 06:28 8阅读 0赞

r语言min-max归一化

Finding min and max values is pretty much simple with the functions **min()** and **max()** in R.

使用R中的**min（）**和**max（）**函数，可以找到最小值和最大值。

You know that we have functions like [mean][], [median][], [sd][], and mode to calculate the average, middle, and dispersion of values respectively. But did you ever thought of a function which gives you min and max values in a [vector][] or a [data frame][]?

你知道，我们有这样的功能[平均值][mean] ， [中位数][median] ， [SD][sd]和模式分别计算平均值，中间和值的波动。 但是您是否想到过一个可以在[向量][vector]或[数据帧中][data frame]为您提供最小值和最大值的函数？

If so, congratulations, you have got functions named **min()** and **max()** which returns the minimum and maximum values respectively.

如果是这样，那么恭喜您，您获得了名为**min（）**和**max（）的**函数，它们分别返回最小值和最大值。

Sounds interesting right? Let’s see how it works!

听起来很有趣吧？ 让我们看看它是如何工作的！

--------------------

## 让我们从语法开始 **(****Let’s start with the syntax****)** ##

The syntax of the min() function is given below.

min（）函数的语法如下。

min(x, na.rm = FALSE)

*  **x =** vector or a data frame.
    
    **x =**向量或数据帧。
 *  **na.rm =** remove NA values, if it mentioned False it considers NA or if it mentioned True it removes NA from the vector or a data frame.
    
    **na.rm =**删除NA值，如果提到False，则认为NA；如果提到True，则从向量或数据帧中删除NA。

The syntax of the max() function is given below.

max（）函数的语法如下。

max(x, na.rm = FALSE)

--------------------

## R中的Max（）函数 **(****Max() function in R****)** ##

In this section, we are going to find the max values present in the vector. For this, we first create a vector and then apply the max() function, which returns the max value in the vector.

在本节中，我们将找到向量中存在的最大值。 为此，我们首先创建一个向量，然后应用max（）函数，该函数返回向量中的最大值。

#creates a vector 
    vector<-c(45.6,78.8,65.0,78.9,456.7,345.89,87.6,988.3)
    
    #returns the max values present in the vector
    max(vector)

**Output= 988.3**

**输出= 988.3**

--------------------

## R中的Min（）函数 **(****Min() function in R****)** ##

Here, we are going to find the minimum value in a vector using function min(). You can create a vector and then apply min() to the vector which returns the minimum value as shown below.

在这里，我们将使用min（）函数在向量中找到最小值。 您可以创建一个向量，然后将min（）应用于该向量，该向量将返回最小值，如下所示。

#creates a vector
    vector<-c(45.6,78.8,65.0,78.9,456.7,345.89,87.6,988.3)
    
    #returns the minimum value present in the vector 
    min(vector)

**Output =**  **45.6**

**输出=** **45.6**

--------------------

## R中具有NA值的Max（）函数 **(****Max() function in R with NA values****)** ##

Sometimes in the data analysis, you may encounter the NA values in a data frame as well as a vector. Then you need to bypass the NA values in order to get the desired result.

有时在数据分析中，您可能会在数据帧和向量中遇到NA值。 然后，您需要绕过NA值以获得所需的结果。

The max function won’t return any values if it encounters the NA values in the process. Hence you have to remove NA values from the vector or a data frame to get the **max** value.

如果max函数在过程中遇到NA值，则不会返回任何值。 因此，您必须从向量或数据帧中删除NA值才能获得**最大值** 。

#creates a vector having NA values
    df<- c(134,555,NA,567,876,543,NA,456)
    
    #max function won't return any value because of the presence of NA. 
    max(df)
    
    #results in NA instead of max value
    Output = NA

So to avoid this and get the max value we are using **na.rm** function to remove NA values from the vector. Now you can see that the max() function is returning the maximum value.

因此，为了避免这种情况并获得最大值，我们使用**na.rm**函数从向量中删除NA值。 现在您可以看到max（）函数正在返回最大值。

#max function with remove NA values is set as TRUE.
    max(df, na.rm = T)

**Output =**  **876**

**输出=** **876**

--------------------

## R中具有NA值的Min（）函数 **(****Min() function in R with NA values****)** ##

Just like we applied the max function in the above section, here we are going to find the minimum value in a vector having NA values.

就像我们在上一节中应用max函数一样，这里我们将在具有NA值的向量中找到最小值。

#creates a vector having NA values
    df<- c(134,555,NA,567,876,543,NA,456)
    
    #returns NA instead of minimum value
    min(df)

**Output = NA**

**输出= NA**

To overcome this, we are using **na.rm** function to remove NA values from the vector. Now you can that the min() function is returning the min value.

为了克服这个问题，我们使用**na.rm**函数从向量中删除NA值。 现在您可以使min（）函数返回最小值。

#creates a vector having NA values
    df<- c(134,555,NA,567,876,543,NA,456)
    
    #removes NA values and returns the minimum value in the vector
    min(df, na.rm = T)

**Output = 134**

**输出= 134**

--------------------

## 字符向量中的Min（）和Max（）函数 **(****Min() and Max() functions in a character vector****)** ##

Till now we have dealt with numerical minimum and maximum values. If I have to tell you something, I wish to say that you can also find the min and max values for a character vector as well. Yes, you heard it right!

到现在为止，我们已经处理了数值的最小值和最大值。 如果需要告诉您一些信息，我想说的是，您也可以找到字符向量的最小值和最大值。 是的，您没听错！

Let’s see how it works!

让我们看看它是如何工作的！

In the case of character vectors, the min and max functions will consider alphabetical order and returns min and max values accordingly as shown below.

对于字符向量，min和max函数将考虑字母顺序，并相应地返回min和max值，如下所示。

#creates a character vector with some names
    character_vector<- c('John','Angelina','Smuts','Garena','Lucifer')
    
    #returns the max value
    max(character_vector)

**Output = “Smuts”**

**输出=“黑穗病”**

Similarly, we can find the minimum values in the character vector as well using min() function which is shown below.

同样，我们也可以使用min（）函数在字符向量中找到最小值，如下所示。

#creates a character vector with some names 
    character_vector<- c('John','Angelina','Smuts','Garena','Lucifer')
    
    #returns the minimum values in the vector
    min(character_vector)

**Output = “Angelina”**

**输出=“天使”**

--------------------

## 数据帧中的Min（）和Max（）函数 **(****Min() and Max() functions in a data frame** **)** ##

Let’s find the minimum and maximum values of a data frame by importing it. The min and max values in a dataset will give a fair idea about the data distribution.

通过导入来查找数据帧的最小值和最大值。 数据集中的最小值和最大值将为数据分配提供一个合理的思路。

This is the air quality dataset that is available in R studio. Note that the dataset includes NA values. With the knowledge of removing NA values using **na.rm** function, let’s find the min and max values in the **Ozone values**.

这是R studio中可用的空气质量数据集。 请注意，数据集包含NA值。 了解使用**na.rm**函数删除NA值后，让我们在**Ozone值中**找到最小值和最大值。

![Airquality Dataset][]

min(airquality$Ozone, na.rm=T)

**Output = 1**

**输出= 1**

max(airquality$Ozone, na.rm = T)

**Output = 168**

**输出= 168**

Let’s find the min and max values of the Temperature values in the airquality dataset.

让我们在空气质量数据集中找到温度值的最小值和最大值。

min(airquality$Temp, na.rm = T)

**Output = 56**

**输出= 56**

max(airquality$Temp, na.rm = T)

**Output = 97**

**输出= 97**

--------------------

## 结语 **(****Wrapping up****)** ##

Well, in this tutorial we have focussed on finding the minimum and maximum values in a vector, data frame, and a character vector as well.

嗯，在本教程中，我们集中于查找向量，数据帧和字符向量中的最小值和最大值。

The min and max functions can be used in both numerical as well as character vectors. You can also remove the NA values using **na.rm** function to get better accuracy and desired results.

最小值和最大值函数可用于数值向量和字符向量。 您也可以使用**na.rm**函数删除NA值，以获得更好的准确性和所需的结果。

That’s all for now. I hope you will find more min and max values as shown in the above sections. Don’t forget to hit the comments section for any queries.

目前为止就这样了。 我希望您会发现更多的最小值和最大值，如以上各节所示。 不要忘记点击注释部分进行任何查询。

**Happy learning!!!**

**学习愉快！**

**More study:** [R documentation][]

**更多研究：** [R文档][R documentation]

> 翻译自: [https://www.journaldev.com/40266/min-max-in-r][https_www.journaldev.com_40266_min-max-in-r]

r语言min-max归一化

[mean]: https://www.journaldev.com/38103/find-the-mean-of-values-in-r
[median]: https://www.journaldev.com/39066/find-the-median-in-r
[sd]: https://www.journaldev.com/38162/find-standard-deviation-in-r
[vector]: https://www.journaldev.com/35322/vectors-in-r
[data frame]: https://www.journaldev.com/35741/data-frames-in-r-programming
[Airquality Dataset]: /images/20230209/1abbb6b880864daba03ca7f86140b102.png
[R documentation]: https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/which.min
[https_www.journaldev.com_40266_min-max-in-r]: https://www.journaldev.com/40266/min-max-in-r