在R中创建框图的循环
我有一个包含数字和分类值的数据集。我正在尝试创建框图,以在我的数据集中的每个数字列上视觉上识别异常值。以下代码可以做到这一点,但它非常笨拙,我不想使用此代码,其中包含更多变量。我正在寻找一种使用循环使用R中的循环创建框图的方法
。这是无循环的笨拙的代码:
#Using Boxplots, check for outliers in each in each float or integer value column.
b <-boxplot(df$item1, main = 'item1')
b <-boxplot(df$item2, main = 'item2')
b <-boxplot(df$item3, main = 'item3')
b <-boxplot(df$item4, main = 'item4')
b <-boxplot(df$item5, main = 'item5')
b <-boxplot(df$item6, main = 'item6')
b <-boxplot(df$item7, main = 'item7')
b <-boxplot(df$item8, main = 'item8')
b <-boxplot(df$item9, main = 'item9')
b <-boxplot(df$item10, main = 'item10')
b <-boxplot(df$item11, main = 'item11')
b <-boxplot(df$item12, main = 'item12')
b <-boxplot(df$item13, main = 'item13')
b <-boxplot(df$item14, main = 'item14')
b <-boxplot(df$item15, main = 'item15')
b <-boxplot(df$item16, main = 'item16')
在Python中,代码将是:(
outliers = ['Item1', 'Item2', 'Item3', 'Item4', 'Item5', 'Item6', 'Item7', 'Item8', 'Item9', 'Item10', 'Item11', 'Item12', 'Item13', 'Item14', 'Item15', 'Item16']
i=0
while i < len(outliers):
sns.boxplot(x = outliers[i], data = df)
plt.show()
i = i + 1
我在R中寻找类似的东西!) 谢谢你!
I have a dataset that contains both numeric and categorical values. I am trying to create box plots to visually identify outliers for each numeric column in my dataset. The below code works to do this, but it is very clunky and I would not want to use this code with even more variables. I am looking for a way to use a loop to create box plots using a loop in R.
Here is the clunky code that works without a loop:
#Using Boxplots, check for outliers in each in each float or integer value column.
b <-boxplot(df$item1, main = 'item1')
b <-boxplot(df$item2, main = 'item2')
b <-boxplot(df$item3, main = 'item3')
b <-boxplot(df$item4, main = 'item4')
b <-boxplot(df$item5, main = 'item5')
b <-boxplot(df$item6, main = 'item6')
b <-boxplot(df$item7, main = 'item7')
b <-boxplot(df$item8, main = 'item8')
b <-boxplot(df$item9, main = 'item9')
b <-boxplot(df$item10, main = 'item10')
b <-boxplot(df$item11, main = 'item11')
b <-boxplot(df$item12, main = 'item12')
b <-boxplot(df$item13, main = 'item13')
b <-boxplot(df$item14, main = 'item14')
b <-boxplot(df$item15, main = 'item15')
b <-boxplot(df$item16, main = 'item16')
In python the code would be:
outliers = ['Item1', 'Item2', 'Item3', 'Item4', 'Item5', 'Item6', 'Item7', 'Item8', 'Item9', 'Item10', 'Item11', 'Item12', 'Item13', 'Item14', 'Item15', 'Item16']
i=0
while i < len(outliers):
sns.boxplot(x = outliers[i], data = df)
plt.show()
i = i + 1
(I am looking for something similar in R!)
Thank you!
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使用
循环在列上循环,并基于
mtcars
的最小preprex,您可以做Using a
for
loop to loop over the columns and a minimal reprex based onmtcars
you could do