R语言从DataFrame中创建表格

在这篇文章中，我们将讨论如何在R编程语言中从给定的数据框架中创建一个表格。

使用的函数

table():这个函数是进行交互式数据分析的一个基本函数。因为它可以简单地创建分类变量的表格结果。

语法：table(..., exclude = if (useNA == "no") c(NA, NaN),useNA = c("no", "ifany", "always"), dnn = list.names(...) , deparse.level = 1)

返回：它将返回带有条件和交叉分析的频率表。

例1：用R语言创建给定数据框的频率表：-

在这个例子中，我们将使用R语言中的table()函数在R语言中建立一个简单的频率表。这个表只是提供数据框中元素的频率。

gfg_data <- data.frame(
  Country = c("France","Spain","Germany","Spain","Germany",
              "France","Spain","France","Germany","France"), 
    
  age = c(44,27,30,38,40,35,52,48,45,37),
    
  salary = c(6000,5000,7000,4000,8000), 
    
  Purchased=c("No","Yes","No","No","Yes",
              "Yes","No","Yes","No","Yes"))
  
gfg_table<-table(gfg_data$Country)
gfg_table

输出

 France Germany   Spain  
     4       3       3

例2：用R语言创建一个带有给定数据框比例的频率表

在这里，我们将使用 prop.table() 函数，它的工作原理与简单的table()函数很相似，可以从给定的数据框中获得带有比例的频率表。

gfg_data <- data.frame(
  Country = c("France","Spain","Germany","Spain","Germany",
              "France","Spain","France","Germany","France"), 
    
  age = c(44,27,30,38,40,35,52,48,45,37),
  salary = c(6000,5000,7000,4000,8000), 
    
  Purchased=c("No","Yes","No","No","Yes","Yes",
              "No","Yes","No","Yes"))
  
gfg_table = as.table(table(gfg_data$Country))
prop.table(gfg_table)

输出

 France Germany   Spain 
    0.4     0.3     0.3

例3：用R语言从给定的数据框中创建一个带条件的频率表 。

在这个例子中，我们将用R语言中的table()函数建立一个简单的频率表，里面有一个条件作为R语言的函数参数。这个表只是提供数据框中符合函数中给定条件的元素的频率。

在这里，我们将使用R语言中的table()函数，从数据框架中制作一个薪金列的频率表，条件是薪金大于6000。

gfg_data <- data.frame(
  Country = c("France","Spain","Germany","Spain","Germany",
              "France","Spain","France","Germany","France"), 
    
  age = c(44,27,30,38,40,35,52,48,45,37),
  salary = c(6000,5000,7000,4000,8000), 
    
  Purchased=c("No","Yes","No","No","Yes","Yes",
              "No","Yes","No","Yes"))
  
gfg_table =table(gfg_data$salary>6000)
gfg_table

输出

FALSE  TRUE 
    6     4

例4：用R语言从给定的数据框中创建一个2-way cross table

在这个例子中，我们将使用R语言中的table()函数建立一个简单的2-way cross table。这个表只是提供数据框架中不同列的元素的频率。

gfg_data <- data.frame(
  Country = c("France","Spain","Germany","Spain","Germany",
              "France","Spain","France","Germany","France"), 
    
  age = c(44,27,30,38,40,35,52,48,45,37),
  salary = c(6000,5000,7000,4000,8000), 
    
  Purchased=c("No","Yes","No","No","Yes","Yes",
              "No","Yes","No","Yes"))
  
gfg_table =table(gfg_datasalary,gfg_dataCountry)
gfg_table

输出

       France Germany Spain
  4000      0       1     1
  5000      0       0     2
  6000      2       0     0
  7000      1       1     0
  8000      1       1     0