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R 语言 – 数据框

数据框(Data Frames)是以表格格式显示的数据。

数据框可以在其中包含不同类型的数据。第一列可以是“字符”(character),第二列和第三列可以是“数字”(numeric)或“逻辑”(logical)。但是,每一列都应具有相同类型的数据。

创建数据框

使用 data.frame() 函数创建数据框:

# Create a data frame
Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

# Print the data frame
Data_Frame

结果为:

  Training Pulse Duration
1 Strength   100       60
2  Stamina   150       30
3    Other   120       45

汇总数据

使用 summary() 函数来汇总数据框中的数据:

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

Data_Frame

summary(Data_Frame)

结果为:

   Training             Pulse          Duration   
 Length:3           Min.   :100.0   Min.   :30.0  
 Class :character   1st Qu.:110.0   1st Qu.:37.5  
 Mode  :character   Median :120.0   Median :45.0  
                    Mean   :123.3   Mean   :45.0  
                    3rd Qu.:135.0   3rd Qu.:52.5  
                    Max.   :150.0   Max.   :60.0

你将在 R 教程的统计部分了解有关 summary() 函数的更多信息。

访问数据

我们可以使用单括号 []、双括号 [[]]$ 来访问数据框中的列:

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

Data_Frame[1]

Data_Frame[["Training"]]

Data_Frame$Training

添加行

使用 rbind() 函数在数据框中添加新行:

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

# Add a new row
New_row_DF <- rbind(Data_Frame, c("Strength", 110, 110))

# Print the new row
New_row_DF

添加列

使用 cbind() 函数在数据框中添加新列:

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

# Add a new column
New_col_DF <- cbind(Data_Frame, Steps = c(1000, 6000, 2000))

# Print the new column
New_col_DF

删除行和列

使用 c() 函数删除数据框中的行和列:

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

# Remove the first row and column
Data_Frame_New <- Data_Frame[-c(1), -c(1)]

# Print the new data frame
Data_Frame_New

行数和列数

使用 dim() 函数可获取数据框中的行数和列数:

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

dim(Data_Frame)

你还可以使用 ncol() 函数查找列数,使用 nrow() 查找行数:

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

ncol(Data_Frame)
nrow(Data_Frame)

数据框长度

使用 length() 函数查找数据框中的列数(类似于 ncol() 函数):

Data_Frame <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

length(Data_Frame)

合并数据框

使用 rbind() 函数垂直组合 R 中的两个或多个数据框:

Data_Frame1 <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

Data_Frame2 <- data.frame (
  Training = c("Stamina", "Stamina", "Strength"),
  Pulse = c(140, 150, 160),
  Duration = c(30, 30, 20)
)

New_Data_Frame <- rbind(Data_Frame1, Data_Frame2)
New_Data_Frame

并使用 cbind() 函数水平组合 R 中的两个或多个数据框:

Data_Frame3 <- data.frame (
  Training = c("Strength", "Stamina", "Other"),
  Pulse = c(100, 150, 120),
  Duration = c(60, 30, 45)
)

Data_Frame4 <- data.frame (
  Steps = c(3000, 6000, 2000),
  Calories = c(300, 400, 300)
)

New_Data_Frame1 <- cbind(Data_Frame3, Data_Frame4)
New_Data_Frame1
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