极客教程R语言 数据框架Data Frames
数据框架是一个表格或类似两维数组的结构，每一列包含一个变量的值，每一行包含来自每一列的一组值。
以下是数据框架的特点。
- 列名不能为空。
- 行名必须是唯一的。
- 数据存储在数据框中可以是数值、因子或字符类型。
- 每个列应包含相同数量的数据项。
创建数据框架
# Create the data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01", "2013-09-23", "2014-11-15", "2014-05-11",
"2015-03-27")),
stringsAsFactors = FALSE
)
# Print the data frame.
print(emp.data)
当我们执行上面的代码时，它会产生以下结果 –
emp_id emp_name salary start_date
1 1 Rick 623.30 2012-01-01
2 2 Dan 515.20 2013-09-23
3 3 Michelle 611.00 2014-11-15
4 4 Ryan 729.00 2014-05-11
5 5 Gary 843.25 2015-03-27
获取数据框的结构
可以使用 str() 函数来查看数据框的结构。
# Create the data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01", "2013-09-23", "2014-11-15", "2014-05-11",
"2015-03-27")),
stringsAsFactors = FALSE
)
# Get the structure of the data frame.
str(emp.data)
当我们执行上述代码时，它会产生以下结果 –
'data.frame': 5 obs. of 4 variables:
emp_id : int 1 2 3 4 5 emp_name : chr "Rick" "Dan" "Michelle" "Ryan" ...
salary : num 623 515 611 729 843 start_date: Date, format: "2012-01-01" "2013-09-23" "2014-11-15" "2014-05-11" ...
数据框的数据摘要
通过应用 summary() 函数可以获取数据的统计摘要和特性。
# Create the data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01", "2013-09-23", "2014-11-15", "2014-05-11",
"2015-03-27")),
stringsAsFactors = FALSE
)
# Print the summary.
print(summary(emp.data))
执行上面的代码时，会产生以下结果−
emp_id emp_name salary start_date
Min. :1 Length:5 Min. :515.2 Min. :2012-01-01
1st Qu.:2 Class :character 1st Qu.:611.0 1st Qu.:2013-09-23
Median :3 Mode :character Median :623.3 Median :2014-05-11
Mean :3 Mean :664.4 Mean :2014-01-14
3rd Qu.:4 3rd Qu.:729.0 3rd Qu.:2014-11-15
Max. :5 Max. :843.2 Max. :2015-03-27
从数据框中提取数据
使用列名提取数据框中的特定列。
# Create the data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01","2013-09-23","2014-11-15","2014-05-11",
"2015-03-27")),
stringsAsFactors = FALSE
)
# Extract Specific columns.
result <- data.frame(emp.dataemp_name,emp.datasalary)
print(result)
当我们执行以上代码时，会产生以下结果−
emp.data.emp_name emp.data.salary
1 Rick 623.30
2 Dan 515.20
3 Michelle 611.00
4 Ryan 729.00
5 Gary 843.25
提取前两行，然后提取所有列
# Create the data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01", "2013-09-23", "2014-11-15", "2014-05-11",
"2015-03-27")),
stringsAsFactors = FALSE
)
# Extract first two rows.
result <- emp.data[1:2,]
print(result)
执行上述代码时，会产生以下结果−
emp_id emp_name salary start_date
1 1 Rick 623.3 2012-01-01
2 2 Dan 515.2 2013-09-23
提取第3rd和第5th行，第2nd和第4th列
# Create the data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01", "2013-09-23", "2014-11-15", "2014-05-11",
"2015-03-27")),
stringsAsFactors = FALSE
)
# Extract 3rd and 5th row with 2nd and 4th column.
result <- emp.data[c(3,5),c(2,4)]
print(result)
当我们执行上面的代码时，会产生以下结果 −
emp_name start_date
3 Michelle 2014-11-15
5 Gary 2015-03-27
扩展数据框
可以通过添加列和行来扩展数据框。
添加列
只需使用新列名添加列向量。
# Create the data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01", "2013-09-23", "2014-11-15", "2014-05-11",
"2015-03-27")),
stringsAsFactors = FALSE
)
# Add the "dept" coulmn.
emp.data$dept <- c("IT","Operations","IT","HR","Finance")
v <- emp.data
print(v)
当我们执行上面的代码时，会产生以下结果−
emp_id emp_name salary start_date dept
1 1 Rick 623.30 2012-01-01 IT
2 2 Dan 515.20 2013-09-23 Operations
3 3 Michelle 611.00 2014-11-15 IT
4 4 Ryan 729.00 2014-05-11 HR
5 5 Gary 843.25 2015-03-27 Finance
添加行
要向现有数据框中永久添加更多行，我们需要以与现有数据框相同的结构引入新行，并使用 rbind() 函数。
在下面的示例中，我们创建一个带有新行的数据框，并将其与现有数据框合并，以创建最终的数据框。
# Create the first data frame.
emp.data <- data.frame(
emp_id = c (1:5),
emp_name = c("Rick","Dan","Michelle","Ryan","Gary"),
salary = c(623.3,515.2,611.0,729.0,843.25),
start_date = as.Date(c("2012-01-01", "2013-09-23", "2014-11-15", "2014-05-11",
"2015-03-27")),
dept = c("IT","Operations","IT","HR","Finance"),
stringsAsFactors = FALSE
)
# Create the second data frame
emp.newdata <- data.frame(
emp_id = c (6:8),
emp_name = c("Rasmi","Pranab","Tusar"),
salary = c(578.0,722.5,632.8),
start_date = as.Date(c("2013-05-21","2013-07-30","2014-06-17")),
dept = c("IT","Operations","Fianance"),
stringsAsFactors = FALSE
)
# Bind the two data frames.
emp.finaldata <- rbind(emp.data,emp.newdata)
print(emp.finaldata)
当我们执行上述代码时，会产生以下结果：
emp_id emp_name salary start_date dept
1 1 Rick 623.30 2012-01-01 IT
2 2 Dan 515.20 2013-09-23 Operations
3 3 Michelle 611.00 2014-11-15 IT
4 4 Ryan 729.00 2014-05-11 HR
5 5 Gary 843.25 2015-03-27 Finance
6 6 Rasmi 578.00 2013-05-21 IT
7 7 Pranab 722.50 2013-07-30 Operations
8 8 Tusar 632.80 2014-06-17 Fianance