資料影格是一個表或二維類似陣列的結構，其中每列包含一個變數的值，每行包含來自每一列的一組值。
以下是資料影格的特徵 -
建立資料影格
# 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("2017-01-01", "2017-09-23", "2017-11-15", "2017-05-11",
"2018-03-27")),
stringsAsFactors = FALSE
)
# Print the data frame.
print(emp.data)
當我們執行上述程式碼時，會產生以下結果 -
emp_id emp_name salary start_date
1 1 Rick 623.30 2017-01-01
2 2 Dan 515.20 2017-09-23
3 3 Michelle 611.00 2017-11-15
4 4 Ryan 729.00 2017-05-11
5 5 Gary 843.25 2018-03-27
通過使用str()函式可以檢視資料影格的結構，參考以下程式碼實現 -
# 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("2017-01-01", "2017-09-23", "2017-11-15", "2017-05-11",
"2018-03-27")),
stringsAsFactors = FALSE
)
# Get the structure of the data frame.
str(emp.data)
當我們執行上述程式碼時，會產生以下結果 -
'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: "2017-01-01" "2017-09-23" ...
資料的統計摘要和性質可以通過應用summary()函式獲得。
# 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("2015-01-01", "2016-09-23", "2017-11-15", "2018-05-11",
"2018-03-27")),
stringsAsFactors = FALSE
)
# Print the summary.
當我們執行上述程式碼時，會產生以下結果 -
emp_id emp_name salary start_date
Min. :1 Length:5 Min. :515.2 Min. :2015-01-01
1st Qu.:2 Class :character 1st Qu.:611.0 1st Qu.:2016-09-23
Median :3 Mode :character Median :623.3 Median :2017-11-15
Mean :3 Mean :664.4 Mean :2017-03-28
3rd Qu.:4 3rd Qu.:729.0 3rd Qu.:2018-03-27
Max. :5 Max. :843.2 Max. :2018-05-11
使用列名稱從資料影格中提取特定列。
# 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.data$emp_name,emp.data$salary)
print(result)
當我們執行上述程式碼時，會產生以下結果 -
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
提取前兩行，然後提取所有列 -
# 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)
當我們執行上述程式碼時，會產生以下結果 -
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2列和第4列和第3行和第5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)
當我們執行上述程式碼時，會產生以下結果 -
emp_name start_date
3 Michelle 2014-11-15
5 Gary 2015-03-27
可以通過新增列和行來擴充套件資料影格。
新增列
只需使用新的列名來新增列向量。參考以下範例程式碼 -
# 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)
當我們執行上述程式碼時，會產生以下結果 -
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
新增行
要將更多行永久新增到現有資料影格，需要使用與現有資料影格相同結構的新行，並使用rbind()函式。
在下面的範例中，我們使用新行建立一個資料影格，並將其與現有的資料影格進行合併，以建立最終的資料影格。
# 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)
當我們執行上述程式碼時，會產生以下結果 -
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