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鍍金池/ 教程/ 數(shù)據(jù)分析&挖掘/ R語言數(shù)據(jù)幀
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R語言數(shù)據(jù)幀

數(shù)據(jù)幀是一個(gè)表或二維類似數(shù)組的結(jié)構(gòu)，其中每列包含一個(gè)變量的值，每行包含來自每一列的一組值。

以下是數(shù)據(jù)幀的特征 -

  • 列名稱應(yīng)該不為空。
  • 行名稱應(yīng)該是唯一的。
  • 存儲(chǔ)在數(shù)據(jù)幀中的數(shù)據(jù)可以是數(shù)字，因子或字符類型。
  • 每列應(yīng)包含相同數(shù)量的數(shù)據(jù)項(xiàng)。

創(chuàng)建數(shù)據(jù)幀

# 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(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)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

獲取數(shù)據(jù)幀的結(jié)構(gòu)

通過使用str()函數(shù)可以查看數(shù)據(jù)幀的結(jié)構(gòu)，參考以下代碼實(shí)現(xiàn) - 

# 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(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)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" ...

數(shù)據(jù)幀數(shù)據(jù)摘要

數(shù)據(jù)的統(tǒng)計(jì)摘要和性質(zhì)可以通過應(yīng)用summary()函數(shù)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(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)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

從數(shù)據(jù)幀提取數(shù)據(jù)

使用列名稱從數(shù)據(jù)幀中提取特定列。

# 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(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)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)

當(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)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(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)果 -

  emp_name start_date
3 Michelle 2014-11-15
5     Gary 2015-03-27

擴(kuò)展數(shù)據(jù)幀

可以通過添加列和行來擴(kuò)展數(shù)據(jù)幀。

添加列

只需使用新的列名來添加列向量。參考以下示例代碼 - 

# 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(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)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

要將更多行永久添加到現(xiàn)有數(shù)據(jù)幀，需要使用與現(xiàn)有數(shù)據(jù)幀相同結(jié)構(gòu)的新行，并使用rbind()函數(shù)。

在下面的示例中，我們使用新行創(chuàng)建一個(gè)數(shù)據(jù)幀，并將其與現(xiàn)有的數(shù)據(jù)幀進(jìn)行合并，以創(chuàng)建最終的數(shù)據(jù)幀。

# 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(dāng)我們執(zhí)行上述代碼時(shí)，會(huì)產(chǎn)生以下結(jié)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