R Data Frames

Data frame (Data frame) can be understood as the 'table' we often say.

Data frame is a data structure in R language, which is a special two-dimensional list.

Each column of the data frame has a unique column name, the length of which is equal, the data type of the same column needs to be consistent, and the data types of different columns can be different.

R language data frames are created using the data.frame() function, the syntax format is as follows:

data.frame(…, row.names = NULL, check.rows = FALSE,
　　　　　　　　　　　check.names = TRUE, fix.empty.names = TRUE,
　　　　　　　　　　　stringsAsFactors = default.stringsAsFactors())

• ...: Column vector, can be of any type (character, numeric, logical), generally represented in the form of tag = value, or just value.

• row.names: Column name, default is NULL, can be set to a single number, string, or a vector of string and number.

• check.rows: Check if the row names and lengths are consistent.

• check.names: Check if the variable names of the data frame are valid.

• fix.empty.names: Set whether the unnamed parameters are automatically named.

• stringsAsFactors: Boolean value, whether characters are converted to factors, factory-fresh's default value is TRUE, which can be modified by setting options (stringsAsFactors=FALSE).

The following creates a simple data frame containing Name, ID, Monthly Salary:

table　=　data.frame(
　　　　Name = c("Zhang San", "Li Si"),
　　　　Work Number　=　c("001","002",
　　　　Monthly Salary　=　c(1000,　2000)
　　　　
)
print(table) # View table data

The output of the above code is as follows:

Name　Work Number　Monthly Salary
1　Zhangsan　　001　1000
2　Lishiqi　　002　2000

The data structure of the data frame can be obtained through str() The function to display is:

table　=　data.frame(
　　　　Name = c("Zhang San", "Li Si"),
　　　　Work Number　=　c("001","002",
　　　　Monthly Salary　=　c(1000,　2000)
)
# Get Data Structure
str(table)

The output of the above code is as follows:

'data.frame':　　　2　obs. of　　3　variables:
　$ Name: chr "Zhang San" "Li Si"
　$ ID: chr "001" 002"
　$ Monthly Salary: num　　1000　2000

summary() You can display the summary information of the data frame:

table　=　data.frame(
　　　　Name = c("Zhang San", "Li Si"),
　　　　Work Number　=　c("001","002",
　　　　Monthly Salary　=　c(1000,　2000)
　　　　
)
# Show Summary
print(summary(table))

The output of the above code is as follows:

Name ID Monthly Salary　　　　　
Length:2　　　　　　　　　　　Length:2　　　　　　　　　　　Min. :1000　　
Class :character Class :character　　　1st Qu. :1250　　
Mode :character Mode :character Median :1500　　
　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　Mean :1500　　
　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　3rd Qu. :1750　　
　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　　Max. :2000

We can also extract specified columns:

table　=　data.frame(
　　　　Name = c("Zhang San", "Li Si"),
　　　　Work Number　=　c("001","002",
　　　　Monthly Salary　=　c(1000,　2000)
)
# Extract specified columns
result　<-　data.frame(table$Name,table$Salary)
print(result)

The output of the above code is as follows:

table.Name table.Salary
1　　　　　　　Zhang San　　　　　　　1000
2　　　　　　　Li Si　　　　　　　2000

The following format displays the first two rows:

table　=　data.frame(
　　　　Name　=　c("Zhangsan",　"Lishiqi","Wangwu"),
　　　　Work Number　=　c("001","002","003",
　　　　Monthly Salary　=　c(1000,　2000,3000)
)
print(table)
# Extract the first two rows
print("---Output the first two rows----))
result　<-　table[1:2,]
print(result)

The output of the above code is as follows:

Name　Work Number　Monthly Salary
1　Zhangsan　　001　1000
2　Lishiqi　　002　2000
3　Wangwu　　003　3000
[1] "---Output the first two rows----"
　　Name　Work Number　Monthly Salary
1　Zhangsan　　001　1000
2　Lishiqi　　002　2000

We can read data from a specific column of a specified row in a similar way to coordinates, the following example reads the 2 ,3 The row number 1 ,2 Column Data: :

table　=　data.frame(
　　　　Name　=　c("Zhangsan",　"Lishiqi","Wangwu"),
　　　　Work Number　=　c("001","002","003",
　　　　Monthly Salary　=　c(1000,　2000,3000)
)
# Read the　2　,3　The row number　1　,2　Column Data:
result　<-　table[c(2,3)),c(1,2)]
print(result)

The output of the above code is as follows:

Name ID
2　Lishiqi　　002
3　Wangwu　　003

Expand Data Frame

We can expand an existing data frame, the following example adds a department column:

table　=　data.frame(
　　　　Name　=　c("Zhangsan",　"Lishiqi","Wangwu"),
　　　　Work Number　=　c("001","002","003",
　　　　Monthly Salary　=　c(1000,　2000,3000)
)
# Add Department Column
table$Department <-　c("Operation","Technology","Editor")
print(table)

The output of the above code is as follows:

Name ID Monthly Salary Department
1　Zhangsan　　001　1000 Operation
2　Lishiqi　　002　2000　Technology
3　Wangwu　　003　3000　Edit

We can use cbind() Function to combine multiple vectors into a data frame：

#　Create vector
sites　<-　c("Google","w3codebox","Taobao")
likes　<-　c(222,111,123)
url　<-　c("www.google.com","www.oldtoolbag.com,"www.taobao.com")
#　Combine vectors into a data frame
addresses　<-　cbind(sites,likes,url)
#　View data frame
print(addresses)

The output of the above code is as follows:

　　　　　sites　　　　likes　url　　　　　　　　　　　　　
[1,]　"Google"　"222"　"www.google.com"
[2,]　"w3codebox"　"111"　"www.oldtoolbag.com"
[3,]　"Taobao"　"123"　"www.taobao.com"

If you want to merge two data frames, you can use rbind() Function：

table　=　data.frame(
　　　　Name　=　c("Zhangsan",　"Lishiqi","Wangwu"),
　　　　Work Number　=　c("001","002","003",
　　　　Monthly Salary　=　c(1000,　2000,3000)
)
newtable　=　data.frame(
　　　　Name　=　c("Xiaoming",　"Little White"),
　　　　Work Number　=　c("101",102",
　　　　Monthly Salary　=　c(5000,　7000)
)
#　Merge two data frames
result　<-　rbind(table,newtable)
print(result)

The output of the above code is as follows:

Name　Work Number　Monthly Salary
1　Zhangsan　　001　1000
2　Lishiqi　　002　2000
3　Wangwu　　003　3000
4　Xiaoming　　101　5000
5　Little White　　102　7000