esProc's two-dimensional structured
data type is sequence table object (TSeq). Sequence table is based on records,
with multiple records forming a row-styled two-dimensional table. In
combination with the column name, this two-dimensional table can form a
complete data structure. R language is based on vector, with multiple vectors
forming a column-styled two-dimensional table. In combination with the column
name, the two-dimensional table can form a complete data structure.
These underlying mechanisms affect actual
user experience. In the following part we will compare the difference in
practical use between sequence table object and data frame, in terms of basic
functions, advanced features, actual use cases and test results.
Note:
Primitive functions of development language are to be used in the following
comparisons, the third party extension packages won’t be involved.
Basic functions
Example 1:retrieve two-dimensional
structured data from the file, and access the value of the second column in the
first row by coordinates.
Data frame:
data<-read.table("e:/sales.txt",header=TRUE,sep="\t")
result<-data[1,2]
Sequence
table:
=data=file("e:/sales.txt").import@t()
=data(1).#2
Comparison:
there is no significant difference in the most basic functions.
Note: the
sales.txt file is tab separated structured data, and the first few lines are as
following:
Example 2: access the value
of the second column in the first row, by row number and by field name.
Data frame:
Result1<-data$Client[1]
Result2<-data[1,]$Client
Sequence table:
=data(1).(Client)
=data.(Client)(1)
Comparison: there is no significant
difference between the two.
Example 3: Access column
data. There are two scenarios, and each falls into two situations: access by
column number and column names:retrieve only the second column, or retrieve a
combination of the second column and the fourth column.
Data frame:
Result1<-data[2]
Result2<-data[,c(2,4)]
Result3<-data$Client
Result4<-data[,c("Client","Amount")]
Sequence table:
=data.(#2)
=data.new(#2,#4)
=data.(Client)
=data.new(Client,Amount)
Comparison: Both can access the column
data. The only difference is in the syntax for retrieving multiple column data.
Data frame is retrieving the number directly, while with sequence table a new sequence
table will be build with the new function.
Although the syntax is different, the actual methods used are the same: both
are duplicating two columns of data from the original objects to new objects.
Example 4: record
manipulation. Includes: retrieve the first two records, appending records,
inserting record in the second row, deleting the record in the second row.
Data frame：
Record1<-data[c(1,2),]
append<-
data.frame(OrderID=152, Client="CA", SellerId=5, Amount=2961.40, OrderDate="2010-12-5 0:00:00")
data<-
rbind(data, append)
insert<-data.frame(OrderID=153, Client="RA", SellerId=4, Amount=1931.20, OrderDate="2009-11-5 0:00:00")
data<-rbind(data[1,],
insert,data[2:151,])
data<-data[-2,]
Sequence table:
=data([1,2])
=data.insert(0,152:OrderID,"CA":Client,5:SellerId,2961.40:Amount,"2010-12-5
0:00:00":OrderDate)
=data.insert(2,153:OrderID,"RA":Client,4:SellerId,1931.20:Amount,"2009-11-5
0:00:00":OrderDate)
=data.delete(2)
Comparison: record manipulation is possible
in both ways. esProc is relatively more convenient. It can use insert function to append or insert
records directly to sequence table, while in R language we need to split the
data frame and then merge them again to achieve the same result in an indirect
way.
Summary:
As both sequence table and data frame are
structured, two-dimensional data object, no significant difference exists in
basic functions for data reading/writing,data access and maintenance.
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