高级文件读取
在 R 中使用 data.table 进行数据处理
Matt Dowle, Arun Srinivasan
Instructors, DataCamp
用 integer64 读取大整数
- R 默认只能表示 ≤ 2^31 - 1 = 2147483647 的数字
- 大整数会自动读取为
integer64类型，由bit64包提供
ans <- fread("id,name\n1234567890123,Jane\n5284782381811,John\n")
ans
id name
1234567890123 Jane
5284782381811 John
class(ans$id)
"integer64"
用 colClasses 指定列类型
str <- "x1,x2,x3,x4,x5\n1,2,1.5,true,cc\n3,4,2.5,false,ff"ans <- fread(str, colClasses = c(x5 = "factor")) str(ans)
Classes 'data.table' and 'data.frame': 2 obs. of 5 variables:
$ x1: int 1 3
$ x2: int 2 4
$ x3: num 1.5 2.5
$ x4: logi TRUE FALSE
$ x5: Factor w/ 2 levels "cc","ff": 1 2
用 colClasses 指定列类型
ans <- fread(str, colClasses = c("integer", "integer",
"numeric", "logical", "factor"))
str(ans)
Classes 'data.table' and 'data.frame': 2 obs. of 5 variables:
$ x1: int 1 3
$ x2: int 2 4
$ x3: num 1.5 2.5
$ x4: logi TRUE FALSE
$ x5: Factor w/ 2 levels "cc","ff": 1 2
用 colClasses 指定列类型
str <- "x1,x2,x3,x4,x5,x6\n1,2,1.5,2.5,aa,bb\n3,4,5.5,6.5,cc,dd"
ans <- fread(str, colClasses = list(numeric = 1:4, factor = c("x5", "x6")))
str(ans)
Classes 'data.table' and 'data.frame': 2 obs. of 6 variables:
$ x1: num 1 3
$ x2: num 2 4
$ x3: num 1.5 5.5
$ x4: num 2.5 6.5
$ x5: Factor w/ 2 levels "aa","cc": 1 2
$ x6: Factor w/ 2 levels "bb","dd": 1 2
fill 参数
str <- "1,2\n3,4,a\n5,6\n7,8,b"
fread(str)
V1 5 6
7 8 b
Warning message:
In fread(str) :
Detected 2 column names but the data has 3 columns (i.e. invalid file).
Added 1 extra default column name for the first column which is guessed to
be row names or an index.
Use setnames() afterwards if this guess is not correct,
or fix the file write command that created the file to create a valid file.
fill 参数
fread(str, fill = TRUE)
V1 V2 V3
1 2
3 4 a
5 6
7 8 b
na.strings 参数
缺失值常被编码为："999"、"##NA" 或 "N/A"
str <- "x,y,z\n1,###,3\n2,4,###\n#N/A,7,9"
ans <- fread(str, na.strings = c("###", "#N/A"))
ans
x y z
1 NA 3
2 4 NA
NA 7 9
让我们练习吧！
在 R 中使用 data.table 进行数据处理
