将简单文本文件读入R-BLS数据
我试图理解如何将BLS数据库中的一些文本文件读入R将简单文本文件读入R-BLS数据,r,read.table,R,Read.table,我试图理解如何将BLS数据库中的一些文本文件读入R url <- "http://download.bls.gov/pub/time.series/oe/oe.datatype" datatype <- read.table(url) Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :line 1 did not have 6 elements 我还试图下载并检查该文件,但不确定
url <- "http://download.bls.gov/pub/time.series/oe/oe.datatype"
datatype <- read.table(url)
Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings, :line 1
did not have 6 elements
我还试图下载并检查该文件,但不确定我在记事本++中看到了什么
download.file(url, "datatype.txt")
datatype <- read.table("datatype.txt", sep='\t')
datatype
datatype_code datatype_name
01 Employment NA
02 Employment percent relative standard error NA
03 Hourly mean wage NA
04 Annual mean wage NA
download.file(url,“datatype.txt”)
数据类型正如@zx8754所指出的,这个特定的文件在每一行中都有一个额外的制表符“\t”,头行除外
您可以读取不带标头的文件:
url <- "http://download.bls.gov/pub/time.series/oe/oe.datatype"
df <- read.delim(url, skip = 1, header = FALSE)
head(df)
# V1 V2 V3
# 1 1 Employment NA
# 2 2 Employment percent relative standard error NA
# 3 3 Hourly mean wage NA
# 4 4 Annual mean wage NA
# 5 5 Wage percent relative standard error NA
# 6 6 Hourly 10th percentile wage NA
url这里有一个很棒的tidyverse选项。事实证明,readr::read_tsv可以有效地处理这个问题
library(tidyverse)
df <- read_tsv(url)
head(df)
# A tibble: 6 x 2
datatype_code datatype_name
<chr> <chr>
1 01 Employment
2 02 Employment percent relative standard error
3 03 Hourly mean wage
4 04 Annual mean wage
5 05 Wage percent relative standard error
6 06 Hourly 10th percentile wage
库(tidyverse)
如果这个几乎可以工作,则删除标题:data.table::fread(“http://download.bls.gov/pub/time.series/oe/oe.datatype,colClasses=rep(“character”,3))[,1:2,with=FALSE]
。这些文件很奇怪,每行末尾都有额外的制表符,除了标题。感谢您指出额外的制表符不在标题行上。帮助我理解错误的原因。谢谢你的帮助。我可以在下载的文件末尾手动添加制表符,但根据您的提示,我可以调整脚本,避免手动调整任何内容。谢谢谢谢你,本。事实上,我最近又在重新审视这个问题。tidyverse readr函数运行良好。出于好奇,您是否收到了一堆警告消息?我收到了,但我相信它们是解析过程的一部分。有关更多信息,请参阅渐晕图和>问题(df)。然而,我无法解释。
download.file(url, "datatype.txt")
datatype <- read.table("datatype.txt", sep='\t')
datatype
datatype_code datatype_name
01 Employment NA
02 Employment percent relative standard error NA
03 Hourly mean wage NA
04 Annual mean wage NA
url <- "http://download.bls.gov/pub/time.series/oe/oe.datatype"
df <- read.delim(url, skip = 1, header = FALSE)
head(df)
# V1 V2 V3
# 1 1 Employment NA
# 2 2 Employment percent relative standard error NA
# 3 3 Hourly mean wage NA
# 4 4 Annual mean wage NA
# 5 5 Wage percent relative standard error NA
# 6 6 Hourly 10th percentile wage NA
header <- read.delim(url, nrows = 1, header = FALSE, stringsAsFactors = FALSE)
names(df) <- header
head(df)
# datatype_code datatype_name NA
# 1 1 Employment NA
# 2 2 Employment percent relative standard error NA
# 3 3 Hourly mean wage NA
# 4 4 Annual mean wage NA
# 5 5 Wage percent relative standard error NA
# 6 6 Hourly 10th percentile wage NA
df <- df[-3]
library(tidyverse)
df <- read_tsv(url)
head(df)
# A tibble: 6 x 2
datatype_code datatype_name
<chr> <chr>
1 01 Employment
2 02 Employment percent relative standard error
3 03 Hourly mean wage
4 04 Annual mean wage
5 05 Wage percent relative standard error
6 06 Hourly 10th percentile wage