Question

我如何在a .txt file on the web上读取此文件并将内容转换为.csv文件？（无论是python还是R，都可以。）

page = readLines('https://www.nass.usda.gov/Data_and_Statistics/County_Data_Files/Frequently_Asked_Questions/county_list.txt')
page <- page[13:4079]
df <- data.frame(matrix(ncol = 5, nrow = 4067))
col_names = c("state", "district", "county", "state_county", "history")
colnames(df) <- col_names
for (row_count in 1:4067){
    df[row_count, 1] = unlist(strsplit(page[row_count], " "))[1]
    df[row_count, 2] = unlist(strsplit(page[row_count], " "))[4]
    df[row_count, 3] = unlist(strsplit(page[row_count], " "))[7]
    df[row_count, 4] = unlist(strsplit(unlist(strsplit(page[row_count], 
           " "))[10], "\t"))[1]
df[row_count, 5] = unlist(strsplit(unlist(strsplit(page[row_count], 
           " "))[10], "\t"))[7]}

第四列中的某些名称由多个单词组成，第四列与第五列之间的间距大小不同，这使我的代码无法正常工作！

Answer 1

这是一个base解决方案

dataStart <- min(which(grepl('^\\d+\\s+\\d+\\s+\\d+\\s+\\w+\\s+\\d$', page, perl = TRUE)))
pageDat <- page[dataStart:length(page)]
pageDat <- gsub("\\s{2,}", ";", pageDat, perl = TRUE)
pageDat <- do.call(rbind, strsplit(pageDat, split = ";"))
# yields
head(pageDat)
     [,1] [,2] [,3]  [,4]         [,5]
[1,] "01" "00" "000" "Alabama"    "1" 
[2,] "01" "10" "033" "Colbert"    "1" 
[3,] "01" "10" "057" "Fayette"    "2" 
[4,] "01" "10" "059" "Franklin"   "1" 
[5,] "01" "10" "075" "Lamar"      "2" 
[6,] "01" "10" "077" "Lauderdale" "1"

其中page如上所述。

Answer 2

另一种基本解决方案，比@ nate.edwinton（来源中的评论）更罗word：

# read the file as fixed field width file
page <- read.fwf( "https://www.nass.usda.gov/Data_and_Statistics/County_Data_Files/Frequently_Asked_Questions/county_list.txt",
    widths = c( 5, 5, 6, 45 ), skip = 12, sep = "^" )
# remove the last line containing NAs
page <- page[ -length( page[,1] ), ]
# convert factors to character
page[ , 4 ] <- as.character( page[ , 4 ] )
# the last character of the fourth field contains the history, move it to a separate variable
page[ 5 ] <- substr( page[ , 4 ], nchar( page[ , 4 ] ), nchar( page[ , 4 ] ) )
# set the column names
colnames( page )[] <- c( "state", "district", "county", "state_county", "history" )
# remove the history info from the state_county field
page[ , 4 ] <- gsub( "[12]$", "", page[ , 4 ] )
# get rid of the tabs
page[ , 4 ] <- gsub( "\t", "", page[ , 4 ] )
# format the output as in the original file (may be necessary or not)
page[ , 1 ] <- sprintf( "%02i", page[ , 1 ] )
page[ , 2 ] <- sprintf( "%02i", page[ , 2 ] )
page[ , 3 ] <- sprintf( "%03i", page[ , 3 ] )

这给了我们

head( page, 15 )
   state district county          state_county history
1     01       00    000               Alabama       1
2     01       10    033               Colbert       1
3     01       10    057               Fayette       2
4     01       10    059              Franklin       1
5     01       10    075                 Lamar       2
6     01       10    077            Lauderdale       1
7     01       10    079              Lawrence       1
8     01       10    083             Limestone       1
9     01       10    089               Madison       1
10    01       10    093                Marion       1
11    01       10    103                Morgan       1
12    01       10    133               Winston       1
13    01       10    888 D10 Combined Counties       1
14    01       10    999   D10 Northern Valley       1
15    01       20    009                Blount       1

Answer 3

这样的帮助吗？

library(tidyverse)
url <- "https://www.nass.usda.gov/Data_and_Statistics/County_Data_Files/Frequently_Asked_Questions/county_list.txt"
df <- read_lines(url, skip = 12) %>%
    data.frame(col = .) %>%
    separate(col, into = paste0("X", 1:5), sep = "\\s{2,}", extra = "drop") %>%
    na.omit()
head(df)
#  X1 X2  X3         X4 X5
#1 01 00 000    Alabama  1
#2 01 10 033    Colbert  1
#3 01 10 057    Fayette  2
#4 01 10 059   Franklin  1
#5 01 10 075      Lamar  2
#6 01 10 077 Lauderdale  1

说明：

用readr::read_lines逐行读取文件
将条目存储在col的{{1}}列中
连续将任何> = 2个空白字符（空格，制表符）上的条目分开并存储在列data.frame
删除X1...X5

从网上读取.txt文件并将其转换为数据框

3 个答案: