我从来没有刮过。仅从下面的链接(从头SRUS43 KMSR 271039
开始,以.END
结尾)从主灰色框中删除文本是否直截了当?我的最终目标是从所有文本中基本上有三列整齐的数据:五位数代码,以英寸为单位的值和盆地高程描述,因此欢迎任何处理文本格式的指针。
感谢您的任何帮助。
阅读文本相当容易(参见@DiceBoyT答案)。清理三列的格式有点复杂。下面可以使用一些清理(特别是使用正则表达式),但它完成了工作:
library(tidyverse)
library(rvest)
text <- read_html("https://www.nohrsc.noaa.gov/shef_archive/index.html?rfc=cnrfc&product=swe&year=2019&month=3&day=27&hour=6") %>%
html_node(".notes") %>%
html_text()
df <- tibble(txt = read_lines(text))
df %>%
mutate(
row = row_number(),
with_code = str_extract(txt, "^[A-z0-9]{5}\\s+\\d+(\\.)?\\d"),
wo_code = str_extract(txt, "^:?\\s+\\d+(\\.)?\\d") %>% str_extract("[:digit:]+\\.?[:digit:]"),
basin_desc = if_else(!is.na(with_code), lag(txt, 1), NA_character_) %>% str_sub(start = 2)
) %>%
separate(with_code, c("code", "val"), sep = "\\s+") %>%
mutate(
combined_val = case_when(
!is.na(val) ~ val,
!is.na(wo_code) ~ wo_code,
TRUE ~ NA_character_
) %>% as.numeric
) %>%
filter(!is.na(combined_val)) %>%
mutate(
code = zoo::na.locf(code),
basin_desc = zoo::na.locf(basin_desc)
) %>%
select(
code, combined_val, basin_desc
)
#> # A tibble: 643 x 3
#> code combined_val basin_desc
#> <chr> <dbl> <chr>
#> 1 ACSC1 0 San Antonio Ck - Sunol
#> 2 ADLC1 0 Arroyo De La Laguna
#> 3 ADOC1 0 Santa Ana R - Prado Dam
#> 4 AHOC1 0 Arroyo Honda nr San Jose
#> 5 AKYC1 41 SF American nr Kyburz
#> 6 AKYC1 3.2 SF American nr Kyburz
#> 7 AKYC1 42.2 SF American nr Kyburz
#> 8 ALQC1 0 Alamo Canal nr Pleasanton
#> 9 ALRC1 0 Alamitos Ck - Almaden Res
#> 10 ANDC1 0 Coyote Ck - Anderson Res
#> # ... with 633 more rows
由reprex package创建于2019-03-27(v0.2.1)
使用rvest
非常简单:
library(rvest)
text <- read_html("https://www.nohrsc.noaa.gov/shef_archive/index.html?rfc=cnrfc&product=swe&year=2019&month=3&day=27&hour=6") %>%
html_node(".notes") %>%
html_text()