从文本中删除字符串并放入单独的列中答案

【问题标题】：Remove strings from text and place into separate columns从文本中删除字符串并放入单独的列中
【发布时间】：2020-04-15 18:51:48
【问题描述】：

我正在尝试删除下面字符串中的纬度/经度坐标，以将其放入 R 中的两个单独的列“lat”和“long”中。我在 dplyr 中使用单独的运气并不好。任何帮助将不胜感激。

data_clean <- c("7205 MILLS CIVIC PKWY\nWEST DES MOINES 50266\n(41.561342, -93.806489)",
                "305 AIRPORT RD\nAMES 50010\n(42.001123, -93.61365)",                   
                "210 EAST TOWER PARK DR\nWATERLOO 50702\n(42.456362, -92.352552)")      

data_clean_df <- as.data.frame(data_clean)

【问题讨论】：

我想你应该可以在这里找到答案：stackoverflow.com/questions/6208367/…

标签： r data-cleaning

【解决方案1】：

我们可以使用tidyr::extract将data_clean中的数据分成3组。

library(dplyr)
library(tidyr)

data_clean_df %>%
   mutate(data_clean = gsub('\n', '', data_clean)) %>%
   extract(data_clean, into = c('address', 'lat', 'lon'), 
      regex = '(.*)\\((.*),\\s+(.*)\\)', convert = TRUE)

#                                    data_clean     lat      lon
#1 7205 MILLS CIVIC PKWY\nWEST DES MOINES 50266 41.5613 -93.8065
#2                   305 AIRPORT RD\nAMES 50010 42.0011 -93.6137
#3       210 EAST TOWER PARK DR\nWATERLOO 50702 42.4564 -92.3526

【讨论】：

【解决方案2】：

library(dplyr)
library(tidyr)
library(stringr)

data_clean_df %>% 
  separate(data_clean, into = c("a", "b", "c"), sep = "\n") %>% 
  mutate(c = str_remove_all(c, "\\(|\\)")) %>%
  separate(c, c("lat", "lon"), sep = ", ", convert = TRUE)

                       a                     b      lat       lon
1  7205 MILLS CIVIC PKWY WEST DES MOINES 50266 41.56134 -93.80649
2         305 AIRPORT RD            AMES 50010 42.00112 -93.61365
3 210 EAST TOWER PARK DR        WATERLOO 50702 42.45636 -92.35255

【讨论】：

【解决方案3】：

如果你只是想拉出经纬度的另一种选择：

library(tidyverse)

data_clean <- c("7205 MILLS CIVIC PKWY\nWEST DES MOINES 50266\n(41.561342, -93.806489)",
                "305 AIRPORT RD\nAMES 50010\n(42.001123, -93.61365)",                   
                "210 EAST TOWER PARK DR\nWATERLOO 50702\n(42.456362, -92.352552)")      

data_clean_df <- as.data.frame(data_clean, stringsAsFactors = F)

data_clean_df %>%
  mutate(lat = str_extract(data_clean, "(?<=\\().*?(?=,)"),
         long = str_extract(data_clean, paste0("(?<=", lat, ",\\s).*?(?=\\))")))
#>                                                              data_clean
#> 1 7205 MILLS CIVIC PKWY\nWEST DES MOINES 50266\n(41.561342, -93.806489)
#> 2                    305 AIRPORT RD\nAMES 50010\n(42.001123, -93.61365)
#> 3       210 EAST TOWER PARK DR\nWATERLOO 50702\n(42.456362, -92.352552)
#>         lat       long
#> 1 41.561342 -93.806489
#> 2 42.001123  -93.61365
#> 3 42.456362 -92.352552

【讨论】：

【解决方案4】：

这是使用gsub() 的基本 R 解决方案

df <- data.frame(data_clean = gsub("(.*)\n.*","\\1",data_clean),
                 lat = gsub(".*?\\((.*),.*","\\1",data_clean),
                 lon = gsub(".*,(.*)\\)","\\1",data_clean))

这样

                                    data_clean       lat         lon
1 7205 MILLS CIVIC PKWY\nWEST DES MOINES 50266 41.561342  -93.806489
2                   305 AIRPORT RD\nAMES 50010 42.001123   -93.61365
3       210 EAST TOWER PARK DR\nWATERLOO 50702 42.456362  -92.352552

【讨论】：