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r - 将 tibble 与来自同一 tibble 的数据合并

问题描述

我有一些污染监测站的数据。我正在尝试创建一个新的 tibble，这样如果数据满足某些条件，它将被合并到列的左侧elevation。要满足的条件是 water_bodies ( water_body) 相等，并且高程 ( elevation) 小于将要合并到的观测值。

试图用语言来解释这听起来很愚蠢，因为英语不是我的第一语言，但这里有一个我正在寻找的例子，我认为它可以解决所有问题。

这是数据：

tribble(
  ~id_emca,       ~water_body,      ~id_estmun,   ~dbo,    ~elevation,
  "DLAGU20",   "RIO CHICALOTE_16",     1005,      364.92,    1865,
  "DLAGU20",   "RIO CHICALOTE_17",     1005,      485.91,    1865,
  "DLAGU20",   "RIO CHICALOTE_18",     1005,      270.32,    1865,
  "DLBAJ155",  "RIO MULEGE_12",        3003,      20.3,      215,
  "DLBAJ155",  "RIO MULEGE_13",        3003,      14.005,    215,
  "DLBAJ157",  "RIO CHICALOTE_17",     3007,      315.34,    1677,
  "DLBAJ157",  "RIO CHICALOTE_18",     3007,      430.21,    1677,
  "DLBAJ159",  "RIO MULEGE_13",        3010,      17.89,     477,
  "DLBAJ159",  "RIO MULEGE_14",        3010,      35.98,     477,
  "DLCAM80",   "RIO CHICALOTE_18",     4012,      157.66,    1003,
  "DLCAM85",   "RIO CHICALOTE_18",     4009,      323.02,    573,
  "DLCAM122",  "RIO MULEGE_12",        4001,      37.81,     300
)


id_emca  water_body       id_estmun   dbo elevation
   <chr>    <chr>                <dbl> <dbl>     <dbl>
 1 DLAGU20  RIO CHICALOTE_16      1005 365.       1865
 2 DLAGU20  RIO CHICALOTE_17      1005 486.       1865
 3 DLAGU20  RIO CHICALOTE_18      1005 270.       1865
 4 DLBAJ155 RIO MULEGE_12         3003  20.3       215
 5 DLBAJ155 RIO MULEGE_13         3003  14.0       215
 6 DLBAJ157 RIO CHICALOTE_17      3007 315.       1677
 7 DLBAJ157 RIO CHICALOTE_18      3007 430.       1677
 8 DLBAJ159 RIO MULEGE_13         3010  17.9       477
 9 DLBAJ159 RIO MULEGE_14         3010  36.0       477
10 DLCAM80  RIO CHICALOTE_18      4012 158.       1003
11 DLCAM85  RIO CHICALOTE_18      4009 323.        573
12 DLCAM122 RIO MULEGE_12         4001  37.8       300

新的 tibble 应该如下所示：

在此处输入图像描述

标签： rdplyrdata-cleaningtibble

解决方案

library(tidyverse)

df <- tribble(
  ~id_emca,       ~water_body,      ~id_estmun,   ~dbo,    ~elevation,
  "DLAGU20",   "RIO CHICALOTE_16",     1005,      364.92,    1865,
  "DLAGU20",   "RIO CHICALOTE_17",     1005,      485.91,    1865,
  "DLAGU20",   "RIO CHICALOTE_18",     1005,      270.32,    1865,
  "DLBAJ155",  "RIO MULEGE_12",        3003,      20.3,      215,
  "DLBAJ155",  "RIO MULEGE_13",        3003,      14.005,    215,
  "DLBAJ157",  "RIO CHICALOTE_17",     3007,      315.34,    1677,
  "DLBAJ157",  "RIO CHICALOTE_18",     3007,      430.21,    1677,
  "DLBAJ159",  "RIO MULEGE_13",        3010,      17.89,     477,
  "DLBAJ159",  "RIO MULEGE_14",        3010,      35.98,     477,
  "DLCAM80",   "RIO CHICALOTE_18",     4012,      157.66,    1003,
  "DLCAM85",   "RIO CHICALOTE_18",     4009,      323.02,    573,
  "DLCAM122",  "RIO MULEGE_12",        4001,      37.81,     300
)

temp <- df %>% 
  group_by(water_body) %>% 
  filter(n() > 1)

df %>% 
  arrange(water_body) %>% 
  left_join(temp, 
            by = "water_body",
            keep = TRUE) %>% 
  filter(elevation.x > elevation.y | is.na(elevation.y))

输出：

# A tibble: 11 x 10
   id_emca.x water_body.x     id_estmun.x dbo.x elevation.x id_emca.y water_body.y     id_estmun.y dbo.y elevation.y
   <chr>     <chr>                  <dbl> <dbl>       <dbl> <chr>     <chr>                  <dbl> <dbl>       <dbl>
 1 DLAGU20   RIO CHICALOTE_16        1005 365.         1865 NA        NA                        NA  NA            NA
 2 DLAGU20   RIO CHICALOTE_17        1005 486.         1865 DLBAJ157  RIO CHICALOTE_17        3007 315.         1677
 3 DLAGU20   RIO CHICALOTE_18        1005 270.         1865 DLBAJ157  RIO CHICALOTE_18        3007 430.         1677
 4 DLAGU20   RIO CHICALOTE_18        1005 270.         1865 DLCAM80   RIO CHICALOTE_18        4012 158.         1003
 5 DLAGU20   RIO CHICALOTE_18        1005 270.         1865 DLCAM85   RIO CHICALOTE_18        4009 323.          573
 6 DLBAJ157  RIO CHICALOTE_18        3007 430.         1677 DLCAM80   RIO CHICALOTE_18        4012 158.         1003
 7 DLBAJ157  RIO CHICALOTE_18        3007 430.         1677 DLCAM85   RIO CHICALOTE_18        4009 323.          573
 8 DLCAM80   RIO CHICALOTE_18        4012 158.         1003 DLCAM85   RIO CHICALOTE_18        4009 323.          573
 9 DLCAM122  RIO MULEGE_12           4001  37.8         300 DLBAJ155  RIO MULEGE_12           3003  20.3         215
10 DLBAJ159  RIO MULEGE_13           3010  17.9         477 DLBAJ155  RIO MULEGE_13           3003  14.0         215
11 DLBAJ159  RIO MULEGE_14           3010  36.0         477 NA        NA                        NA  NA            NA

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