【发布时间】:2020-03-08 02:53:24
【问题描述】:
我有两个数据帧,我想将数据帧对 b 与数据帧对 a 进行比较,并查看来自 b 的对是否在(包括)这些对/范围内在a。例如,见下文:
df_1 <- data.frame(x= c(-82.38319, -82.38318, -82.40397, -82.40417, -82.40423),
y= c(29.61212, 29.61125, 29.61130, 29.61134, 29.61167))
#Output:
# x y
# 1 -82.38319 29.61212
# 2 -82.38318 29.61125
# 3 -82.40397 29.61130
# 4 -82.40417 29.61134
# 5 -82.40423 29.61167
df_2 <- data.frame(o= c(-82.38320,-82.38317,-82.40397,-82.40416,-82.40424),
t= c(29.61212, 29.6114, 29.61130, 29.61133, 29.61167))
#Output:
# o t
# 1 -82.38320 29.61212
# 2 -82.38317 29.61140
# 3 -82.40397 29.61130
# 4 -82.40416 29.61133
# 5 -82.40424 29.61167
#made this dataframe as an example only.
desired_output <- data.frame(lat= df_2$o, lon= df_2$t, exists= c(NA, "YES","YES","YES",NA))
#Output I seek:
# lat lon exists
# 1 -82.38320 29.61212 <NA>
# 2 -82.38317 29.61140 YES
# 3 -82.40397 29.61130 YES
# 4 -82.40416 29.61133 YES
# 5 -82.40424 29.61167 <NA>
#explanation:
#1- even though 82.38320 is OK & is in rows 3,4,5 in df_1, 29.61212 is out of bounds with their co-pairings.
#2- row 2 of df_2 is within the row 5 of df_1.
#3- row 3 of df_2 matches to row 3 of df_1 thus inclusive
#4- row 4 pair matches and its co_pair is less than those pair of row 4 in df_1
#5- This pair at row 5 is out of bounds in all of the rows of df_1
#Column "exists" can be appended to dataframe b, result matters only, neatness is not an issue.
我已经在 Stack Overflow 中四处挖掘,除了 this listing 什么都没有。但是这个人将单个值与成对进行比较,而不是成对与成对或成对内的成对进行比较。我已经对两个数据框完成了cbind 并使用它进行了比较。但我失败了。
接下来我可以尝试什么?
【问题讨论】:
-
比较规则是什么?为什么第 2 行是“YES”而第 1 行是 NA。
-
谢谢 Ronak,规则是数据帧 df_2 中的 (a2,b2) 必须小于 a1 和 b1 或等于 a1 和 b1 或 (a2,b2) 中的任何一个实体对可以相等,但它的共同对必须匹配,或者必须从数据帧 df_1 的对中变小。我的术语有点弱,我可以进一步解释。之所以 2 是 YES,是因为 df_2 的第 2 对都小于 df_1 的第 5 对(因此在里面)。 df_2 的第 1 对是 NA,因为它不符合我提到的标准。含义 (a2,b2) 是不匹配的,并且它的配对之一超出了界限。抱歉修改。
标签: r dataframe comparison pairwise