如何根据第一个数据帧的数据对从第二个数据帧中提取行？答案

【问题标题】：How can I extract row from a second dataframe based on data-pairs from first dataframe?如何根据第一个数据帧的数据对从第二个数据帧中提取行？
【发布时间】：2015-10-14 02:47:38
【问题描述】：

我有两个数据框，df1（2000 行）和df2（100,000 行）。我想：

从 df1 读取 lat/long 组合
与 df2 中的 lat/long 匹配
读取df2对应的“m”值
将其添加到 df1

我该怎么办？

df1
lat      long       val
33.29083 -109.19556 12.5000
32.96583 -109.30972 11.5000
33.04944 -109.29528 1.7500
33.06444 -109.44167 1.7500
33.61944 -110.92083 0.2500
33.98000 -111.30278 3.7500
33.79806 -110.49917 1.00008
38.37972 -119.44917 3.2500

和

df2<-structure(list(lat = c(33.29, 32.96, 48.15, 48.1, 48.18, 48.14
    ), lon = c(-109.19, -109.31, -124.69, -124.69, -124.68, -124.68
    ), m = c(0.4713, 0.8998, 0.4891, 0.8418, 0.7998, 0.5292), flagar = c(0L, 
    1L, 0L, 1L, 1L, 0L), flagk = c(0L, 0L, 0L, 0L, 0L, 0L), flagsi = c(0L, 
    0L, 0L, 0L, 0L, 0L), flags2o = c(0L, 0L, 0L, 0L, 0L, 0L), flagap = c(0L, 
    0L, 0L, 0L, 0L, 0L), flagmt = c(0L, 0L, 0L, 0L, 0L, 0L), flagcn = c(0L, 
    0L, 0L, 0L, 0L, 0L), flagkf = c(1L, 1L, 1L, 1L, 1L, 1L), flagrd = c(1L, 
    1L, 1L, 1L, 1L, 1L), flagrv = c(2L, 2L, 2L, 2L, 2L, 2L), flagpt = c(1L, 
    1L, 1L, 1L, 1L, 1L)), .Names = c("lat", "lon", "m", "flagar", 
    "flagk", "flagsi", "flags2o", "flagap", "flagmt", "flagcn", "flagkf", 
    "flagrd", "flagrv", "flagpt"), row.names = c(NA, 6L), class = "data.frame")

【问题讨论】：

两个数据帧中没有相同的纬度/经度点。你想怎么搭配？在确切位置上将不会与示例数据匹配。你想在最短距离上匹配吗？
对不起，实际数据集有匹配点。这些是子集，所以....我会编辑它。
现在添加。匹配最多可保留 2 个小数点

标签： r dataframe

【解决方案1】：

使用data.table 包你可以这样做：

library(data.table)
# convert the dataframes to datatables (which are an extended form of a dataframe)
# and round the lat & lon variables to one decimal
setDT(df1)[, `:=` (lat = round(lat,1), lon = round(lon,1))]
setDT(df2)[, `:=` (lat = round(lat,1), lon = round(lon,1))]

# joining the m column of df2 to df1 based on exact matches of the rounded lat/lon values
# m = i.m transfers the matching values to the df1 dataframe
df1[df2, m := i.m, on=c("lat","lon")]

这给出了：

> df1
    lat    lon      val      m
1: 33.3 -109.2 12.50000 0.4713
2: 33.0 -109.3 11.50000 0.8998
3: 33.0 -109.3  1.75000 0.8998
4: 33.1 -109.4  1.75000     NA
5: 33.6 -110.9  0.25000     NA
6: 34.0 -111.3  3.75000     NA
7: 33.8 -110.5  1.00008     NA
8: 38.4 -119.4  3.25000     NA

如果您想在最短距离上进行匹配，请参阅this answer 示例。

【讨论】：