我有两个分别称为main_df和usd_eur的数据帧。 main_df有每周数据，而usd_eur有每日数据。
第二，我尝试使用usd_eur软件包将tidyquant数据转换为每周数据
library(tidyquant)
x <- usd_eur %>%
tq_transmute(select = DEXUSEU,
mutate_fun = apply.weekly,
FUN = mean)
但是，首先，我在usd_eur中的数据两边各有大约一个月的时间，拥有“太多”的main_df数据。
min(main_df$WEEK)
min(usd_eur$DATE)
max(main_df$WEEK)
max(usd_eur$DATE)
因此，我正在尝试修剪尾端，以便两个数据帧都在同一天开始，然后将usd_eur中的每日数据转换为每周数据。但是，我在思考如何修剪数据的尾端时遇到了一些困难。
Main_df：
main_df <- structure(list(WEEK = structure(c(1333922400, 1326668400, 1330902000,
1329692400, 1353884400, 1335736800, 1331506800, 1345413600, 1325458800,
1338156000, 1327273200, 1346018400, 1346623200, 1326063600, 1355094000,
1344808800, 1326668400, 1327878000, 1349647200, 1327878000, 1349647200,
1333922400, 1354489200, 1327273200, 1339365600, 1340575200, 1336946400,
1338760800, 1336946400, 1355698800, 1331506800, 1344808800, 1336946400,
1341784800, 1325458800, 1355698800, 1333317600, 1330297200, 1342994400,
1342994400, 1339970400, 1347832800, 1342389600, 1354489200, 1333317600,
1333317600, 1329692400, 1355698800, 1339365600, 1332712800, 1338760800,
1333317600, 1347228000, 1335736800, 1349647200, 1336341600, 1349647200,
1337551200, 1333922400, 1348437600, 1342389600, 1349647200, 1346623200,
1341180000, 1330297200, 1327273200, 1352070000, 1345413600, 1342994400,
1347832800, 1338760800, 1350856800, 1350252000, 1344808800, 1355698800,
1333922400, 1345413600, 1351465200, 1344204000, 1344808800, 1350252000,
1339970400, 1324854000, 1327878000, 1335736800, 1350252000, 1353279600,
1336946400, 1343599200, 1346623200, 1339365600, 1336341600, 1329087600,
1338156000, 1339970400, 1341180000, 1353884400, 1336341600, 1327878000,
1329692400, 1355094000, 1349647200, 1346623200, 1349042400, 1334527200,
1349647200, 1343599200, 1347832800, 1330902000, 1330297200, 1336341600,
1354489200, 1330902000, 1333922400, 1352674800, 1350252000, 1336946400,
1355094000, 1344204000, 1346018400, 1344808800, 1328482800, 1330297200,
1348437600, 1341180000, 1341180000, 1344808800, 1354489200, 1355698800,
1330902000, 1344204000, 1338156000, 1350856800, 1337551200, 1324854000,
1338156000, 1338156000, 1350252000, 1337551200, 1347228000, 1351465200,
1335132000, 1341180000, 1347832800, 1335736800, 1336341600, 1349042400,
1353279600, 1352070000, 1334527200, 1349647200, 1330297200, 1355094000,
1327273200, 1338156000, 1347228000, 1326063600, 1342994400, 1329087600,
1330297200, 1349647200, 1329692400, 1350856800, 1329692400, 1346623200,
1335736800, 1341784800, 1344808800, 1341784800, 1344808800, 1341784800,
1355094000, 1352070000, 1333922400, 1340575200, 1331506800, 1326063600,
1333922400, 1341180000, 1345413600, 1353884400, 1344808800, 1348437600,
1327878000, 1343599200, 1339365600, 1338156000, 1338760800, 1326063600,
1346623200, 1352674800, 1332111600, 1353884400, 1355698800, 1325458800,
1342994400, 1341784800, 1339970400, 1335132000, 1333922400, 1348437600,
1350252000, 1347228000, 1339365600, 1347228000, 1353884400, 1346623200,
1355698800, 1332111600, 1346018400, 1330902000, 1342994400, 1331506800,
1328482800, 1331506800, 1349042400, 1324854000, 1324854000, 1350856800,
1350252000, 1348437600, 1339365600, 1346623200, 1343599200, 1345413600,
1337551200, 1355698800, 1332111600, 1335736800, 1349647200, 1348437600,
1343599200, 1336341600, 1345413600, 1339365600, 1332712800, 1345413600,
1348437600, 1347832800, 1333922400, 1330902000, 1324854000, 1354489200,
1355698800, 1326063600, 1343599200, 1350252000, 1353884400, 1355698800,
1327273200, 1342994400, 1341180000, 1355094000, 1353884400, 1347832800,
1327273200, 1333317600, 1348437600, 1342994400, 1326668400, 1355094000,
1349042400, 1332111600, 1350252000, 1344808800, 1344204000, 1353884400,
1341180000, 1349647200, 1344204000, 1352674800, 1340575200, 1327273200,
1350252000, 1349042400, 1349647200, 1347228000, 1353279600, 1343599200,
1342389600, 1353884400, 1339970400, 1334527200, 1343599200, 1350856800,
1346018400, 1329087600, 1336946400, 1334527200, 1350856800, 1341180000,
1326668400, 1337551200, 1346018400, 1346623200, 1343599200, 1324854000,
1339970400, 1346623200, 1340575200, 1334527200, 1324854000, 1338760800,
1346018400, 1327273200, 1324854000, 1335736800, 1351465200, 1347228000,
1341180000, 1335736800, 1338156000, 1333922400, 1338156000, 1334527200,
1329087600, 1356303600, 1346018400, 1330902000, 1333922400, 1339365600,
1338156000, 1353884400, 1344204000, 1336341600, 1337551200, 1354489200,
1334527200, 1332712800, 1349647200, 1344204000, 1353279600, 1336341600,
1347832800, 1353884400, 1353884400, 1341784800, 1353884400, 1347832800,
1342389600, 1332111600, 1342994400, 1347228000, 1341784800, 1326063600,
1330297200, 1354489200, 1332111600, 1350252000, 1326063600, 1353884400,
1324854000, 1336341600, 1340575200, 1331506800, 1350252000, 1348437600,
1326668400, 1350856800, 1332111600, 1347832800, 1349042400, 1352070000,
1335736800, 1343599200, 1324854000, 1355698800, 1341784800, 1342994400,
1343599200, 1330297200, 1335736800, 1338156000, 1339365600, 1341784800,
1325458800, 1329692400, 1339970400, 1351465200, 1344808800, 1324854000,
1356303600, 1338156000, 1353279600, 1342389600, 1355698800, 1327878000,
1326063600, 1347228000, 1341784800, 1335132000, 1335132000, 1340575200,
1329087600, 1347832800, 1350856800, 1338156000, 1326063600, 1347228000,
1352674800, 1333922400, 1336946400, 1340575200, 1330902000, 1325458800,
1342994400, 1336341600, 1346623200, 1339365600, 1355094000, 1353279600,
1355698800, 1355698800, 1336341600, 1324854000, 1333317600, 1347832800,
1345413600, 1339970400, 1342994400, 1353279600, 1339365600, 1342389600,
1350856800, 1339365600, 1332712800, 1352674800, 1341784800, 1339365600,
1342994400, 1345413600, 1348437600, 1340575200, 1352674800, 1346018400,
1324854000, 1335736800, 1352674800, 1349042400, 1324854000, 1332111600,
1346018400, 1335132000, 1338156000, 1327273200, 1335736800, 1345413600,
1346623200, 1328482800, 1353279600, 1355698800, 1335132000, 1330902000,
1355094000, 1342994400, 1350252000, 1352070000, 1330297200, 1340575200,
1334527200, 1347228000, 1344808800, 1347832800, 1351465200, 1342994400,
1327273200, 1333317600, 1341784800, 1346018400, 1353884400, 1341784800,
1353279600, 1335132000, 1350252000, 1337551200, 1326063600, 1341784800,
1349647200, 1351465200, 1329692400, 1331506800, 1327878000, 1352070000,
1332111600, 1338156000, 1331506800, 1350252000, 1346623200, 1335132000,
1325458800, 1349647200, 1328482800, 1324854000, 1355094000, 1327273200,
1343599200, 1330297200, 1350252000, 1343599200, 1326668400), class = c("POSIXct",
"POSIXt"), tzone = ""), DOLLARS = c(95.52, 20.98, 24.38, 242.77,
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7.49, 17.97, 38.97, 19.47, 98.91, 1.67, 27, 89.95, 8.99, 2.59,
35.97, 25.33, 15.99, 27.46, 27.17, 16.99, 7.56, 16.98, 94.43,
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29.94, 49.95, 127.92, 8.49, 9.99, 13.98, 6.79, 48.86, 21.98,
22.38, 43.47, 113.82, 27.98, 276.76, 25.47, 203.83, 29.9, 18.49,
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27.45, 14.49, 9.96, 8.99, 11.99, 33.95, 223.86, 7.99, 17.8, 23.97,
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43.96, 113.94, 47.96, 35.56, 6.39, 23.38, 49.44, 299.85, 3.98,
6.87, 37.94, 11.99, 27.09, 29.97, 5.01, 6.49, 12.98, 11.79, 83.93,
175.84, 27.9, 17.98, 70.14, 7.99, 20.97, 43.98, 154.66, 45.43,
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16.49, 179.8, 1.49, 7.99, 44.97, 25.94, 79.96, 90.79, 39.96,
84.95, 49.57, 41.96, 92.64, 9.98, 21.89, 13.98, 3.39, 14.07,
12.49, 39.87, 15.98, 37.95, 27.96, 53.97, 241.78, 15.9, 37.53,
90.91, 5.29, 76.41, 62.93, 6.99, 52.43, 7.99, 55.12, 19.47, 111.93,
41.61, 6.99, 23.56, 115.92, 13.99, 13.98, 146.93, 5.58, 71.91,
34.47, 1.49, 7.49, 14.97, 50.97, 9.98, 10.99, 2.99, 58.95, 14.49,
73.43, 17.97, 19.96, 19.99, 58.05, 24.43, 8.99, 27.96, 159.7,
98.94, 11.49, 7.99, 6.49, 65.87, 134.91, 31.47, 12.69, 7.49,
83.23, 6.99, 73.95, 19.99, 3.49, 31.96, 12.99, 8.69, 15.12, 35.97,
12.38, 90.93, 46.08, 7.49, 116.41, 14.99, 7.99, 600.14, 28.98,
127.89, 223.68, 23.98, 71.92, 1.39, 47.97, 35.94, 13.12, 76.93,
350.49, 34.93, 69.9, 35.97, 12.58, 6.99, 4.99, 41.94, 179.85,
14.07, 14.98, 19.98, 34.95, 30.95, 23.97, 55.16, 6.41, 191.58,
17.98, 9.49, 19.98, 6.98, 59.77, 27.98, 41.97, 90.93, 83.88,
155.88, 5.18, 6.49, 19.47, 51.92, 10.99, 47.45, 71.95, 7.99,
119.92, 75.96, 13.99, 69.54, 17.99, 123.6, 125.91, 23.91, 35.97,
117.8, 15.98, 59.95, 41.43, 20.07, 95.84, 36.87, 31.96, 7.99,
51.92, 17.78, 34.95, 29.77, 19.9, 15.98, 16.99, 16.99, 55.92,
9.99, 25.96, 47.53, 11.99, 19.47, 41.96, 11.49, 71.88, 41.93,
32.73, 11.88, 12.99, 119.92, 45.43, 33.83, 35.98, 4.59, 22.45,
17.99, 19.74, 63.48, 23.98, 12.99, 19.35, 47.96, 269.7, 19.99,
6.99, 39.97, 16.03, 12.78, 21.98, 61.95, 1371.02, 8.99, 27.98,
22.47, 28.38, 21.16, 378.1, 12.99, 21.98, 10.76, 1237.28, 33.98,
87.45, 33.74, 29.37, 42.98, 63.92, 359.7, 21.98, 74.94, 6.99,
95.94, 42.45, 26.97, 41.96, 42.96, 12.18, 208.81, 39.95)), row.names = c(1067085L,
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货币df
usd_eur <- structure(list(DATE = structure(c(1322521200, 1322607600, 1322694000,
1322780400, 1323039600, 1323126000, 1323212400, 1323298800, 1323385200,
1323644400, 1323730800, 1323817200, 1323903600, 1323990000, 1324249200,
1324335600, 1324422000, 1324508400, 1324594800, 1324854000, 1324940400,
1325026800, 1325113200, 1325199600, 1325458800, 1325545200, 1325631600,
1325718000, 1325804400, 1326063600, 1326150000, 1326236400, 1326322800,
1326409200, 1326668400, 1326754800, 1326841200, 1326927600, 1327014000,
1327273200, 1327359600, 1327446000, 1327532400, 1327618800, 1327878000,
1327964400, 1328050800, 1328137200, 1328223600, 1328482800, 1328569200,
1328655600, 1328742000, 1328828400, 1329087600, 1329174000, 1329260400,
1329346800, 1329433200, 1329692400, 1329778800, 1329865200, 1329951600,
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答案 0 :(得分：0)
这是一种方法-
result <- usd_eur[usd_eur$DATE >= min(main_df$WEEK) & usd_eur$DATE <= max(main_df$WEEK), ]
> min(main_df$WEEK)
[1] "2011-12-25 18:00:00 EST"
> min(result$DATE)
[1] "2011-12-25 18:00:00 EST"
>
> max(main_df$WEEK)
[1] "2012-12-23 18:00:00 EST"
> max(result$DATE)
[1] "2012-12-23 18:00:00 EST"