为什么橄榄酸无法根据同一时区的Olson名称来解析一些日期？
我正在使用加那利群岛的一些数据。这个西班牙地区的时区正式湿/西。但是这个时区也与英国的时区相吻合-GMT/BST。两者都会改变同一天和同一天。
我尝试使用lubritation库将一些字符（日月）转换为日期，我感到惊讶的是，根据我使用的时区，函数dmy（）可以无法解析。
当我尝试使用dmy（） tz =“ atlantic/canary”> wet/west中的时区直接使用时区直接解析所有日期列。解析。这个：
example = c("06/04/1980", "06/04/1980", "06/04/1980", "06/04/1980", "06/04/1980",
"23/10/2008", "27/03/2017", "24/02/2011", "06/04/1980")
但是，与以前不同，它独自一人尝试了3/9。
> dmy(example, tz = "Atlantic/Canary")
[1] NA NA NA NA NA "2008-10-23 WEST"
[7] "2017-03-27 WEST" "2011-02-24 WET" NA
Warning message:
6 failed to parse.
更令人惊讶的是，如果我将时区设置为英国人，它可以很好地工作。另外，英国人一次可以立即适合所有专栏：
> dmy(example, tz = "Europe/London")
[1] "1980-04-06 BST" "1980-04-06 BST" "1980-04-06 BST" "1980-04-06 BST" "1980-04-06 BST" "2008-10-23 BST" "2017-03-27 BST"
[8] "2011-02-24 GMT" "1980-04-06 BST"
我不明白为什么三个案例有所不同。我最初的DF是1000万行。但是，即使有9个日期的列表，我也不知道为什么使用一个TZ或另一个TZ dmy（）函数输出有所不同。如果我使用数小时，也许会发生一些变化，但事实并非如此。任何答案都将不胜感激。
I'm working with some data from the Canary Islands. The timezone in this Spanish region is officially WET/WEST. But this timezone also coincides with the British one for example - GMT/BST. Both change same hour and same day.
I tried to convert some characters (day-month-year) to dates using lubridate library and I am surprised that depending on the timezone I use, the function dmy() can fail to parse or not.
When I tried to parse directly all the date column using the timezone in dmy() tz = "Atlantic/Canary" - which is WET/WEST - it returns 9 failings to parse. This ones:
example = c("06/04/1980", "06/04/1980", "06/04/1980", "06/04/1980", "06/04/1980",
"23/10/2008", "27/03/2017", "24/02/2011", "06/04/1980")
However, trying them alone, it successfully converts 3 / 9, unlike before.
> dmy(example, tz = "Atlantic/Canary")
[1] NA NA NA NA NA "2008-10-23 WEST"
[7] "2017-03-27 WEST" "2011-02-24 WET" NA
Warning message:
6 failed to parse.
And more surprisingly, If I set the timezone to British, it works perfectly. Also, the British one works perfectly for all the column at once:
> dmy(example, tz = "Europe/London")
[1] "1980-04-06 BST" "1980-04-06 BST" "1980-04-06 BST" "1980-04-06 BST" "1980-04-06 BST" "2008-10-23 BST" "2017-03-27 BST"
[8] "2011-02-24 GMT" "1980-04-06 BST"
I don't understand why the 3 cases are different. My original df is 10 million rows. However, even with the list of 9 dates, I don't know why the dmy() function output differs using one tz or another. If I were using hours, maybe it would be for some change, but that is not the case. Any answer will be appreciated.
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