排列功能:lubridate和dplyr R之间的冲突 [英] Arrange function: Conflict between lubridate and dplyr R

问题描述

我想用 dplyr 中的 arrange 函数重新排列df.问题是，当我有另一列(比如说v2)与我要安排df的列不同时，这两个软件包似乎有冲突:

I want to rearrange a df with the function arrange from dplyr. The problem is that seems that these two packages have a conflict when I have another column (let's say v2) distinct from the column I want to arrange the df:

   library(dplyr)
library(lubridate)

start_dates <- as.Date(1:10, origin = "2018-01-01")
my_df <- data.frame(x = 10:1, y = interval(start_dates, start_dates + 1), 
                    z=c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J"))

my_df %>% arrange(z)

range_impl(.data，点)中的错误:列 y 类当前不支持lubridate的Period和Interval.

Error in arrange_impl(.data, dots) : Column y classes Period and Interval from lubridate are currently not supported.

如何订购数据框?谢谢你.

How I can order my dataframe? Thank you in advanced.

推荐答案

我不会将其本身称为冲突"，只是一个软件包不支持另一个软件包的功能.

I wouldn't call this a "conflict" per se, just one package not supporting the features of another.

如果 dplyr 的 arrange()不支持 Interval 类，则只需使用 order()像往常一样:

If dplyr's arrange() doesn't support Interval classes, just use order() like normal:

library(dplyr)
library(lubridate)

start_dates <- as.Date(1:10, origin = "2018-01-01")
my_df <- data.frame(x = 10:1, y = interval(start_dates, start_dates + 1))

my_df %>% arrange(y)

range_impl(.data，点)中的错误:
当前不支持y列类lubridate的Period和Interval.

Error in arrange_impl(.data, dots) :
Column `y` classes Period and Interval from lubridate are currently not supported.

my_df[order(my_df$y), ]

#     x                              y
# 1  10 2018-01-02 UTC--2018-01-03 UTC
# 2   9 2018-01-03 UTC--2018-01-04 UTC
# 3   8 2018-01-04 UTC--2018-01-05 UTC
# 4   7 2018-01-05 UTC--2018-01-06 UTC
# 5   6 2018-01-06 UTC--2018-01-07 UTC
# 6   5 2018-01-07 UTC--2018-01-08 UTC
# 7   4 2018-01-08 UTC--2018-01-09 UTC
# 8   3 2018-01-09 UTC--2018-01-10 UTC
# 9   2 2018-01-10 UTC--2018-01-11 UTC
# 10  1 2018-01-11 UTC--2018-01-12 UTC

注意

为将来参考，我会认真对待 OTStats 的警告-通常没有示例数据，很难做到这一点别人来帮助你.我会查看如何制作出色的R可再现示例

Note

For future reference, I would take seriously the admonition by OTStats -- often without example data it is very difficult for others to help you. I would check out How to Make a Great R Reproducible Example.

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