1

我有很多类似的小问题：

dftest_tw <- structure(list(text = c("RT @BitMEXdotcom: A new high: US$500M turnover in the last 24 hours, over 80% of it on $XBTUSD. Congrats to the team and thank you to our u…", 
"RT @Crowd_indicator: Thank you for this nice video, @Nicholas_Merten", 
"RT @Crowd_indicator: Review of #Cindicator by DataDash: t.co/D0da3u5y3V"
), Tweet.id = c("896858423521837057", "896858275689398272", "896858135314538497"
), created.date = structure(c(17391, 17391, 17391), class = "Date"), 
    created.week = c(33, 33, 33)), .Names = c("text", "Tweet.id", 
"created.date", "created.week"), row.names = c(NA, -3L), class = c("tbl_df", 
"tbl", "data.frame"))

为了测试，我们添加另一个：

dftest2_tw <- dftest_tw

我有我的 df 列表：

myUserList <- ls(,pattern = "_tw")

我想做的是：

1-添加一个名为的新列Twitter.name

2-用 df name填充列，所有这些都在一个函数中。以下代码适用于一一采取的每个 df：

dftest_tw %>% rowwise() %>% mutate(Twitter.name = myUserList[1])

期望的结果是这样的：

MyRes <- structure(list(text = c("RT @BitMEXdotcom: A new high: US$500M turnover in the last 24 hours, over 80% of it on $XBTUSD. Congrats to the team and thank you to our u…", 
"RT @Crowd_indicator: Thank you for this nice video, @Nicholas_Merten", 
"RT @Crowd_indicator: Review of #Cindicator by DataDash: t.co/D0da3u5y3V"
), Tweet.id = c("896858423521837057", "896858275689398272", "896858135314538497"
), created.date = structure(c(17391, 17391, 17391), class = "Date"), 
    created.week = c(33, 33, 33), retweet = c(0, 0, 0), custom = c(0, 
    0, 0), Twitter.name = c("dftest_tw", "dftest_tw", "dftest_tw"
    )), .Names = c("text", "Tweet.id", "created.date", "created.week", 
"retweet", "custom", "Twitter.name"), class = c("rowwise_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -3L))

当要编写一个函数以应用于我所有的 df（超过 100 个）时，我无法实现它。任何帮助，将不胜感激。

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1 回答 1

1

我们可以使用tidyverse选项。使用 获取多个字符串对象的值mget，然后使用map2from ，在'myUserList' 的对应字符串元素的purrr每个数据集中创建新列 'Twitter.namelist

library(tidyverse) 
lst <- mget(myUserList) %>% 
          map2(myUserList,  ~mutate(.data = .x, Twitter.name = .y))

如果我们需要修改全局环境中的对象，使用list2env

list2env(lst, envir = .GlobalEnv)
于 2017-08-31T15:35:14.703 回答