r - 如何根据r中的日期/天拆分和制作新的csv文件？

Question

嗨，我有一个 8GB 的​​文件，我需要对其进行一些分析。但是我的 RAM 不是很好。为了有效地工作，我决定使用以下代码根据行拆分我的 csv 文件:

library(tidyverse)

sample_df <- readr::read_csv("sample.csv") #Read in the csv file
dput(sample_df)

#break the large CSV so RAM and Rstudio doesn't crash

groups <- (split(sample_df, (seq(nrow(sample_df))-1) %/% 20)) #here I want 20 rows per file until last row is reached

for (i in seq_along(groups)) {
  write.csv(groups[[i]], paste0("sample_output_file", i, ".csv")) #iterate and write file
}

这非常有效，直到我的高级导师要求我根据每个日期/天进行分析。我遇到了一个问题，因为通过按行拆分，我最终将日期传播到多个 csv。当我尝试读取 3-4 个 csv 以进行基于每天的分析时，这会产生 RAM 和内存管理不足的问题。

示例文件在这里: https://github.com/THsTestingGround/SO_splitbydate_question/blob/master/sample.csv

那么有人可以帮助我如何根据日期拆分我最初读取的以下示例 csv 文件吗？我想将所有 Aprl1 放在一个 csv 文件中，然后将 Aprl2 放在另一个文件中，依此类推。我确实尝试过，但我无法成功。

另外我想知道 readr::read_csv_chunked 是否可以以任何方式帮助我们？从文档中我看不到任何具体内容。

这是 csv 文件的 dput:

dput(sample_df)
structure(list(createdAt = c("Fri Apr 01 04:04:32 +0000 2020", 
"Fri Apr 01 04:04:36 +0000 2020", "Fri Apr 01 04:04:37 +0000 2020", 
"Fri Apr 02 04:04:40 +0000 2020", "Fri Apr 02 04:04:44 +0000 2020", 
"Fri Apr 02 04:04:46 +0000 2020", "Fri Apr 02 04:04:54 +0000 2020", 
"Fri Apr 02 04:04:56 +0000 2020", "Fri Apr 02 04:05:07 +0000 2020", 
"Fri Apr 02 04:05:12 +0000 2020", "Fri Apr 03 04:05:12 +0000 2020", 
"Fri Apr 03 04:05:19 +0000 2020", "Fri Apr 03 04:05:27 +0000 2020", 
"Fri Apr 03 04:05:33 +0000 2020", "Fri Apr 03 04:05:36 +0000 2020", 
"Fri Apr 03 04:06:11 +0000 2020", "Fri Apr 03 04:07:08 +0000 2020", 
"Fri Apr 03 04:07:14 +0000 2020", "Fri Apr 03 04:07:15 +0000 2020", 
"Fri Apr 03 04:07:20 +0000 2020", "Fri Apr 03 04:07:30 +0000 2020", 
"Fri Apr 03 04:07:51 +0000 2020", "Fri Apr 03 04:08:04 +0000 2020", 
"Fri Apr 03 04:08:09 +0000 2020", "Fri Apr 03 04:08:15 +0000 2020", 
"Fri Apr 03 04:08:22 +0000 2020", "Fri Apr 03 04:08:36 +0000 2020", 
"Fri Apr 03 04:08:46 +0000 2020", "Fri Apr 03 04:08:46 +0000 2020", 
"Fri Apr 03 04:09:01 +0000 2020", "Fri Apr 03 04:09:08 +0000 2020", 
"Fri Apr 03 04:09:10 +0000 2020", "Fri Apr 03 04:09:15 +0000 2020", 
"Fri Apr 03 04:09:26 +0000 2020", "Fri Apr 03 04:09:27 +0000 2020", 
"Fri Apr 03 04:09:28 +0000 2020", "Fri Apr 03 04:09:28 +0000 2020", 
"Fri Apr 03 04:09:35 +0000 2020", "Fri Apr 03 04:09:36 +0000 2020", 
"Fri Apr 03 04:09:41 +0000 2020", "Fri Apr 03 04:09:45 +0000 2020", 
"Fri Apr 03 04:10:16 +0000 2020", "Fri Apr 03 04:10:19 +0000 2020", 
"Fri Apr 03 04:10:22 +0000 2020", "Fri Apr 03 04:10:26 +0000 2020", 
"Fri Apr 03 04:10:31 +0000 2020", "Fri Apr 03 04:10:48 +0000 2020", 
"Fri Apr 04 04:11:19 +0000 2020", "Fri Apr 04 04:11:32 +0000 2020", 
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    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA)), class = c("spec_tbl_df", "tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -50L), spec = structure(list(
    cols = list(createdAt = structure(list(), class = c("collector_character", 
    "collector")), timestamp = structure(list(), class = c("collector_double", 
    "collector")), id_str = structure(list(), class = c("collector_double", 
    "collector")), text = structure(list(), class = c("collector_character", 
    "collector")), retweetCount = structure(list(), class = c("collector_double", 
    "collector")), favorite_count = structure(list(), class = c("collector_double", 
    "collector")), url = structure(list(), class = c("collector_character", 
    "collector")), friendCount = structure(list(), class = c("collector_double", 
    "collector")), screenNames = structure(list(), class = c("collector_character", 
    "collector")), userID = structure(list(), class = c("collector_double", 
    "collector")), language = structure(list(), class = c("collector_character", 
    "collector")), replyToScreenName = structure(list(), class = c("collector_character", 
    "collector")), replyToID = structure(list(), class = c("collector_character", 
    "collector")), retweetUserScreenName = structure(list(), class = c("collector_logical", 
    "collector")), retweetUserID = structure(list(), class = c("collector_logical", 
    "collector")), followersCount = structure(list(), class = c("collector_double", 
    "collector")), userMentions = structure(list(), class = c("collector_character", 
    "collector")), userMentionsID = structure(list(), class = c("collector_double", 
    "collector")), hashtag1 = structure(list(), class = c("collector_character", 
    "collector")), hashtag2 = structure(list(), class = c("collector_logical", 
    "collector")), mediatype = structure(list(), class = c("collector_logical", 
    "collector")), mediaURL = structure(list(), class = c("collector_logical", 
    "collector"))), default = structure(list(), class = c("collector_guess", 
    "collector")), skip = 1), class = "col_spec"))
> groups <- (split(sample_df, (seq(nrow(sample_df))-1) %/% 20)) #here I want 20 rows per file until last row is reached
> for (i in seq_along(groups)) {
+   write.csv(groups[[i]], paste0("sample_output_file", i, ".csv")) #iterate and write file
+ }

Answer 1

我们可以从 createdAt 创建一个变量然后做 group_split到 list数据框。在这里，我们可以使用 str_replace 提取特定的子串。通过删除第一个单词后跟空格，同时捕获下一个单词、空格、一些数字并在替换中使用它们。

library(dplyr)
library(stringr)
sample_df %>% 
  mutate(month_day = str_replace(createdAt, 
           "^\\w+\\s+(\\w+\\s+\\d+).*", "\\1")) %>%
  group_split(month_day)

注意:不需要 mutate如 month_day可以在 group_split 中即时创建本身