使用 col_types 在 readr 中解析日期时获取 NA [关闭]答案

【问题标题】：Getting NAs when parsing dates in readr using col_types [closed]使用 col_types 在 readr 中解析日期时获取 NA [关闭]
【发布时间】：2021-10-17 01:50:31
【问题描述】：

我有一个 this 数据集，我正在尝试使用 col_types 规范解析日期

dailyActivityMerged <- read_csv("/cloud/project/Fitabase Data/dailyActivity_merged.csv", 
                            col_types = list(
                              Id = col_double(),
                              ActivityDate = col_date(format = "%m %d %Y"),
                              TotalSteps = col_double(),
                              TotalDistance = col_double(),
                              TrackerDistance = col_double(),
                              LoggedActivitiesDistance = col_double(),
                              VeryActiveDistance = col_double(),
                              ModeratelyActiveDistance = col_double(),
                              LightActiveDistance = col_double(),
                              SedentaryActiveDistance = col_double(),
                              VeryActiveMinutes = col_double(),
                              FairlyActiveMinutes = col_double(),
                              LightlyActiveMinutes = col_double(),
                              SedentaryMinutes = col_double(),
                              Calories = col_double()
                            ))

但我收到一个错误，所有日期都在 ActivityDate 列中转换为 NA。

你能告诉我为什么会发生这种情况以及如何获取日期格式的日期吗？

【问题讨论】：

标签： r date parsing

【解决方案1】：

原因是格式应该是%m/%d/%Y而不是%m %d %Y，根据链接中显示的数据中的列格式

library(readr)
dailyActivityMerged <- read_csv("/cloud/project/Fitabase Data/dailyActivity_merged.csv", 
                            col_types = list(
                              Id = col_double(),
                              ActivityDate = col_date(format = "%m/%d/%Y"),
                              TotalSteps = col_double(),
                              TotalDistance = col_double(),
                              TrackerDistance = col_double(),
                              LoggedActivitiesDistance = col_double(),
                              VeryActiveDistance = col_double(),
                              ModeratelyActiveDistance = col_double(),
                              LightActiveDistance = col_double(),
                              SedentaryActiveDistance = col_double(),
                              VeryActiveMinutes = col_double(),
                              FairlyActiveMinutes = col_double(),
                              LightlyActiveMinutes = col_double(),
                              SedentaryMinutes = col_double(),
                              Calories = col_double()
                            ))

-现在检查结构

> str(dailyActivityMerged)
spec_tbl_df [940 × 15] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ Id                      : num [1:940] 1.5e+09 1.5e+09 1.5e+09 1.5e+09 1.5e+09 ...
 $ ActivityDate            : Date[1:940], format: "2016-04-12" "2016-04-13" "2016-04-14" "2016-04-15" ...
 $ TotalSteps              : num [1:940] 13162 10735 10460 9762 12669 ...
 $ TotalDistance           : num [1:940] 8.5 6.97 6.74 6.28 8.16 ...
 $ TrackerDistance         : num [1:940] 8.5 6.97 6.74 6.28 8.16 ...
 $ LoggedActivitiesDistance: num [1:940] 0 0 0 0 0 0 0 0 0 0 ...
 $ VeryActiveDistance      : num [1:940] 1.88 1.57 2.44 2.14 2.71 ...
 $ ModeratelyActiveDistance: num [1:940] 0.55 0.69 0.4 1.26 0.41 ...
 $ LightActiveDistance     : num [1:940] 6.06 4.71 3.91 2.83 5.04 ...
 $ SedentaryActiveDistance : num [1:940] 0 0 0 0 0 0 0 0 0 0 ...
 $ VeryActiveMinutes       : num [1:940] 25 21 30 29 36 38 42 50 28 19 ...
 $ FairlyActiveMinutes     : num [1:940] 13 19 11 34 10 20 16 31 12 8 ...
 $ LightlyActiveMinutes    : num [1:940] 328 217 181 209 221 164 233 264 205 211 ...
 $ SedentaryMinutes        : num [1:940] 728 776 1218 726 773 ...
 $ Calories                : num [1:940] 1985 1797 1776 1745 1863 ...
 - attr(*, "spec")=
  .. cols(
  ..   Id = col_double(),
  ..   ActivityDate = col_date(format = "%m/%d/%Y"),
  ..   TotalSteps = col_double(),
  ..   TotalDistance = col_double(),
  ..   TrackerDistance = col_double(),
  ..   LoggedActivitiesDistance = col_double(),
  ..   VeryActiveDistance = col_double(),
  ..   ModeratelyActiveDistance = col_double(),
  ..   LightActiveDistance = col_double(),
  ..   SedentaryActiveDistance = col_double(),
  ..   VeryActiveMinutes = col_double(),
  ..   FairlyActiveMinutes = col_double(),
  ..   LightlyActiveMinutes = col_double(),
  ..   SedentaryMinutes = col_double(),
  ..   Calories = col_double()
  .. )

【讨论】：