我在一年中的几天和几次中的平均行进距离数据为meters。这是我正在使用的数据集的样子：
> print(datanet)
Date & Time [Local] meters
1: 2017-06-01 00:00:14 2.333355
2: 2017-06-01 01:00:13 6.952414
3: 2017-06-01 02:00:30 61.727543
4: 2017-06-01 03:00:15 235.873883
5: 2017-06-01 04:00:15 138.136375
---
1428: 2017-07-30 19:00:21 40.602983
1429: 2017-07-30 20:00:47 34.292888
1430: 2017-07-30 21:00:20 303.478297
1431: 2017-07-30 22:00:18 5.741059
现在，我想对这张表进行转换，以便它基于多天的数据，提供从0到23每天每一小时的平均行驶距离。这是我一直用于此目的的代码（另外包括一个sd列）：
data_travel<-datanet %>%
mutate(
date = ymd_hms(`Date & Time [Local]`),
hour = hour(date)
) %>%
group_by(hour) %>%
summarise(
avg_meters = mean(meters),
sd_meters = sd(meters)
)
这有效，但遗憾的是，一天23的最后一小时始终显示NA值：
> head(data_travel[19:24,])
# A tibble: 6 x 3
hour avg_meters sd_meters
<int> <dbl> <dbl>
1 18 57.4 109.
2 19 96.5 177.
3 20 121. 248.
4 21 141. 299.
5 22 76.4 86.4
6 23 NA NaN
有人知道如何修改此代码，以便获得avg_meters小时的平均行进距离sd和23吗？任何输入表示赞赏！
> dput(datanet[1:700,])
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```
答案 0 :(得分：1)
您的meters字段可能具有NA值。
因此将na.rm = T添加到mean和sd函数将解决此问题。