根据R中的另一列删除重复的日期 [英] Removing duplicate dates based on another column in R
问题描述
我有一个具有多个条目的时间数小时。
I have a timeseries with multiple entries for some hours.
date wd ws temp sol octa pg mh daterep
1 2007-01-01 00:00:00 100 1.5 9.0 0 8 D 100 FALSE
2 2007-01-01 01:00:00 90 2.6 9.0 0 7 E 50 TRUE
3 2007-01-01 01:00:00 90 2.6 9.0 0 8 D 100 TRUE
4 2007-01-01 02:00:00 40 1.0 8.8 0 7 F 50 FALSE
5 2007-01-01 03:00:00 20 2.1 8.0 0 8 D 100 FALSE
6 2007-01-01 04:00:00 30 1.0 8.0 0 8 D 100 FALSE
我需要得到一个时间序列，每小时一个条目，取最小mh值的条目有多个条目。 （所以在上面的数据我的第二个条目应该是行2和行3应该被删除。）
我一直在处理这两种方法：挑选我想要的一个新的数据框，并删除我所做的不想在现有的，但没有得到任何地方。感谢您的帮助。
I need to get to a time series with one entry per hour, taking the entry with the minimum mh value where there are multiple entries. (So in the data above my second entry should be row 2 and row 3 should be removed.) I've been working on both approaches: picking out what I want into a new dataframe, and removing what I don't want in the existing, but not getting anywhere. Thanks for your help.
推荐答案
您可以通过日期排序您的数据和 mh 使用 plyr :: arrange ，然后删除重复项：
You could sort your data by date and mh using plyr::arrange, then remove duplicates:
df <- read.table(textConnection("
date wd ws temp sol octa pg mh daterep
'2007-01-01 00:00:00' 100 1.5 9.0 0 8 D 100 FALSE
'2007-01-01 01:00:00' 90 2.6 9.0 0 7 E 50 TRUE
'2007-01-01 01:00:00' 90 2.6 9.0 0 8 D 100 TRUE
'2007-01-01 02:00:00' 40 1.0 8.8 0 7 F 50 FALSE
'2007-01-01 03:00:00' 20 2.1 8.0 0 8 D 100 FALSE
'2007-01-01 04:00:00' 30 1.0 8.0 0 8 D 100 FALSE
"), header = TRUE)
library(plyr)
df <- arrange(df, date, mh)
df <- df[!duplicated(df$date), ]
df
# date wd ws temp sol octa pg mh daterep
# 1 2007-01-01 00:00:00 100 1.5 9.0 0 8 D 100 FALSE
# 2 2007-01-01 01:00:00 90 2.6 9.0 0 7 E 50 TRUE
# 4 2007-01-01 02:00:00 40 1.0 8.8 0 7 F 50 FALSE
# 5 2007-01-01 03:00:00 20 2.1 8.0 0 8 D 100 FALSE
# 6 2007-01-01 04:00:00 30 1.0 8.0 0 8 D 100 FALSE
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