要详细说明我的上一个问题:我想在R中为大型csv数据集子集。我想获取“ timestamp”列的信息,仅提取7pm到12am(含)之间的时间间隔。下面是数据示例:
Deer ID TimeStamp Location
1 4/16/18 12:00AM DMA 1
2 4/16/18 3:00AM DMA 1
3 4/16/18 9:30AM DMA 2
4 4/16/18 7:00PM DMA 1
5 4/16/18 8:30PM DMA 2
6 4/16/18 11:00PM DMA 3
7 4/17/18 1:30AM DMA 2
8 4/17/18 5:00AM DMA 1
9 4/17/18 9:00PM DMA 3
10 4/17/18 11:30PM DMA 1
11 4/18/18 12:30AM DMA 2
所以我的最终目标是使自己达到以下目标:
Deer ID TimeStamp Location
4 4/16/18 7:00PM DMA 1
5 4/16/18 8:30PM DMA 2
6 4/16/18 11:00PM DMA 3
9 4/17/18 9:00PM DMA 3
10 4/17/18 11:30PM DMA 1
关于如何实现此目标的任何想法?谢谢!
答案 0 :(得分:2)
您可以执行以下操作
# Convert TimeStamp to POSIXct
df <- transform(df, TimeStamp = strptime(TimeStamp, "%m/%d/%Y %I:%M%p"))
# Use lubridate::hour to extract the hours from the POSIXct timestamp
library(lubridate)
df[(hour(df$TimeStamp) >= 19 & hour(df$TimeStamp) <= 24), ]
# Deer.ID TimeStamp Location
#4 4 0018-04-16 19:00:00 DMA 1
#5 5 0018-04-16 20:30:00 DMA 2
#6 6 0018-04-16 23:00:00 DMA 3
#9 9 0018-04-17 21:00:00 DMA 3
#10 10 0018-04-17 23:30:00 DMA 1
df <- read.table(text =
"'Deer ID' TimeStamp Location
1 '4/16/18 12:00AM' 'DMA 1'
2 '4/16/18 3:00AM' 'DMA 1'
3 '4/16/18 9:30AM' 'DMA 2'
4 '4/16/18 7:00PM' 'DMA 1'
5 '4/16/18 8:30PM' 'DMA 2'
6 '4/16/18 11:00PM' 'DMA 3'
7 '4/17/18 1:30AM' 'DMA 2'
8 '4/17/18 5:00AM' 'DMA 1'
9 '4/17/18 9:00PM' 'DMA 3'
10 '4/17/18 11:30PM' 'DMA 1'
11 '4/18/18 12:30AM' 'DMA 2'", header = T)
答案 1 :(得分:0)
tidyverse方式将遵循以下原则:
library(dplyr)
df <- read.table(
text =
"id timestamp location
1 '4/16/18 12:00AM' 'DMA 1'
2 '4/16/18 3:00AM' 'DMA 1'
3 '4/16/18 9:30AM' 'DMA 2'
4 '4/16/18 7:00PM' 'DMA 1'
5 '4/16/18 8:30PM' 'DMA 2'
6 '4/16/18 11:00PM' 'DMA 3'
7 '4/17/18 1:30AM' 'DMA 2'
8 '4/17/18 5:00AM' 'DMA 1'
9 '4/17/18 9:00PM' 'DMA 3'
10 '4/17/18 11:30PM' 'DMA 1'
11 '4/18/18 12:30AM' 'DMA 2'",
header = TRUE
) %>%
as_tibble()
df %>%
mutate(timestamp = as.POSIXct(strptime(.data$timestamp, "%m/%d/%Y %I:%M%p"))) %>%
filter(between(lubridate::hour(.data$timestamp), 19, 24))
#> # A tibble: 5 x 3
#> id timestamp location
#> <int> <dttm> <chr>
#> 1 4 0018-04-16 19:00:00 DMA 1
#> 2 5 0018-04-16 20:30:00 DMA 2
#> 3 6 0018-04-16 23:00:00 DMA 3
#> 4 9 0018-04-17 21:00:00 DMA 3
#> 5 10 0018-04-17 23:30:00 DMA 1
由reprex package(v0.2.1)于2019-02-19创建