我有一个像这样的数据框df.sample
id <- c("A","A","A","A","A","A","A","A","A","A","A")
date <- c("2018-11-12","2018-11-12","2018-11-12","2018-11-12","2018-11-12",
"2018-11-12","2018-11-12","2018-11-14","2018-11-14","2018-11-14",
"2018-11-12")
hour <- c(8,8,9,9,13,13,16,6,7,19,7)
min <- c(47,59,6,18,22,36,12,32,12,21,47)
value <- c(70,70,86,86,86,74,81,77,79,83,91)
df.sample <- data.frame(id,date,hour,min,value,stringsAsFactors = F)
df.sample$date <- as.Date(df.sample$date,format="%Y-%m-%d")
我还有另一个数据框df.state
id <- c("A","A","A")
starttime <- c("2018-11-12 08:59:00","2018-11-14 06:24:17","2018-11-15 09:17:00")
endtime <- c("2018-11-12 15:57:00","2018-11-14 17:22:16","2018-11-15 12:17:32")
state <- c("Pass","Pass","Pass")
df.state <- data.frame(id,starttime,endtime,state,stringsAsFactors = F)
df.state$starttime <- as.POSIXct(df.state$starttime,format="%Y-%m-%d %H:%M:%S")
df.state$endtime <- as.POSIXct(df.state$endtime,format="%Y-%m-%d %H:%M:%S")
我正在尝试根据条件合并这两个数据帧
如果hour中的min和df.sample在starttime的{{1}}和endtime内，则合并df.state在state = Pass中。
例如，df.sample中的行2具有df.sample，hour = 8，并且由于它位于min = 59中的starttime = 2018-11-12 08:59:00之内，因此值{{1 }}已添加
这是我的所需输出
df.state我能够像这样合并这两个数据帧，但无法在df.state的开始时间和结束时间中查找df.sample的小时和分钟
Pass有人可以指出我正确的方向
答案 0 :(得分：4)
如果碰巧有大数据框架，则使用data.table软件包中的非等额联接会更快，更容易： Benchmark | Video
library(data.table)
## convert both data.frames to data.tables by reference
setDT(df.sample)
setDT(df.state)
## create a `time` column in df.sample
df.sample[, time := as.POSIXct(paste0(date, " ", hour, ":", min, ":00"))]
## change column order
setcolorder(df.sample, c("id", "time"))
# join by id and time within start & end time limits
# "x." is used so we can refer to the column in other data.table explicitly
df.state[df.sample, .(id, time, date, hour, min, value, state = x.state),
on = .(id, starttime <= time, endtime >= time)]
#> id time date hour min value state
#> 1: A 2018-11-12 08:47:00 2018-11-12 8 47 70 <NA>
#> 2: A 2018-11-12 08:59:00 2018-11-12 8 59 70 Pass
#> 3: A 2018-11-12 09:06:00 2018-11-12 9 6 86 Pass
#> 4: A 2018-11-12 09:18:00 2018-11-12 9 18 86 Pass
#> 5: A 2018-11-12 13:22:00 2018-11-12 13 22 86 Pass
#> 6: A 2018-11-12 13:36:00 2018-11-12 13 36 74 Pass
#> 7: A 2018-11-12 16:12:00 2018-11-12 16 12 81 <NA>
#> 8: A 2018-11-14 06:32:00 2018-11-14 6 32 77 Pass
#> 9: A 2018-11-14 07:12:00 2018-11-14 7 12 79 Pass
#> 10: A 2018-11-14 19:21:00 2018-11-14 19 21 83 <NA>
#> 11: A 2018-11-12 07:47:00 2018-11-12 7 47 91 <NA>
### remove NA
df.state[df.sample, .(id, time, date, hour, min, value, state = x.state),
on = .(id, starttime <= time, endtime >= time), nomatch = 0L]
#> id time date hour min value state
#> 1: A 2018-11-12 08:59:00 2018-11-12 8 59 70 Pass
#> 2: A 2018-11-12 09:06:00 2018-11-12 9 6 86 Pass
#> 3: A 2018-11-12 09:18:00 2018-11-12 9 18 86 Pass
#> 4: A 2018-11-12 13:22:00 2018-11-12 13 22 86 Pass
#> 5: A 2018-11-12 13:36:00 2018-11-12 13 36 74 Pass
#> 6: A 2018-11-14 06:32:00 2018-11-14 6 32 77 Pass
#> 7: A 2018-11-14 07:12:00 2018-11-14 7 12 79 Pass
由reprex package（v0.3.0）于2019-05-23创建
答案 1 :(得分：1)
（重要的备考笔记：import React, {Component} from 'react';
import Slide from 'react-reveal/Slide';
class RedBox extends Component {
constructor(props){
super(props);
this.handleChange = this.handleChange.bind(this);
this.state = {
text: props.text
}
}
handleChange(event) {
this.setState({text: event.target.value});
}
render(){
const { toggleState, text, style} = this.props;
return(
<div style={style}
onClick={()=>{console.log('red clicked'); toggleState({text: this.state.text})}}>
<input onChange={this.handleChange}
type="text" value={this.state.text}
onClick={(event)=>{event.stopPropagation()}}
style={{zIndex: '999'}}
/>
{ text }
</div>
);
}
}
const BlueBox = ({toggleState, passedProps, style })=> {
return (
<div onClick={toggleState} style={style}>
{ passedProps.text }
</div>
);
};
class MouseTracker extends React.Component {
constructor(props) {
super(props);
this.handleClick = this.handleClick.bind(this);
}
handleClick(event) {
const coords = {
x: event.clientX,
y: event.clientY
};
this.props.toggleState(coords);
}
render() {
return (
<div style={{ height: '100px' }} onClick={this.handleClick}>
<h1>Click me!</h1>
</div>
);
}
}
const MouseInformer = ({toggleState, passedProps}) => (
<div>
You clicked {passedProps.x}, {passedProps.y}!
<button onClick={toggleState}>Go Back</button>
</div>
);
class SlidePair extends Component {
constructor(props){
super(props);
this.state = { left: true, passedProps: {}};
this.toggleState = this.toggleState.bind(this);
}
toggleState(passedProps){
const left = !this.state.left;
console.log(`Toggling left to ${left}`);
this.setState({ left, passedProps });
}
render(){
const {left, passedProps } = this.state;
return(
<div style={{position: 'relative'}}>
<Slide left when={left} >
<div style={ {position: 'absolute', top: '0px', right: '0px', width: '100%', zIndex: left ? '998' : -1 }}>
{this.props.renderLeft(this.toggleState, passedProps)}
</div>
</Slide>
<Slide right when={!left}>
<div style={{position: 'absolute', top: '0px', right: '0px', width: '100%', zIndex: left ? -1 : 1}}>
{ this.props.renderRight(this.toggleState, passedProps) }
</div>
</Slide>
</div>
)
}
}
class App extends Component {
render(){
const redBox = (toggleState, passedProps)=>(
<RedBox toggleState={toggleState}
style={{width: '100%', border: '5px solid red', height: '100px'}}/>
);
const blueBox = (toggleState, passedProps) => (
<BlueBox
toggleState={toggleState}
passedProps={passedProps}
style={{width: '100%', border: '5px solid blue', height: '100px'}}
/>
);
const mouseTracker = (toggleState, passedProps) => (
<MouseTracker toggleState={toggleState} passedProps={passedProps} style={{top: '300px'}}/>
);
const mouseInformer = (toggleState, passedProps) => (
<MouseInformer toggleState={toggleState} passedProps={passedProps} style={{top: '300px'}}/>
);
return (
<div className="App">
<SlidePair renderLeft={redBox} renderRight={blueBox}/>
<br/>
<SlidePair renderLeft={mouseTracker} renderRight={mouseInformer} />
</div>
);
}
}
export default App;
使用本地时区创建POSIXct值，而as.POSIXct创建UTC时间。如果以下联接中的时区不同，您将得到意想不到的结果。）
lubridate::ymd这可以通过Fuzzyjoin完成：
df.state$starttime <- lubridate::ymd_hms(df.state$starttime)
df.state$endtime <- lubridate::ymd_hms(df.state$endtime)
答案 2 :(得分：1)
可以通过以下操作来完成：首先在您的df.sample data.frame中添加一个时间列，然后使用sapply根据您的条件进行评估，然后将此结果添加到df.sample
df.sample$time <- paste0(df.sample$date, ' ', sprintf('%02d', df.sample$hour),':', sprintf('%02d', df.sample$min), ':00')
df.sample$state <- sapply(df.sample$time, function(x) {
after_start <- x >= df.state$starttime
before_end <- x <= df.state$endtime
y <- cbind(after_start, before_end)
pass_check <- apply(y, 1, sum)
if (2 %in% pass_check) {'PASS'} else {''}
})
df.sample
id date hour min value time state
1 A 2018-11-12 8 47 70 2018-11-12 08:47:00
2 A 2018-11-12 8 59 70 2018-11-12 08:59:00 PASS
3 A 2018-11-12 9 6 86 2018-11-12 09:06:00 PASS
4 A 2018-11-12 9 18 86 2018-11-12 09:18:00 PASS
5 A 2018-11-12 13 22 86 2018-11-12 13:22:00 PASS
6 A 2018-11-12 13 36 74 2018-11-12 13:36:00 PASS
7 A 2018-11-12 16 12 81 2018-11-12 16:12:00
8 A 2018-11-14 6 32 77 2018-11-14 06:32:00 PASS
9 A 2018-11-14 7 12 79 2018-11-14 07:12:00 PASS
10 A 2018-11-14 19 21 83 2018-11-14 19:21:00
11 A 2018-11-12 7 47 91 2018-11-12 07:47:00
答案 3 :(得分：1)
我所做的是从您提供的每个数据框中提取十进制小时，以便我询问是否在该十进制小时内找到了一个值。但是首先，您必须基于id（假设您还有其他id）和日期（假设每天只有一个州;或者换句话说df.state数据集中每天只有一个日期）合并数据集。 / p>
id <- c("A","A","A","A","A","A","A","A","A","A","A")
date <- c("2018-11-12","2018-11-12","2018-11-12","2018-11-12","2018-11-12",
"2018-11-12","2018-11-12","2018-11-14","2018-11-14","2018-11-14",
"2018-11-12")
hour <- c(8,8,9,9,13,13,16,6,7,19,7)
min <- c(47,59,6,18,22,36,12,32,12,21,47)
value <- c(70,70,86,86,86,74,81,77,79,83,91)
df.sample <- data.frame(id,date,hour,min,value,stringsAsFactors = F)
df.sample$date <- as.Date(df.sample$date,format="%Y-%m-%d")
df.sample$dec.hour <- as.numeric(df.sample$hour) +
as.numeric(df.sample$min)/60
我在上面添加的全部内容都是这些最后几行内容，它们可根据您提供的小时和分钟值计算出十进制小时
id <- c("A","A","A")
starttime <- c("2018-11-12 08:59:00","2018-11-14 06:24:17","2018-11-15 09:17:00")
endtime <- c("2018-11-12 15:57:00","2018-11-14 17:22:16","2018-11-15 12:17:32")
state <- c("Pass","Pass","Pass")
df.state <- data.frame(id,starttime,endtime,state,stringsAsFactors = F)
在这里，我添加了一个日期向量（用于合并）。假设开始日期和结束时间始终相同，我可以任意选择开始时间。
df.state$date <- as.Date(df.state$starttime,format="%Y-%m-%d")
然后我在该日期的开始时间和结束时间都得到了十进制小时
t.str <- strptime(df.state$starttime, "%Y-%m-%d %H:%M:%S")
df.state$dec.hour.start <- as.numeric(format(t.str, "%H")) +
as.numeric(format(t.str, "%M"))/60
t.end <- strptime(df.state$endtime, "%Y-%m-%d %H:%M:%S")
df.state$dec.hour.end <- as.numeric(format(t.end, "%H")) +
as.numeric(format(t.end, "%M"))/60
按ID和日期合并数据框
df<-merge(df.sample, df.state, by=c("id","date"))
如果样本的十进制小时在该日期的开始或结束十进制小时之内，则返回状态TRUE。
df<-df %>%
mutate(state = dec.hour >= dec.hour.start & dec.hour <= dec.hour.end)
现在，如果您想摆脱我创建的所有这些额外的列（看起来像您想要的输出）：
df<-df[,-c(6:8,10:11)]
因为df $ state是逻辑的，所以如果要更改TRUE以传递，而将FALSE更改为空格，则必须首先将值转换为字符：
df$state<-as.character(df$state)
df$state[df$state=="TRUE"]<-"pass"
df$state[df$state=="FALSE"]<-""
看看：
df
> df
id date hour min value state
1 A 2018-11-12 8 47 70
2 A 2018-11-12 8 59 70 pass
3 A 2018-11-12 9 6 86 pass
4 A 2018-11-12 9 18 86 pass
5 A 2018-11-12 13 22 86 pass
6 A 2018-11-12 13 36 74 pass
7 A 2018-11-12 16 12 81
8 A 2018-11-12 7 47 91
9 A 2018-11-14 6 32 77 pass
10 A 2018-11-14 7 12 79 pass
11 A 2018-11-14 19 21 83
我使用了这篇文章：extract hours and seconds from POSIXct for plotting purposes in R提取十进制小时数 还有一个：Check to see if a value is within a range?，以查看您的采样时间是否在您的状态时间内。