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为方便处理，在数据集中增加一列car

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

gather-宽数据转为长数据,类似于reshape2包中的melt函数

mtcarsNew <- mtcars%>%gather(attribute,value,-car)
#tidyr很好的一点是可以只gather若干列而其他列保持不变。如果你想gather在map和gear之间的所有列而保持carb和car列不变
mtcarsNew <- mtcars%>%gather(attribute,value,mpg:gear)

spread—长数据转为宽数据,类似于reshape2包中的cast函数

mtcarsSpread <- mtcarsNew%>%spread(attribute,value)

unit—多列合并为一列

set.seed(1)
date <- as.Date('2016-01-01') + 0:14
hour <- sample(1:24, 15)
min <- sample(1:60, 15)
second <- sample(1:60, 15)
event <- sample(letters, 15)
data <- data.frame(date, hour, min, second, event)

dataNew <- data%>%
  unite(datehour,date,hour,sep=' ')%>%
  unite(datetime,datehour,min,second,sep=':')

separate—将一列分离为多列

data1 <- dataNew%>%
  separate(datetime,c('date','time'),sep=' ')%>%
  separate(time,c('hour','min','second'),sep=':')