The use of dcast and melt in R language is simple and easy to understand

R In language dcast and melt Use

2.  Example 
 Example data ：

set.seed(123)
dat = data.frame(ID = paste0("ID_",1:10),y1 = rnorm(10),y2=rnorm(10),y3=rnorm(10),y4 = rnorm(10))
dat
 result 

> dat
      ID          y1         y2         y3          y4
1   ID_1 -0.56047565  1.2240818 -1.0678237  0.42646422
2   ID_2 -0.23017749  0.3598138 -0.2179749 -0.29507148
3   ID_3  1.55870831  0.4007715 -1.0260044  0.89512566
4   ID_4  0.07050839  0.1106827 -0.7288912  0.87813349
5   ID_5  0.12928774 -0.5558411 -0.6250393  0.82158108
6   ID_6  1.71506499  1.7869131 -1.6866933  0.68864025
7   ID_7  0.46091621  0.4978505  0.8377870  0.55391765
8   ID_8 -1.26506123 -1.9666172  0.1533731 -0.06191171
9   ID_9 -0.68685285  0.7013559 -1.1381369 -0.30596266
10 ID_10 -0.44566197 -0.4727914  1.2538149 -0.38047100
3.  Change to three columns ：ID,trait,y
melt  Code 
re1 = melt(data = dat,id.vars=c("ID"),variable.name="Loc",value.name="y")
head(re1)
 Results Preview 

> head(re1)
    ID Loc           y
1 ID_1  y1 -0.56047565
2 ID_2  y1 -0.23017749
3 ID_3  y1  1.55870831
4 ID_4  y1  0.07050839
5 ID_5  y1  0.12928774
6 ID_6  y1  1.71506499
4. dcast Code 
dcast(data=re1,ID ~Loc)
 result 

> dcast(data=re1,ID ~Loc)
Using 'y' as value column. Use 'value.var' to override
      ID          y1         y2         y3          y4
1   ID_1 -0.56047565  1.2240818 -1.0678237  0.42646422
2  ID_10 -0.44566197 -0.4727914  1.2538149 -0.38047100
3   ID_2 -0.23017749  0.3598138 -0.2179749 -0.29507148
4   ID_3  1.55870831  0.4007715 -1.0260044  0.89512566
5   ID_4  0.07050839  0.1106827 -0.7288912  0.87813349
6   ID_5  0.12928774 -0.5558411 -0.6250393  0.82158108
7   ID_6  1.71506499  1.7869131 -1.6866933  0.68864025
8   ID_7  0.46091621  0.4978505  0.8377870  0.55391765
9   ID_8 -1.26506123 -1.9666172  0.1533731 -0.06191171
10  ID_9 -0.68685285  0.7013559 -1.1381369 -0.30596266
5. Command parsing 
melt It means integration , Put wide data , Become long data . For example, in field data ,ID,Loc,rep1, rep2, re3, there rep1,rep2,rep3 It's repetition 1,2,3 Value , You need to turn the data into ：ID,Loc,Rep,y Four columns of data . In this way, you can use melt command 
melt(dat,c("ID","Loc"))
> ex1 = data.frame(Cul = rep(1:10,2),Loc=rep(1:2,each=10),rep1=rnorm(20),rep2=rnorm(20),rep3=rnorm(20))
> head(ex1)
  Cul Loc        rep1       rep2       rep3
1   1   1 -0.71040656  0.1176466  0.7017843
2   2   1  0.25688371 -0.9474746 -0.2621975
3   3   1 -0.24669188 -0.4905574 -1.5721442
4   4   1 -0.34754260 -0.2560922 -1.5146677
5   5   1 -0.95161857  1.8438620 -1.6015362
6   6   1 -0.04502772 -0.6519499 -0.5309065
> ex1_re = melt(ex1,c("Cul","Loc"))
> head(ex1_re)
  Cul Loc variable       value
1   1   1     rep1 -0.71040656
2   2   1     rep1  0.25688371
3   3   1     rep1 -0.24669188
4   4   1     rep1 -0.34754260
5   5   1     rep1 -0.95161857
6   6   1     rep1 -0.04502772
dcast Long data , Widening data , therefore ex1_re If you want to change back , use dcast(ex1_re, Cul + Loc ~ variable), ~ To the left of the sign is the column name that remains unchanged ,~ On the right is the column name that needs to be extended ,  Omitted value Is the data that needs to be filled .
> dcast(ex1_re,Cul+Loc~variable)
   Cul Loc        rep1        rep2       rep3
1    1   1 -0.71040656  0.11764660  0.7017843
2    1   2 -0.57534696  1.44455086  0.7877388
3    2   1  0.25688371 -0.94747461 -0.2621975
4    2   2  0.60796432  0.45150405  0.7690422
5    3   1 -0.24669188 -0.49055744 -1.5721442
6    3   2 -1.61788271  0.04123292  0.3322026
7    4   1 -0.34754260 -0.25609219 -1.5146677
8    4   2 -0.05556197 -0.42249683 -1.0083766
9    5   1 -0.95161857  1.84386201 -1.6015362
10   5   2  0.51940720 -2.05324722 -0.1194526
11   6   1 -0.04502772 -0.65194990 -0.5309065
12   6   2  0.30115336  1.13133721 -0.2803953
13   7   1 -0.78490447  0.23538657 -1.4617556
14   7   2  0.10567619 -1.46064007  0.5629895
15   8   1 -1.66794194  0.07796085  0.6879168
16   8   2 -0.64070601  0.73994751 -0.3724388
17   9   1 -0.38022652 -0.96185663  2.1001089
18   9   2 -0.84970435  1.90910357  0.9769734
19  10   1  0.91899661 -0.07130809 -1.2870305
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