CODEWITHSUNDEEP
rdataframe
Dinoop Nair
Dinoop Nair

Reputation: 2773

multiplying two data frames

In R, i have 2 data frames "df1" and "df2". The df1 and df2 are as follows.

>df1
  date      value
1 1990-10-10  3
2 1990-10-11  2.3
3 1990-10-12  2.5

>df2
  date      value
1 1990-10-10  3
2 1990-10-11  2
3 1990-10-12  2

I need a third data frame "df3", that contains the same column names as df1 and df2. But the value field should be the product of values in df1 and df2. I am expecting the following output

>df3
  date      value
1 1990-10-10  9
2 1990-10-11  4.6
3 1990-10-12  4

Is it possible in R?

Upvotes: 1

Views: 14930

Answers (4)

Ricardo Saporta
Ricardo Saporta

Reputation: 55350

If all the dates are identical, then you can simply use: 

df3 <- df1
df3$value <- as.numeric(as.character(df3$value))
df3$value <- df3$value * as.numeric(as.character(df2$value))

If the dates are NOT identical in the two data.frames, please use @MatthewLundberg answer below

Upvotes: 5

IRTFM
IRTFM

Reputation: 263342

After you fix you problems with df1 and df2 having "values" of type factor which is really someting you should do before attempting this, you can do just this:

df3 <- data.frame( data=df1$date, value=df1[ ,"value"]*df2[ ,"value"])

The conversion of factors that should be numeric is covered in the R-FAQ: FAQ 7.10

Upvotes: 2

Matthew Lundberg
Matthew Lundberg

Reputation: 42649

"Merge" the long way with rbind, and use aggregate to produce the products:

aggregate(value ~ date, data=rbind(df1,df2), FUN=prod)
##         date value
## 1 1990-10-10   9.0
## 2 1990-10-11   4.6
## 3 1990-10-12   5.0

If you have mode factor for the value columns of the data frames, you'll have to convert to character then to numeric to extract the value:

df1$value <- as.factor(df1$value)
df2$value <- as.factor(df2$value)

aggregate(as.numeric(as.character(value)) ~ date, data=rbind(df1,df2), FUN=prod)
##         date as.numeric(as.character(value))
## 1 1990-10-10                             9.0
## 2 1990-10-11                             4.6
## 3 1990-10-12                             5.0

You can also convert with as.numeric(levels(value))[value]. See ?factor for details.

Upvotes: 9

A5C1D2H2I1M1N2O1R2T1
A5C1D2H2I1M1N2O1R2T1

Reputation: 193517

Perhaps you can merge the two data.frames first and then proceed with transform:

> temp <- merge(df1, df2, by = "date")
> temp
        date value.x value.y
1 1990-10-10     3.0       3
2 1990-10-11     2.3       2
3 1990-10-12     2.5       2
> transform(temp, Prod = value.x * value.y)
        date value.x value.y Prod
1 1990-10-10     3.0       3  9.0
2 1990-10-11     2.3       2  4.6
3 1990-10-12     2.5       2  5.0

Here, since both data.frames have the same column names, I've specified that we want to merge only by the "date" variable so that both "value" variables would be present in the "temp" data.frame.

Upvotes: 3

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