New column in original df using another df

[serialknitter]

Hi all,

I have two dummy data frames and they are shown below. I would like to create a new column in df1 with the calculation "conc*height" if the month corresponding to the concentration in df1 matches the month in df2. It seems relatively straight-forward, but I'm afraid my R skills are not up to par yet.

Thanks so much in advance!

df1:
Year	Month	conc
2000	1	4
2000	2	3
2000	3	7
2000	4	4
2000	5	1
2000	6	4
2000	7	6
2000	8	8
2000	9	5
2000	10	3
2000	11	4
2000	12	3
2001	1	7
2001	2	3
2001	3	45
2001	4	2
2001	5	3
2001	6	7
2001	7	9
2001	8	7
2001	9	4
2001	10	2
2001	11	45
2001	12	7

df2:
Month	height
1	250
2	300
3	350
4	400
5	450
6	500
7	450
8	400
9	350
10	300
11	250
12    200

[williaml]

Probably a join:

https://dplyr.tidyverse.org/reference/join.html

[andresrcs]

This is how to do it

library(dplyr)

df1 <- data.frame(
        Year = c(2000,2000,2000,2000,2000,2000,2000,
                 2000,2000,2000,2000,2000,2001,2001,2001,2001,2001,2001,
                 2001,2001,2001,2001,2001,2001),
       Month = c(1,2,3,4,5,6,7,8,9,10,11,12,1,2,
                 3,4,5,6,7,8,9,10,11,12),
        conc = c(4,3,7,4,1,4,6,8,5,3,4,3,7,3,
                 45,2,3,7,9,7,4,2,45,7)
)

df2 <- data.frame(
       Month = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12),
      height = c(250, 300, 350, 400, 450, 500, 450, 400, 350, 300, 250, 200)
)

df1 %>% 
    left_join(df2, by = "Month") %>% 
    mutate(new_col = conc * height)
#>    Year Month conc height new_col
#> 1  2000     1    4    250    1000
#> 2  2000     2    3    300     900
#> 3  2000     3    7    350    2450
#> 4  2000     4    4    400    1600
#> 5  2000     5    1    450     450
#> 6  2000     6    4    500    2000
#> 7  2000     7    6    450    2700
#> 8  2000     8    8    400    3200
#> 9  2000     9    5    350    1750
#> 10 2000    10    3    300     900
#> 11 2000    11    4    250    1000
#> 12 2000    12    3    200     600
#> 13 2001     1    7    250    1750
#> 14 2001     2    3    300     900
#> 15 2001     3   45    350   15750
#> 16 2001     4    2    400     800
#> 17 2001     5    3    450    1350
#> 18 2001     6    7    500    3500
#> 19 2001     7    9    450    4050
#> 20 2001     8    7    400    2800
#> 21 2001     9    4    350    1400
#> 22 2001    10    2    300     600
#> 23 2001    11   45    250   11250
#> 24 2001    12    7    200    1400

^{Created on 2020-04-19 by the reprex package (v0.3.0.9001)}

Please notice the way I'm posting the answer, that would be a proper reproducible example, next time please try to make your questions providing one. Here is how to do it:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…