scalar multipling two data.frames in r

Question

I have two data.frames in r.THe first one is

                cases      population  urbanisation  density temperature  h_dev_index
Austria         563.375758 10.7969091     63.07388  134.08690   13.011172   0.9898000
Belgium         109.400000 13.5885455     99.38933  443.52112   16.185297   0.9829455
Bulgaria          0.000000  5.5320606     85.84782   52.30011   20.825068   0.9669576
Croatia           2.000000  3.4548485     64.21382   60.46082   20.855372   0.9288667

THe second one is:

Estimate Std. Error t value Pr(>|t|)

(Intercept)                        -1.916e+00  7.144e-01  -2.682  0.00785 ** 
population                         -7.327e-03  1.572e-03  -4.659 5.37e-06 ***
cases                               1.473e-03  1.544e-04   9.541  < 2e-16 ***
urbanisation                        3.798e-03  1.962e-03   1.936  0.05410 .  
density                             8.132e-05  2.512e-04   0.324  0.74641    
temperature                        -3.518e-02  8.641e-03  -4.071 6.43e-05 ***
h_dev_index                         1.842e+00  8.800e-01   2.093  0.03743 *  

I need to multiply the coeffient from the first column from second data.frame to the dataframe.THe result should be(for Austria):

-1.916e+00 + 563.375758*(-7.327e-03)+ 10.7969091*(1.473e-03)+ 63.07388*(3.798e-03)+134.08690*(8.132e-05)+     13.011172*(-3.518e-02)+   0.9898000*1.842e+00

How should I solve this problem?

Answer 1

Try reshaping and merging:

library(tidyverse)
#Code
res <- df1 %>% rownames_to_column('id') %>%
  pivot_longer(-id) %>%
  left_join(df2 %>% select(1,2) %>% rename(name=V1)) %>%
  group_by(id) %>%
  summarise(Val=sum(value*V2)+df2$V2[df2$V1=='(Intercept)'])

Output:

# A tibble: 4 x 2
  id          Val
  <chr>     <dbl>
1 Austria   0.451
2 Belgium  -0.200
3 Bulgaria -0.578
4 Croatia  -0.712

Some data used:

#Data
df1 <- structure(list(cases = c(563.375758, 109.4, 0, 2), population = c(10.7969091, 
13.5885455, 5.5320606, 3.4548485), urbanisation = c(63.07388, 
99.38933, 85.84782, 64.21382), density = c(134.0869, 443.52112, 
52.30011, 60.46082), temperature = c(13.011172, 16.185297, 20.825068, 
20.855372), h_dev_index = c(0.9898, 0.9829455, 0.9669576, 0.9288667
)), class = "data.frame", row.names = c("Austria", "Belgium", 
"Bulgaria", "Croatia"))

df2 <- structure(list(V1 = c("(Intercept)", "population", "cases", "urbanisation", 
"density", "temperature", "h_dev_index"), V2 = c(-1.916, -0.007327, 
0.001473, 0.003798, 8.132e-05, -0.03518, 1.842), V3 = c(0.7144, 
0.001572, 0.0001544, 0.001962, 0.0002512, 0.008641, 0.88), V4 = c(-2.682, 
-4.659, 9.541, 1.936, 0.324, -4.071, 2.093), V5 = c("0.00785", 
"5.37e-06", "<", "0.05410", "0.74641", "6.43e-05", "0.03743"), 
    V6 = c("**", "***", "2e-16", ".", "", "***", "*"), V7 = c("", 
    "", "***", "", "", "", "")), class = "data.frame", row.names = c(NA, 
-7L))

Be careful about the names of your dataframes.