如何对R中的数据框中的某些行求和和加权？

Question

I currently have a data.frame which is as follows:

  State      Area_name    LessHSD        HSD    SomeCAD   BDorMore P_LessHSD P_HSD ZIP
1    US  United States 26,948,057 59,265,308 63,365,655 68,867,051      12.3  27.1 1009
1913 NY Richmond County    37,675    101,738     81,014    108,326      11.5  30.9 36085
2    AL        Alabama    470,043  1,020,172    987,148    822,595      14.2  30.9 1020
3    AL Autauga County      4,204     12,119     10,552     10,291      11.3  32.6 7080
1873 NY Bronx County      258,956    255,427    226,620    183,134       28   27.6 36005
1911 NY Queens County     303,881    454,105    369,271    518,999      18.5  27.6 36081  
4    AL Baldwin County     14,310     40,579     46,025     46,075       9.7  27.6 1088
1901 NY New York County   162,237    155,048    171,461    758,325        13  12.4 36061
5    AL Barbour County      4,901      6,486      4,566      2,220      27.0  35.7 20012
1894 NY Kings County      326,469    455,299 3   47,052    648,461      18.4  25.6 36047
6    AL    Bibb County      2,650      7,471      3,846      1,813      16.8  47.3 9012

I would like to sum up the 5 New York City burroughs (ZIP 36005,36047,36061,36081,36085) data for the columns LessHSD , HSD , SomeCAD and create a new row with these sums with Area_name = New York Proper (see output below).

For the columns P_LessHSD , and P_HSD , I would like to weight these variables by population into a new row. I have already calculated the weights myself from another set. I would like to multiply Richmond County by 0.05669632 , Bronx County by 0.17051732 , Queens by 0.27133878 , New York County by 0.19392188 , and Kings by 0.3075256 .

Tangibly, for the column P_LessHSD, this would look like:

11.5*0.05669632 
+ 28*0.17051732
+ 18.5*0.27133878 
+ 13*0.19392188 
+ 18.4*0.3075256

giving 18.6 (when rounded to tens place). This would be done for P_HSD too. I would like the ZIP of the new row to be 55555. I would also like to delete all 5 rows with the Burroughs.

Output should be:

  State      Area_name    LessHSD        HSD    SomeCAD   BDorMore P_LessHSD P_HSD ZIP
1    US  United States 26,948,057 59,265,308 63,365,655 68,867,051      12.3  27.1 1009
2    AL        Alabama    470,043  1,020,172    987,148    822,595      14.2  30.9 1020
3    AL Autauga County      4,204     12,119     10,552     10,291      11.3  32.6 7080  
4    AL Baldwin County     14,310     40,579     46,025     46,075       9.7  27.6 1088
5    AL Barbour County      4,901      6,486      4,566      2,220      27.0  35.7 20012
6    AL    Bibb County      2,650      7,471      3,846      1,813      16.8  47.3 9012
7    NY New York Proper   1089218    1421617     895418    2217245      18.6  24.2 55555

Answer 1

Might it helps.

It use dplyr package. You need install it first

install.packages("dplyr")

library(dplyr)

DF %>% 
  filter(!(ZIP %in% c(36005,36047,36061,36081,36085))) %>%
  bind_rows(
        DF %>%
          filter(ZIP %in% c(36005,36047,36061,36081,36085)) %>%
          mutate(wg = case_when(Area_name == "Richmond County" ~ 0.05669632, 
                                Area_name == "Bronx County" ~ 0.17051732,
                                Area_name == "Queens County" ~ 0.27133878,
                                Area_name == "New York County" ~ 0.19392188, 
                                Area_name == "Kings County" ~ 0.3075256,
                                TRUE ~ 0),
                 P_LessHSD = wg*P_LessHSD,
                 P_HSD = wg*P_HSD,
                 Area_name = "New York Proper") %>%
          group_by(State, Area_name) %>%
          summarize_at(vars(LessHSD:P_HSD), sum) %>%
          mutate(ZIP = 55555) )

# # A tibble: 7 x 9
#   State Area_name        LessHSD      HSD  SomeCAD BDorMore P_LessHSD P_HSD   ZIP
#   <chr> <chr>              <dbl>    <dbl>    <dbl>    <dbl>     <dbl> <dbl> <dbl>
# 1 US    United States   26948057 59265308 63365655 68867051      12.3  27.1  1009
# 2 AL    Alabama           470043  1020172   987148   822595      14.2  30.9  1020
# 3 AL    Autauga County      4204    12119    10552    10291      11.3  32.6  7080
# 4 AL    Baldwin County     14310    40579    46025    46075       9.7  27.6  1088
# 5 AL    Barbour County      4901     6486     4566     2220      27    35.7 20012
# 6 AL    Bibb County         2650     7471     3846     1813      16.8  47.3  9012
# 7 NY    New York Proper  1089218  1421617  1195418  2217245      18.6  24.2 55555

PS. It gives different result for someCAD .