R - conditionally replace rows in data table [duplicate]

I am trying to conditionally replace row values in a data table.Please consider the following dataset excerpt:

library(data.table)txt1 <- "Date Location Measurement Scenario         Var Month    Decade  1960-01-01  4100103        23.3  CRU3.2 Temperature   Jan 1960-1990  1960-02-01  4100103        24.1  CRU3.2 Temperature   Feb 1960-1990  1960-03-01  4100103        23.6  CRU3.2 Temperature   Mar 1960-1990  1960-04-01  4100103        20.4  CRU3.2 Temperature   Apr 1960-1990  1960-05-01  4100103        16.2  CRU3.2 Temperature   May 1960-1990  1960-06-01  4100103        16.5  CRU3.2 Temperature   Jun 1960-1990"dt <- data.table(read.table(textConnection(txt1), header=TRUE))

This is just a sample. My actual data has about 2.5 million rows.

As you can see, I have temperature measurements for multiple locations.However, the locations are identified with geocode instead of names, which is not very readable.

Therefore, I have another dataset that relates geocode and city name:

txt2 <- "GEOCODIG_M, Name4100103,              Abatiá4100202,        Adrianópolis4100301,       Agudos do Sul4100400, Almirante Tamandaré4100459,  Altamira do Paraná4100509,             Altônia"df <- read.csv(textConnection(txt2),sep=',', header=TRUE)

So, what I need to do is compare the field Location in dt to GEOCODIG_M in df and replace geocode by name.

The expected outcome for this case would be:

        Date    Name Measurement Scenario         Var Month    Decade  1960-01-01  Abatiá        23.3  CRU3.2 Temperature   Jan 1960-1990  1960-02-01  Abatiá        24.1  CRU3.2 Temperature   Feb 1960-1990  1960-03-01  Abatiá        23.6  CRU3.2 Temperature   Mar 1960-1990  1960-04-01  Abatiá        20.4  CRU3.2 Temperature   Apr 1960-1990  1960-05-01  Abatiá        16.2  CRU3.2 Temperature   May 1960-1990  1960-06-01  Abatiá        16.5  CRU3.2 Temperature   Jun 1960-1990

What is the best way to do this using data tables?