Comments (1)
join
seems to require that key variables are of the same generic type. Is this related to the hashing algorithm? It seems to be fine with both being strings or both being numeric but not one of each.
Minimal example:
* generate data
clear
* master dataset
set seed 09092019
set obs 10
gen string_id = "A"
replace string_id = "B" if _n > 5
gen number_id = int(runiform() * 2)
save temp_master_dataset, replace
* using dataset
duplicates drop
gen usingvar = "BLA" * (number_id + 1)
tostring number_id, gen(number_id_tostring)
save temp_using_dataset, replace
use master, clear
* error when joining
join, from(temp_using_dataset) by(string_id number_id)
* case with no error when using only strings
tostring number_id, gen(number_id_tostring)
join usingvar, from(temp_using_dataset) by(string_id number_id_tostring)
Thank you for the package!
from ftools.
Related Issues (20)
- fmerge error HOT 1
- data type following fcollapse HOT 1
- fcollapse with any missing weights returns all missing HOT 1
- fcollapse incorrectly parses negative weights HOT 6
- join: do not copy certain chars
- Adding update / replace to fmerge HOT 9
- join: problems with spaces in filepath HOT 1
- fmerge error HOT 4
- error with join HOT 3
- join: error when using labels and key has different name in using
- fmerge overwrites master dataset's xtset HOT 2
- fmerge: 1:1 merge, error 3498, <id1 id2> do not uniquely identify obs. in the master data HOT 5
- Running ftools commands such as `join` can clear mata objects unrelated to ftools HOT 1
- Dict size exceeds Mata limits? HOT 5
- fmerge / join changes using-keys>100 to missing HOT 1
- Treat negative values in verbose(#) as if they were zero instead of positive HOT 1
- join does not clear sortedby macro HOT 6
- Support many to many join HOT 1
- fcollapse issue with double identifier HOT 2
- parallel_map crashes on computers with slow temp folder
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