search for: dtax

....matrix( dta ) # If you have any values that R cannot clearly identify as numeric # or integer, then the next most general type of variable is # character... and that is often something that trips up newbies, # though I have no evidence that you have any non-numeric columns # in your data frames. dtax <- as.vector( dta ) str(dtax) #> 'data.frame': 1 obs. of 7 variables: #> $ V1: num 1.1 #> $ V2: num 3 #> $ V3: int 5 #> $ V4: num 7.4 #> $ V5: int 4 #> $ V6: num 2.2 #> $ V7: int 0 # This actually makes no change to dta, because a data frame is already...

....matrix( dta ) # If you have any values that R cannot clearly identify as numeric # or integer, then the next most general type of variable is # character... and that is often something that trips up newbies, # though I have no evidence that you have any non-numeric columns # in your data frames. dtax <- as.vector( dta ) str(dtax) #> 'data.frame': 1 obs. of 7 variables: #> $ V1: num 1.1 #> $ V2: num 3 #> $ V3: int 5 #> $ V4: num 7.4 #> $ V5: int 4 #> $ V6: num 2.2 #> $ V7: int 0 # This actually makes no change to dta, because a data frame is already...

:-) I don't insist on anything, I'm just struggling to learn a new language and partly a new way of thinking, and I really appreciate the corrections. I hope I someday will be able to handle lists in R as easy as I handle loops in Stata... Thanks again! Love -----Ursprungligt meddelande----- Fr?n: peter dalgaard [mailto:pdalgd at gmail.com] Skickat: den 4 december 2017 23:09 Till:

...have any values that R cannot clearly identify as numeric # or > integer, then the next most general type of variable is # character... and > that is often something that trips up newbies, # though I have no evidence > that you have any non-numeric columns # in your data frames. > > dtax <- as.vector( dta ) > str(dtax) > #> 'data.frame': 1 obs. of 7 variables: > #> $ V1: num 1.1 > #> $ V2: num 3 > #> $ V3: int 5 > #> $ V4: num 7.4 > #> $ V5: int 4 > #> $ V6: num 2.2 > #> $ V7: int 0 > > # This actually m...