Great! Thanks for this!
On Thursday, March 17, 2016 at 3:45:31 PM UTC+1, tshort wrote: > > See complete_cases and complete_cases!. > On Mar 17, 2016 10:37 AM, "Cedric St-Jean" <[email protected] > <javascript:>> wrote: > >> I use this function: >> >> """ `dropnan_dumb(df::DataFrame, axis=1)` >> >> Returns `df` with all rows that have any `NA` removed """ >> function dropnan_dumb(df::DataFrame, axis=1) >> @assert axis==1 # TODO >> todrop = fill(false, size(df, 1)) >> for col in names(df) >> todrop = todrop | [isna(el) for el in df[col]] >> end >> df[find(~todrop), :] >> end >> >> >> >> On Thursday, March 17, 2016 at 10:17:36 AM UTC-4, Eugen Neu wrote: >>> >>> >>> Hi, >>> >>> I am a new julia user. I have a dataset ( >>> http://www-bcf.usc.edu/~gareth/ISL/Auto.csv) where one column contains >>> NAs. The data can be read using: >>> >>> Auto = readtable("data/Auto.csv", nastrings = ["?"]) >>> >>> I would like to remove the rows that contain NAs. I found the dropna >>> function. However, this seems to work only for DataArrays not for >>> DataFrames. I also found: >>> http://stackoverflow.com/questions/27844621/how-can-i-delete-all-rows-of-a-dataframe-that-have-an-na-in-a-specific-column >>> However, this only works when one specifies the column that contains >>> NAs. >>> >>> Is there a function that removes every DataFrame row that includes one >>> or more NAs? >>> >>> Kind regards, >>> Eugen >>> >>
