See complete_cases and complete_cases!. On Mar 17, 2016 10:37 AM, "Cedric St-Jean" <[email protected]> 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 >> >
