Just found the DataFrames.isna() function, so that's solved, only the iteration question remains.
On Wednesday, September 9, 2015 at 2:26:23 PM UTC-4, Cedric St-Jean wrote: > > In 0.3, what's the best way of replacing all NA with a given value (eg. > 0)? Pandas has df.fillna. I've noticed that > > isnan(DataFrames.NA) > > is undefined and > > DataFrames.NA == DataFrames.NA > > is NA. The docs say it's a singleton, so I assume that I should use === to > check if it's NA? Likewise, how should I iterate over all elements? I was > disappointed that `map(fun, df)` is not defined (is that an omission? it's > defined for matrices). Should I just go over all columns one by one? > > Cédric >
