def table_nan_locs ( table ) : ans = [ ] for rownum , row in enumerate ( table ) : try : if pd . isnull ( row ) . any ( ) : colnums = pd . isnull ( row ) . nonzero ( ) [ 0 ] ans += [ ( rownum , colnum ) for colnum in colnums ] except AttributeError : # table is really just a sequence of scalars if pd . isnull ( row ) : ans += [ ( rownum , 0 ) ] return ans
how to identify columsn with missing data in python 3
from http : // stackoverflow . com / a / 14033137 / 623735 # gets the indices of the rows with nan values in a dataframe pd . isnull ( df ) . any ( 1 ) . nonzero () [ 0 ]
def table_nan_locs(table):
    """
    from http://stackoverflow.com/a/14033137/623735
    # gets the indices of the rows with nan values in a dataframe
    pd.isnull(df).any(1).nonzero()[0]
    """
    ans = []
    for rownum, row in enumerate(table):
        try:
            if pd.isnull(row).any():
                colnums = pd.isnull(row).nonzero()[0]
                ans += [(rownum, colnum) for colnum in colnums]
        except AttributeError:  # table is really just a sequence of scalars
            if pd.isnull(row):
                ans += [(rownum, 0)]
    return ans