Series.nunique(dropna=True) [source] Return number of unique elements in the object. Excludes NA values by default. Parameters: dropna : boolean, default True Don?t include NaN in the count. Returns: nunique : int

Series.nsmallest(*args, **kwargs) [source] Return the smallest n elements. Parameters: n : int Return this many ascending sorted values keep : {?first?, ?last?, False}, default ?first? Where there are duplicate values: - first : take the first occurrence. - last : take the last occurrence. take_last : deprecated Returns: bottom_n : Series The n smallest values in the Series, in sorted order See also Series.nlargest Notes Faster than .sort_values().head(n) for small n relative to

Series.notnull() [source] Return a boolean same-sized object indicating if the values are not null. See also isnull boolean inverse of notnull

Series.nonzero() [source] Return the indices of the elements that are non-zero This method is equivalent to calling numpy.nonzero on the series data. For compatability with NumPy, the return value is the same (a tuple with an array of indices for each dimension), but it will always be a one-item tuple because series only have one dimension. See also numpy.nonzero Examples >>> s = pd.Series([0, 3, 0, 4]) >>> s.nonzero() (array([1, 3]),) >>> s.iloc[s.nonzero()[0]]

Series.nlargest(*args, **kwargs) [source] Return the largest n elements. Parameters: n : int Return this many descending sorted values keep : {?first?, ?last?, False}, default ?first? Where there are duplicate values: - first : take the first occurrence. - last : take the last occurrence. take_last : deprecated Returns: top_n : Series The n largest values in the Series, in sorted order See also Series.nsmallest Notes Faster than .sort_values(ascending=False).head(n) for small n

Series.ne(other, level=None, fill_value=None, axis=0) [source] Not equal to of series and other, element-wise (binary operator ne). Equivalent to series != other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a level, matchi

Series.ndim return the number of dimensions of the underlying data, by definition 1

Series.nbytes return the number of bytes in the underlying data

Series.name

Series.multiply(other, level=None, fill_value=None, axis=0) [source] Multiplication of series and other, element-wise (binary operator mul). Equivalent to series * other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a level