Descriptive

Series.chunk_lengths()	Get the length of each individual chunk.
Series.describe([percentiles, interpolation])	Quick summary statistics of a Series.
Series.estimated_size([unit])	Return an estimation of the total (heap) allocated size of the Series.
Series.has_nulls()	Check whether the Series contains one or more null values.
Series.has_validity()	Return True if the Series has a validity bitmask.
Series.is_duplicated()	Get mask of all duplicated values.
Series.is_empty()	Check if the Series is empty.
Series.is_finite()	Returns a boolean Series indicating which values are finite.
Series.is_first_distinct()	Return a boolean mask indicating the first occurrence of each distinct value.
Series.is_in(other)	Check if elements of this Series are in the other Series.
Series.is_infinite()	Returns a boolean Series indicating which values are infinite.
Series.is_last_distinct()	Return a boolean mask indicating the last occurrence of each distinct value.
Series.is_nan()	Returns a boolean Series indicating which values are not NaN.
Series.is_not_nan()	Returns a boolean Series indicating which values are not NaN.
Series.is_not_null()	Returns a boolean Series indicating which values are not null.
Series.is_null()	Returns a boolean Series indicating which values are null.
Series.is_sorted(*[, descending, nulls_last])	Check if the Series is sorted.
Series.is_unique()	Get mask of all unique values.
Series.len()	Return the number of elements in the Series.
Series.lower_bound()	Return the lower bound of this Series' dtype as a unit Series.
Series.n_chunks()	Get the number of chunks that this Series contains.
Series.n_unique()	Count the number of unique values in this Series.
Series.null_count()	Count the null values in this Series.
Series.unique_counts()	Return a count of the unique values in the order of appearance.
Series.upper_bound()	Return the upper bound of this Series' dtype as a unit Series.
Series.value_counts(*[, sort, parallel, name])	Count the occurrences of unique values.