Manipulation/selection

Series.alias(name)	Return a copy of the Series with a new alias/name.
Series.append(other[, append_chunks])	Append a Series to this one.
Series.arg_sort(*[, descending, nulls_last])	Get the index values that would sort this Series.
Series.argsort([descending, nulls_last])	Get the index values that would sort this Series.
Series.cast(dtype, *[, strict])	Cast between data types.
Series.ceil()	Rounds up to the nearest integer value.
Series.clear([n])	Create an empty copy of the current Series, with zero to 'n' elements.
Series.clip(min_val, max_val)	Clip (limit) the values in an array to a min and max boundary.
Series.clip_max(max_val)	Clip (limit) the values in an array to a max boundary.
Series.clip_min(min_val)	Clip (limit) the values in an array to a min boundary.
Series.clone()	Very cheap deepcopy/clone.
Series.cut(bins[, labels, ...])	Bin values into discrete values.
Series.drop_nans()	Drop NaN values.
Series.drop_nulls()	Drop all null values.
Series.explode()	Explode a list or utf8 Series.
Series.extend_constant(value, n)	Extremely fast method for extending the Series with 'n' copies of a value.
Series.fill_nan(fill_value)	Fill floating point NaN value with a fill value.
Series.fill_null([value, strategy, limit])	Fill null values using the specified value or strategy.
Series.filter(predicate)	Filter elements by a boolean mask.
Series.floor()	Rounds down to the nearest integer value.
Series.head([n])	Get the first n elements.
Series.hist([bins, bin_count])	Bin values into buckets and count their occurrences.
Series.interpolate([method])	Interpolate intermediate values.
Series.item()	Return the series as a scalar.
Series.limit([n])	Get the first n elements.
Series.new_from_index(index, length)	Create a new Series filled with values from the given index.
Series.qcut(quantiles[, labels, ...])	Bin values into discrete values based on their quantiles.
Series.rechunk(*[, in_place])	Create a single chunk of memory for this Series.
Series.rename(name[, in_place])	Rename this Series.
Series.reshape(dims)	Reshape this Series to a flat Series or a Series of Lists.
Series.reverse()	Return Series in reverse order.
Series.round(decimals)	Round underlying floating point data by decimals digits.
Series.sample([n, frac, with_replacement, ...])	Sample from this Series.
Series.set(filter, value)	Set masked values.
Series.set_at_idx(idx, value)	Set values at the index locations.
Series.shift([periods])	Shift the values by a given period.
Series.shift_and_fill(periods, fill_value)	Shift the values by a given period and fill the resulting null values.
Series.shrink_dtype()	Shrink numeric columns to the minimal required datatype.
Series.shrink_to_fit([in_place])	Shrink Series memory usage.
Series.shuffle([seed])	Shuffle the contents of this Series.
Series.slice(offset[, length])	Get a slice of this Series.
Series.sort(*[, descending, in_place])	Sort this Series.
Series.tail([n])	Get the last n elements.
Series.take(indices)	Take values by index.
Series.take_every(n)	Take every nth value in the Series and return as new Series.
Series.to_dummies([separator])	Get dummy/indicator variables.
Series.top_k(*[, k, descending])	Return the k largest elements.
Series.unique([maintain_order])	Get unique elements in series.
Series.view([ignore_nulls])	Get a view into this Series data with a numpy array.
Series.zip_with(mask, other)	Take values from self or other based on the given mask.