TimeSeriesClustering is a Julia implementation of unsupervised learning methods for time series datasets. It provides functionality for clustering and aggregating, detecting motifs, and quantifying similarity between time series datasets. The software provides a type system for temporal data, and provides an implementation of the most commonly used clustering methods and extreme value selection methods for temporal data. It provides simple integration of multi-dimensional time-series data (e.g. multiple attributes such as wind availability, solar availability, and electricity demand) in a single aggregation process. The software is applicable to general time series datasets and lends itself well to a multitude of application areas within the field of time series data mining.