🙈Pandas is a great Python-library for data analysis library that uses every Data Scientist. However, this tool does not support multiprocessing and is rather slow on large datasets. Therefore, for fast Big Data processing, you should choose Vaex and Dask.
👍🏻Dask https://dask.org/ is a Pandas-based data analysis library with parallel computing and scalable performance. In addition to Pandas, it also integrates with the Numpy and Scikit-learn libraries, providing easy switching between them through Python APIs and data structures.
👍🏻Vaex https://vaex.io/docs/index.html is a high-performance Python library for lazy evaluations with dataframes similar to Pandas, as well as Big Data visualization and aggregation. It allows you to calculate basic statistics at a billion lines per second, but unlike Dask, it is not fully integrated with other libraries.