Summary
This chapter has addressed various preparation methods applicable to on-chain data scenarios. We explored techniques such as unhexing data, decimal treatment, handling checksum addresses, and converting Unix timestamps to datetime formats. These methods have proven foundational in preparing the on-chain data for subsequent analysis.
Moreover, we introduced the concept of EDA as a crucial step in understanding and summarizing datasets, with a specific focus on central tendency metrics. Additionally, we delved into outlier detection techniques, such as box plots and the IQR method, aiding in the identification of extreme observations deviating significantly from the majority of the data.
By applying these cleaning and EDA techniques, we have equipped ourselves with essential tools for the effective analysis and interpretation of on-chain data. These foundational concepts serve as building blocks for more advanced techniques and methodologies as we continue this journey...
