Bitcoin is a peer-to-peer electronic payment system that popularized rapidly in recent years. Usually, we need to query the complete history of Bitcoin blockchain data to acquire variables with economic meaning. This becomes increasingly difficult now with over 1.6 billion historical transactions on the Bitcoin blockchain. It is thus important to query Bitcoin transaction data in a way that is more efficient and provides economic insights. We apply cohort analysis that interprets Bitcoin blockchain data using methods developed for population data in social science. Specifically, we query and process the Bitcoin transaction input and output data within each daily cohort, which enables us to create datasets and visualizations for some key indicators of Bitcoin transactions, including the daily lifespan distributions of spent transaction output (STXO) and the daily age distributions of the accumulated unspent transaction output (UTXO). We provide a computationally feasible approach to characterize Bitcoin transactions, which paves the way for the future economic studies of Bitcoin.
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