SHIB or PEPE?

    Investigating and comparing the behavior of PEPE and SHIB tokens in the first month of launch.

    Many people believe that Pepe has come to replace Shib or say that Pepe is a serious competitor for Shib. Pepe Token was launched on April 17th this year and had many ups and downs in the initial days of the launch. It went through sudden price increases and decreases and many bought this token. Many people have also held this token in the hope that it will rise to higher prices like shib. However, we intend to compare these two tokens in this dashboard. We are going to see what was the reason for the sudden jumps and drops of pepe and how it compares with shib.

    In this dashboard, we used to check the price reactions and price changes of Pepe and Shib tokens by checking the supply and demand of these two tokens in decentralized exchanges. Of course, supply and demand in centralized exchanges are also important in this field, but buying and selling transactions are not available in these exchanges, and many token transfers to these platforms may not be for buying and selling and are done only to create excitement or fear. For this reason, we checked the supply and demand of these two tokens in the dexes. In order to make a complete and correct comparison between these two tokens, we checked the statistics of the first month of these tokens. It seems that in this situation everything is the same and comparable.

    In this dashboard, we defined a parameter called ROC, which is the difference between supply and demand. In other words, ROC expresses the range of changes in supply and demand data. The most key table used in this dashboard is the ez_token_transfers table. By joining this table with the dim_labels table and setting the destination of transactions to label_type = dex, we called the data related to swap transactions about these two tokens. The hourly_price table is used to call the price of tokens. It is important to mention that since the price of the two discussed tokens is equal in terms of decimals, we used one million of these tokens in order to get clearer data.

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