Bendford analysis of Ethereum transaction

The python script script.py extract from already downloaded archive file the ethereum transaction. The values of those transactions will then been classified by the their first digit (e.g 10 will be classified under 1).

We will then show the distribution of the amounts starting by either 1, 2, 3, 4, 5, 6, 7, 8 and 9.

It will allow us to answer the question: does ethereum's transaction value follow bendford's law ?

Why ?

Because I have watched Netflix's Connected during lockdown.

Sample

The sample data is from Blockchair (https://gz.blockchair.com/ethereum/transactions/)

I have the data for several years, contact me if you are interested.

How to use it ?

You will need python3 installed.

$ python3 script.py

or

$ python3 script.py &> output.txt &

Result

This is the result on the sample data (first month of Ethereum running).

Total count : 80664

Transaction `value` first digit distribution

    1 : 29344 (36.38%)
    2 : 12022 (14.9%)
    3 : 7596 (9.42%)
    4 : 8631 (10.7%)
    5 : 7572 (9.39%)
    6 : 3698 (4.58%)
    7 : 3292 (4.08%)
    8 : 3041 (3.77%)
    9 : 5468 (6.78%)



Transaction `fee` first digit distribution

    1 : 75007 (92.99%)
    2 : 4134 (5.12%)
    3 : 541 (0.67%)
    4 : 215 (0.27%)
    5 : 297 (0.37%)
    6 : 344 (0.43%)
    7 : 35 (0.04%)
    8 : 32 (0.04%)
    9 : 59 (0.07%)



Transaction `gas_used` first digit distribution

    1 : 457 (0.57%)
    2 : 78306 (97.08%)
    3 : 370 (0.46%)
    4 : 282 (0.35%)
    5 : 866 (1.07%)
    6 : 36 (0.04%)
    7 : 20 (0.02%)
    8 : 59 (0.07%)
    9 : 268 (0.33%)

What's next ?

This script will be run against a bigger sample of data (from 2015 to 2020).

It could be interesting to check the amount being moved to top 10 smart contract.