Hi @ninjas, great to see a new contributor in the Utopian analysis category - welcome and great start! I see this is your first utopian contribution - awesome!
An analysis with a similar scope was published by @paulag around two months ago here. Your results on the distribution of the beneficiary account seems mostly in line with Paula's results. However, I think there are a few issues with your approach that might have led to not fully correct results:

• with_benef.beneficiaries.apply(lambda d: d[0]['account']) -> I think this captures only the first beneficiary of each post, while a post can have up to 8 beneficiaries. There are a couple of Steem apps that set multiple beneficiaries.

• that part is unfortunately not correct:

with_benef['author_payout_value'] = with_benef.total_payout_value - with_benef.curator_payout_value
with_benef.author_payout_value = with_benef.author_payout_value.astype('float64')
with_benef['benef_payout_value'] = with_benef.benef_weight * with_benef.author_payout_value / 100

Despite its name,total_payout_value is only the author share of the post payout and has possible beneficiary rewards already removed. As a result, subtracting the curation rewards from this author share and then additionally reducing this by the beneficiary weight gives lower rewards than what the beneficiaries actually received. The comparison of the payouts of posts with and without beneficiaries as well as the sums of benefactor rewards are affected by this.

Summing up rewards over time in general has to be treated carefully, depending on what you want to show. Since the Steem price lost a factor of ten since the start of the year, the SBD payouts are also affected from this. A metric that is independent of the price could be to look at the sum of vote rshares per post, but that easily goes deep down the rabbit hole...

Nevertheless, great start, and we'd love to see more from you! Feel free to contact us on discord (see link below) if you have any questions.

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