Good evening to everyone , today I am here with yet another statistical post which focuses on the voting data with respect to LeoFinance only .

Steps followed

• I have taken every user who has staked LEO or has delegation for their account -

from hiveengine.tokenobject import Token
token=Token('LEO')
s=[]
end=0
x=0
while(end!=1):
    res=token.get_holder(offset=x) # function used to retrieve all user balance
    s.append(res)

    x=x+len(res)
    if(len(res)<500):
        end=1


list_holders=[]
for i in range(0,len(s)):
    for j in range(0,len(s[i])):
        list_holders.append(s[i][j])
user_list=[]
for i in range(0,len(list_holders)):
    if(float(list_holders[i]['stake'])>0 or float(list_holders[i]['delegationsIn'])>0): # checking for stake and delegations IN balance
        user_list.append(list_holders[i]['account']) # If yes , storing it in a list . 
    else:
        pass

I have explained the code above itself .

• I have then gone through each and every user from user_list and searched for their curation reward in LEO and then stored it in a DataFrame . It looks like this -

Note - above data is for 25th Feb to 3rd March

• Then all the statistical functions

df_leo_curation.groupby(['curator','author']).count().reset_index().groupby('curator').count().sort_values('author',ascending=False).head(30)['author'].to_frame()

Data

So for those who aren't interested in the code but want to see the data here it is -

Top 30 users who have got curation rewards from various authors -

User	Number of different users they have upvoted
@uwelang	533
@mk-leo-token	458
@leovoter	431
@onealfa.leo	426
@r0nd0n	413
@gadrian	335
@babytarazkp	329
@leo.voter	316
@leofinance	315
@roleerob	309
@engrsayful	306
@snoochieboochies	286
@sbi-tokens	285
@localgrower	273
@leoneil.leo	272
@ikaro	272
@megavest	254
@haxxdump	253
@empoderat	252
@alokkumar121	243
@beehivetrader	238
@abh12345.leo	236
@travelwritemoney	235
@shurbertum	234
@thahodler	233
@abdul.qadir	232
@taskmaster4450le	231
@onestop	225
@alphacore	222
@jeanlucsr	203

What is this data? This tells us that in the past 7 days these people have voted for 200 and above different authors on LeoFinance .

Number of authors actually posted on LeoFinance

893 - that means the top 5 curators of LeoFinance has upvoted for 50% of the authors who have posted/commented using LeoFinance tag . 1 in 2 ( in 7 days ) - isn't that amazing? If you check the accounts - most of them have good amount of LP or good amount of HP .

Note - some are auto upvoting accounts but others aren't , I am sure I need not mention here who actually curates manually in the above list , you all know it

Average number of authors upvoted by curators on LeoFinance ( over 7 days )

36.35

Average number of authors upvoted by curators on LeoFinance ( per day )

5.19 - This is not an impressive number . This tells us either of two things

1. People aren't utiziling all their upvotes
2. People are voting for few others only .

5.19 means one curator per day is earning curation reward from 5 authors only .

Proportion of curators based on number of authors they have voted

Note

1. Many of you might argue that whales have large voting value so they can diversify but a new user cannot do that -
   • This is partially correct and partially wrong because they need not vote different users at all . They can vote just 20 authors - 30 authors but clearly the data says otherwise , they aren't doing it .
2. Out of 800 users who have posted using #leofinance during the period , there are many bots which you have to take into consideration .
3. If you want your curation rewards total from 25th Feb to 4th March ( now ) let me know in the comments .

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Regards,
Mr.