Good morning to everyone , I have been posting recently about various investment tokens , how they are performing , how much they are paying to the holders.

Today the post is about one of the most rewarding tokens on Hive blockchain - The BRO token.

BRO

It is a token created by @raymondspeaks . To put it in simple words , he uses the money raised by selling BRO to invest in various projects and provide dividends to the holders .
If you want to buy it - go to H-E market since it can be puchased only on the market now .

The price right now is - 9 HIVE .

Dividends in 8 tokens

If you are holding BRO , you will receive dividends in 8 tokens .

import shelve 
import pandas as pd
import json
from datetime import datetime as dt

s=shelve.open('Blocks\Blockchain') # Where I store 2nd layer token transaction details

df=pd.DataFrame.from_dict(s.items()) # Converting to DataFrame 

df.columns=['Blocks','Transactions'] # Naming the columns 

Now let's dive into the real part -

brofund_list=[]
for i in range(0,len(df)): 
    if(df['Transactions'][i]['Transaction']['action']=='transfer'):# To get only transfer tx
        json_all_transfers=json.loads(df['Transactions'][i]['Transaction']['logs'])
        if 'events' in json_all_transfers:
            if(str(json_all_transfers['events'][0]['data']['from']).startswith('brofund-')): # Since different tokens are sent by different accounts I have used startswith to match all the accounts
                brofund_list.append([json_all_transfers['events'][0]['data']['from'],json_all_transfers['events'][0]['data']['to'],json_all_transfers['events'][0]['data']['symbol'],json_all_transfers['events'][0]['data']['quantity'],pd.to_datetime(df['Transactions'][i]['Date']).date()]) # Storing it in a list . 

Output looks something like this if I print the above -

The above is only a part of the output , there are totally 37635 rows in the output .

df_brofund=pd.DataFrame(brofund_list) # Converting list to dataframe
df_brofund.columns=['from','to','symbol','quantity','date'] # Naming the columns
df_brofund['quantity']=pd.to_numeric(df_brofund['quantity']) # Converting to float type 
df_grouped=df_brofund.groupby(['date','symbol']).sum().reset_index() # Grouping the dividends using date and symbol column

Output -

#To get individual token details 

df_arc=df_grouped[df_grouped['symbol']=='ARCHON']
df_bee=df_grouped[df_grouped['symbol']=='BEE']
df_leo=df_grouped[df_grouped['symbol']=='LEO']
df_ag=df_grouped[df_grouped['symbol']=='NEOXAG']
df_pal=df_grouped[df_grouped['symbol']=='PAL']
df_sim=df_grouped[df_grouped['symbol']=='SIM']
df_stem=df_grouped[df_grouped['symbol']=='STEM']
df_weed=df_grouped[df_grouped['symbol']=='WEED']

Now I have just plotted it in chart so I will stop with all this codes and stuff lol .

Dividends from BRO for the period Jan 1 to Jan 26

ARCHON

NEOXAG

BEE

LEO

SIM

PAL

STEM

WEED

Note: The above is dividends paid to all the holders of BRO for the period - JAN 1 to JAN 26.

We can see from the above that the dividends has been consistent to the holders . Although we can see dips on somedays , it has always recovered and paid good dividends to holders .

Example of @trumpman account who holds 1k BRO

df_trumpman=df_brofund[df_brofund['to']=='trumpman'].groupby(['date','symbol']).sum().reset_index()
df_trumpman.groupby(['symbol']).sum()

For the period of Jan 1 to Jan 26 - @trumpman has got -

Example of @spinvest account which holds 4k BRO

For the period of Jan 1 to Jan 26 - @spinvest has got -

Do you hold BRO ?

If you want data for your account , let me know in the comments I will get it for you :)
But know that I can get only for the period Jan 1 to Jan 26 .

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Follow me on noise.cash - https://noise.cash/u/AMR where I post about LEO / HIVE or photography .

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Regards ,
MR.

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