BRO - dividends DATA and CHARTS + Python codes .
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 .
Follow me on noise.cash - https://noise.cash/u/AMR where I post about LEO / HIVE or photography .
Regards ,
MR.
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