In previous analysis I have explored Masternode API data to get an understanding of the data contained and to explore insights hidden in the data and also to compare Masternode coins.
Repository
https://github.com/Crave-Project/Crave-NG
https://github.com/zcoinofficial/zcoin
Since last carrying out these analysis, the markets have dropped and confidence is at a low.
In today’s analysis I will continue to analyse and compare Masternode data but this time we can make some time comparisons.
Both coins have a public API making it easy to compare blockchain transaction data once the API Json data has been extracted and transformed to a useable format.
Both coins are also listed on Coinmarketcap and on Masternodes.online. This allows for further analysis and comparison in addition to the blockchain data.
Aim of Analysis
• To Explore and present Crave and ZCoin data in a meaningful way
• Revile insights hidden in the data
• Make comparisons over time
• Make comparisons against the crypto market in general
ZCoin Data
March Snapshot
The last 100 transactions on the ZCoin blockchain in the March Snapshot were made up of 238-line items. These 100 transactions moved 29.42 BTC worth of ZCoins from 87 unique addresses to 30 unique addresses.
These 100 transactions took place over 1509 seconds. That equates to 0.066 transactions per second.
The values shown in light purple relate to data from Coinmarketcap. At the time of analysis, the price of ZCoin was 0.00434 BTC or $35.56 USD.
1000 coins are required for a masternode with a value of $35,561 US$. The marketcap. for ZCoin is 153.49M and the volume traded in the last 24 hours is $1.31M USD
July Snapshot
The last 100 transactions on the ZCoin blockchain in today’s snapshot were made up of 586-line items. These 100 transactions moved 47.44 BTC worth of ZCoins from 113 unique addresses to 147 unique addresses.
These 100 transactions took place over 21K seconds. That equates to 0.005 transactions per second.
The values shown in light purple relate to data from Coinmarketcap. At the time of analysis, the price of ZCoin was 0.0025120 BTC or $16.54 USD.
1000 coins are required for a masternode with a value of $16,540.US$. The marketcap. for ZCoin is 84.87M and the volume traded in the last 24 hours is $1.02M USD
Changes Over time
Taking the key metrics for each snapshot I have calculated the % change.
ZCoin US$ price is down 53% since last analysed, and the BTC price is down 42% the marketcap is down 45% and the volume traded is down 22%
The transactions per second are down 92%, however over 100 transactions 61% more was moved. As it took 1292% more time to process a transaction, the BTC equ moved per second was also down 88% and if we exclude MN rewards there has been a change of -89% in BTC equ moved.
Crave
March Snapshot
The last 100 transactions on the blockchain from the March snapshot were made up of 226-line items. These 100 transactions moved 4.28 BTC worth of Crave coins from 49 unique addresses to 51 unique addresses.
These 100 transactions took place over 24K seconds. That equates to 0.004 transactions per second.
The values shown in light purple relate to data from Coinmarketcap. At the time of analysis, the price of crave was 0.00002859 BTC or $0.31 USD.
5000 coins are required for a masternode with a value of $1.65KUS$. The marketcap. for Crave was not available at the time but the volume traded in the last 24 hours is $6.74K USD
July Snapshot
The last 100 transactions on the blockchain from the July snapshot were made up of 406-line items. These 100 transactions moved 1.28 BTC worth of Crave coins from 85 unique addresses to 145 unique addresses.
These 100 transactions took place over 127K seconds. That equates to 0.0008 transactions per second.
The values shown in light purple relate to data from Coinmarketcap. At the time of analysis, the price of crave was $0.08779 USD.
5000 coins are required for a masternode with a value of $438.93 US$. The marketcap for Crave was 1.35M and the volume traded in the last 24 hours is $2.71K USD
Changes Over time
Taking the key metrics for each snapshot I have calculated the % change.
Crave US$ price is down 73% since last analysed, and the BTC price is down 50% and the volume traded is down 60%
The transactions per second are down 80%, and 70% less BTC equal. was transferred. As it took 429% more time to process a transaction, the BTC equal moved per second was also down 80%.
Conclusion
Both blockchains activity are down since reported in March. Although both Blockchains are down in activity, they both have more addresses in use. This would suggest that there are more people using the coins, however with far less volume and lower transaction value.
As the BTC equ. transferred on Crave is down more than Zcoin, I am not entirely surprised to see the price of crave drop further than the price of Zcoin.
I also had a look at masternodes.online and the % of Zcoins locked in has increase to 63% from 53%, however Craves lockin has dropped from 35% to 33%, showing more investors are thinking long term with Zcoin than Crave
The above chart shows Market Cap for the crypto market as per coinmarketcap. The entire marketcap is down 42% since March and the daily trade volume is down 31% and the price of BTC is down 33%
Zcoin marketcap is down 45% slightly more than the market average, we do not have marketcap values for Crave for March
Zcoin trade volume is down 22%, therefore preforming better than market average and Crave trade volume is down 60%, preforming worse than the market average
What would you make of this analysis and conclusion? Please do leave your comments and feedback
Would you like to see a comparison of your two favourite Masternode Coins? If so and they have an API I can work with, then do leave your comments below.
Analysing coins in this way adds to the information already available for those considering investing in masternode coin. However this is not meant as investment advice. There are also other things to consider when investing in a masternode, such as the team, the roadmap, the community.
Data and Queries
March data was taken from previous posts and analysis carried out here on steemit
Current data queries
The complete M code used in Power BI query editor for Crave was:
let
Source =
Json.Document(Web.Contents("http://explorer.craveproject.net/ext/getlasttxs/10/100")),
#"Converted to Table" = Record.ToTable(Source),
#"Expanded Value" = Table.ExpandListColumn(#"Converted to Table", "Value"),
#"Expanded Value1" = Table.ExpandRecordColumn(#"Expanded Value", "Value", {"_id", "txid",
"blockhash", "__v", "blockindex", "timestamp", "total", "vout", "vin"}, {"_id", "txid", "blockhash", "__v",
"blockindex", "timestamp", "total", "vout", "vin"}),
#"Expanded vout" = Table.ExpandListColumn(#"Expanded Value1", "vout"),
#"Expanded vout1" = Table.ExpandRecordColumn(#"Expanded vout", "vout", {"addresses",
"amount"}, {"addresses", "amount"}),
#"Renamed Columns" = Table.RenameColumns(#"Expanded vout1",{{"addresses", "rec. address"}}),
#"Added Custom2" = Table.AddColumn(#"Renamed Columns", "Coin", each "CRAVE"),
#"Removed Columns" = Table.RemoveColumns(#"Added Custom2",{"vin"}),
#"Added Custom" = Table.AddColumn(#"Removed Columns", "Rec Amt Crave", each
[amount]/100000000),
#"Appended Query" = Table.Combine({#"Added Custom", #"crave (2)"}),
#"Changed Type" = Table.TransformColumnTypes(#"Appended Query",{{"sending amt crave", type
number}, {"sending amount", type number}, {"Rec Amt Crave", type number}, {"amount", type
number}})
in
#"Changed Type"
and for zcoin the code was
let Source = Json.Document(Web.Contents("https://explorer.zcoin.io/ext/getlasttxs/10/100")), #"Converted to Table" = Record.ToTable(Source), #"Expanded Value" = Table.ExpandListColumn(#"Converted to Table", "Value"), #"Expanded Value1" = Table.ExpandRecordColumn(#"Expanded Value", "Value", {"_id", "txid", "blockhash", "__v", "blockindex", "timestamp", "total", "vout", "vin"}, {"_id", "txid", "blockhash", "__v", "blockindex", "timestamp", "total", "vout", "vin"}), #"Expanded vout" = Table.ExpandListColumn(#"Expanded Value1", "vout"), #"Expanded vout1" = Table.ExpandRecordColumn(#"Expanded vout", "vout", {"addresses", "amount"}, {"addresses", "amount"}), #"Renamed Columns" = Table.RenameColumns(#"Expanded vout1",{{"addresses", "rec. address"}}), #"Added Custom2" = Table.AddColumn(#"Renamed Columns", "Coin", each "ZCoin"), #"Removed Columns" = Table.RemoveColumns(#"Added Custom2",{"vin"}), #"Added Custom" = Table.AddColumn(#"Removed Columns", "Rec Amt ZCoin", each [amount]/100000000), #"Appended Query" = Table.Combine({#"Added Custom", zcoin}), #"Changed Type" = Table.TransformColumnTypes(#"Appended Query",{{"amount", type number}, {"Rec Amt ZCoin", type number}, {"sending amount", type number}, {"sending amt ZCoin", type number}})in #"Changed Type"
To get live data from Coinmarketcap, I also connected to the live ticker API for each of the coins and then carried out an append on each of the tables.The full M code used in Power BI query editor was:
let
Source = Json.Document(Web.Contents("https://api.coinmarketcap.com/v1/ticker/crave/")),
#"Converted to Table" = Table.FromList(Source, Splitter.SplitByNothing(), null, null,
ExtraValues.Error),
#"Expanded Column1" = Table.ExpandRecordColumn(#"Converted to Table", "Column1", {"id",
"name", "symbol", "rank", "price_usd", "price_btc", "24h_volume_usd", "market_cap_usd",
"available_supply", "total_supply", "max_supply", "percent_change_1h", "percent_change_24h",
"percent_change_7d", "last_updated"}, {"id", "name", "symbol", "rank", "price_usd", "price_btc",
"24h_volume_usd", "market_cap_usd", "available_supply", "total_supply", "max_supply", "
percent_change_1h", "percent_change_24h", "percent_change_7d", "last_updated"}),
#"Changed Type" = Table.TransformColumnTypes(#"Expanded Column1",{{"rank", type number},
{"price_usd", type number}, {"price_btc", type number}, {"total_supply", type number},
{"24h_volume_usd", type number}, {"market_cap_usd", type number}}),
#"Appended Query" = Table.Combine({#"Changed Type", #"ticker (2)", #"ticker (3)"}),
#"Appended Query1" = Table.Combine({#"Appended Query", #"ticker (4)"})
in
#"Appended Query1"
Once I had gathered all of the data, I then carried out many calculations using DAX.