About this Dataset

[Crypto] CoinGecko Vs CoinMarketCap Data

Use the CMC_CG_Combo dataset, unless you want to recollect and DIY!

Context

On a quest to compare different cryptoexchanges, I came up with the idea to compare metrics across multiple platforms (at the moment just two). CoinGecko and CoinMarketCap are two of the biggest websites for monitoring both exchanges and cryptoprojects. In response to over-inflated volumes faked by crypto exchanges, both websites came up with independent metrics for assessing the worth of a given exchange.

Content

Collected on May 10, 2020

CoinGecko's data is a bit more holistic, containing metrics across a multitude of areas (you can read more in the original blog post here. The data from CoinGecko consists of the following:

-Exchange Name
-Trust Score (on a scale of N/A-10)
-Type (centralized/decentralized)
-AML (risk: How well prepared are they to handle financial crime?)
-API Coverage (Blanket Measure that includes: (1) Tickers Data (2) Historical Trades Data (3) Order Book Data (4) Candlestick/OHLC (5) WebSocket API (6) API Trading (7) Public Documentation
-API Last Updated (When was the API last updated?)
-Bid Ask Spread (Average buy/sell spread across all pairs)
-Candlestick (Available/Not)
-Combined Orderbook Percentile (See above link)
-Estimated_Reserves (estimated holdings of major crypto)
-Grade_Score (Overall API score)
-Historical Data (available/not)
-Jurisdiction Risk (risk: risk of Terrorist activity/bribery/corruption?)
-KYC Procedures (risk: Know Your Customer?)
-License and Authorization (risk: has exchange sought regulatory approval?)
-Liquidity (don't confuse with "CMC Liquidity". THIS column is a combo of (1) Web traffic & Reported Volume (2) Order book spread (3) Trading Activity (4) Trust Score on Trading Pairs
-Negative News (risk: any bad news?)
-Normalized Trading Volume (Trading Volume normalized to web traffic)
-Normalized Volume Percentile (see above blog link)
-Orderbook (available/not)
-Public Documentation (got well documented API available to everyone?)
-Regulatory Compliance (risk rating from compliance perspective)
-Regulatory last updated (last time regulatory metrics were updated)
-Reported Trading Volume (volume as listed by the exchange)
-Reported Normalized Trading Volume (Ratio of normalized to reported volume [0-1])
-Sanctions (risk: risk of sanctions?)
-Scale (based on: (1) Normalized Trading Volume Percentile (2) Normalized Order Book Depth Percentile
-Senior Public Figure (risk: does exchange have transparent public relations? etc)
-Tickers (tick tick tick...)
-Trading via API (can data be traded through the API?)
-Websocket (got websockets?)

-Green Pairs (Percentage of trading pairs deemed to have good liquidity)
-Yellow Pairs (Percentage of trading pairs deemed to have fair liquidity
-Red Pairs (Percentage of trading pairs deemed to have poor liquidity)
-Unknown Pairs (percentage of trading pairs that do not have sufficient order book data)

Again, CoinMarketCap only has one metric (that was recently updated and scales from 1-1000, 1000 being very liquid and 1 not. You can go check the article out for yourself. In the dataset, this is the "CMC Liquidity" column, not to be confused with the "Liquidity" column, which refers to the CoinGecko Metric!

Acknowledgements

Thanks to coingecko and cmc for making their data scrapable :)

[CMC, you should try to give us a little more access to the figures that define your metric. Thanks!]

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

Tables

Cg Data05102020

@kaggle.thesherpafromalabama_coingecko_vs_coinmarketcap_data.cg_data05102020

46.56 KB
386 rows
35 columns


CREATE TABLE cg_data05102020 (
  "exchange_name" VARCHAR,
  "trust_score" DOUBLE,
  "type" VARCHAR,
  "aml" VARCHAR,
  "api_coverage" VARCHAR,
  "api_last_updated" TIMESTAMP,
  "bid_ask_spread" VARCHAR,
  "candlestick" VARCHAR,
  "combined_orderbook_percentile" VARCHAR,
  "estimated_reserves" VARCHAR,
  "grade_score" VARCHAR,
  "green_pairs" DOUBLE,
  "historical_data" VARCHAR,
  "jurisdiction_risk" VARCHAR,
  "kyc_procedures" VARCHAR,
  "license_and_authorization" VARCHAR,
  "liquidity" VARCHAR,
  "negative_news" VARCHAR,
  "normalized_trading_volume" VARCHAR,
  "normalized_volume_percent" VARCHAR,
  "orderbook" VARCHAR,
  "public_documentation" VARCHAR,
  "red_pairs" DOUBLE,
  "regulatory_compliance" VARCHAR,
  "regulatory_last_updated" TIMESTAMP,
  "reported_trading_volume" VARCHAR,
  "reported_normalized_trading_volume" VARCHAR,
  "sanctions" VARCHAR,
  "scale" VARCHAR,
  "senior_public_figure" VARCHAR,
  "tickers" VARCHAR,
  "trading_via_api" VARCHAR,
  "unknown_pairs" DOUBLE,
  "websocket" VARCHAR,
  "yellow_pairs" DOUBLE
);

Liquidity Data 2020–05–10–13

@kaggle.thesherpafromalabama_coingecko_vs_coinmarketcap_data.liquidity_data_2020_05_10_13

3.59 KB
100 rows
2 columns


CREATE TABLE liquidity_data_2020_05_10_13 (
  "exchange_name" VARCHAR,
  "cmc_liquidity" BIGINT
);

May Cmc Cg Combo

@kaggle.thesherpafromalabama_coingecko_vs_coinmarketcap_data.may_cmc_cg_combo

30.09 KB
75 rows
36 columns


CREATE TABLE may_cmc_cg_combo (
  "exchange_name" VARCHAR,
  "trust_score" DOUBLE,
  "type" VARCHAR,
  "aml" VARCHAR,
  "api_coverage" DOUBLE,
  "api_last_updated" TIMESTAMP,
  "bidask_spread" DOUBLE,
  "candlestick" VARCHAR,
  "combined_orderbook_percentile" VARCHAR,
  "estimated_reserves" VARCHAR,
  "grade_score" VARCHAR,
  "green_pairs" DOUBLE,
  "historical_data" VARCHAR,
  "jurisdiction_risk" VARCHAR,
  "kyc_procedures" VARCHAR,
  "license_and_authorization" VARCHAR,
  "liquidity" DOUBLE,
  "negative_news" VARCHAR,
  "normalized_trading_volume" VARCHAR,
  "normalized_volume_percent" VARCHAR,
  "orderbook" VARCHAR,
  "public_documentation" VARCHAR,
  "red_pairs" DOUBLE,
  "regulatory_compliance" VARCHAR,
  "regulatory_last_updated" TIMESTAMP,
  "reported_trading_volume" DOUBLE,
  "reportednormalized_trading_volume" DOUBLE,
  "sanctions" VARCHAR,
  "scale" DOUBLE,
  "senior_public_figure" VARCHAR,
  "tickers" VARCHAR,
  "trading_via_api" VARCHAR,
  "unknown_pairs" DOUBLE,
  "websocket" VARCHAR,
  "yellow_pairs" DOUBLE,
  "cmc_liquidity" BIGINT
);