Name: Crypto Data Hourly Price Since 2017 To 2023-10
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Crypto Data Hourly Price Since 2017 To 2023-10

Find my notebook : Advanced EDA & Data Wrangling - Crypto Market Data where I cover the full EDA and advanced data wrangling to get beautiful dataset ready for analysis.

Find my Deep Reinforcement Learning v1 notebook: Deep Reinforcement Learning for Trading

Find my Quant Analysis notebook:💎 Quant Analysis & Visualization | BTC V1

Dataset Presentation:

This dataset provides a comprehensive collection of hourly price data for 34 major cryptocurrencies, covering a time span from January 2017 to the present day. The dataset includes Open, High, Low, Close, Volume (OHLCV), and the number of trades for each cryptocurrency for each hour (row).

Making it a valuable resource for cryptocurrency market analysis, research, and trading strategies. Whether you are interested in historical trends or real-time market dynamics, this dataset offers insights into the price movements of a diverse range of cryptocurrencies.

This is a pure gold mine, for all kind of analysis and predictive models. The granularity of the dataset offers a wide range of possibilities. Have Fun!

Ready to Use - Cleaned and arranged dataset less than 0.015% of missing data hour: crypto_data.csv

First Draft - Before External Sources Merge (to cover missing data points): crypto_force.csv

Original dataset merged from all individual token datasets: cryptotoken_full.csv

crypto_data.csv & cryptotoken_full.csv highly challenging wrangling situations:

fix 'Date' formats and inconsistencies
find missing hours and isolate them for each token
import external data source containing targeted missing hours and merge dataframes to fill missing rows

see notebook 'Advanced EDA & Data Wrangling - Crypto Market Data' to follow along and have a look at the EDA, wrangling and cleaning process.

Date Range: From 2017-08-17 04:00:00 to 2023-10-19 23:00:00

Date Format: YYYY-MM-DD HH-MM-SS (raw data to be converted to datetime)

Data Source: Binance API (some missing rows filled using Kraken & Poloniex market data)

Crypto Token in the dataset (also available as independent dataset):

1INCH
AAVE
ADA (Cardano)
ALGO (Algorand)
ATOM (Cosmos)
AVAX (Avalanche)
BAL (Balancer)
BCH (Bitcoin Cash)
BNB (Binance Coin)
BTC (Bitcoin)
COMP (Compound)
CRV (Curve DAO Token)
DENT
DOGE (Dogecoin)
DOT (Polkadot)
DYDX
ETC (Ethereum Classic)
ETH (Ethereum)
FIL (Filecoin)
HBAR (Hedera Hashgraph)
ICP (Internet Computer)
LINK (Chainlink)
LTC (Litecoin)
MATIC (Polygon)
MKR (Maker)
RVN (Ravencoin)
SHIB (Shiba Inu)
SOL (Solana)
SUSHI (SushiSwap)
TRX (Tron)
UNI (Uniswap)
VET (VeChain)
XLM (Stellar)
XMR (Monero)

Date column presents some inconsistencies that need to be cleaned before formatting to datetime:

For column 'Symbol' and 'ETCUSDT' = '23-07-27': it is missing all hours (no data, no hourly rows for this day). I fixed it by using the only one row available for that day and duplicated the values for each hour. Can be fixed using this code:

start_timestamp = pd.Timestamp('2023-07-27 00:00:00')
end_timestamp = pd.Timestamp('2023-07-27 23:00:00')

hourly_timestamps = pd.date_range(start=start_timestamp, end=end_timestamp, freq='H')

hourly_data = {
    'Date': hourly_timestamps,
    'Symbol': 'ETCUSDT',
    'Open': 18.29,
    'High': 18.3,
    'Low': 18.17,
    'Close': 18.22,
    'Volume USDT': 127468,
    'tradecount': 623,
    'Token': 'ETC'
}

hourly_df = pd.DataFrame(hourly_data)
df = pd.concat([df, hourly_df], ignore_index=True)

df = df.drop(550341)

Some rows for 'Date' have extra digits '.000' '.874' etc.. instead of the right format YYYY-MM-DD HH-MM-SS. To clean it you can use the following code:

## Count the occurrences of the pattern '.xxx' in the 'Date' column
count_occurrences_before = df['Date'].str.count(r'\.\d{3}')
print("Occurrences before cleaning:", count_occurrences_before.sum()) 

## Remove '.xxx' pattern from the 'Date' column
df['Date'] = df['Date'].str.replace(r'\.\d{3}', '', regex=True)

## Count the occurrences of the pattern '.xxx' in the 'Date' column after cleaning
count_occurrences_after = df['Date'].str.count(r'\.\d{3}')
print("Occurrences after cleaning:", count_occurrences_after.sum())

Disclaimer: Any individual or entity choosing to engage in market analysis, develop predictive models, or utilize data for trading purposes must do so at their own discretion and risk. It is important to understand that trading involves potential financial loss, and decisions made in the financial markets carry inherent risks. This dataset is provided for informational and research purposes only, and its use in trading decisions should be made with full awareness of the associated risks. Users are urged to exercise caution, conduct thorough research, and consider seeking advice from qualified financial professionals when engaging in trading activities. The dataset provider assumes no responsibility for trading outcomes. NFA.

Tables

Binance 1inchusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_1inchusdt_1h_1

1.05 MB
24672 rows
9 columns


CREATE TABLE binance_1inchusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_1inch" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Aaveusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_aaveusdt_1h_1

1.14 MB
26373 rows
9 columns


CREATE TABLE binance_aaveusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_aave" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Adausdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_adausdt_1h_1

2.31 MB
48192 rows
9 columns


CREATE TABLE binance_adausdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_ada" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Algousdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_algousdt_1h_1

1.59 MB
37900 rows
9 columns


CREATE TABLE binance_algousdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_algo" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Atomusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_atomusdt_1h_1

1.67 MB
39182 rows
9 columns


CREATE TABLE binance_atomusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_atom" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Avaxusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_avaxusdt_1h_1

1.22 MB
26926 rows
9 columns


CREATE TABLE binance_avaxusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_avax" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Balusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_balusdt_1h_1

1.18 MB
27934 rows
9 columns


CREATE TABLE binance_balusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_bal" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Bchusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_bchusdt_1h_1

1.49 MB
34086 rows
9 columns


CREATE TABLE binance_bchusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_bch" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Bnbusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_bnbusdt_1h_1

2.46 MB
52052 rows
9 columns


CREATE TABLE binance_bnbusdt_1h_1 (
  "date" VARCHAR,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_bnb" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Btcusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_btcusdt_1h_1

2.99 MB
53988 rows
9 columns


CREATE TABLE binance_btcusdt_1h_1 (
  "date" VARCHAR,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_btc" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Compusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_compusdt_1h_1

1.27 MB
29059 rows
9 columns


CREATE TABLE binance_compusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_comp" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Crvusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_crvusdt_1h_1

1.07 MB
27840 rows
9 columns


CREATE TABLE binance_crvusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_crv" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Dentusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_dentusdt_1h_1

1.61 MB
36320 rows
9 columns


CREATE TABLE binance_dentusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_dent" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Dogeusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_dogeusdt_1h_1

1.95 MB
37576 rows
9 columns


CREATE TABLE binance_dogeusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_doge" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Dotusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_dotusdt_1h_1

1.27 MB
27749 rows
9 columns


CREATE TABLE binance_dotusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_dot" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Dydxusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_dydxusdt_1h_1

789.15 KB
18477 rows
9 columns


CREATE TABLE binance_dydxusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_dydx" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Etcusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_etcusdt_1h_1

2.13 MB
46841 rows
9 columns


CREATE TABLE binance_etcusdt_1h_1 (
  "date" VARCHAR,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_etc" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Ethusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_ethusdt_1h_1

2.69 MB
53988 rows
9 columns


CREATE TABLE binance_ethusdt_1h_1 (
  "date" VARCHAR,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_eth" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Filusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_filusdt_1h_1

1.19 MB
26363 rows
9 columns


CREATE TABLE binance_filusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_fil" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Hbarusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_hbarusdt_1h_1

1.5 MB
35528 rows
9 columns


CREATE TABLE binance_hbarusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_hbar" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Icpusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_icpusdt_1h_1

908.94 KB
21399 rows
9 columns


CREATE TABLE binance_icpusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_icp" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Linkusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_linkusdt_1h_1

2 MB
41642 rows
9 columns


CREATE TABLE binance_linkusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_link" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Ltcusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_ltcusdt_1h_1

1.99 MB
51164 rows
9 columns


CREATE TABLE binance_ltcusdt_1h_1 (
  "date" VARCHAR,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_ltc" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Maticusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_maticusdt_1h_1

1.77 MB
39243 rows
9 columns


CREATE TABLE binance_maticusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_matic" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);

Binance Mkrusdt 1h 1

@kaggle.franoisgeorgesjulien_crypto.binance_mkrusdt_1h_1

1.2 MB
28382 rows
9 columns


CREATE TABLE binance_mkrusdt_1h_1 (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume_mkr" DOUBLE,
  "volume_usdt" DOUBLE,
  "tradecount" BIGINT
);