Here’s a step-by-step guide on how to create an Ethereum candle chart using matplotlib in Python:

import matplotlib.pyplot as plt

import matplotlib.dates as mdates

import numpy as np

import yfinance as yf

from datetime import datetime, timedelta











Get the current time (will be displayed as the x-axis)

start_date = datetime.today().strftime('%Y-%m-%d')

end_date = (datetime.today() - timedelta(days=30)).strftime('%Y-%m-%d')



Define the API endpoint for Ethereum prices

apiEndpoint = "



Set the parameters for the API request

params = {

    'symbol': 'ETH',

    'interval': '1m',

    'limit': 100,  
Max number of data points to retrieve

    'timeRange': start_date + ',' + end_date,

}



Send the API request and get the response

response = yf.get(apiEndpoint, params=params)



Convert the response to a pandas DataFrame

df = pd.DataFrame(response).T



Create the x-axis dates (index) from 1 to 100 (assuming we need at least 100 data points)

dates = np.arange(1, len(df.columns))



Set the date format for matplotlib

plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))



Plot the candle chart

plt.figure(figsize=(14,10))

for i in range(len(dates)-1):

    plt.plot([i0.01, (i+1)0.01], [df.loc[i,'close'].mean(), df.loc[i+1,'close'].mean()], color='g')

    if not (i == len(df.columns) - 2): 
do not plot the last candle

        plt.plot([i0.01, i0.01 + 0.01], [df.loc[i,'high'].mean(), df.loc[i+1,'high'].mean()], color='g')

    elif (i == len(df.columns) - 2): 
do not plot the first candle

        plt.plot([i0.01, i0.01 + 0.02], [df.loc[i,'low'].mean(), df.loc[i+1,'low'].mean()], color='g')


plt.xlabel('Date')

plt.ylabel('Price (USD)')

plt.title("Ethereum Candle Chart")

plt.show()

To run this script, you need to have the required libraries installed (matplotlib, pandas and yfinance). You also need a Binance API key.

Please ensure that your Binance API endpoint is correctly set as per your API documentation.