Here is a step-by-step guide on how to create an Ethereum candlestick 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 (displayed as 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
parameters = {
'symbol': 'ETH',
'interval': '1m',
'limit': 100, 
Maximum number of data points to retrieve
'timeRange': start_date + ',' + end_date,
}

Send an 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 x-axis dates (index) from 1 to 100 (assuming we need at least 100 data points)
dates = np.arange(1, length(df.columns))

Set the date format for matplotlib
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))

Draw a candlestick chart
plt.figure(figuresize=(14,10))
for i in range (len(dates)-1):
plt.plot([i۰.۰۱, (i+1)۰.۰۱], [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([i۰.۰۱, i۰.۰۱ + ۰.۰۱], [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([i۰.۰۱, i۰.۰۱ + ۰.۰۲], [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 must have the required libraries (matplotlib, pandas, and yfinance) installed. You also need a Binance API key.

Make sure your Binance API endpoint is set up correctly according to your API documentation.

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