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Here is a well-structured article with an example of how to use Heiken Ashi candles and plot them on graph Binance:

Ethereum: Plotting Heiken Ash Candles in Python

When working with cryptocurrency markets like Ethereum, it is essential to visualize the market data to understand trends and patterns. One popular indicator used for this purpose is Heiken Ashi candles. In this article, we will explore how to plot Heiken Ashi candles on a graph using Binance API.

Prerequisites

• You have a Binance API account and client ID.

• You have installed the pandas library to work with data structures such as arrays and matrices.

• You have the necessary permissions to access historical market data on Binance.

Example Code: Plotting Heiken Ash Candles

import pandas as pd

from binance.client import Client


def heaking_ash():

    """

    Get historical Klines data for Ethereum ( SYMBOL )

    and Plot Heiken Ash Candles.

    """

    client = Client()

    symbol = "ETH" 




Replace with your desired cryptocurrency

    interval = "1m" 
1 minute interval

    

    
Get historical Klines data

    clines_data = client.get_historical_clines(

        symbol=symbol, 

        interval=interval, 

        limit=1000 
Limit to 1000 bars for simplicity

    )

    

    
Convert Klines data to pandas DataFrame

    df = pd.DataFrame(clines_data);

    

    
Binance Graph - Heiken Ashi Candles plot

    import matplotlib.pyplot as plt


    
Set up the plot

    plt. figure(figure size=(16, 8))

    plt.plot(df["close"], label="Close Price")

    plt.xlabel("Time")

    plt.ylabel("Price (USD)")

    plt.title("Binance Chart for Heiken Ashi Candles")

    

    
Add Heiken Ash candles to the plot

    plt.plot(df.index[1:], df["high"] - df["low"], color='green', label="Heiken Ashi")

    plt.legend()

    

    plt . show ( )



Example usage:

heikin_ashi()

This code snippet does the following:

• Establishes a Binance API client and specifies the desired cryptocurrency (ETH) and interval (1 minute).

• Retrieves historical Clines data using client.get_historical_clines().

• Converts the Klines data to a Pandas DataFrame for easier manipulation.

• Plots the Heiken Ashi candles on a graph using matplotlib, plotting the close price and adding Heiken Ashi lines as green bars.

Tips and Variations

• To customize the plot, explore additional options in the plot() function, such as changing the color scheme or modifying the candle body shape.

• Consider using other indicators such as Moving Averages or Bollinger Bands to create a more comprehensive analysis of market trends.

• For production-grade applications, ensure you’re handling sensitive data and API keys securely.

Remember to replace the symbol variable with your desired cryptocurrency symbol (e.g., “BTC”, “LTC”, etc.) and adjust the interval and limit settings according to your requirements. Happy charting!