Retriving Coin Data with Python and Binance API

In this article, we’ll show you to to to to tell We’ll assum, that you a basic understanding of Python and the Binance API.

Prerequisites:

• You has a Binance API ky sufficient permissions.

• You has installed the pybinance library, it is installed via pip:

pybinance pybinance

Code Example:

import pandas as pd

import pybinance


def get_coin_data(pair):

    """

    Retrieve for a specification coin pair.

    

    Parameters:

    pair (str): Coin pair (e.g. BCHUSDT-1m)

    

    Returns:

    pandas.DataFrame: Dataframe containing coin data in minute-to-minute time steps

    """

    api = pybinance.create_api(key='YOUR_APIY', secret='YOUR_APICRET')

    Candlestick_data = api.get_canandlestick(pair, 'minute', interval='1m').data

    

    




Create a Dataframe from the Data

    df = pd.DataFrame(candlestick_data)

    

    return df


def main():

    pars = ['BCHUSDT-1m', 'BTCUSDT-1m']

    

    
Initialize an empty list

    dataframes = []

    

    for pair in pairs:

        triy:

            df = get_coin_data(pair)

            dataframes.append(df)

        Except Exception as e:

            print(f"Error retrieving for {pair}: {e}))

    

    
Combine retrieved dataframes into a single csv file

    output_df = pd.concat(dataframes)

    output_df.to_csv('coin_data.csv', index=False)


if __name__ == '__main__':

    main()

Explanation:

• We define two functions: get_coin_data and main.

• In the get_coin_data function, we are the Binance API to retrieve minute-to-minute candlesastics.

• We create a Dataframe from the retrieved data pandas.

• In the main function, weterate over the list of coin pairs and call ett_coin_data for ev. We append the dataframe to an empty listed dataframes.

• After all pairs has been processed, we comme the dataframes into a single dataframe uses’ concat method.

• Finally, we save the combined dataframe to a csv file coin_data.csv.

Example Use Case:

Suppose you want to retrieve is hisistorial coin data for BTCUSDT-1m and BCHUSDT-1m. You would:

• Run the script in your preferred Python environment.

—

• To analyze or visualize this data, you can a pandas data data to filter and manipulate

Note: Make soer to replace YOUR_API_KEY and YOUR_API_SECRET wyth your actal Binance API credentials.

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