Level I Trades and Quotes (TAQ) Data

[BGTCapital]

Hi
We are trying to build a very simple dataframe in panda with basic bid-ask price and volume

Could you kindly help us understand how can we do that with Cryptofeed? I am still struggling to understand the documentation, and since I am new to python, I would highly appreciate if you could share some sample code
Thanks in advance for your support
Best

[bmoscon]

I'm not sure where this data would come from. Is this just the top level of the orderbook? If so, you can subscribe to an L2_BOOK channel and take the top level off the book in each callback and append it to a dataframe. The code in examples/demo.py does something like this because it uses the top level to calculate the spread (in the book callback).

[bmoscon]

the callback would be something like

async def book(data, receipt_timestamp):
     ask, ask_size = data.book.asks.index(0)
     bid, bid_size = data.book.bids.index(0)
     df.append({'ask': ask, 'ask_size': ask_size, 'bid': bid, 'bid_size': bid_size, 'timestamp': data.timestamp if data.timestamp else receipt_timestamp}, inplace=True)

[BGTCapital]

Thank you very (very!) much for your support. Since I am new to pandas, I was wondering if there is any way to add the data to the dataframe. the code from above returns: TypeError: append() got an unexpected keyword argument 'inplace'
On the other side, If I use this definition:

async def book(data, receipt_timestamp):
ask, ask_size = data.book.asks.index(0)
bid, bid_size = data.book.bids.index(0)
print({'ask': ask, 'ask_size': ask_size, 'bid': bid, 'bid_size': bid_size, 'timestamp': data.timestamp if data.timestamp else receipt_timestamp})

I receive this data

{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369936.971917}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.1687636}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.1692595}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.16953}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.1697989}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.1700351}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.170259}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.1704915}
{'ask': Decimal('58561'), 'ask_size': Decimal('0.00041392'), 'bid': Decimal('58547'), 'bid_size': Decimal('0.00695'), 'timestamp': 1638369937.1707687}

Sorry for asking again, but since I am new to this, I was wondering if you could be so kind to help me structuring the dataframe and saving to csv file so that multiple coins are aggregated as columns as in this example

sample_file.csv
.
Thanks in advance for your support

[bmoscon]

ok yeah looks like append doesnt support inplace, so it would just be df = df.append(.....) (leaving out the inplace kawrg).