asks_price asks_qty exchange_name_ask bids_price bids_qty exchange_name_bid
0 20156.51 0.000745 Coinbase 20153.28 0.000200 Coinbase
1 20157.52 0.050000 Coinbase 20152.27 0.051000 Coinbase
2 20158.52 0.000745 Coinbase 20151.28 0.000200 Kraken
3 20158.52 0.050000 FTX 20151.28 0.051000 Coinbase
I would like to group the same price, add quantity together and combine the name of the exchange like :
asks_price asks_qty exchange_name_ask bids_price bids_qty exchange_name_bid
0 20156.51 0.000745 Coinbase 20153.28 0.000200 Coinbase
1 20157.52 0.050000 Coinbase 20152.27 0.051000 Coinbase
2 20158.52 0.050745 CoinbaseFTX 20151.28 0.051200 KrakenCoinbase
I received a good answer simply if it is the same name I do not want it to be concat, example CoinbaseCoinbase. How can i do that ?
group the dataframe by asks_price then call sum passing False to numeric_only argument, the solution assumes that the data is in the order you've provided in the sample data, else you need to handle the logic for sorting:
>>> df.groupby(['asks_price', 'bids_price']).sum(False)
asks_qty exchange_name_ask bids_qty exchange_name_bid
asks_price bids_price
20156.51 20153.28 0.000745 Coinbase 0.0002 Coinbase
20157.52 20152.27 0.050000 Coinbase 0.0510 Coinbase
20158.52 20151.28 0.050745 CoinbaseFTX 0.0512 KrakenCoinbase
You can call reset_index() at last if you want to have prices as column rather than index.