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pandasで読込までできたのであれば、あとは`data`と`side`で`groupby`して`volume`の`sum`をとればよいと思います。
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参考：[pandas.DataFrameをGroupByでグルーピングし統計量を算出](https://note.nkmk.me/python-pandas-groupby-statistics/)
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```Python
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import pandas as pd
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from io import StringIO
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s = """2019-01-11 06:00:42 SELL 392684.0 0.080000
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2019-01-11 06:00:42 SELL 392685.0 0.080000
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2019-01-11 06:00:42 SELL 392685.0 0.020000
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2019-01-11 06:00:41 SELL 392684.0 0.010000
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2019-01-11 06:00:41 BUY 392694.0 0.047977
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2019-01-11 06:00:41 BUY 392691.0 0.051023
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2019-01-11 06:00:41 SELL 392684.0 0.010000
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2019-01-11 06:00:41 SELL 392684.0 0.100000
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2019-01-11 06:00:41 SELL 392684.0 0.090000
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"""
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df = pd.read_csv(StringIO(s),header=None,delim_whitespace=True,names=['date','side','price','volume'])
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grouped = df.groupby(['date','side'])
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print(grouped.sum()['volume'])
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```
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