This is my dataframe:
df = pd.DataFrame({'sym': ['a', 'b'], 'vol_1': [100, 50], 'price_1': [5, 150], 'vol_2': [1500, 2000], 'price_2': [20, 175],
'vol_3': [123, 500], 'price_3': [22, 1000], 'min': [18, 150], 'max': [23, 176]})
I want to add a column that sums vol_1, vol_2, and vol_3 for each row if the price that is in the next column for each vol is in range of min and max cols. For example for the first row I want vol_2 and vol_3 because the prices are in range of min and max. My desired outcome looks like this:
sym vol_1 price_1 vol_2 price_2 vol_3 price_3 min max vol_sum
0 a 100 5 1500 20 123 22 18 23 1623
1 b 50 150 2000 175 500 1000 150 176 2050
Reshape the data so you have individual columns for vol, price, min and max. Next, filter for only rows where price is between min and max, group by the sym column and append result to df.
df["vol_sum"] = (pd.wide_to_long(df,
stubnames=["vol", "price"],
i=["sym", "min", "max"],
j="number",
sep="_")
.query("min <= price <= max", engine="python")
.groupby("sym")
.vol
.sum()
.array
)
sym vol_1 price_1 vol_2 price_2 vol_3 price_3 min max vol_sum
0 a 100 5 1500 20 123 22 18 23 1623
1 b 50 150 2000 175 500 1000 150 176 2050
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