Pandas 列的条件平均值，其中值大于或小于零

Question

I want to calculate the conditional mean of a column: If the values of the row elements are >0 then calculate mean of all such elements and if <0 then calculate the mean of these and store in avgGain and avgLoss.

Input:

ProfitLoss
    -8.000
    14.400
    13.150
     3.050
    -8.000
    -8.000
     3.425
     7.350
    -8.000
    -8.000
     0.000

Output:

avgGain     avgLoss
 8.275      -8.000

All these calculations should happen using either pandas apply or aggregate functions in a single statement.

Thanks

Answer 1

IIUC, could do:

# Setup (for reproducibility)
import pandas as pd

data = [-8.000,
    14.400,
    13.150,
     3.050,
    -8.000,
    -8.000,
     3.425,
     7.350,
    -8.000,
    -8.000,
     0.000]
df = pd.DataFrame(data, columns=["ProfitLoss"])

# Calculate the respective means (vectorized)
avgGain = df[df['ProfitLoss'] > 0].mean().values[0]
avgLoss = df[df['ProfitLoss'] < 0].mean().values[0]

# Print outputs to console
print("avgGain:", avgGain)
print("avgLoss:", avgLoss)

outputs:

Matthews-MacBook-Pro:stackoverflow matt$ python test.py
avgGain: 8.275
avgLoss: -8.0

as desired