熊猫数据框中的分组比加权平均值和总和

编辑： 更新聚合，以便它与熊猫的最新版本一起使用

要将多个函数传递给groupby对象，您需要传递带有聚合函数和该函数适用的列的元组：

# Define a lambda function to compute the weighted mean:wm = lambda x: np.average(x, weights=df.loc[x.index, "adjusted_lots"])# Define a dictionary with the functions to apply for a given column:# the following is deprecated since pandas 0.20:# f = {'adjusted_lots': ['sum'], 'price': {'weighted_mean' : wm} }# df.groupby(["contract", "month", "year", "buys"]).agg(f)# Groupby and [aggregate with namedAgg][1]:df.groupby(["contract", "month", "year", "buys"]).agg(adjusted_lots=("adjusted_lots", "sum"), price_weighted_mean=("price", wm))    adjusted_lots  price_weighted_meancontract month year buys   C        Z     5    Sell -19424.828947CC       U     5    Buy    5          3328.000000SB       V     5    Buy   12 11.637500W        Z     5    Sell  -5554.850000