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首页 > 解决方案 > 熊猫 | 替代 lambda 函数 => .loc[row_indexer,col_indexer] = value

python - 熊猫 | 替代 lambda 函数 => .loc[row_indexer,col_indexer] = value

问题描述

我有一种方法可以从熊猫数据框的两列中计算加权平均值。由于这些列不是浮点数据类型，因此必须首先将它们转换为适当的格式。在计算之后，它们被转换回原始格式。

def calculate_weighted_average(self, dataframe, column_for_average, column_for_weight):
    a = dataframe[column_for_average]
    w = dataframe[column_for_weight]
    # convert german decimal to float
    a = a.apply( lambda x : self.convert_german_decimal_to_float(x) )
    # calulate average
    weighted_average = (a * w).sum() / w.sum()
    # convert float to german decimal 
    weighted_average = self.convert_float_to_german_decimal(weighted_average)
    return weighted_average

对于转换，我使用 Lambda 函数，它会生成一条警告消息：

SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

如何使用 .loc 定义此方法？

标签： pythonpandas

解决方案

你可以忽略警告，但如果你不想警告试试这个

def calculate_weighted_average(self, dataframe, column_for_average, column_for_weight):
    a = dataframe[column_for_average]
    w = dataframe[column_for_weight]
    # convert german decimal to float
    a1 = a.apply( lambda x : self.convert_german_decimal_to_float(x))
    # calulate average
    weighted_average = (a1 * w).sum() / w.sum()
    # convert float to german decimal 
    weighted_average = self.convert_float_to_german_decimal(weighted_average)
    return weighted_average

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