熊猫| lambda函数的替代方法=> .loc [row_indexer,col_indexer] =值

时间:2020-08-10 20:14:22

标签: python pandas

我有一种方法可以从熊猫数据帧的两列计算加权平均值。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。计算后,它们将转换回原始格式。

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,该函数会生成警告消息:

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

如何用.loc定义此方法?

1 个答案:

答案 0 :(得分:1)

您可以忽略警告,但是如果您不想警告 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