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我有一个数据框df1：

    Plant name      Brand       Region  Units produced  capacity  Cost incurred
    Gujarat Plant   Hyundai     Asia    8500            9250      18500000
    Haryana Plant   Honda       Asia    10000           10750     21500000
    Chennai Plant   Hyundai     Asia    12000           12750     25500000
    Zurich Plant    Volkswagen  Europe  25000           25750     77250000
    Chennai Plant   Suzuki      Asia    6000            6750      13500000
    Rengensburg     BMW         Europe  12500           13250     92750000
    Dingolfing      Mercedes    Europe  14000           14750     103250000

我想要一个具有以下格式的输出数据框：

df2=    Region      BMW   Mercedes  Volkswagen  Toyota  Suzuki  Honda   Hyundai                             
        Europe
        North America
        Asia
        Oceania

其中每个单元格的内容等于sum(cost incurred) / sum(units produced)那个特定的Region和Brand。

我尝试过的代码导致ValueError：

for i,j in itertools.zip_longest(range(len(df2),range(len(df2.columns)):
    if (df2.index[i] in list(df1["Region"]) & df2.columns[j] in list(df1["Brand"])==True:
        temp1 = df1["Region"]==df2.index[i]
        temp2 = df1["Brand"]==df2.columns[j]] 
        df2.loc[df2.index[i],df2.columns[j]] = df1(temp1&temp2)["Cost incurred"].sum()/
                                            df1(temp1&temp2)["Units Produced"].sum()
    elif (df2.index[i] in list(df1["Region"]) & df2.columns[j] in list(df1["Brand"])==False:
        df2.loc[df2.index[i],df2.columns[j]] = 0

ValueError：具有多个元素的数组的真值不明确。使用 a.any() 或 a.all()

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1 回答 1

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df.pivot_table()专为数据透视和聚合功能而设计。一个快速（？）和肮脏的解决方案：

df1.pivot_table(index="Region", columns="Brand", values="Cost incurred", aggfunc=np.sum)\
/ df1.pivot_table(index="Region", columns="Brand", values="Units produced", aggfunc=np.sum)

输出

Brand      BMW   Honda      Hyundai  Mercedes  Suzuki  Volkswagen
Region                                                           
Asia       NaN  2150.0  2146.341463       NaN  2250.0         NaN
Europe  7420.0     NaN          NaN    7375.0     NaN      3090.0
于 2020-11-23T18:33:50.330 回答