python - 根据另一个表中的多个列在一个表中创建一列 [python]

Question

我正在创建一个 csv 表，其中包含有关我所有订单的信息。现在我想卖掉这些元素，但我想根据元素的价格添加额外的附加费。我创建了一个带有 surcharge 的新表，其中有名为“from”和“to”的列，我必须从中比较商品价格，然后在销售价格中包含正确的附加费。

但是我做不到。我尝试了不同的方法，但似乎都不起作用。任何帮助都会很好:)

我的表格是这样的:

    OrderNo      NetPerPiece costsDividedPerOrder  HandlingPerPiece

0  7027514279        44.24     0.008007          0.354232

1  7027514279        15.93     0.008007          0.127552

2  7027514279        15.93     0.008007          0.127552

3  7027514279        15.93     0.008007          0.127552

4  7027514279        15.93     0.008007          0.127552

surcharges = {'surcharge': [0.35, 0.25, 0.2, 0.15, 0.12, 0.1],
'from': [0, 20, 200, 500, 1500, 5000], 
'to' : [20, 200, 500, 1500, 5000,1000000000] }
surchargeTable = DataFrame(surcharges, columns=['surcharge', 'from', 'to'])


productsPerOrder['NetPerpieceSale'] = numpy.where(((productsPerOrder['NetPerPiece'] >= surchargeTable['from']) & (productsPerOrder['NetPerPiece'] < surchargeTable['to'])), surchargeTable['surcharge'])


#I also tried this:

for index, row in productsPerOrder.iterrows():
        if row['NetPerPiece'] >= surchargeTable['from'] & row['NetPerPiece'] < surchargeTable['to']:
                productsPerOrder.loc[index,'NerPerPieceSale'] = surchargeTable.loc[row,'NetPerPieceSale'].values(0)

我希望它看起来像这样:

 OrderNo   NetPerPiece costsDividedPerOrder  HandlingPerPiece NetPerPieceSale

0  7027514279   44.24           0.008007          0.354232    0.25

1  7027514279   15.93           0.008007          0.127552    0.35

2  7027514279   15.93           0.008007          0.127552    0.35

3  7027514279   15.93           0.008007          0.127552    0.35

4  7027514279   15.93           0.008007          0.127552    0.35

提醒一下，带有项目的文件要大得多，我只显示了 csv 列表的头部。所以表格的长度不同

SurchargeTable 看起来像这样:

 surcharge  from          to
0       0.35     0          20
1       0.25    20         200
2       0.20   200         500
3       0.15   500        1500
4       0.12  1500        5000
5       0.10  5000  1000000000

Answer 1

另一种方法是使用 pd.IntervalIndex 和 map:

# Create IntervalIndex on surchageTable dataframe
surchargeTable = surchargeTable.set_index(pd.IntervalIndex.from_arrays(surchargeTable['from'],
                                                                       surchargeTable['to']))

#Use map to pd.Series created from surchargeTable IntervalIndex and surcharge column.
productsPerOrder['NetPerPieceSale'] = productsPerOrder['NetPerPiece'].map(surchargeTable['surcharge'])

productsPerOrder

输出:

      OrderNo  NetPerPiece  costsDividedPerOrder  HandlingPerPiece  NetPerPieceSale
0  7027514279        44.24              0.008007          0.354232             0.25
1  7027514279        15.93              0.008007          0.127552             0.35
2  7027514279        15.93              0.008007          0.127552             0.35
3  7027514279        15.93              0.008007          0.127552             0.35
4  7027514279        15.93              0.008007          0.127552             0.35