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pandas - 逐行将多列与特定列进行元素乘法

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{0: {"Nov '18": 0.1666471015536077, "Dec '18": 0.5403863967743445, "Jan '19": 0.5362702245675458, "Feb '19": 0.3538342118892141, "Mar '19": 0.6068213241958712, "Apr '19": 0.6959594096743349, "May '19": 0.682575498865738}, 1: {"Nov '18": 0.2993902407933448, "Dec '18": 0.44429158402908286, "Jan '19": 0.3729695419273137, "Feb '19": 0.3980823560973494, "Mar '19": 0.3200835471705221, "Apr '19": 0.29763667231002056, "May '19": 0.2840070502525354}, 2: {"Nov '18": 0.5337308848310992, "Dec '18": 0.013817091931355035, "Jan '19": 0.07008689274226004, "Feb '19": 0.10680130054564026, "Mar '19": 0.06818860955654642, "Apr '19": 0.004524516700862339, "May '19": 0.004338865464848797}, 'xTrader (838)': {"Nov '18": 75319.0, "Dec '18": 42484.39, "Jan '19": 40484.71, "Feb '19": 40470.29, "Mar '19": 66609.0, "Apr '19": 71057.87999999999, "May '19": 89627.88}}



{0: {'Owner': 'system_voy', 'App': 'Voyager', 'LOB': 'Risk Management: Capital Markets', 'Transit': '83534', "Nov '18": 0.1666471015536077, "Dec '18": 0.5403863967743445, "Jan '19": 0.5362702245675458, "Feb '19": 0.3538342118892141, "Mar '19": 0.6068213241958712, "Apr '19": 0.6959594096743349, "May '19": 0.682575498865738, "Jun '19": 0.7032990347937492}, 1: {'Owner': 'eu\\xtradereod', 'App': 'xTrader', 'LOB': 'Capital Markets: Global Markets', 'Transit': '75088', "Nov '18": 0.2993902407933448, "Dec '18": 0.44429158402908286, "Jan '19": 0.3729695419273137, "Feb '19": 0.3980823560973494, "Mar '19": 0.3200835471705221, "Apr '19": 0.29763667231002056, "May '19": 0.2840070502525354, "Jun '19": 0.2929727958768866}, 2: {'Owner': 'eu\\system_xtrader2', 'App': 'xTrader', 'LOB': 'Capital Markets: Global Markets', 'Transit': '75088', "Nov '18": 0.5337308848310992, "Dec '18": 0.013817091931355035, "Jan '19": 0.07008689274226004, "Feb '19": 0.10680130054564026, "Mar '19": 0.06818860955654642, "Apr '19": 0.004524516700862339, "May '19": 0.004338865464848797, "Jun '19": 0.0027272448226331497}, 3: {'Owner': 'mr-tech', 'App': 'FRTB', 'LOB': 'Risk Management: Capital Markets', 'Transit': '83534', "Nov '18": 4.021308836676355e-06, "Dec '18": 7.853538029670704e-05, "Jan '19": 0.015370002324550705, "Feb '19": 0.11787934038028858, "Mar '19": 1.5161864573662851e-07, "Apr '19": 1.0092819280702894e-06, "May '19": 9.714219073341933e-06, "Jun '19": 1.1635748117981739e-07}, 4: {'Owner': 'eu\\system_xtsup_prd', 'App': 'xTrader', 'LOB': 'Capital Markets: Global Markets', 'Transit': '75088', "Nov '18": 0, "Dec '18": 0, "Jan '19": 0, "Feb '19": 0.021433060967667138, "Mar '19": 0, "Apr '19": 0, "May '19": 0.016256659135696943, "Jun '19": 0}, 5: {'Owner': 'xt-tech', 'App': 'xTrader', 'LOB': 'Capital Markets: Global Markets', 'Transit': '75088', "Nov '18": 0.00022774976090734464, "Dec '18": 2.212229303038311e-06, "Jan '19": 0.004022482749891066, "Feb '19": 0.00011334322251753845, "Mar '19": 0.0036268312234368394, "Apr '19": 4.7611888584087586e-05, "May '19": 0.0103897652257289, "Jun '19": 0.0010008081492497863}, 6: {'Owner': 'ad\\watb', 'App': 'CVATrader', 'LOB': 'Capital Markets: RMG', 'Transit': '91707', "Nov '18": 0, "Dec '18": 0, "Jan '19": 0.0012585476083139418, "Feb '19": 0.0017582009987088963, "Mar '19": 0.001275486891583217, "Apr '19": 0.0015783820251811566, "May '19": 0.0006181777165474082, "Jun '19": 0}, 7: {'Owner': 'ad\\xustev', 'App': 'xTrader', 'LOB': 'Capital Markets: Global Markets', 'Transit': '75088', "Nov '18": 0, "Dec '18": 0.0014241796556178747, "Jan '19": 2.2308080124760536e-05, "Feb '19": 9.818589861410218e-05, "Mar '19": 4.049343394433275e-06, "Apr '19": 0.00025239811908896236, "May '19": 0.0006735771849304808, "Jun '19": 0}, 8: {'Owner': 'ad\\cvatrader', 'App': 'CVATrader', 'LOB': 'Capital Markets: RMG', 'Transit': '91707', "Nov '18": 0, "Dec '18": 0, "Jan '19": 0, "Feb '19": 0, "Mar '19": 0, "Apr '19": 0, "May '19": 0.0011116369831956367, "Jun '19": 0}, 9: {'Owner': 'ad\\mccloske', 'App': 'xTrader', 'LOB': 'Capital Markets: Global Markets', 'Transit': '75088', "Nov '18": 0, "Dec '18": 0, "Jan '19": 0, "Feb '19": 0, "Mar '19": 0, "Apr '19": 0, "May '19": 1.905495170508051e-05, "Jun '19": 0}, 10: {'Owner': 'anonymous', 'App': 'xTrader', 'LOB': 'Capital Markets: Global Markets', 'Transit': '75088', "Nov '18": 1.752204286133488e-09, "Dec '18": 0, "Jan '19": 0.0, "Feb '19": 0, "Mar '19": 0, "Apr '19": 0, "May '19": 0, "Jun '19": 0}, 'xTrader (838)': {'Owner': 0.0, 'App': 0.0, 'LOB': 0.0, 'Transit': 0.0, "Nov '18": 75319.0, "Dec '18": 42484.39, "Jan '19": 40484.71, "Feb '19": 40470.29, "Mar '19": 66609.0, "Apr '19": 71057.87999999999, "May '19": 89627.88, "Jun '19": 0.0}}

标签： pandasdataframe

解决方案

IIUC，您df.mul()需要df.iloc[]：

data.iloc[:,:-1]=data.iloc[:,:-1].mul(data.iloc[:,-1],axis=0)
print(data)

                    0             1             2  xTrader (838)
Apr '19  49453.400218  21149.430945    321.502565       71057.88
Dec '18  22957.986431  18875.456930    587.010722       42484.39
Feb '19  14319.773167  16110.508395   4322.279605       40470.29
Jan '19  21710.744523  15099.563744   2837.447527       40484.71
Mar '19  40419.761583  21320.444993   4541.975094       66609.00
May '19  61177.794903  25454.949819    388.883313       89627.88
Nov '18  12551.693042  22549.773546  40200.076515       75319.00

注意：提供的数据的总和是0.9981205987006647，这就是为什么每行的总和与最后一个不匹配的原因。否则，这个逻辑应该有效。

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