Python 如何将具有多个值的嵌套字典导出到excel中

Python 如何将具有多个值的嵌套字典导出到excel中,python,python-3.x,pandas,Python,Python 3.x,Pandas,我已经为子字典创建了一个列表形式的嵌套字典,其中包含多个值。简而言之,它看起来是这样的: {1: {'Parameter 1': ['Value 1', 'Value 2', 'Value 3'], 'Parameter 2': ['Value 11', 'Value 22', 'Value 33'], 'Parameter 3': ['Num1', 'Num2', 'Num3']}, 2: {'Parameter 1': ['Data 1', 'Da

我已经为子字典创建了一个列表形式的嵌套字典,其中包含多个值。简而言之,它看起来是这样的:

{1: 
    {'Parameter 1': ['Value 1', 'Value 2', 'Value 3'], 
     'Parameter 2': ['Value 11', 'Value 22', 'Value 33'], 
     'Parameter 3': ['Num1', 'Num2', 'Num3']},
 2:
    {'Parameter 1': ['Data 1', 'Data 2', 'Data 3'], 
     'Parameter 2': ['Data 11', 'Data 22', 'Data 33'], 
     'Parameter 3': ['Numb1', 'Numb2', 'Numb3'],
     'Parameter 4': ['Numb11', 'Numb22', 'Numb33']}
}
我需要将其导出到Excel工作表。我想要的是:

            |               1             |             2            |    
---------------------------------------------------------------------
Parameter 1 | Value 1 | Value 2 | Value 3 | Data 1 | Data 2 | Data 3 |
----------------------------------------------------------------------
Parameter 2 | Value 11| Value 22| Value 33| Data 1 | Data 2 | Data 3 |
----------------------------------------------------------------------
Parameter 3 |   Num1  |   Num2  |   Num3  | Numb1  | Numb2  | Numb3  |
----------------------------------------------------------------------
Parameter 4 |         |         |         | Numb11 | Numb22 | Numb33 | 
----------------------------------------------------------------------
但当我使用to_excel方法时,我得到以下结果:

            |               1                    |             2                     |    
--------------------------------------------------------------------------------------
Parameter 1 |['Value 1', 'Value 2', 'Value 3']   |  ['Data 1', 'Data 2', 'Data 3']   |
--------------------------------------------------------------------------------------
Parameter 2 |['Value 11', 'Value 22', 'Value 33']| ['Data 11', 'Data 22', 'Data 33'] |
--------------------------------------------------------------------------------------
Parameter 3 |       ['Num1', 'Num2', 'Num3']     |     ['Numb1', 'Numb2', 'Numb3']   |
--------------------------------------------------------------------------------------
Parameter 4 |                                    |    ['Numb11', 'Numb22', 'Numb33'] | 
--------------------------------------------------------------------------------------
这很明显

将这样的字典导出到.csv是没有用的,因为带有参数4的行中的列将向左移动。因此,我正在研究如何使这些值分别填充单元格,或者如何在工作表中有多列的情况下将文本拆分为列。我是否应该以某种方式重新排列源词典

我还猜测,在我的例子中,不可能填充字典中的“缺失”行,因为每次我们得到新的子字典时,键都会更新

下面是一个实际的例子:

{1: {'Field Cluster': ['This', 'This', 'This'], 'Exploration Block': ['Is', 'Is', 'Is'], 'Producing since': [1923.0, 1923.0, 1923.0], 'Fluids': ['A ', 'A ', 'A '], 'Reservoirs': ['Test', 'Test', 'Test'], 'Area (km2)': ['File', 'File', 'File'], 'Depth (m)': ['A\nHuge\nDepth', 'A\nHuge\nDepth', 'A\nHuge\nDepth'], 'Concession License No.': ['UNIX license', 'UNIX license', 'UNIX license'], 'License Expiry Date / Extension': ['Everlasting', 'Everlasting', 'Everlasting'], 'Working Interest': ['There is one\n', 'There is one\n', 'There is one\n'], 'Gouvernment approval:': ['It is!', 'It is!', 'It is!'], 'Last study:': ['Million years ago', 'Million years ago', 'Million years ago'], 'Parameters': ['Horizon1', 'Horizon2', 'Horizon3'], 'Reservoir rock': ['First', 'Second', 'Third'], 'Net pay thickness (m)': [1.0, 21.0, 41.0], 'Avr. porosity (%)': [2.0, 22.0, 42.0], 'Average absolute permeability  (mD)': [3.0, 23.0, 43.0], 'Swi (%)': [4.0, 24.0, 44.0], 'Initial pressure (at)': [5.0, 25.0, 45.0], 'Bubble Pressure (at.)': [6.0, 26.0, 46.0], 'Dew Point Pressure (at)': [7.0, 27.0, 47.0], 'Initial Solution Ratio (Stm3/m3)': [8.0, 28.0, 48.0], 'Initial Condensate Gas Ratio (g/Stm3)': [9.0, 29.0, 49.0], 'Oil density (kg/cm)': [10.0, 30.0, 50.0], 'Oil viscosity (Pb) (cP)': [11.0, 31.0, 51.0], 'Contaminants (H2S, CO2)': [12.0, 32.0, 52.0], 'Initial Oil in Place (e3 to)': [13.0, 33.0, 53.0], 'Initial NGL in Place (e3 to)': [14.0, 34.0, 54.0], 'Initial Gas (assoc.) in Place (e6 m3) sol.gas/gas cap': [15.0, 35.0, 55.0], 'Initial Gas (non assoc.) in Place (e6 m3)': [16.0, 36.0, 56.0], 'Primary recovery / drive mechanism\nNone': ['Wow\nA', 'Recovery\nNone', 'Mechanism\nNone', ''], 'Secondary recovery': ['Another one', '', '', ''], 'Total Wells': ['1000', '-', '-', ''], 'Productive wells (oil/gas)': ['500', '-', '-', ''], 'Injection wells (water/gas)': ['500', '-', '-', ''], 'Rate of best producer in the field (tons / e3 Sm3/day)': ['30', '-', '-', ''], 'Water injection (e3 m3/day)': ['49', '-', '-', ''], 'Actual Pressure (at)': ['500', '434-3443', '48930', ''], 'Oil cumulative production (e3 tons)': ['37', '-', '-', ''], 'Associated gas cum. production (e6 sm3)': ['4535', '-', '-', ''], 'Non-associated gas cum. production (e6 sm3)': ['-', '-', '-', ''], 'NGL cumulative production (e3 tons)': ['', '-', '-', ''], 'Water Cut (%)': ['378', '-', '-', ''], 'Recovery Factor': ['I love hydrocarbons', '', '', ''], 'Current (%)': ['30 20 46 3', '', '', ''], 'Expected 2P (%)': ['Not really expected', '', '', ''], 'Oil production (tons/day)': ['44', '-', '-', ''], 'Associated gas production (e3 sm3/day)': ['-', '-', '-', ''], 'Non-associated gas production (e3 sm3/day)': ['-', '-', '-', ''], 'NGL production (tons/day)': ['-', '-', '-', '']},
2: {'Field Cluster': ['This', 'This', 'This'], 'Exploration Block': ['Is', 'Is', 'Is'], 'Producing since': [1923.0, 1923.0, 1923.0], 'Fluids': ['A ', 'A ', 'A '], 'Reservoirs': ['Test', 'Test', 'Test'], 'Area (km2)': ['File', 'File', 'File'], 'Depth (m)': ['A\nHuge\nDepth', 'A\nHuge\nDepth', 'A\nHuge\nDepth'], 'Concession License No.': ['UNIX license', 'UNIX license', 'UNIX license'], 'License Expiry Date / Extension': ['Everlasting', 'Everlasting', 'Everlasting'], 'Working Interest': ['There is one\n', 'There is one\n', 'There is one\n'], 'Gouvernment approval:': ['It is!', 'It is!', 'It is!'], 'Last study:': ['Million years ago', 'Million years ago', 'Million years ago'], 'Parameters': ['Horizon1', 'Horizon2', 'Horizon3'], 'Reservoir rock': ['First', 'Second', 'Third'], 'Net pay thickness (m)': [1.0, 21.0, 41.0], 'Avr. porosity (%)': [2.0, 22.0, 42.0], 'Average absolute permeability  (mD)': [3.0, 23.0, 43.0], 'Swi (%)': [4.0, 24.0, 44.0], 'Initial pressure (at)': [5.0, 25.0, 45.0], 'Bubble Pressure (at.)': [6.0, 26.0, 46.0], 'Dew Point Pressure (at)': [7.0, 27.0, 47.0], 'Initial Solution Ratio (Stm3/m3)': [8.0, 28.0, 48.0], 'Initial Condensate Gas Ratio (g/Stm3)': [9.0, 29.0, 49.0], 'Oil density (kg/cm)': [10.0, 30.0, 50.0], 'Oil viscosity (Pb) (cP)': [11.0, 31.0, 51.0], 'Contaminants (H2S, CO2)': [12.0, 32.0, 52.0], 'Initial Oil in Place (e3 to)': [13.0, 33.0, 53.0], 'Initial NGL in Place (e3 to)': [14.0, 34.0, 54.0], 'Initial Gas (assoc.) in Place (e6 m3) sol.gas/gas cap': [15.0, 35.0, 55.0], 'Initial Gas (non assoc.) in Place (e6 m3)': [16.0, 36.0, 56.0], 'Primary recovery / drive mechanism\nNone': ['Wow\nA', 'Recovery\nNone', 'Mechanism\nNone', ''], 'Secondary recovery': ['Another one', '', '', ''], 'Total Wells': ['1000', '-', '-', ''], 'Productive wells (oil/gas)': ['500', '-', '-', ''], 'Injection wells (water/gas)': ['500', '-', '-', ''], 'Rate of best producer in the field (tons / e3 Sm3/day)': ['30', '-', '-', ''], 'Water injection (e3 m3/day)': ['49', '-', '-', ''], 'Actual Pressure (at)': ['500', '434-3443', '48930', ''], 'Oil cumulative production (e3 tons)': ['37', '-', '-', ''], 'Associated gas cum. production (e6 sm3)': ['4535', '-', '-', ''], 'Non-associated gas cum. production (e6 sm3)': ['-', '-', '-', ''], 'NGL cumulative production (e3 tons)': ['', '-', '-', ''], 'Water Cut (%)': ['378', '-', '-', ''], 'Recovery Factor': ['I love hydrocarbons', '', '', ''], 'Current (%)': ['30 20 46 3', '', '', ''], 'Expected 2P (%)': ['Not really expected', '', '', ''], 'Oil production (tons/day)': ['44', '-', '-', ''], 'Associated gas production (e3 sm3/day)': ['-', '-', '-', ''], 'Non-associated gas production (e3 sm3/day)': ['-', '-', '-', ''], 'NGL production (tons/day)': ['-', '-', '-', ''], 'WOW Production (Something)': ['1', 2.0, '3', '']}}
例如,哪一个应该真正起作用

{1: {'Field Cluster': ['This', 'This', 'This'], 'Exploration Block': ['Is', 'Is', 'Is'], 'Producing since': [1923.0, 1923.0, 1923.0], 'Fluids': ['A ', 'A ', 'A '], 'Reservoirs': ['Test', 'Test', 'Test'], 'Area (km2)': ['File', 'File', 'File'], 'Depth (m)': ['A\nHuge\nDepth', 'A\nHuge\nDepth', 'A\nHuge\nDepth'], 'Concession License No.': ['UNIX license', 'UNIX license', 'UNIX license'], 'License Expiry Date / Extension': ['Everlasting', 'Everlasting', 'Everlasting'], 'Working Interest': ['There is one\n', 'There is one\n', 'There is one\n'], 'Gouvernment approval:': ['It is!', 'It is!', 'It is!'], 'Last study:': ['Million years ago', 'Million years ago', 'Million years ago'], 'Parameters': ['Horizon1', 'Horizon2', 'Horizon3'], 'Reservoir rock': ['First', 'Second', 'Third'], 'Net pay thickness (m)': [1.0, 21.0, 41.0], 'Avr. porosity (%)': [2.0, 22.0, 42.0], 'Average absolute permeability  (mD)': [3.0, 23.0, 43.0], 'Swi (%)': [4.0, 24.0, 44.0], 'Initial pressure (at)': [5.0, 25.0, 45.0], 'Bubble Pressure (at.)': [6.0, 26.0, 46.0], 'Dew Point Pressure (at)': [7.0, 27.0, 47.0], 'Initial Solution Ratio (Stm3/m3)': [8.0, 28.0, 48.0], 'Initial Condensate Gas Ratio (g/Stm3)': [9.0, 29.0, 49.0], 'Oil density (kg/cm)': [10.0, 30.0, 50.0], 'Oil viscosity (Pb) (cP)': [11.0, 31.0, 51.0], 'Contaminants (H2S, CO2)': [12.0, 32.0, 52.0], 'Initial Oil in Place (e3 to)': [13.0, 33.0, 53.0], 'Initial NGL in Place (e3 to)': [14.0, 34.0, 54.0], 'Initial Gas (assoc.) in Place (e6 m3) sol.gas/gas cap': [15.0, 35.0, 55.0], 'Initial Gas (non assoc.) in Place (e6 m3)': [16.0, 36.0, 56.0], 'Primary recovery / drive mechanism\nNone': ['Wow\nA', 'Recovery\nNone', 'Mechanism\nNone', ''], 'Secondary recovery': ['Another one', '', '', ''], 'Total Wells': ['1000', '-', '-', ''], 'Productive wells (oil/gas)': ['500', '-', '-', ''], 'Injection wells (water/gas)': ['500', '-', '-', ''], 'Rate of best producer in the field (tons / e3 Sm3/day)': ['30', '-', '-', ''], 'Water injection (e3 m3/day)': ['49', '-', '-', ''], 'Actual Pressure (at)': ['500', '434-3443', '48930', ''], 'Oil cumulative production (e3 tons)': ['37', '-', '-', ''], 'Associated gas cum. production (e6 sm3)': ['4535', '-', '-', ''], 'Non-associated gas cum. production (e6 sm3)': ['-', '-', '-', ''], 'NGL cumulative production (e3 tons)': ['', '-', '-', ''], 'Water Cut (%)': ['378', '-', '-', ''], 'Recovery Factor': ['I love hydrocarbons', '', '', ''], 'Current (%)': ['30 20 46 3', '', '', ''], 'Expected 2P (%)': ['Not really expected', '', '', ''], 'Oil production (tons/day)': ['44', '-', '-', ''], 'Associated gas production (e3 sm3/day)': ['-', '-', '-', ''], 'Non-associated gas production (e3 sm3/day)': ['-', '-', '-', ''], 'NGL production (tons/day)': ['-', '-', '-', '']}, 2: {'Field Cluster': ['This fff', 'This fff', 'This fff', 'This fff'], 'Exploration Block': ['fff', 'fff', 'fff', 'fff'], 'Producing since': ['1923fff', '1923fff', '1923fff', '1923fff'], 'Fluids': ['A fff', 'A fff', 'A fff', 'A fff'], 'Reservoirs': ['Test', 'Test', 'Test', 'Test'], 'Area (km2)': ['File', 'File', 'File', 'File'], 'Depth (m)': ['A\nHuge\nDepthfff', 'A\nHuge\nDepthfff', 'A\nHuge\nDepthfff', 'A\nHuge\nDepthfff'], 'Concession License No.': ['UNIX license', 'UNIX license', 'UNIX license', 'UNIX license'], 'License Expiry Date / Extension': ['Everlastingfff', 'Everlastingfff', 'Everlastingfff', 'Everlastingfff'], 'Working Interest': ['There is one\n', 'There is one\n', 'There is one\n', 'There is one\n'], 'Gouvernment approval:': ['ffff', 'ffff', 'ffff', 'ffff'], 'Last study:': ['Million years fffff', 'Million years fffff', 'Million years fffff', 'Million years fffff'], 'Parameters': ['Horizon1', 'Horizon2', 'Horizon3', 'Horizon4'], 'Reservoir rock': ['First', 'Second', 'Third', 'Fourth'], 'Net pay thickness (m)': [1.0, 21.0, 41.0, 61.0], 'Avr. porosity (%)': [2.0, 22.0, 42.0, 62.0], 'Average absolute permeability  (mD)': [3.0, 23.0, 43.0, 63.0], 'Swi (%)': [4.0, 24.0, 44.0, 64.0], 'Initial pressure (at)': [5.0, 25.0, 45.0, 65.0], 'Bubble Pressure (at.)': [6.0, 26.0, 46.0, 66.0], 'Dew Point Pressure (at)': [7.0, 27.0, 47.0, 67.0], 'Initial Solution Ratio (Stm3/m3)': [8.0, 28.0, 48.0, 68.0], 'Initial Condensate Gas Ratio (g/Stm3)': [9.0, 29.0, 49.0, 69.0], 'Oil density (kg/cm)': [10.0, 30.0, 50.0, 70.0], 'Oil viscosity (Pb) (cP)': [11.0, 31.0, 51.0, 71.0], 'Contaminants (H2S, CO2)': [12.0, 32.0, 52.0, 72.0], 'Initial Oil in Place (e3 to)': [13.0, 33.0, 53.0, 73.0], 'Initial NGL in Place (e3 to)': [14.0, 34.0, 54.0, 74.0], 'Initial Gas (assoc.) in Place (e6 m3) sol.gas/gas cap': [15.0, 35.0, 55.0, 75.0], 'Initial Gas (non assoc.) in Place (e6 m3)': [16.0, 36.0, 56.0, 76.0], 'Primary recovery / drive mechanism\nNone': ['Wow\nA', 'Recovery\nNone', 'Mechanism\nNone', 'Nice\nNone', ''], 'Secondary recovery': ['Another one', '', '', '', ''], 'Total Wells': ['1000', '-', '-', '-', ''], 'Productive wells (oil/gas)': ['500', '-', '-', '-', ''], 'Injection wells (water/gas)': ['500', '-', '-', '-', ''], 'Rate of best producer in the field (tons / e3 Sm3/day)': ['30', '-', '-', '-', ''], 'Water injection (e3 m3/day)': ['49', '-', '-', '-', ''], 'Actual Pressure (at)': ['500', '434-3443', '48930', '4433', ''], 'Oil cumulative production (e3 tons)': ['37', '-', '-', '-', ''], 'Associated gas cum. production (e6 sm3)': ['4535', '-', '-', '-', ''], 'Non-associated gas cum. production (e6 sm3)': ['-', '-', '-', '-', ''], 'NGL cumulative production (e3 tons)': ['', '-', '-', '-', ''], 'Water Cut (%)': ['378', '-', '-', '-', ''], 'Recovery Factor': ['I love hydrocarbons', '', '', '', ''], 'Current (%)': ['30 20 46 3', '', '', '', ''], 'Expected 2P (%)': ['Not really expected', '', '', '', ''], 'Oil production (tons/day)': ['44', '-', '-', '-', ''], 'Associated gas production (e3 sm3/day)': ['-', '-', '-', '-', ''], 'Non-associated gas production (e3 sm3/day)': ['-', '-', '-', '-', ''], 'NGL production (tons/day)': ['-', '-', '-', '-', ''], 'WOW Production (Something)': ['1', 2.0, '3', '4', '']}}
我正在研究如何使这些值分别填充单元格

我认为您可以在这里创建一个多索引:

df=pd.DataFrame(d) # assuming d is the name of the dict
cols=df.columns


编辑最后添加的示例:

final1=pd.concat([pd.DataFrame(v).T for k,v in d.items()],axis=1,sort=False,keys=d.keys())


感谢您的回答,但在我的例子中,我得到了一个错误:“长度不匹配:预期轴有83个元素,新值有104个元素”。这是因为我在第一个子字典中有83个键,在两个子字典中都有104个键。我怎样才能修复它?@anki_91 UPD,你的代码终于可以工作了!但前提是我对#final.index=df.index行进行注释。但是如果没有它,我会得到第一列的数字(索引),而不是参数。如果我离开这一行,我会得到这个错误,就像在前面的评论中一样。@anki_91我目前无法在几个小时内给你一个指向dictionary(pastebin或其他任何东西)文件的链接。@anki_91好的,在问题的最后,我已经包括了和我一样的外观字典。它在我身上起作用是有原因的,但在我身上却不起作用。很抱歉,由于行为准则,我无法提交我实际拥有的数据。@anki_91我终于找到了问题所在。在我的例子中,第二个字典缺少一些参数(我已将新字典附加到问题上)。在这种情况下,第二个子字典中的参数4行转到第一个子字典中参数3所在的行。因此,这些值并没有真正附加到参数。
                    1                            2                  
                    0         1         2        0        1        2
Parameter 1   Value 1   Value 2   Value 3   Data 1   Data 2   Data 3
Parameter 2  Value 11  Value 22  Value 33  Data 11  Data 22  Data 33
Parameter 3      Num1      Num2      Num3    Numb1    Numb2    Numb3
Parameter 4       NaN       NaN       NaN   Numb11   Numb22   Numb33
final1=pd.concat([pd.DataFrame(v).T for k,v in d.items()],axis=1,sort=False,keys=d.keys())
                   1                           2                    
                   0        1        2         0         1         2
Parameter 1   Data 1   Data 2   Data 3   Value 1   Value 2   Value 3
Parameter 2  Data 11  Data 22  Data 33  Value 11  Value 22  Value 33
Parameter 3    Numb1    Numb2    Numb3       NaN       NaN       NaN
Parameter 4   Numb11   Numb22   Numb33      Num1      Num2      Num3