从列表创建数据框

时间：2019-12-07 11:33:52

标签： python pandas

我正在尝试从列表创建数据框。 列表的内容是这样的：

 [Position(account='DUC00074', contract=Stock(conId=333970434, symbol='ESGV', exchange='BATS', currency='USD', localSymbol='ESGV', tradingClass='ESGV'), position=1142.0, avgCost=52.7765556),
 Position(account='DUC00074', contract=Stock(conId=238760476, symbol='ESGD', exchange='NASDAQ', currency='USD', localSymbol='ESGD', tradingClass='NMS'), position=954.0, avgCost=64.1715282),
 Position(account='DUC00074', contract=Stock(conId=26653236, symbol='DVY', exchange='NASDAQ', currency='USD', localSymbol='DVY', tradingClass='NMS'), position=292.0, avgCost=101.06176745),
 Position(account='DUC00074', contract=Stock(conId=27638087, symbol='VO', exchange='ARCA', currency='USD', localSymbol='VO', tradingClass='VO'), position=50.0, avgCost=170.48881),
 Position(account='DUC00074', contract=Stock(conId=27684036, symbol='VDE', exchange='ARCA', currency='USD', localSymbol='VDE', tradingClass='VDE'), position=99.0, avgCost=81.962902),
 Position(account='DUC00074', contract=Stock(conId=225020107, symbol='TFI', exchange='ARCA', currency='USD', localSymbol='TFI', tradingClass='TFI'), position=1109.0, avgCost=50.50644005),
 Position(account='DUC00074', contract=Stock(conId=43645865, symbol='IBKR', exchange='NASDAQ', currency='USD', localSymbol='IBKR', tradingClass='NMS'), position=2800.0, avgCost=39.4058383),
 Position(account='DUC00074', contract=Stock(conId=26787475, symbol='TIP', exchange='ARCA', currency='USD', localSymbol='TIP', tradingClass='TIP'), position=207.0, avgCost=115.00465265),
 Position(account='DUC00074', contract=Stock(conId=46577293, symbol='BWX', exchange='ARCA', currency='USD', localSymbol='BWX', tradingClass='BWX'), position=712.0, avgCost=28.57725195),
 Position(account='DUC00074', contract=Stock(conId=15547816, symbol='LQD', exchange='ARCA', currency='USD', localSymbol='LQD', tradingClass='LQD'), position=99.0, avgCost=124.4389121),
 Position(account='DUC00074', contract=Stock(conId=313845618, symbol='ESML', exchange='BATS', currency='USD', localSymbol='ESML', tradingClass='ESML'), position=309.0, avgCost=27.38696345),
 Position(account='DUC00074', contract=Stock(conId=31230302, symbol='VNQ', exchange='ARCA', currency='USD', localSymbol='VNQ', tradingClass='VNQ'), position=137.0, avgCost=88.7322321),
 Position(account='DUC00074', contract=Stock(conId=238760480, symbol='ESGE', exchange='NASDAQ', currency='USD', localSymbol='ESGE', tradingClass='NMS'), position=1221.0, avgCost=33.994677),
 Position(account='DUC00074', contract=Stock(conId=338719585, symbol='EAGG', exchange='ARCA', currency='USD', localSymbol='EAGG', tradingClass='EAGG'), position=1280.0, avgCost=53.3022901),

要创建列表，请使用：

df = pd.DataFrame(dict)

但是它会像这样返回df：

df image

我应该怎么做才能以正确的方式可视化df中的所有信息，以便以后只选择我需要的列？

正确地=每个逗号，一列。

非常感谢您的帮助。

2 个答案:

答案 0 :(得分：0)

尝试：

cols=[el.split("=")[0] for el in df['contract'].iloc[0].split(",")]
for el in cols:
    df[el]=""
df[cols]=df['contract'].str.split(",")
df[cols]=[df[col].str.split("=").apply(lambda x: x[1]) for col in cols]

答案 1 :(得分：0)

使用：

t = [{k: v for k, v in {**x.contract._asdict(), **x._asdict()}.items() 
      if k != 'contract'} for x in L]

df = pd.DataFrame(t)

print (df.head())
        conId symbol exchange currency localSymbol tradingClass   account  \
0   333970434   ESGV     BATS      USD        ESGV         ESGV  DUC00074   
1   238760476   ESGD   NASDAQ      USD        ESGD          NMS  DUC00074   
2    26653236    DVY   NASDAQ      USD         DVY          NMS  DUC00074   
3    27638087     VO     ARCA      USD          VO           VO  DUC00074   
4    27684036    VDE     ARCA      USD         VDE          VDE  DUC00074   

    position     avgCost  
0     1142.0   52.776556  
1      954.0   64.171528  
2      292.0  101.061767  
3       50.0  170.488810  
4       99.0   81.962902

如果列的顺序很重要，请使用：

t = []
for x in L:
    out = {}
    d = x._asdict()
    for k, v in d.items():
        if isinstance(v, tuple):
            d1 = v._asdict()
            for k1, v1 in d1.items():
                out[k1] = v1
        else:
            out[k] = v
    t.append(out)


df = pd.DataFrame(t)
print (df.head())

    account      conId symbol exchange currency localSymbol tradingClass  \
0  DUC00074  333970434   ESGV     BATS      USD        ESGV         ESGV   
1  DUC00074  238760476   ESGD   NASDAQ      USD        ESGD          NMS   
2  DUC00074   26653236    DVY   NASDAQ      USD         DVY          NMS   
3  DUC00074   27638087     VO     ARCA      USD          VO           VO   
4  DUC00074   27684036    VDE     ARCA      USD         VDE          VDE   

   position     avgCost  
0    1142.0   52.776556  
1     954.0   64.171528  
2     292.0  101.061767  
3      50.0  170.488810  
4      99.0   81.962902

设置：

L = [Position(account='DUC00074', contract=Stock(conId=333970434, symbol='ESGV', exchange='BATS', currency='USD', localSymbol='ESGV', tradingClass='ESGV'), position=1142.0, avgCost=52.7765556),
 Position(account='DUC00074', contract=Stock(conId=238760476, symbol='ESGD', exchange='NASDAQ', currency='USD', localSymbol='ESGD', tradingClass='NMS'), position=954.0, avgCost=64.1715282),
 Position(account='DUC00074', contract=Stock(conId=26653236, symbol='DVY', exchange='NASDAQ', currency='USD', localSymbol='DVY', tradingClass='NMS'), position=292.0, avgCost=101.06176745),
 Position(account='DUC00074', contract=Stock(conId=27638087, symbol='VO', exchange='ARCA', currency='USD', localSymbol='VO', tradingClass='VO'), position=50.0, avgCost=170.48881),
 Position(account='DUC00074', contract=Stock(conId=27684036, symbol='VDE', exchange='ARCA', currency='USD', localSymbol='VDE', tradingClass='VDE'), position=99.0, avgCost=81.962902),
 Position(account='DUC00074', contract=Stock(conId=225020107, symbol='TFI', exchange='ARCA', currency='USD', localSymbol='TFI', tradingClass='TFI'), position=1109.0, avgCost=50.50644005),
 Position(account='DUC00074', contract=Stock(conId=43645865, symbol='IBKR', exchange='NASDAQ', currency='USD', localSymbol='IBKR', tradingClass='NMS'), position=2800.0, avgCost=39.4058383),
 Position(account='DUC00074', contract=Stock(conId=26787475, symbol='TIP', exchange='ARCA', currency='USD', localSymbol='TIP', tradingClass='TIP'), position=207.0, avgCost=115.00465265),
 Position(account='DUC00074', contract=Stock(conId=46577293, symbol='BWX', exchange='ARCA', currency='USD', localSymbol='BWX', tradingClass='BWX'), position=712.0, avgCost=28.57725195),
 Position(account='DUC00074', contract=Stock(conId=15547816, symbol='LQD', exchange='ARCA', currency='USD', localSymbol='LQD', tradingClass='LQD'), position=99.0, avgCost=124.4389121),
 Position(account='DUC00074', contract=Stock(conId=313845618, symbol='ESML', exchange='BATS', currency='USD', localSymbol='ESML', tradingClass='ESML'), position=309.0, avgCost=27.38696345),
 Position(account='DUC00074', contract=Stock(conId=31230302, symbol='VNQ', exchange='ARCA', currency='USD', localSymbol='VNQ', tradingClass='VNQ'), position=137.0, avgCost=88.7322321),
 Position(account='DUC00074', contract=Stock(conId=238760480, symbol='ESGE', exchange='NASDAQ', currency='USD', localSymbol='ESGE', tradingClass='NMS'), position=1221.0, avgCost=33.994677),
 Position(account='DUC00074', contract=Stock(conId=338719585, symbol='EAGG', exchange='ARCA', currency='USD', localSymbol='EAGG', tradingClass='EAGG'), position=1280.0, avgCost=53.3022901)]
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