Question

我希望将此输出转换为具有少量感兴趣列的pandas DataFrame。请注意，我的输出实际上更多，但我只发布了部分输出，但希望您能理解我的实际需求

我的数据框应具有列[['Date'，'OI的更改'，'未平仓头寸']。最好日期应该是索引。

strikes=[690,700,710]
data={}
for s in strikes:
    data[s]=get_history(symbol="CIPLA",
                        start=date(2020,7,1),
                        end=date(2201,7,17),
                        option_type="CE",
                        strike_price=s,
                        expiry_date=date(2020,7,30))

输出

{690:            Symbol      Expiry Option Type  Strike Price   Open   High    Low  \
 Date                                                                           
 2020-07-01  CIPLA  2020-07-30          CE         690.0  11.50  11.50   7.70   
 2020-07-02  CIPLA  2020-07-30          CE         690.0   8.90  20.90   8.50   
 2020-07-03  CIPLA  2020-07-30          CE         690.0  17.75  17.75  12.00   
 2020-07-06  CIPLA  2020-07-30          CE         690.0  11.30  11.30   9.60   
 2020-07-07  CIPLA  2020-07-30          CE         690.0  10.70  12.25  10.60   
 2020-07-08  CIPLA  2020-07-30          CE         690.0  12.95  14.10  11.45   
 2020-07-09  CIPLA  2020-07-30          CE         690.0  14.00  14.00  11.60   
 2020-07-10  CIPLA  2020-07-30          CE         690.0  12.50  13.00  10.95   
 2020-07-13  CIPLA  2020-07-30          CE         690.0  11.10  11.65   9.65   
 2020-07-14  CIPLA  2020-07-30          CE         690.0  10.65  10.70   8.40   
 2020-07-15  CIPLA  2020-07-30          CE         690.0   7.55  10.00   7.55   
 2020-07-16  CIPLA  2020-07-30          CE         690.0  11.20  18.65   7.25   
 2020-07-17  CIPLA  2020-07-30          CE         690.0  18.85  25.75  14.80   
 
             Close   Last  Settle Price Number of Contracts      Turnover  \
 Date                                                                       
 2020-07-01   8.85   8.85          8.85                  66  5.995900e+07   
 2020-07-02  16.85  20.50         16.85                  68  6.235500e+07   
 2020-07-03  13.00  13.25         13.00                 117  1.069840e+08   
 2020-07-06  10.65  10.75         10.65                  76  6.918800e+07   
 2020-07-07  11.00  11.00         11.00                  64  5.836300e+07   
 2020-07-08  11.95  11.95         11.95                  84  7.674300e+07   
 2020-07-09  12.00  12.00         12.00                  25  2.284000e+07   
 2020-07-10  11.10  11.10         11.10                  50  4.564100e+07   
 2020-07-13  10.05  10.05         10.05                  36  3.278000e+07   
 2020-07-14   8.50   8.40          8.50                  39  3.546700e+07   
 2020-07-15   8.45   8.40          8.45                  31  2.816200e+07   
 2020-07-16  17.20  16.80         17.20                 803  7.350000e+08   
 2020-07-17  20.05  19.30         20.05                1708  1.577693e+09   
 
             Premium Turnover Open Interest Change in OI  Underlying  
 Date                                                                 
 2020-07-01          757000.0        119600         5200         NaN  
 2020-07-02         1359000.0        113100        -6500      646.20  
 2020-07-03         2035000.0        131300        18200      638.80  
 2020-07-06         1016000.0        123500        -7800         NaN  
 2020-07-07          955000.0        128700         5200      636.55  
 2020-07-08         1395000.0        130000         1300         NaN  
 2020-07-09          415000.0        130000            0         NaN  
 2020-07-10          791000.0        130000            0         NaN  
 2020-07-13          488000.0        123500        -6500         NaN  
 2020-07-14          484000.0        115700        -7800         NaN  
 2020-07-15          355000.0        124800         9100         NaN  
 2020-07-16        14709000.0        302900       178100         NaN  
 2020-07-17        45617000.0        243100       -59800      689.10  }

输出中的罢工= [700,710]中的值也是如此

已经尝试使用pd.DataFrame.from_dict（data）没用

Answer 1

您可以尝试以下方法

1。

import pandas as pd
df =  pd.DatFrame(<<your dictionary>>)   # you can pass the dictionary

或者，您也可以使用以下

import pandas as pd

cols = [<<list of column names>>]   # to specify different column names 

df = pd.DataFrame.from_dict(<<dictionary name>>,columns=cols)

Answer 2

以这种方式使用字典将其转换为数据框

import pandas as pd
df = pd.DataFrame({"your dictionary here"})

如何将字典转换为pandas数据框？

2 个答案: