如何在pandas中将python字典转换为dataframe

Question

我有以下python字典

 {'CARDIAC SURGERY':      IPD_Date  forecasted  net_bill_amount        flag
 0  2012-08-31  936400.306       467600.000       Train
 1  2012-09-30 1812637.364      2915615.000       Train
 2  2012-10-31 2829177.535      4369266.700       Train
 3  2012-11-30 2849109.782      4152424.500       Train,
  'OPTHALMIC':      IPD_Date  forecasted  net_bill_amount        flag
 0  2012-08-31   81881.051        75734.000       Train
 1  2012-09-30  238591.765       202252.000       Train
 2  2012-10-31  324813.299       345450.000       Train
 3  2012-11-30  310018.236       277028.000       Train}

如何在pandas中的dataframe中转换此词典

我试过跟随

df= pd.DataFrame(dict_df.items())

但是，这并没有达到预期效果。我想要的数据帧如下

 Dept                   IPD_Date     forecasted   net_bill_amount     flag     
 CARDIAC SURGERY        2012-08-31  936400.306       467600.000       Train
 CARDIAC SURGERY        2012-09-30 1812637.364      2915615.000       Train
 CARDIAC SURGERY        2012-10-31 2829177.535      4369266.700       Train
 CARDIAC SURGERY        2012-11-30 2849109.782      4152424.500       Train
 OPTHALMIC              2012-08-31   81881.051        75734.000       Train
 OPTHALMIC              2012-09-30  238591.765       202252.000       Train
 OPTHALMIC              2012-10-31  324813.299       345450.000       Train
 OPTHALMIC              2012-11-30  310018.236       277028.000       Train

Answer 1

将^{}与删除第二级MultiIndex一起使用，更改级别名称并最后将其转换为新列：

df = pd.concat(dict_df).reset_index(level=1, drop=True).rename_axis('Dept').reset_index()

Answer 2

尝试链接concat、droplevel和rename_axis，如下所示：

pd.concat(dict_df).droplevel(1).rename_axis('Dept')