Having this dictionary
{'ON': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.0895 -0.008 0.0015 -0.014 0.004,
'1W': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.0785 -0.01 0.002 -0.017 0.0065,
'2W': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.0795 -0.011 0.0025 -0.019 0.00837,
'1M': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.077 -0.0115 0.0025 -0.0207 0.00925,
'2M': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.075 -0.0115 0.0025 -0.0207 0.00937,
'3M': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.07325 -0.012 0.00255 -0.0222 0.00969,
'6M': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.07175 -0.0125 0.00265 -0.02375 0.0102,
'9M': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.07125 -0.0125 0.00295 -0.02375 0.0115,
'1Y': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.071 -0.0125 0.003 -0.02381 0.0117,
'2Y': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.072 -0.0125 0.0032 -0.02375 0.01248}
I would like to convert it to this dataFrame
I tried different approaches by using pd.DataFrame.from_dict but didn’t help
>Solution :
Use pd.concat:
df = pd.concat(data).droplevel(1)
Output:
>>> df
time atm rr25 bf25 rr10 bf10
ON 2022-03-29 23:00:00 0.0895 -0.008 0.0015 -0.014 0.0040
1W 2022-03-29 23:00:00 0.0785 -0.010 0.0020 -0.017 0.0065
Data
>>> data
{'ON': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.0895 -0.008 0.0015 -0.014 0.004,
'1W': time atm rr25 bf25 rr10 bf10
0 2022-03-29 23:00:00 0.0785 -0.01 0.002 -0.017 0.0065}