是否有更有效的方法来生成这个数据框架?

Question

我有一个代码来转换"将字典转换成pd.DataFrame。结果，我得到了我需要的数据帧，但我认为代码是无效的。

python
import datetime
import pandas as pd
data = {}
for index, row in get_data_row_by_row():
data[index] = row
'''
As result i get something like
data = {"2022-04-22": {"Open": 4268.169485565509, "Close": 4225.4345703125, "Low": 4217.979029960617,
"High": 4331.431780377489},
"2022-04-25": {"Open": 4237.487568541329, "Close": 4204.16748046875, "Low": 4171.766769167242,
"High": 4315.181737583676}}
'''
df = pd.DataFrame({'Date': [datetime.datetime.strptime(i, "%Y-%m-%d") for i in data.keys()],
'Open': [val['Open'] for key, val in data.items()],
'Close': [val['Close'] for key, val in data.items()], 'Low': [val['Low'] for key, val in data.items()],
'High': [val['High'] for key, val in data.items()]})
df = df.set_index('Date')

如何更有效地生成相同的DataFrame ?

Answer 1

如何:

out = pd.DataFrame.from_dict(data, orient='index').rename_axis(index='Date')
out.index = pd.to_datetime(out.index)

输出:

Open       Close          Low         High
Date                                                         
2022-04-22  4268.169486  4225.43457  4217.979030  4331.431780
2022-04-25  4237.487569  4204.16748  4171.766769  4315.181738

Answer 2

只使用pd.DataFrame，然后将(.T)置换:

df = pd.DataFrame(data).T.reset_index()

输出:

>>> df
index         Open       Close          Low         High
0  2022-04-22  4268.169486  4225.43457  4217.979030  4331.431780
1  2022-04-25  4237.487569  4204.16748  4171.766769  4315.181738