有没有更有效的方法来生成这个数据框？

Question

我有一个代码可以将 dict “转换”为pd.DataFrame 。 结果，我得到了我需要的数据框，但我认为代码无效。

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')

如何以更有效的方式生成相同的 DataFrame？

Answer 1

怎么样：

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

只需使用pd.DataFrame然后转置（ .T ）它：

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