I have a defaultdict that is constructed as below:
data = defaultdict(dict)
symbol_list = [
'ETHUSDT',
'BTCUSDT'
]
for symbol in symbol_list:
data[symbol] = load_binance_data(c, symbol, '2021-12-23', timeframe='5m')
This is the axes of the dataframes stored in the dictionary as values:
[DatetimeIndex(['2021-12-23 00:05:00', '2021-12-23 00:10:00',
'2021-12-23 00:15:00', '2021-12-23 00:20:00',
'2021-12-23 00:25:00', '2021-12-23 00:30:00',
'2021-12-23 00:35:00', '2021-12-23 00:40:00',
'2021-12-23 00:45:00', '2021-12-23 00:50:00',
...
'2021-12-24 19:05:00', '2021-12-24 19:10:00',
'2021-12-24 19:15:00', '2021-12-24 19:20:00',
'2021-12-24 19:25:00', '2021-12-24 19:30:00',
'2021-12-24 19:35:00', '2021-12-24 19:40:00',
'2021-12-24 19:45:00', '2021-12-24 19:50:00'],
dtype='datetime64[ns]', name='time', length=526, freq=None), Index(['open', 'high', 'low', 'close', 'volume'],
dtype='object')]
I want to transform this dictionary to a single dataframe with multiple index as below:
[DatetimeIndex(['2021-12-23 00:05:00', '2021-12-23 00:10:00',
'2021-12-23 00:15:00', '2021-12-23 00:20:00',
'2021-12-23 00:25:00', '2021-12-23 00:30:00',
'2021-12-23 00:35:00', '2021-12-23 00:40:00',
'2021-12-23 00:45:00', '2021-12-23 00:50:00',
...
'2021-12-24 19:05:00', '2021-12-24 19:10:00',
'2021-12-24 19:15:00', '2021-12-24 19:20:00',
'2021-12-24 19:25:00', '2021-12-24 19:30:00',
'2021-12-24 19:35:00', '2021-12-24 19:40:00',
'2021-12-24 19:45:00', '2021-12-24 19:50:00'],
dtype='datetime64[ns]', name='time', freq=None),
MultiIndex([
('open', 'ETHUSDT'),
('open', 'BTCUSDT'),
('high', 'ETHUSDT'),
('high', 'BTCUSDT'),
('low', 'ETHUSDT'),
('low', 'BTCUSDT'),
('close', 'ETHUSDT'),
('close', 'BTCUSDT'),
('volume', 'ETHUSDT'),
('volume', 'BTCUSDT')],
names=['Attributes', 'Symbols'])]
How can I do this conversion?
Thanks in advance,
from Converting dictionary to a multi indexed dataframe
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