带有Data_Time数据转换的Python Financial OHLC：将数组列表转换为Pandas，并为每个列表追加列名

Question

I have this raw data retreive from some source as list array enclosed by ()

[('2018-10-13T21:00:00.000000000', 71.457, 72.675, 68.45 , 69.252, 71.51 , 72.725, 68.505, 69.31 , 507708)
 ('2018-10-20T21:00:00.000000000', 69.252, 69.806, 65.72 , 67.685, 69.31 , 69.855, 65.77 , 67.74 , 389174)
 ('2018-10-27T21:00:00.000000000', 67.685, 67.924, 62.61 , 62.855, 67.74 , 67.975, 62.665, 62.905, 454709)
 ('2018-11-03T21:00:00.000000000', 62.855, 64.115, 59.244, 59.815, 62.905, 64.165, 59.295, 59.87 , 858696)
 ('2018-11-10T22:00:00.000000000', 59.815, 61.262, 54.732, 56.125, 59.87 , 61.315, 54.787, 56.175, 440074)]

I want to make this as pandas data frame and add column name ,using the for loop this is achieved with desired output ,however how to do this without for loop directly using pandas built in resources and how to store this is in pandas object.

for row in history:
    print("{0:s}, {1:,.5f}, {2:,.5f}, {3:,.5f}, {4:,.5f}, {5:d}".format(
    pd.to_datetime(str(row['Date'])).strftime(date_format), row['BidOpen'], row['BidHigh'],row['BidLow'], row['BidClose'], row['Volume']))

output : Here T in between the Date and Time removed and float ,decimal also take care .If not other solution how this can be stored in pandas object.

Date, BidOpen, BidHigh, BidLow, BidClose, Volume
13.10.2018 21:00:00, 71.45700, 72.67500, 68.45000, 69.25200, 507708
20.10.2018 21:00:00, 69.25200, 69.80600, 65.72000, 67.68500, 389174
27.10.2018 21:00:00, 67.68500, 67.92400, 62.61000, 62.85500, 454709
03.11.2018 21:00:00, 62.85500, 64.11500, 59.24400, 59.81500, 858696
10.11.2018 22:00:00, 59.81500, 61.26200, 54.73200, 56.12500, 440074

Answer 1

This gives the correct output

df = pd.DataFrame(history, columns=['Date', 'BidOpen', 'BidHigh','BidLow', 'BidClose', 'AskOpen', 'AskHigh', 'AskLow', 'AskClose', 'Volume'])

Here the column name can be of any name.