Я хочу преобразовать данные pandas в дату и время - PullRequest
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Я хочу преобразовать данные pandas в дату и время

0 голосов
/ 20 апреля 2020 
names=['Ticker','Date','Time','open','high','low','close','Volume']
havellsdata = pd.read_csv('C:\\Users\\nEW u\Desktop\havellsjuly2015.csv',names=names,index_col= ' 
Ticker'])
k=havellsdata['high']-havellsdata['open']
havellsdata.insert(6,'openhighcheck',k)
havellsdata
#havellsdata[15]

    Date    Time    open    high    low close   openhighcheck   Volume
Ticker                              
HAVELLS 20150703    09:16:00    287.90  287.90  285.00  285.90  0.00    2978
HAVELLS 20150703    09:17:00    286.00  286.95  284.70  286.95  0.95    2684
HAVELLS 20150703    09:18:00    287.00  287.55  285.90  287.15  0.55    3717
HAVELLS 20150703    09:19:00    287.40  287.40  286.75  286.75  0.00    1451
HAVELLS 20150703    09:20:00    287.00  287.15  286.25  286.60  0.15    2721
HAVELLS 20150703    09:21:00    286.40  286.45  285.70  285.95  0.05    6084
HAVELLS 20150703    09:22:00    286.25  286.30  286.00  286.25  0.05    3466
HAVELLS 20150703    09:23:00    285.90  286.95  285.90  286.50  1.05    3831
HAVELLS 20150703    09:24:00    287.25  287.80  286.95  287.80  0.55    5686
HAVELLS 20150703    09:25:00    288.00  288.10  287.60  288.00  0.10    2844
HAVELLS 20150703    09:26:00    287.95  288.10  287.50  288.00  0.15    3149
HAVELLS 20150703    09:27:00    288.10  288.10  287.15  287.40  0.00    2216
HAVELLS 20150703    09:28:00    287.35  288.00  287.15  287.15  0.65    2511
HAVELLS 20150703    09:29:00    287.25  287.25  286.65  286.80  0.00    2744
HAVELLS 20150703    09:30:00    287.10  287.10  286.75  287.00  0.00    1588
HAVELLS 20150703    09:31:00    286.85  287.00  286.65  286.95  0.15    652
HAVELLS 20150703    09:32:00    286.85  286.90  286.75  286.75  0.05    481
HAVELLS 20150703    09:33:00    286.75  286.90  286.75  286.85  0.15    664
HAVELLS 20150703    09:34:00    286.90  287.00  286.75  287.00  0.10    608
HAVELLS 20150703    09:35:00    287.20  287.20  287.00  287.00  0.00    467
HAVELLS 20150703    09:36:00    287.00  287.15  286.70  286.70  0.15    2505
HAVELLS 20150703    09:37:00    286.50  287.40  286.00  287.40  0.90    4426
HAVELLS 20150703    09:38:00    287.40  287.65  286.45  286.75  0.25    5032
HAVELLS 20150703    09:39:00    286.65  288.25  286.65  288.05  1.60    5384
HAVELLS 20150703    09:40:00    288.05  288.50  287.80  287.80  0.45    8018
HAVELLS 20150703    09:41:00    287.70  287.70  286.45  287.40  0.00    9697
HAVELLS 20150703    09:42:00    287.55  287.55  287.05  287.10  0.00    1113
HAVELLS 20150703    09:43:00    287.30  287.45  287.00  287.45  0.15    2392
HAVELLS 20150703    09:44:00    287.65  287.65  287.05  287.10  0.00    857
HAVELLS 20150703    09:45:00    287.35  287.35  286.75  287.15  0.00    3159
... ... ... ... ... ... ... ... ...
HAVELLS 20150720    15:01:00    310.40  310.65  310.35  310.55  0.25    2222
HAVELLS 20150720    15:02:00    310.50  310.70  310.50  310.70  0.20    1250
HAVELLS 20150720    15:03:00    310.70  310.70  310.45  310.60  0.00    1667
HAVELLS 20150720    15:04:00    310.60  310.70  310.45  310.50  0.10    4395
HAVELLS 20150720    15:05:00    310.70  310.70  310.40  310.65  0.00    2580
HAVELLS 20150720    15:06:00    310.65  310.65  310.15  310.30  0.00    3864
HAVELLS 20150720    15:07:00    310.25  310.55  310.25  310.50  0.30    2275
HAVELLS 20150720    15:08:00    310.50  310.50  309.85  309.95  0.00    15803
HAVELLS 20150720    15:09:00    309.95  310.00  309.50  309.90  0.05    8086
HAVELLS 20150720    15:10:00    309.85  309.90  309.55  309.65  0.05    3743
HAVELLS 20150720    15:11:00    309.65  309.70  309.50  309.50  0.05    7241
HAVELLS 20150720    15:12:00    309.55  309.70  309.30  309.35  0.15    3823
HAVELLS 20150720    15:13:00    309.35  309.50  309.25  309.50  0.15    6280
HAVELLS 20150720    15:14:00    309.60  309.70  309.25  309.50  0.10    9540
HAVELLS 20150720    15:15:00    309.50  309.65  309.25  309.50  0.15    5264
HAVELLS 20150720    15:16:00    309.50  309.65  309.25  309.60  0.15    5783
HAVELLS 20150720    15:17:00    309.40  310.00  309.25  309.80  0.60    6529
HAVELLS 20150720    15:18:00    309.85  310.45  309.75  310.30  0.60    15943
HAVELLS 20150720    15:19:00    310.35  310.80  310.10  310.80  0.45    3616
HAVELLS 20150720    15:20:00    310.75  310.85  310.40  310.50  0.10    6405
HAVELLS 20150720    15:21:00    310.35  310.75  310.15  310.40  0.40    7800
HAVELLS 20150720    15:22:00    310.35  310.65  310.10  310.40  0.30    10439
HAVELLS 20150720    15:23:00    310.50  310.65  310.05  310.40  0.15    4467
HAVELLS 20150720    15:24:00    310.40  310.65  310.35  310.65  0.25    7938
HAVELLS 20150720    15:25:00    310.65  310.65  310.50  310.65  0.00    3290
HAVELLS 20150720    15:26:00    310.65  310.65  310.50  310.60  0.00    4851
HAVELLS 20150720    15:27:00    310.60  310.80  310.55  310.55  0.20    3662
HAVELLS 20150720    15:28:00    310.60  310.85  310.55  310.60  0.25    3874
HAVELLS 20150720    15:29:00    310.60  310.90  310.60  310.90  0.30    13271
HAVELLS 20150720    15:30:00    310.90  311.00  310.00  311.00  0.10    8751

1 Ответ

2 голосов
/ 20 апреля 2020

IIU C: 

havellsdata['Datetime'] = pd.to_datetime(havellsdata['Date'].apply(str) + ' ' + havellsdata['Time'])
havellsdata = havellsdata.set_index('Datetime')

Пример: 

In [1723]: df                                                                                                                                                                                               
Out[1723]: 
       Date      Time
0  20150703  09:16:00
1  20150703  09:17:00
2  20150703  09:18:00

In [1725]: df['Datetime'] = pd.to_datetime(df['Date'].apply(str) + ' ' + df['Time'])

In [1727]: df = df.set_index('Datetime')                                                                                                                                                                    

In [1728]: df                                                                                                                                                                                               
Out[1728]: 
                         Date      Time
Datetime                               
2015-07-03 09:16:00  20150703  09:16:00
2015-07-03 09:17:00  20150703  09:17:00
2015-07-03 09:18:00  20150703  09:18:00
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