import pandas as pd
data = pd.read_csv("AAPL.csv", index_col=0, parse_dates=True)
data.head()
Open | High | Low | Close | Adj Close | Volume | |
---|---|---|---|---|---|---|
Date | ||||||
2020-01-27 | 77.514999 | 77.942497 | 76.220001 | 77.237503 | 76.576187 | 161940000 |
2020-01-28 | 78.150002 | 79.599998 | 78.047501 | 79.422501 | 78.742477 | 162234000 |
2020-01-29 | 81.112503 | 81.962502 | 80.345001 | 81.084999 | 80.390747 | 216229200 |
2020-01-30 | 80.135002 | 81.022499 | 79.687500 | 80.967499 | 80.274246 | 126743200 |
2020-01-31 | 80.232498 | 80.669998 | 77.072502 | 77.377502 | 76.714989 | 199588400 |
data.dtypes
Open float64 High float64 Low float64 Close float64 Adj Close float64 Volume int64 dtype: object
data.index
DatetimeIndex(['2020-01-27', '2020-01-28', '2020-01-29', '2020-01-30', '2020-01-31', '2020-02-03', '2020-02-04', '2020-02-05', '2020-02-06', '2020-02-07', ... '2021-01-12', '2021-01-13', '2021-01-14', '2021-01-15', '2021-01-19', '2021-01-20', '2021-01-21', '2021-01-22', '2021-01-25', '2021-01-26'], dtype='datetime64[ns]', name='Date', length=253, freq=None)
data.loc['2020-01-27']
Open 7.751500e+01 High 7.794250e+01 Low 7.622000e+01 Close 7.723750e+01 Adj Close 7.657619e+01 Volume 1.619400e+08 Name: 2020-01-27 00:00:00, dtype: float64
data.loc['2021-01-01':]
Open | High | Low | Close | Adj Close | Volume | |
---|---|---|---|---|---|---|
Date | ||||||
2021-01-04 | 133.520004 | 133.610001 | 126.760002 | 129.410004 | 129.410004 | 143301900 |
2021-01-05 | 128.889999 | 131.740005 | 128.429993 | 131.009995 | 131.009995 | 97664900 |
2021-01-06 | 127.720001 | 131.050003 | 126.379997 | 126.599998 | 126.599998 | 155088000 |
2021-01-07 | 128.360001 | 131.630005 | 127.860001 | 130.919998 | 130.919998 | 109578200 |
2021-01-08 | 132.429993 | 132.630005 | 130.229996 | 132.050003 | 132.050003 | 105158200 |
2021-01-11 | 129.190002 | 130.169998 | 128.500000 | 128.979996 | 128.979996 | 100620900 |
2021-01-12 | 128.500000 | 129.690002 | 126.860001 | 128.800003 | 128.800003 | 91951100 |
2021-01-13 | 128.759995 | 131.449997 | 128.490005 | 130.889999 | 130.889999 | 88636800 |
2021-01-14 | 130.800003 | 131.000000 | 128.759995 | 128.910004 | 128.910004 | 90221800 |
2021-01-15 | 128.779999 | 130.220001 | 127.000000 | 127.139999 | 127.139999 | 111598500 |
2021-01-19 | 127.779999 | 128.710007 | 126.940002 | 127.830002 | 127.830002 | 90757300 |
2021-01-20 | 128.660004 | 132.490005 | 128.550003 | 132.029999 | 132.029999 | 104319500 |
2021-01-21 | 133.800003 | 139.669998 | 133.589996 | 136.869995 | 136.869995 | 120529500 |
2021-01-22 | 136.279999 | 139.850006 | 135.020004 | 139.070007 | 139.070007 | 114459400 |
2021-01-25 | 143.070007 | 145.089996 | 136.539993 | 142.919998 | 142.919998 | 157282400 |
2021-01-26 | 143.600006 | 144.300003 | 141.369995 | 142.080002 | 142.080002 | 50388565 |
data.loc[:'2020-07-01']
Open | High | Low | Close | Adj Close | Volume | |
---|---|---|---|---|---|---|
Date | ||||||
2020-01-27 | 77.514999 | 77.942497 | 76.220001 | 77.237503 | 76.576187 | 161940000 |
2020-01-28 | 78.150002 | 79.599998 | 78.047501 | 79.422501 | 78.742477 | 162234000 |
2020-01-29 | 81.112503 | 81.962502 | 80.345001 | 81.084999 | 80.390747 | 216229200 |
2020-01-30 | 80.135002 | 81.022499 | 79.687500 | 80.967499 | 80.274246 | 126743200 |
2020-01-31 | 80.232498 | 80.669998 | 77.072502 | 77.377502 | 76.714989 | 199588400 |
... | ... | ... | ... | ... | ... | ... |
2020-06-25 | 90.175003 | 91.250000 | 89.392502 | 91.209999 | 90.889038 | 34380600 |
2020-06-26 | 91.102501 | 91.330002 | 88.254997 | 88.407501 | 88.096405 | 51314200 |
2020-06-29 | 88.312500 | 90.542503 | 87.820000 | 90.445000 | 90.126732 | 32661500 |
2020-06-30 | 90.019997 | 91.495003 | 90.000000 | 91.199997 | 90.879066 | 35055800 |
2020-07-01 | 91.279999 | 91.839996 | 90.977501 | 91.027496 | 90.707176 | 27684300 |
110 rows × 6 columns
data.iloc[0]
Open 7.751500e+01 High 7.794250e+01 Low 7.622000e+01 Close 7.723750e+01 Adj Close 7.657619e+01 Volume 1.619400e+08 Name: 2020-01-27 00:00:00, dtype: float64
data.loc['2020-01-27']
Open 7.751500e+01 High 7.794250e+01 Low 7.622000e+01 Close 7.723750e+01 Adj Close 7.657619e+01 Volume 1.619400e+08 Name: 2020-01-27 00:00:00, dtype: float64
data.iloc[-1]
Open 1.436000e+02 High 1.443000e+02 Low 1.413700e+02 Close 1.420800e+02 Adj Close 1.420800e+02 Volume 5.038856e+07 Name: 2021-01-26 00:00:00, dtype: float64
data.tail()
Open | High | Low | Close | Adj Close | Volume | |
---|---|---|---|---|---|---|
Date | ||||||
2021-01-20 | 128.660004 | 132.490005 | 128.550003 | 132.029999 | 132.029999 | 104319500 |
2021-01-21 | 133.800003 | 139.669998 | 133.589996 | 136.869995 | 136.869995 | 120529500 |
2021-01-22 | 136.279999 | 139.850006 | 135.020004 | 139.070007 | 139.070007 | 114459400 |
2021-01-25 | 143.070007 | 145.089996 | 136.539993 | 142.919998 | 142.919998 | 157282400 |
2021-01-26 | 143.600006 | 144.300003 | 141.369995 | 142.080002 | 142.080002 | 50388565 |