Working With time Series - date_range() Method in Python Pandas
This method is used to generate a range of date values.
pandas.date_range(start=None, end=None, periods=None, freq=None, tz=None, normalize=False, name=None, closed=None, **kwargs)
The Sample Code
With start and end parameters
DatetimeIndex(['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04',
'2019-01-05', '2019-01-06', '2019-01-07', '2019-01-08'],
dtype='datetime64[ns]', freq='D')
DatetimeIndex(['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04',
'2019-01-05', '2019-01-06', '2019-01-07', '2019-01-08'],
dtype='datetime64[ns]', freq='D')
DatetimeIndex(['2018-12-25', '2018-12-26', '2018-12-27', '2018-12-28',
'2018-12-29', '2018-12-30', '2018-12-31', '2019-01-01'],
dtype='datetime64[ns]', freq='D')
DatetimeIndex(['2019-01-01 00:00:00', '2019-01-03 02:40:00',
'2019-01-05 05:20:00', '2019-01-07 08:00:00',
'2019-01-09 10:40:00', '2019-01-11 13:20:00',
'2019-01-13 16:00:00', '2019-01-15 18:40:00',
'2019-01-17 21:20:00', '2019-01-20 00:00:00'],
dtype='datetime64[ns]', freq=None)
DatetimeIndex(['2019-01-01', '2019-01-02', '2019-01-03', '2019-01-04',
'2019-01-07', '2019-01-08', '2019-01-09', '2019-01-10',
'2019-01-11', '2019-01-14', '2019-01-15', '2019-01-16'],
dtype='datetime64[ns]', freq='B')
DatetimeIndex(['2019-01-01 00:00:00+05:30', '2019-01-02 00:00:00+05:30',
'2019-01-03 00:00:00+05:30', '2019-01-04 00:00:00+05:30',
'2019-01-05 00:00:00+05:30', '2019-01-06 00:00:00+05:30',
'2019-01-07 00:00:00+05:30', '2019-01-08 00:00:00+05:30',
'2019-01-09 00:00:00+05:30', '2019-01-10 00:00:00+05:30',
'2019-01-11 00:00:00+05:30', '2019-01-12 00:00:00+05:30',
'2019-01-13 00:00:00+05:30', '2019-01-14 00:00:00+05:30',
'2019-01-15 00:00:00+05:30', '2019-01-16 00:00:00+05:30',
'2019-01-17 00:00:00+05:30', '2019-01-18 00:00:00+05:30',
'2019-01-19 00:00:00+05:30', '2019-01-20 00:00:00+05:30',
'2019-01-21 00:00:00+05:30', '2019-01-22 00:00:00+05:30'],
dtype='datetime64[ns, Asia/Kolkata]', freq='D')
DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04',
'2020-01-05', '2020-01-06', '2020-01-07', '2020-01-08',
'2020-01-09', '2020-01-10'],
dtype='datetime64[ns]', freq='D')
|
meantemp |
humidity |
wind_speed |
meanpressure |
| 2020-01-01 |
15.913043 |
85.869565 |
2.743478 |
59.000000 |
| 2020-01-02 |
18.500000 |
77.222222 |
2.894444 |
1018.277778 |
| 2020-01-03 |
17.111111 |
81.888889 |
4.016667 |
1018.333333 |
| 2020-01-04 |
18.700000 |
70.050000 |
4.545000 |
1015.700000 |
| 2020-01-05 |
18.388889 |
74.944444 |
3.300000 |
1014.333333 |
| 2020-01-06 |
19.318182 |
79.318182 |
8.681818 |
1011.772727 |
| 2020-01-07 |
14.708333 |
95.833333 |
10.041667 |
1011.375000 |
| 2020-01-08 |
15.684211 |
83.526316 |
1.950000 |
1015.550000 |
| 2020-01-09 |
14.571429 |
80.809524 |
6.542857 |
1015.952381 |
