Working With time Series - date_range() Method in Python Pandas
*It 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
# Generate 8 Dates
Input - pd.date_range(start='1/1/2019', end='1/08/2019')
Input - pd.date_range(start='1/1/2019', periods=8)
Input - pd.date_range(end='1/1/2019', periods=8)
Input - pd.date_range(start='1/1/2019', end='1/20/2019', periods=10)
Input - pd.date_range(start='1/1/2019', periods=12, freq='B')
# How to set timezone
Input - pd.date_range(start='1/1/2019', periods=22, tz='Asia/Kolkata')
dates = pd.date_range(start='1/1/2020', end='1/10/2020')
dates
df.set_index(dates, inplace=True)
df
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 |