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Pandas: Sequences of fixed-frequency dates and time spans

Pandas Time Series: Exercise-23 with Solution

Write a Pandas program to generate sequences of fixed-frequency dates and time spans intervals.

Sample Solution:

Python Code :

import pandas as pd
print("Sequences of fixed-frequency dates and time spans (1 H):\n")
r1 = pd.date_range('2030-01-01', periods=10, freq='H')
print(r1)
print("\nSequences of fixed-frequency dates and time spans (3 H):\n")
r2 = pd.date_range('2030-01-01', periods=10, freq='3H')
print(r2)

Sample Output:

Sequences of fixed-frequency dates and time spans (1 H):

DatetimeIndex(['2030-01-01 00:00:00', '2030-01-01 01:00:00',
               '2030-01-01 02:00:00', '2030-01-01 03:00:00',
               '2030-01-01 04:00:00', '2030-01-01 05:00:00',
               '2030-01-01 06:00:00', '2030-01-01 07:00:00',
               '2030-01-01 08:00:00', '2030-01-01 09:00:00'],
              dtype='datetime64[ns]', freq='H')

Sequences of fixed-frequency dates and time spans (3 H):

DatetimeIndex(['2030-01-01 00:00:00', '2030-01-01 03:00:00',
               '2030-01-01 06:00:00', '2030-01-01 09:00:00',
               '2030-01-01 12:00:00', '2030-01-01 15:00:00',
               '2030-01-01 18:00:00', '2030-01-01 21:00:00',
               '2030-01-02 00:00:00', '2030-01-02 03:00:00'],
              dtype='datetime64[ns]', freq='3H')

Python Code Editor:


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Next: Write a Pandas program to generate time series combining day and intraday offsets intervals.

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Merging two dicts in Python 3.5+ with a single expression

Example:

# How to merge two dictionaries
# in Python 3.5+

x = {'p': 1, 'q': 3}
y = {'q': 5, 'r': 8}

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z
{'r': 4, 'p': 1, 'q': 3}

z = dict(x, **y)
print(z)

Output:

{'p': 1, 'q': 5, 'r': 8}