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Pandas Datetime: Manipulate and convert date times with timezone information

Pandas Datetime: Exercise-16 with Solution

Write a Pandas program to manipulate and convert date times with timezone information.

Sample Solution :

Python Code :

import pandas as pd
dtt = pd.date_range('2018-01-01', periods=3, freq='H')
dtt = dtt.tz_localize('UTC')
print(dtt)
print("\nFrom UTC to America/Los_Angeles:")
dtt = dtt.tz_convert('America/Los_Angeles')
print(dtt)

Sample Output:

DatetimeIndex(['2018-01-01 00:00:00+00:00', '2018-01-01 01:00:00+00:00',
               '2018-01-01 02:00:00+00:00'],
              dtype='datetime64[ns, UTC]', freq='H')

From UTC to America/Los_Angeles:
DatetimeIndex(['2017-12-31 16:00:00-08:00', '2017-12-31 17:00:00-08:00',
               '2017-12-31 18:00:00-08:00'],
              dtype='datetime64[ns, America/Los_Angeles]', freq='H')

Python Code Editor:

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Python: Tips of the Day

F strings:

It is a common practice to add variables inside strings. F strings are by far the coolest way of doing it. To appreciate the f strings more, let's first perform the operation with the format function.

name = 'Owen'
age = 25
print("{} is {} years old".format(name, age))

Output:

Owen is 25 years old

We specify the variables that go inside the curly braces by using the format function at the end. F strings allow for specifying the variables inside the string.

name = 'Owen'
age = 25
print(f"{name} is {age} years old")

Output:

Owen is 25 years old

F strings are easier to follow and type. Moreover, they make the code more readable.

A, B, C = {2, 4, 6}
print(A, B, C)
A, B, C = ['p', 'q', 'r']
print(A, B, C)

Output:

2 4 6
p q r