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("\nFrom UTC to America/Los_Angeles:")
dtt = dtt.tz_convert('America/Los_Angeles')

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:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Pandas program to create a conversion between strings and datetime.
Next: Write a Pandas program to get the average mean of the UFO (unidentified flying object) sighting was reported.

What is the difficulty level of this exercise?

Follow us on Facebook and Twitter for latest update.

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))


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")


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)


2 4 6
p q r