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
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