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Compare naive and tz-aware Values

Explore the differences between naive and timezone-aware timestamps in pandas. Learn why comparing these two types raises exceptions, how to localize naive timestamps, and convert tz-aware timestamps between time zones. This lesson helps you handle datetime data effectively and avoid common pitfalls when working with pandas timestamps.

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Try it yourself

Try executing the code below to see the result.

Python 3.8
import pandas as pd
s1 = pd.to_datetime([
'2020-01-01T00:00:00+00:00',
'2020-02-02T00:00:00+00:00',
'2020-03-03T00:00:00+00:00',
])
s2 = pd.Series([
pd.Timestamp(2020, 1, 1),
pd.Timestamp(2020, 2, 2),
pd.Timestamp(2020, 3, 3),
])
print(s1 == s2)
pd.to_datetime(df['timestamp'], unit='s')

Explanation

In pandas and Python, there is one Timestamp or datetime type. However, that one type is divided into these two subtypes:

  1. naive
  2. tz-aware
...