Round Pandas Datetime in Python with dt.floor, dt.ceil, dt.round

Want to check if two #Python #Pandas datetimes are in the same month/quarter/year? Convert them both to periods, and compare with ==: date1.to_period('M') == date2.to_period('M') # same month? date1.to_period('Q') == date2.to_period('Q') # same quarter?

If a #Python string contains an ISO-formatted date, skip strptime and use datetime.fromisoformat: import datetime as dt dt.datetime.fromisoformat('2026-04-12') # returns datetime at midnight dt.datetime.fromisoformat('2026-04-12 12:34:56') # returns datetime at 12:34:56

🔄 Input & Output in Python input() → take user input print() → show output Use case: Take server name → display status Simple but powerful. #PythonBasics

Want to parse a #Python string into a datetime? Use strptime, passing (a) the string and (b) the date format spec: datetime.datetime.strptime('2026-04-01', '%Y-%m-%d') datetime.datetime.strptime('26-April-01', '%y-%B-%d') Both return datetime.datetime(2026, 4, 1, 0, 0)

Have you used #Python's `divmod()` function before? If not, `divmod()` takes two numbers as arguments and returns a tuple containing their quotient and remainder in a single operation

Want to take a #Python #Pandas series of strings, and get datetime values? Use pd.to_datetime: pd.to_datetime(df['x']) Notice: It's not a method! It's a top-level pd function. Specify a non-standard "format" with a strftime string: pd.to_datetime(df['x'], format='%d/%m/%Y')

🚀 Day 13 of My Python + DSA Journey Today’s problem focused on frequency counting 👇 ✅ Majority Element (#169) 💡 Majority Element Find the element that appears more than n/2 times 🔍 Approach: Used hashmap → counted frequency and returned element exceeding n/2 ⏱ O(n) time | O(n) space 🔥 What I learned today: • Hashmaps make counting problems simple • Frequency-based logic is very common in arrays • Early exit improves efficiency Getting faster at recognizing patterns ⚡ #Day13 #LeetCode #Python #DSA #CodingJourney #100DaysOfCode

Transitioning from pandas to Polars for data manipulation. When you are parsing massive security logs or SBOMs, the multi-threaded performance of Polars is absolutely unmatched. #DataEngineering #Python

Want a #Python datetime with a timezone? Use the "zoneinfo" module: import zoneinfo tz = zoneinfo.ZoneInfo('US/Eastern') Then pass it to the "tzinfo" keyword arg: dt = datetime.datetime(2026, 4, 1, 13, tzinfo=tz)

We missed qplot. So we built the Python equivalent for Altair. marimo turned out to be a surprisingly good environment for this project, because it was so small and visual. Implementation, tests, and docs are in one place. A build step strips out marimo before publishing, so users get plain Python. Video out now: https://lnkd.in/g47eh__f #python #openSource #altair #marimo