Use day_name() instead of dt.day_of_week in Pandas

Want to set the time on a #Python #Pandas series of datetimes to midnight? Use dt.normalize: df['x'].dt.normalize() You get back series of datetime values, but all times are 00:00:00.

Generate a #Python #Pandas DatetimeIndex of datetime values with pd.date_range: pd.date_range(start='2026-03-01', end='2026-05-01', periods=10) This returns a 10-element series with evenly-spaced datetime values in that period.

Dunder methods (aka “double underscore” or “magic methods”) are what make Python objects behave like built-ins. From __init__ for initialization to __str__ for readable output and __add__ for operator overloading — this is where OOP in Python gets powerful. Learn these, and your classes stop being basic… and start being Pythonic. #Python #PythonProgramming #DunderMethods #MagicMethods #OOP #LearnPython #CodingJourney #SoftwareDevelopment #PythonTips #DeveloperLife # AadyaTechnovate

Generate a #Python #Pandas DatetimeIndex of datetime values, specifying the frequency, by passing freq and a code: pd.date_range(start='2026-03-01', end='2026-05-01', freq='8h') This returns a 184-element DatetimeIndex with evenly-spaced datetime values in that period.

Have a #Python #Pandas series with datetime values, and want all those until now? Compare with pd.Timestamp.now(): df.loc[ pd.col('when') < pd.Timestamp.now() ] This returns the rows from df where the "when" column is before now.

Day 38/100 – #100DaysOfCode 🚀 Solved LeetCode #2011 – Final Value of Variable After Performing Operations (Python). Today I practiced string handling and simple iteration to compute the final value after a series of operations. Approach: 1) Initialize a variable x = 0. 2) Traverse through each operation in the list. 3) If the operation contains "++", increment x by 1. 4) Otherwise, decrement x by 1. 5) Return the final value of x. Time Complexity: O(n) Space Complexity: O(1) Simple logic but great practice for handling strings and loops 💪 #LeetCode #Python #DSA #Strings #ProblemSolving #100DaysOfCode

Day 20 | Problem-Solving Practice Today I worked on determining the number of days in a given month and year. • Implemented a basic conditional approach • Optimized the solution using a set and simplified leap year logic Focused on handling edge cases like invalid month inputs and leap years correctly. Consistency over intensity — showing up every day and improving step by step. GitHub: https://lnkd.in/g35tV9Gj #ProblemSolving #Python #LearningInPublic #Consistency

💡 Tiny Python tip that improves code clarity With a normal tuple, you have to remember what each index stands for. That knowledge lives in your head, not in the code. `namedtuple` fixes this by giving semantic meaning to each position. You still get immutability and performance, but with clear, self-documenting access. #Python #PythonProgramming #CleanCode #CodingBestPractices #CodeReadability

Want to find which time period contains a #Python #Pandas datetime? Use to_period: pd.Timestamp.now().to_period('1D') pd.Timestamp.now().to_period('6W') This returns a Pandas "Period" object, useful (among other things) for checking if two dates are within the same period.

Did you know you can use #Python's `bisect` module to do a binary search? Here's a fun example using school grade latters and matching them with grade letters: