Python datetime with US Eastern timezone using zoneinfo

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

Having a tough time remembering #Python strptime vs. strftime? - The "p" (strptime) is for parsing, getting a datetime from a string - The "f" (strftime) is for formatting, getting a string from a datetime For help remembering the format codes, turn to https://buff.ly/oEdYGMI !

#Python includes a handy built-in function called `exec()` that can execute arbitrary code Never expose your APIs to this or the related `eval()` function since that could allow people to harm your computer!

Dashboard with DASH. Using a series of synthetic data, I created this dashboard using the DASH library in Python, but I must admit that it's easier to work with the Shainy library in R. Which do you prefer? The advantages of using these two libraries I just mentioned are that they are completely free and that you can also share and interact with the image in a professional meeting without having to pay a single cent. This is much more expensive with other solutions. #DataVisualization #PythonProgramming #BusinessIntelligence

Want to round #Python #Pandas datetimes? You have 3 options: - dt.floor — earlier - dt.ceil - later - dt.round — nearest For example: s.dt.floor('3h') # previous multiple-of-3 hour s.dt.ceil('15m') # next 15-minute block s.dt.round('1D') # nearest 1 day

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

Reading a CSV into #Python #Pandas, and want a column to be treated as datetime values? Use parse_dates: df = pd.read_csv(filename, parse_dates=['x', 'y']) Bonus: The PyArrow engine often (not always) parses columns that look like dates.

📊 Python Program: Find Maximum Value ```python numbers = [10, 25, 5, 40, 15] max_value = max(numbers) print("Max Value:", max_value) ``` 💡 Real use: ✔ Finding peak CPU usage ✔ Monitoring data #Python #DataHandling

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')

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?