Python str.strip() Function Removes Leading/Trailing Characters

A file you're loading into #Python #Pandas uses weird strings for missing values? Use the na_values parameter in read_* methods: pd.read_csv(f, na_values='.') pd.read_csv(f, na_values=['.', '*']) # multiple pd.read_csv(f, na_values={'a':'.', 'b':'*'}) # per column

#Python #Pandas astype() returns a NEW series — it doesn't modify in place: s = s.astype('int8') s = s.astype('float64') s = s.astype(str) Watch out: You'll get a TypeError if any value can't be converted.

Does your #Python #Pandas column contain repeated strings? Turn it into a 'category' series (like an enum) to save memory: df['c'].memory_usage() # 124,957,472 df['c'] = (df['c'].astype('category')) df['c'].memory_usage() 12,496,555 That's right — 90% less memory!

A tiny Python trick I learned while using Claude Code While building an app with Claude Code, I noticed it repeatedly using a neat Python pattern I had somehow missed for years. d = {'A': 1, 'B': 2} e = {**d, 'A': 2} print(e) # {'A': 2, 'B': 2} This looks trivial. But the idea behind it is powerful: start from a default dictionary and selectively override fields. It’s a small trick, but it creates a very clean pattern for: ✅ Generating test cases ✅ Configuration overrides ✅ Scenario simulation Sometimes the most useful ideas are not big algorithms. They are small patterns that quietly make code cleaner. #pythonic #claudecode #claude #software #pythontricks #python

Just built a simple way to add your own custom trained chatbot to any website in just three lines of code. Upload your PDFs, and the system turns them into a smart assistant that understands your content and answers questions instantly. Powered by FastAPI, ChromaDB, Groq with Llama 3.1, and Sentence Transformers. Code is open on GitHub under: https://lnkd.in/g4WUJf4Q #SoftwareEngineering #FastAPI #MachineLearning #VectorDatabase #Groq #Python #OpenSource

LeetCode #100 – Same Tree | Python Implementation I implemented a recursive DFS approach that simultaneously traverses both trees, comparing nodes at each step. Core Insight: Tree equality decomposes into three checks: both null (base case), structural equality, and value equality. Recursion naturally handles the "and both subtrees match" requirement. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinaryTree #Recursion #DFS #CodingInterview #SoftwareEngineering

A classic #Python mistake: What's wrong with this code? s = 'What's your name?' The string uses '' as delimiters. But it also contains a ' inside. Solutions: s = "What's your name?" # Delimit with "" s = 'What\'s your name?' # Escape literal ' with \

The built-in #Revit warnings tool is fairly frustrating- it's compact but displaying an element with a warning requires multiple clicks. In #pyRevitChallenge day 8 we built the Warning Snitch - finding all the warnings in the model, filtering them by warning type, associating the element category and host level (if relevant) then displaying on a clickable table (as well as optionally a CSV export). I can see this is a tool I'm going to get some use out of. #revitAPI #pyRevit #python #AECcoding

Day 54 of 365 Days of code 1) Capacity to Ship Packages Within D Days Approach: Binary search 1)set low = max(weights) 2) high= low*sum(weights) 3) perform the below steps until low<=high condition fails i) mid=low+(high-low)//2;res=0 ii) set w = mid and initialize day=1 iii) iterate through the loop and perform the stuff i put in screenshot (ahh life hurts :") ) iv) if the day <= days: set res=mid ; set high=mid-1 v) else low=mid+1 4) return res #365daysOfCode #NeetCode  #leetcode  #DSA  #python #LeetCode #ProblemSolving  #Algorithms #365dayschallenge

Python A/B Test Tools Compared: tea-tasting Pingouin vs statsmodels and SciPy 📌 Python’s A/B testing scene just got more organized-tea-tasting stands out with a sleek, experiment-focused API that auto-calculates effect sizes, confidence intervals, and p-values in one go. While statsmodels and SciPy offer deep stats power, tea-tasting cuts through the noise for teams craving speed and clarity. No more manual variance calculations or boilerplate code-just clean, production-ready insights. 🔗 Read more: https://lnkd.in/d88Xhtxe #TeaTasting #Pingouin #Statsmodels #Scipy #ABtesting