Code With MEMO

Every other day of the year is for the men, but today is Women's. Happy Women's Day❤️

💡 Typical Django Development Flow 1. Create project 2. Create app 3. Add app to settings 4. Create models 5. Run migrations 6. Create views 7. Add URLs 8. Create templates 9. Connect database and logic

Useful Python Scripts for Automated Data Quality Checks 📌 Introduction Data quality issues are pervasive and can lead to incorrect business decisions, broken analysis, and pipeline failures. Manual data validation is time-consuming and prone to errors, making it essential to automate the process. This article discusses five useful Python scripts for automated data quality checks, addressing common issues such as missing data, invalid data types, duplicate records, outliers, and cross-field inconsistencies. 📌 Main Content / Discussion The five Python scripts are designed to handle specific data quality issues.

import pandas as pd
import numpy as np

# Example 1: Missing data analyzer script
def analyze_missing_data(df):
    missing_data = df.isnull().sum()
    return missing_data

# Example 2: Data type validator script
def validate_data_types(df, schema):
    for column, dtype in schema.items():
        if df[column].dtype != dtype:
            print(f"Invalid data type for column {column}")
    return df

# Example 3: Duplicate record detector script
def detect_duplicates(df):
    duplicates = df.duplicated().sum()
    return duplicates

# Example 4: Outlier detection script
def detect_outliers(df, column):
    Q1 = df[column].quantile(0.25)
    Q3 = df[column].quantile(0.75)
    IQR = Q3 - Q1
    lower_bound = Q1 - 1.5 * IQR
    upper_bound = Q3 + 1.5 * IQR
    outliers = df[(df[column] < lower_bound) | (df[column] > upper_bound)]
    return outliers

# Example 5: Cross-field consistency checker script
def check_cross_field_consistency(df):
    # Check for temporal consistency
    df['start_date'] = pd.to_datetime(df['start_date'])
    df['end_date'] = pd.to_datetime(df['end_date'])
    inconsistencies = df[df['start_date'] > df['end_date']]
    return inconsistencies

These scripts can be used to identify and address data quality issues, ensuring that the data is accurate, complete, and consistent.

always learning new thing is challenging, but it's really good vibe🎉

Have a nice Saturday ❤

I've completed a RAG-based full stack AI . It's named Medi, a smart medical assistant chatbot. I've tested it thoroughly to ensure that Medi won't hallucinate any concepts , it seems really smart! 🔥 Check out the demo video and feel free to leave your comments. I'll share the live link after testing it again and again in various ways.. @codewithmemo @codewithmemo

Different databases ChromaDB ✅ Open-source, runs locally Simple Python API Metadata filtering HNSW indexing LangChain integration Pinecone ✅ Fully managed, zero maintenance Real-time updates Automatic scaling REST API + SDKs High availability MySQL ✅ ACID compliant Mature ecosystem Great for structured data Primary-replica replication Full-text search PostgreSQL ✅ ACID compliant Advanced indexing (partial, expression) JSON support pgvector extension for vectors MVCC concurrency MongoDB ✅ Schema-less documents Horizontal scaling (sharding) Replica sets for HA Atlas vector search (cloud) Flexible querying

🎙 PODCAST TALK SHOW: Experience Sharing We’re officially back! 🚀 Our weekly podcast/workshop series resumes this semester with powerful conversations and real-world insights. 📅 Date: March 4, 2026 ⏰ Time: 8:00 PM 🎤 Host: Mihret Daniel 📍 Live on our Telegram Channel 👤 Guest Speaker: Bemhreth Gezahegn (Co-founder of Gebeta Maps) Join us as we dive into the journey of building impactful tech solutions, lessons from entrepreneurship, and practical insights for aspiring innovators. Don’t miss it — set your reminder and tune in live! #InformationSystemsHub #WeeklyPodcast #BemhrethGezahegn Telegram|LinkedIn|YouTube | Tiktok |

Looks good, guys🙌

🌐 Web Design Tools & Their Use Cases 🎨🌐 🔹 Figma ➜ Collaborative UI/UX prototyping and wireframing for teams 🔹 Adobe XD ➜ Interactive design mockups and user experience flows 🔹 Sketch ➜ Vector-based interface design for Mac users and plugins 🔹 Canva ➜ Drag-and-drop graphics for quick social media and marketing assets 🔹 Adobe Photoshop ➜ Image editing, compositing, and raster graphics manipulation 🔹 Adobe Illustrator ➜ Vector illustrations, logos, and scalable icons 🔹 InVision Studio ➜ High-fidelity prototyping with animations and transitions 🔹 Webflow ➜ No-code visual website building with responsive layouts 🔹 Framer ➜ Interactive prototypes and animations for advanced UX 🔹 Tailwind CSS ➜ Utility-first styling for custom, responsive web designs 🔹 Bootstrap ➜ Pre-built components for rapid mobile-first layouts 🔹 Material Design ➜ Google's UI guidelines for consistent Android/web interfaces 🔹 Principle ➜ Micro-interactions and motion design for app prototypes 🔹 Zeplin ➜ Design handoff to developers with specs and assets 🔹 Marvel ➜ Simple prototyping and user testing for early concepts

this is how your assistants and chatbots work

have a nice friday fam

web app👌

Do you think about. There is high performance difference when the system build in different frameworks.