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Hello everyone Today'd update Day 8/100 • Worked on a mini Zomato project • Performed basic data analysis on the dataset • Explored insights using Python • Created visualizations using Matplotlib • Revised important NumPy concepts and functions Focu

Hello everyone day 9/100 Today’s Study Update 📘 • Learned Python exception handling • Covered try, except, else, and finally blocks • Understood how to handle runtime errors properly • Started with Streamlit basics • Explored how to build simple int

Essential Python Topics for Data Analysts 😄👇 - Data Structures: Lists, Dictionaries, Sets, and Tuples. - NumPy: Array manipulation for numerical operations. - Pandas: Data manipulation and analysis with DataFrame. - Data Cleaning: Handling missin

I know the basics of python language like functions, file handling, stack, etc what should I learn in python to get the fastest internship or job as freshers

I want to learn C in such a way that I'll be able to get to C++ faster without botching any concepts. I'm done till pointers and structures with fundamentals out of the way, yet to do file-handling and importing code from other files. What do I do?

Day 10 of learning data science as a beginner Topic: data analysis using pandas Pandas is one of the python's most famous open source library and it is used for a variety of tasks like data manipulation, data cleaning and for analysis of data. Pand

I’ve been strengthening my data analysis and visualization fundamentals by building multiple end-to-end analytical projects using Python, Pandas, Matplotlib, and Seaborn. Projects worked on: Video Game Market Analysis Football Performance Analysis (

Day 11 of learning Data science as a beginner Topic: creating data structure In my previous post I discussed about the difference between panda's series and data frames we typically use data frames more often as compared to series There are a lot

Day 02 - - Learned about Pydantic in Python after exploring asyncio yesterday. It felt easier to understand because of my familiarity with other Python libraries and data validation concepts. - In JavaScript, studied callbacks and promises to under

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