Epython Lab

Featured Projects in our Github Check them out : https://github.com/epythonlab

MongoDB Basics and Setup: Your First Steps with MongoDB and VS Code : https://www.youtube.com/watch?v=nm-7rM5mnYE Next we will share you how to create collections and read data. Stay tuned!!

Master MongoDB with VS Code: Step-by-Step Guide to Creating Databases, Collections, and Documents https://youtu.be/KiQKCafwMXU

Sales Forecasting Report Github Source Link Resources

Full-stack web app development full tutorial with python and flask framework https://www.youtube.com/watch?v=tbvZcyTwocA

Python is a general-purpose programming language. It can do almost all of what other languages can do with comparable, or faster, speed. It is often chosen by Data Analysts and Data Scientists for prototyping, visualization, and execution of data analyses on datasets. There’s an important question here. Plenty of other programming languages, like R, can be useful in the field of data science. Why are so many people choosing Python? One major factor is Python’s versatility. There are over 125,000 third-party Python libraries. These libraries make Python more useful for specific purposes, from the traditional (e.g. web development, text processing) to the cutting edge (e.g. AI and machine learning). For example, a biologist might use the Biopython library to aid their work in genetic sequencing. Additionally, Python has become a go-to language for data analysis. With data-focused libraries like pandas, NumPy, and Matplotlib, anyone familiar with Python’s syntax and rules can use it as a powerful tool to process, manipulate, and visualize data. #FaceMask #KeepDistancing #LearnPython #LearnDataScience Join @python4fds for more information

✅TIP Indentation is important for python programming you never miss it. Indentation refers to the spaces at the beginning of a code line. Where in other programming languages the indentation in code is for readability only, the indentation in Python is very important. Python uses indentation to indicate a block of code. Example: for x in range (2, 5): print x N.B: Python will give you an error if you skip the indentation: EXAMPLE: for x in 5: print x

#Tips Why NumPy is faster than array list? ✅Size:- Numpy data structures take up less space ✅Performance:- they have a need for speed and are faster than lists ✅Functionality: - SciPy and NumPy have optimized functions such as linear algebra operations built in. ✅Memory:- The main benefits of using NumPy arrays should be smaller memory consumption and better runtime behavior. 

🖥 Which are positional arguments? ➕Check out solution here:https://www.youtube.com/watch?v=K-u3vndXulg 👉Join Telegram https://t.me/epythonlab/ #python #shorts #pythontricks #epythonlab #projects

​​How to make box move with the python

We learn how to analysis data in future data science. You stay at home and learn new futures of Data Science. Think this is an opportunity to be future Data Scientist. I share you my knowledge and experience. #QuarantineYourself #Bioinformatics #DataAnalysis #DataScience

#COVID19 data analysis using #Pandas #DataScience #Bioinformatics

Training Neural Network with Tensorflow and Keras https://youtu.be/MXERXMbp15k

You notice that we have started writing a blog on topics that many developers, especially beginners, find challenging.

Debugging and Troubleshooting in Python: A Developer’s Essential Guide https://medium.com/@epythonlab/debugging-and-troubleshooting-in-python-a-developers-essential-guide-b3415f53b1e0

Python POP QUIZ: What is the output of the following code? 👉Learn More Python Tips and Tricks: https://bit.ly/Pythontoptips 👉Join Telegram https://t.me/epythonlab/ #python #shorts #pythontricks #epythonlab

Learn how to perform hypothesis testing, t-tests, ANOVA, and chi-squared tests using SciPy! https://youtu.be/CDE81yY7VNA

This is a comprehensive beginner's guide to pandas tutorial. In this tutorial, the following topics will be covered: 1. Overview of Pandas - Understanding the basic concepts of pdans 2. Pandas Data Structures - creating and manipulating pandas series and dataframe 3. Data Preprocessing 4. Data aggregation 5. Data visualization https://youtu.be/CU0ejeVJGKo

Today we will share Beginners Pandas Step By Step Guide on YouTube. Topics to be covered: 1. Overview of Pandas 2. Pandas Data Structures 3. Data Preprocessing 4. Data aggregation 5. Data visualization. This tutorial is a guide for having pandas zero experience beginners. Stay Tuned and Subscribe @epythonlab on YouTube and Medium