36.6K
PRComplete Python Notes π
@programmer_talkz
#Python Data Analysis Notebook Charts
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DAPython + Pandas = Data Analysis
β YouTube: Corey Schafer, Data School, Krish Naik
Python + scikit-learn = Machine Learning
β YouTube: StatQuest, CodeBasics, freeCodeCamp
Python + PyTorch = Deep Learning
β YouTube: DeepLizard, Aladdin Persson, PyTorch official
Python + TensorFlow = Deep Learning
β YouTube: TensorFlow, The AI Epiphany, freeCodeCamp
Python + FastAPI = Web Development (APIs)
β YouTube: Tech With Tim, FastAPI Docs, freeCodeCamp
Python + Django = Full-Stack Web Development
β YouTube: Dennis Ivy, Traversy Media, Code With Stein
Python + Flask = Lightweight Web Dev
β YouTube: Tech With Tim, Corey Schafer, freeCodeCamp
Python + NumPy + Matplotlib = Scientific Computing
β YouTube: Data School, StatQuest, freeCodeCamp
Python + Selenium = Web Automation
β YouTube: Naveen AutomationLabs, Mukesh otwani
Python + BeautifulSoup / Scrapy = Web Scraping
β YouTube: CodeBasics, freeCodeCamp, John Watson Rooney
Python + OpenCV = Computer Vision
β YouTube: Murtaza's Workshop, Pysource, freeCodeCamp
Python + NLTK / spaCy = NLP
β YouTube: freeCodeCamp, CodeBasics, DataWithHarsh
Python + Streamlit / Gradio = ML App Deployment
β YouTube: Chanin Nantasenamat (Data Professor), freeCodeCamp
Python + Airflow = Data Pipelines
β YouTube: Data With Danny, freeCodeCamp, Astronomer
Python + PySpark = Big Data
β YouTube: Databricks, freeCodeCamp, Simplilearn
Python + Kivy / PyQt = Desktop Apps
β YouTube: Tech With Tim (Kivy), Parwiz Forogh (PyQt5)
Python + boto3 = AWS Automation
β YouTube: AWS Tutorials, Be A Better Dev
Python + LangChain = AI Agents
β YouTube: Prompt Engineering, Data Professor, LangChain Official
π Follow @freshgrad.com.officia and @datasciencebrain l for more updates on career-boosting courses! πβ¨
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#datascience #machinelearning #python #ai #dataanalytics #artificialintelligence #deeplearning #bigdata #agenticai #aiagents #statistics #dataanalysis #datavisualization #analytics #datascientist #neuralnetworks #100daysofcode #genai #llms #datasciencebootcamp #AIagents #NoCode #LangChain #CrewAI #AutoGen #AItools #AgenticAI #TechStack2025 #DataScience #AIworkflow
@datasciencebrain
43.2K
COπ Top 15 Python Libraries Every Data Analyst Must Know π
If you are starting your Data Analytics journey, the right Python libraries can save you hours of effort and make your projects 10x more powerful. π
Hereβs a quick breakdown of the must-know libraries:
β
Pandas β Data cleaning & manipulation
β
NumPy β Fast numerical computing
β
Matplotlib & Seaborn β Stunning visualizations
β
Plotly β Interactive dashboards
β
Scikit-learn β Easy machine learning
β
Statsmodels & SciPy β Statistical analysis
β
TensorFlow / PyTorch β Advanced AI & analytics
β
OpenPyXL, Dask, BeautifulSoup, NLTK, SQLAlchemy β Excel automation, big data, web scraping, text analytics, and databases!
π‘ Whether youβre preparing for a job, building projects, or just learning, these libraries are the backbone of Data Analytics.
π Save this reel for quick reference π
π Share it with your data friends π
π Follow @codeandcrush for more daily Data Analytics tips, tricks & career hacks π
#python #dataanalytics #pythonlibraries #datascience #machinelearning #sql #powerbi #dataanalyst #learnpython #learnandgrow #careergoals #instagram #pythonprogramming #reelsiΜnstagram #trendings
@codeandcrush
18.7K
ASLetβs work on a Data Analysis in Python in 2 minutes βοΈποΈ
In this video, weβre working with Formula 1 @f1 data including
- Loading and exploring the dataset
- Doing an analysis (plus adding a time series!)
- Plotting charts & graphs to see the trends
Comment βF1β if you want a link to my GitHub repo with this code!
#datascience #dataanalytics #dataanalysis #datascientist #python #formula1 #grandprix
@askdatadawn
1.9M
MORelaxing Python & Pygame Creations #coding #programming
@mohcinale
1.8M
STPython Graphics Pattern Design....
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Visit our site for free source codes & Tutorials, HTML, CSS, Python, JavaScript, Java and More Coding. www.studymuch.in
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Follow @studymuch.in #studymuch for more content on computer science, programming, technology, and the Programming languages.
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#python #programming #coding #java #javascript #studymuch #programmer #developer #html #snake #coder #code #computerscience #technology #css #software #graphicdesign #graphics #ai #robot #reels #reel #trending #pythontutorials #pythonmodule #short
@studymuch.in
942.9K
ZUNever modify a list while iterating it but what ACTUALLY happens?
What does this print? π±
Drop your answer in the comments.
This one has caused real production bugs share yours π
#PythonTrick #PythonQuiz #LearnPython #CodePuzzle #DeveloperLife
@zuhrah.tech
606.4K
DEItβs literally perfect π« #coding #java #programmer #computer #python
@deskmateco
456.0K
HAInput and typecasting in python
Join daily free live classes of PYTHON on HappyCoding YouTube channel
Offline batches are starting very soon in Jaipur!
#prishu #happycoding#happycodingwithprishu #programming #python #prishugawalia
@happycoding_with_prishu
4.3K
LOHow to create line graph using python in just 60 sec
#coding #python #datavisualization #matplotlib #datavisualization
Converting raw data into stunning line chart using matplotlib
Software development | Python | Data science | Data visualization | Matplotlib
@logicwithpython
27.2K
DAR vs Python: Key Differences
R:
- Focuses on data analysis and statistics
- Used primarily by academics and researchers
- Powerful data visualization with libraries like ggplot2
- Runs on the RStudio IDE
- Steeper learning curve initially
Python:
- Versatile language used for deployment and production
- Favored by programmers and developers
- Strong data manipulation capabilities with pandas
- Integrates with machine learning libraries like TensorFlow
- Smoother, more linear learning curve
Both are robust data analysis tools, but have different strengths and user bases. Choosing between R and Python depends on your specific needs and background.
#DataScience #Programming #RvsPython
#DataAnalysis #Statistics #AcademicResearch
#Developers #MachineLearning
#DataVisualization #RStudio #Python #DataManipulation
@datapatashala_official
175.1K
JEComment βprojectβ for my full video that breaks each of these projects down in detail with examples from my own work.
If youβre using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream βnewbieβ. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude!
Here are the 3 types of projects you need:
β³Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables
β³Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one.
β³Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it
Save this video for later + send to a data friend!
@jessramosdata
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