1.3M
SWIf I was a beginner learning to code, I would use this Python roadmap step by step for beginners 💪 #coding #codingforbeginners #learntocode #codingtips #cs #python #computerscience #usemassive
@swerikcodes
#Data Visualization With Python 2026
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عمليات بحث ذات صلة
24ريلز رائجة
(12)
11.4K
MA🎨Top-4 libraries for data visualization
Matplotlib is a go-to choice for many data scientists. With Matplotlib, you can create various types of plots, such as line plots, bar plots, scatter plots, and histograms.
Seaborn is a high-level library built on top of Matplotlib. Seaborn simplifies the creation of statistical graphics and offers a range of attractive themes and color palettes.
Plotly is a library for interactive visualizations. With Plotly, you can create dynamic charts that allow users to zoom, select, and hover over data points.
Bokeh is another library that excels in interactive data visualization. Bokeh’s server-based architecture allows for real-time updates and streaming, making it a popular choice for live data visualizations.
Go ahead, explore their capabilities, and unleash the power of data visualization in Python.
Follow @ai.marina.io to know how to succeed in data science field!
#datascientist #datascience #dataanalytics #womenwhocode #womenintech #code #datasciencecareers #programming #python #data #datavisualization #datavizualisation #matplotlib #seaborn #bokeh #plotly #pythonlibrary #visualization #pythontips #pythonprogramming #pythoncode
@marina.petzel.tech
413.4K
PRIf I Had to Start Over in 2026 to Become a Data Analyst-
First: The mindset (non-negotiable)
In 2026, data analysts are not hired for tools.
They’re hired for:
“Can you find insights fast and explain them clearly—with or without AI?”
AI is your assistant, not your replacement.
WHAT I’D LEARN (IN ORDER)
1️⃣ SQL — Still the KING
How much SQL is enough?
👉 80% of real work.
Must-know:
SELECT, WHERE, ORDER BY
JOINs (INNER, LEFT, RIGHT)
GROUP BY + HAVING
Subqueries
Window functions (ROW_NUMBER, RANK, LAG)
Case statements
How AI fits:
Use AI to optimize queries
Ask AI to explain slow queries
Convert business questions → SQL
💡If you’re weak in SQL, AI won’t save you.
2️⃣ Python — Not Software Engineer Level
You don’t need DSA. Period.
Exactly what I’d learn:
Python basics
Pandas (VERY IMPORTANT)
NumPy (basic)
Data cleaning
EDA
Simple functions
What I’d SKIP:
Complex OOP
LeetCode / DSA
Building frameworks
Goal: “I can clean messy data, analyze it, and explain patterns.”
3️⃣ Data Visualization — INSIGHTS > CHARTS
Tools don’t matter much:
Power BI / Tableau / Looker
What matters:
Choosing the right chart
Writing 1-line insights
Storytelling
AI use:
Auto-generate dashboards
Improve chart explanations
Convert insights into stakeholder language
🤖 AI TOOLS I’D ACTUALLY USE (2026-Ready)
🔹 Must-Use AI Skills
(Not tools only—skills)
1️⃣ ChatGPT / Claude / Gemini
Use for:
Writing SQL queries
Debugging Python
Explaining concepts
Generating insights from data
Resume + interview prep
2️⃣ Excel + AI
Excel Copilot
AI formulas
Auto-clean data
3️⃣ AI for Data Cleaning
Tools like:
AI-powered data prep tools
Auto-mapping columns
Outlier detection
(You don’t need names—just show you can do it)
📊 PROJECTS I’D BUILD (MOST IMPORTANT)
❌What I wouldn’t do:
Titanic dataset
Iris dataset
House price prediction
✅ What I’d do:
Business-style projects:
Sales performance analysis
Customer churn analysis
Marketing funnel analysis
Product usage analysis
Each project MUST have:
Problem statement
Business questions
SQL + Python
Dashboard
Final insights
AI can help—but YOU explain.
Comment “pdf” for complete guide.
@prernaa.py
2.3K
SDData project: web scraping and data visualization with Python. Use the Pandas and Matplotlib libraries to create a dashboard to visualize data from a HTML table. #dataanalytics #dataengineering #techtok
@sdw.online
218
DA!! New Project Uploaded !!
🚀 Real Project – 14 | Salary Data Analysis Using Python | Python Coding for Data Science
Watch on YouTube (copy-paste) - https://youtu.be/TLIotspGcng
You will learn the complete data analysis workflow, just like in real industry projects:
✅ Data Understanding & Exploration (EDA)
✅ Data Cleaning & Handling Duplicates
✅ Outlier Detection using IQR Method
✅ Data Visualization using Matplotlib & Seaborn
✅ Business Questions & Insights
✅ Correlation Analysis
✅ Advanced Charts (Scatter, Line, Histogram, Dashboard)
✅ Final Mini Dashboard
✅ Portfolio-Ready Project
#datasciencewithrg #datasciencelovers #python #project #dataanalysis #dataanalytics #coding #salarydataanalysis #pythonproject
#datascience #dataanalytics #datavisualization #datasciencelovers
@data_science_lovers
83.6K
JEComment “SQL” for my free intro to SQL course perfect for newbies to build your first project in 30min!
Save for later and follow for more!
If you haven’t learned Python yet, this is your sign.
Here’s exactly how I’d learn it ⬇️
Beginner — Build confidence with real data:
↳ Import libraries
↳ Read CSV & Excel files
↳ Explore and understand your data
↳ Select rows & columns
↳ Filter with conditions
↳ Handle missing values
↳ Rename columns & change data types
↳ Basic string manipulation
↳ Basic charts & visualization
Intermediate — Answer real business questions:
↳ Group & aggregate
↳ Create new columns
↳ Conditional logic
↳ Sort & rank
↳ Merge & join datasets
↳ Handle duplicates
↳ Date & time manipulation
↳ Exploratory data analysis
↳ Statistical charts & customization
Advanced — Build analysis that drives decisions:
↳ Complex transformations
↳ Reshape data
↳ Work with large datasets
↳ Write reusable functions
↳ Automate your analysis
↳ Data quality checks
↳ Advanced visuals
↳ KPI & trend analysis
↳ Stakeholder-ready insights
#python #sql #dataanalytics #datascience #roadmap
🏷️ python, sql, data analytics, data science, data, tech
@jessramosdata
23.0K
ENFree Data Visualization Using python course with certificate.
SAVE it for later & comment "GRAPHS" FOR the link.
Follow @engineer_bhaiya_yt
Don't forget to share the reel with your fellow friends.
Hashtag
#data #datascience #dataanalytics #visuslization #python #pythonprogramming #learn #free #certificate
@engineer_bhaiya_yt
85.2K
THYou only need to learn these 10 Python Topics to crack any data analyst interview #python #sql #dataanalyst
@thedataguy16
41.2K
SHPython Data Visualization for Exploratory Analysis
Good data analysis starts with asking the right questions, and visualization helps you answer them faster.
This cheat-sheet style guide brings together essential Python visualization techniques used during exploratory data analysis. It covers patterns at a single-variable level, relationships between variables, multivariate insights, time-based trends, text exploration, and plot customization. These are the exact visual checks analysts rely on before modeling or reporting.
Whether you work with business data, research datasets, or real-world production data, strong visuals help you spot outliers, understand distributions, compare categories, and communicate insights clearly.
Save it for reference and revisit it whenever you start exploring a new dataset.
[python,data visualization,exploratory data analysis,eda,matplotlib,seaborn,pandas,data analysis,analytics,data science,charts,plots,statistical analysis,univariate analysis,bivariate analysis,multivariate analysis,time series,text analysis,data insights,data storytelling,correlation,distribution,outliers,trend analysis,heatmap,scatter plot,box plot,violin plot,histogram,kde plot,regression plot,pair plot,data preparation,data workflow,python for analytics,data visualization best practices]
#Python #DataVisualization #EDA #DataAnalysis #DataScience
@she_explores_data
27.2K
PY#rprogramming #pythonprogramming #heatmap #datavisualisation #gene #dataanalytics
@python_for_bioinformatics
43.2K
CO🐍 Top 15 Python Libraries Every Data Analyst Must Know 📊
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. 🚀
Here’s a quick breakdown of the must-know libraries:
✅ Pandas → Data cleaning & manipulation
✅ NumPy → Fast numerical computing
✅ Matplotlib & Seaborn → Stunning visualizations
✅ Plotly → Interactive dashboards
✅ Scikit-learn → Easy machine learning
✅ Statsmodels & SciPy → Statistical analysis
✅ TensorFlow / PyTorch → Advanced AI & analytics
✅ OpenPyXL, Dask, BeautifulSoup, NLTK, SQLAlchemy → Excel automation, big data, web scraping, text analytics, and databases!
💡 Whether you’re preparing for a job, building projects, or just learning, these libraries are the backbone of Data Analytics.
👉 Save this reel for quick reference 🔖
👉 Share it with your data friends 🔄
👉 Follow @codeandcrush for more daily Data Analytics tips, tricks & career hacks 🚀
#python #dataanalytics #pythonlibraries #datascience #machinelearning #sql #powerbi #dataanalyst #learnpython #learnandgrow #careergoals #instagram #pythonprogramming #reelsi̇nstagram #trendings
@codeandcrush
70.6K
DAPython for Data Science : https://cognitiveclass.ai/courses/python-for-data-science/
Machine Learning with Python : https://cognitiveclass.ai/courses/machine-learning-with-python/
Data Visualization with Python : https://cognitiveclass.ai/courses/data-visualization-with-python/
Introduction to Data Science : https://cognitiveclass.ai/courses/data-science-101/
Deep Learning Fundementals : https://cognitiveclass.ai/courses/introduction-deep-learning/
Data Analysis with Python : https://cognitiveclass.ai/courses/data-analysis-python/
Deep Learning with TensorFlow : https://cognitiveclass.ai/courses/deep-learning-tensorflow/
Big Data 101 : https://cognitiveclass.ai/courses/what-is-big-data/
Hadoop 101 : https://cognitiveclass.ai/courses/introduction-to-hadoop/
R 101 : https://cognitiveclass.ai/courses/r-101/
🏆 Follow @datasciencebrain #dsbrain for more amazing Data Science resources and News
📌Share with & tag your friends who would like to know about this
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#datascience #freecertification #datasciencecertification #onlinelearning #datasciencetraining #learndatascience #certifieddatascientist #freedatasciencecourse #datasciencecommunity #datasciencetools #datasciencelife #onlineeducation #datasciencejobs #dataanalysis #datascientist
@datasciencebrain
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