Python for Data Analysts
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Find top Python resources from global universities, cool projects, and learning materials for data analytics. For promotions: @coderfun Useful links: heylink.me/DataAnalytics
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Red:📈 Análisis del canal de Telegram Python for Data Analysts
El canal Python for Data Analysts (@pythonanalyst) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 51 827 suscriptores, ocupando la posición 2 495 en la categoría Tecnologías y Aplicaciones y el puesto 6 883 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 51 827 suscriptores.
Según los últimos datos del 26 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 118, y en las últimas 24 horas de -5, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 4.34%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.00% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 2 248 visualizaciones. En el primer día suele acumular 519 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 8.
- Intereses temáticos: El contenido se centra en temas clave como visualization, panda, analyst, sql, analytic.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Find top Python resources from global universities, cool projects, and learning materials for data analytics.
For promotions: @coderfun
Useful links: heylink.me/DataAnalytics”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 27 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
51 827
Suscriptores
-524 horas
-297 días
+11830 días
Archivo de publicaciones
51 827
🚀Greetings from PVR Cloud Tech!! 🌈
💡 From Beginner to Pro in Azure Data Engineering – Start Your Journey the Smart Way in 2025
📌 Start Date: 29th November 2025
⏰ Time: 10 AM – 11 AM IST | Saturday
🔹 Course Content:
https://drive.google.com/file/d/1YufWV0Ru6SyYt-oNf5Mi5H8mmeV_kfP-/view
📱 Join WhatsApp Group:
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51 827
Greetings from PVR Cloud Tech!! 🌈
🚀 Along with our highly successful Azure Data Engineering program, we are now launching a brand-new Data Engineering with Snowflake, DBT, and Airflow training track!
Course: Snowflake + DBT + Airflow
📌 Start Date: 24th Nov 2025
⏰ Time: 8 PM – 9 PM IST | Monday
🔹 Course Content:
https://drive.google.com/file/d/1luKHrhYZ6zKuXZpVPGzMydrU_6R2yQnL/view
📱 Join WhatsApp Group:
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📥 Register Now:
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📺 WhatsApp Channel:
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51 827
Tune in to the 10th AI Journey 2025 international conference: scientists, visionaries, and global AI practitioners will come together on one stage. Here, you will hear the voices of those who don't just believe in the future—they are creating it!
Speakers include visionaries Kai-Fu Lee and Chen Qufan, as well as dozens of global AI gurus! Do you agree with their predictions about AI?
On November 20, we will focus on the role of AI in business and economic development and present technologies that will help businesses and developers be more effective by unlocking human potential.
On November 21, we will talk about how engineers and scientists are making scientific and technological breakthroughs and creating the future today! The day's program includes presentations by scientists from around the world:
- Ajit Abraham (Sai University, India) will present on “Generative AI in Healthcare”
- Nebojša Bačanin Džakula (Singidunum University, Serbia) will talk about the latest advances in bio-inspired metaheuristics
- AIexandre Ferreira Ramos (University of São Paulo, Brazil) will present his work on using thermodynamic models to study the regulatory logic of transcriptional control at the DNA level
- Anderson Rocha (University of Campinas, Brazil) will give a presentation entitled “AI in the New Era: From Basics to Trends, Opportunities, and Global Cooperation”.
And in the special AIJ Junior track, we will talk about how AI helps us learn, create and ride the wave with AI.
The day will conclude with an award ceremony for the winners of the AI Challenge for aspiring data scientists and the AIJ Contest for experienced AI specialists. The results of an open selection of AIJ Science research papers will be announced.
Ride the wave with AI into the future!
Tune in to the AI Journey webcast on November 19-21.
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The program for the 10th AI Journey 2025 international conference has been unveiled: scientists, visionaries, and global AI practitioners will come together on one stage. Here, you will hear the voices of those who don't just believe in the future—they are creating it!
Speakers include visionaries Kai-Fu Lee and Chen Qufan, as well as dozens of global AI gurus from around the world!
On the first day of the conference, November 19, we will talk about how AI is already being used in various areas of life, helping to unlock human potential for the future and changing creative industries, and what impact it has on humans and on a sustainable future.
On November 20, we will focus on the role of AI in business and economic development and present technologies that will help businesses and developers be more effective by unlocking human potential.
On November 21, we will talk about how engineers and scientists are making scientific and technological breakthroughs and creating the future today!
Ride the wave with AI into the future!
Tune in to the AI Journey webcast on November 19-21.
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🚀 The Ultimate Data Science Roadmap — 2025 Edition
Ready to start or upgrade your Data Science journey? Here’s your quick guide from basics to Gen AI 👇
🧮 1️⃣ Math & Stats – Master algebra, probability & calculus — the core of ML & AI.
💻 2️⃣ Python & SQL – Learn Python (NumPy, APIs, OOPs) & SQL for data wrangling.
📊 3️⃣ Excel – Still key for quick analysis, pivot tables & data cleaning.
📈 4️⃣ Data Analysis – Do EDA, build dashboards (Power BI/Tableau), and visualize with Pandas.
🤖 5️⃣ Machine Learning – Start with regression, classification & model tuning.
🧠 6️⃣ Deep Learning – Learn CNNs, RNNs & model deployment for CV & NLP.
⚙️ 7️⃣ Generative AI & LLMs – Explore RAG, AutoGPT & reasoning frameworks.
🤯 8️⃣ Agentic AI – Dive into LangChain, OpenAI APIs & intelligent agents.
🎯 Pro Tip:
Don’t rush. Be consistent. Build projects, join Kaggle, and solve real problems — that’s where real learning happens.
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🚀 Greetings from PVR Cloud Tech!! 🌈
💡 From Beginner to Pro in Azure Data Engineering – Start Your Journey the Smart Way in 2025
📌 Start Date: 10th November 2025
⏰ Time: 08 PM – 09 PM IST | Monday
🔹 Course Content:
https://drive.google.com/file/d/1YufWV0Ru6SyYt-oNf5Mi5H8mmeV_kfP-/view
📱 Join WhatsApp Group:
https://chat.whatsapp.com/D0i5h9Vrq4FLLMfVKCny7u
📥 Register Now:
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📺 WhatsApp Channel:
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Team
PVR Cloud Tech:)
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51 827
Free Data Analytics Courses With Certificate
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https://www.linkedin.com/posts/sql-analysts_dataanalyst-datascience-datacamp-activity-7392164126371958784-cFIc
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✅ How Much Python is Enough to Crack a Data Analyst Interview? 🐍📊
Python is a must-have for data analyst roles in 2025—interviewers expect you to handle data cleaning, analysis, and basic viz with it. You don't need to be an expert in ML or advanced scripting; focus on practical skills to process and interpret data efficiently. Based on current trends, here's what gets you interview-ready:
📌 Basic Syntax & Data Types
⦁ Variables, strings, integers, floats
⦁ Lists, tuples, dictionaries, sets
🔁 Conditions & Loops
⦁ if, elif, else
⦁ for and while loops
🧰 Functions & Scope
⦁ def, parameters, return values
⦁ Lambda functions, *args, **kwargs
📦 Pandas Foundation
⦁ DataFrame, Series
⦁ read_csv(), head(), info(), describe()
⦁ Filtering, sorting, indexing
🧮 Data Analysis
⦁ groupby(), agg(), pivot_table()
⦁ Handling missing values: isnull(), fillna()
⦁ Duplicates & outliers
📊 Visualization
⦁ matplotlib.pyplot & seaborn
⦁ Line, bar, scatter, histogram
⦁ Styling and labeling charts
🗃️ Working with Files
⦁ Reading/writing CSV, Excel
⦁ JSON basics
⦁ Using with open() for text files
📅 Date & Time
⦁ datetime, pd.to_datetime()
⦁ Extracting day, month, year
⦁ Time-based filtering
✅ Must-Have Strengths:
⦁ Writing clean, readable Python code
⦁ Analyzing DataFrames confidently
⦁ Explaining logic behind analysis
⦁ Connecting analysis to business goals
Aim for 2-3 months of consistent practice (20-30 hours/week) on platforms like DataCamp or LeetCode. Pair it with SQL and Excel for a strong edge—many jobs test Python via coding challenges on datasets.
Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
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💻 Python Programming Roadmap
🔹 Stage 1: Python Basics (Syntax, Variables, Data Types)
🔹 Stage 2: Control Flow (if/else, loops)
🔹 Stage 3: Functions & Modules
🔹 Stage 4: Data Structures (Lists, Tuples, Sets, Dicts)
🔹 Stage 5: File Handling (Read/Write, CSV, JSON)
🔹 Stage 6: Error Handling (try/except, custom exceptions)
🔹 Stage 7: Object-Oriented Programming (Classes, Inheritance)
🔹 Stage 8: Standard Libraries (os, datetime, math)
🔹 Stage 9: Virtual Environments & pip package management
🔹 Stage 10: Working with APIs (Requests, JSON data)
🔹 Stage 11: Web Development Basics (Flask/Django)
🔹 Stage 12: Databases (SQLite, PostgreSQL, SQLAlchemy ORM)
🔹 Stage 13: Testing (unittest, pytest frameworks)
🔹 Stage 14: Version Control with Git & GitHub
🔹 Stage 15: Package Development (setup.py, publishing on PyPI)
🔹 Stage 16: Data Analysis (Pandas, NumPy libraries)
🔹 Stage 17: Data Visualization (Matplotlib, Seaborn)
🔹 Stage 18: Web Scraping (BeautifulSoup, Selenium)
🔹 Stage 19: Automation & Scripting projects
🔹 Stage 20: Advanced Topics (AsyncIO, Type Hints, Design Patterns)
💡 Tip: Master one stage before moving to the next. Build mini-projects to solidify your learning.
You can find detailed explanation here: 👇 https://whatsapp.com/channel/0029VbBDoisBvvscrno41d1l
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51 827
🚀Greetings from PVR Cloud Tech!! 🌈
💡 From Beginner to Pro in Azure Data Engineering – Start Your Journey the Smart Way in 2025
📌 Start Date: 25th October 2025
⏰ Time: 10 AM – 11 AM IST | Saturday
🔹 Course Content:
https://drive.google.com/file/d/1YufWV0Ru6SyYt-oNf5Mi5H8mmeV_kfP-/view
📱 Join WhatsApp Group:
https://chat.whatsapp.com/CONhbkkRrnB8MK7GjXbXS4
📥 Register Now:
https://forms.gle/gvDyHekgq2TWc2619
📺 WhatsApp Channel:
https://www.whatsapp.com/channel/0029Vb60rGU8V0thkpbFFW2n
Team
PVR Cloud Tech :)
+91-9346060794
51 827
✅Python Checklist for Data Analysts 🧠
1. Python Basics
▪ Variables, data types (int, float, str, bool)
▪ Control flow: if-else, loops (for, while)
▪ Functions and lambda expressions
▪ List, dict, tuple, set basics
2. Data Handling & Manipulation
▪ NumPy: arrays, vectorized operations, broadcasting
▪ Pandas: Series & DataFrame, reading/writing CSV, Excel
▪ Data inspection:
head(), info(), describe()
▪ Filtering, sorting, grouping (groupby), merging/joining datasets
▪ Handling missing data (isnull(), fillna(), dropna())
3. Data Visualization
▪ Matplotlib basics: plots, histograms, scatter plots
▪ Seaborn: statistical visualizations (heatmaps, boxplots)
▪ Plotly (optional): interactive charts
4. Statistics & Probability
▪ Descriptive stats (mean, median, std)
▪ Probability distributions, hypothesis testing (SciPy, statsmodels)
▪ Correlation, covariance
5. Working with APIs & Data Sources
▪ Fetching data via APIs (requests library)
▪ Reading JSON, XML
▪ Web scraping basics (BeautifulSoup, Scrapy)
6. Automation & Scripting
▪ Automate repetitive data tasks using loops, functions
▪ Excel automation (openpyxl, xlrd)
▪ File handling and regular expressions
7. Machine Learning Basics (Optional starting point)
▪ Scikit-learn for basic models (regression, classification)
▪ Train-test split, evaluation metrics
8. Version Control & Collaboration
▪ Git basics: init, commit, push, pull
▪ Sharing notebooks or scripts via GitHub
9. Environment & Tools
▪ Jupyter Notebook / JupyterLab for interactive analysis
▪ Python IDEs (VSCode, PyCharm)
▪ Virtual environments (venv, conda)
10. Projects & Portfolio
▪ Analyze real datasets (Kaggle, UCI)
▪ Document insights in notebooks or blogs
▪ Showcase code & analysis on GitHub
💡 Tips:
⦁ Practice coding daily with mini-projects and challenges
⦁ Use interactive platforms like Kaggle, DataCamp, or LeetCode (Python)
⦁ Combine SQL + Python skills for powerful data querying & analysis
Python Programming Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
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