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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Network:š Analytical overview of Telegram channel Python for Data Analysts
Channel Python for Data Analysts (@pythonanalyst) in the English language segment is an active participant. Currently, the community unites 51 824 subscribers, ranking 2 511 in the Technologies & Applications category and 6 945 in the India region.
š Audience metrics and dynamics
Since its creation on Š½ŠµŠ²ŃŠ“Š¾Š¼Š¾, the project has demonstrated rapid growth, gathering an audience of 51 824 subscribers.
According to the latest data from 25 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 138 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 4.24%. Within the first 24 hours after publication, content typically collects 1.00% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 197 views. Within the first day, a publication typically gains 519 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
- Thematic interests: Content is focused on key topics such as visualization, panda, analyst, sql, analytic.
š Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
āFind top Python resources from global universities, cool projects, and learning materials for data analytics.
For promotions: @coderfun
Useful links: heylink.me/DataAnalyticsā
Thanks to the high frequency of updates (latest data received on 26 August, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
51 824
Subscribers
No data24 hours
-227 days
+13830 days
Posts Archive
51 827
šGreetings from PVR Cloud Tech!! š
š” From Beginner to Pro in Azure Data Engineering ā Start Your Journey the Smart Way in 2025
š Start Date: 29th November 2025
ā° Time: 10 AM ā 11 AM IST | Saturday
š¹ Course Content:
https://drive.google.com/file/d/1YufWV0Ru6SyYt-oNf5Mi5H8mmeV_kfP-/view
š± Join WhatsApp Group:
https://chat.whatsapp.com/D0i5h9Vrq4FLLMfVKCny7u
š„ Register Now:
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šŗ WhatsApp Channel:
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Team
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51 827
Greetings from PVR Cloud Tech!! š
š 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
š Start Date: 24th Nov 2025
ā° Time: 8 PM ā 9 PM IST | Monday
š¹ Course Content:
https://drive.google.com/file/d/1luKHrhYZ6zKuXZpVPGzMydrU_6R2yQnL/view
š± Join WhatsApp Group:
https://chat.whatsapp.com/EZghn5PVmryDgJZ1TjIMRk?mode=wwt
š„ Register Now:
https://forms.gle/Vaofd52rkJcUpKPV7
šŗ WhatsApp Channel:
https://www.whatsapp.com/channel/0029Vb60rGU8V0thkpbFFW2n
Team
PVR Cloud Tech:)
+91-9346060794
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 futureāthey 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 āGenerative AI in Healthcareā
- NebojÅ”a BaÄanin Džakula (Singidunum University, Serbia) will talk about the latest advances in bio-inspired metaheuristics
- AIexandre Ferreira Ramos (University of SĆ£o 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 āAI in the New Era: From Basics to Trends, Opportunities, and Global Cooperationā.
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.
51 827
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 futureāthey 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.
51 827
š The Ultimate Data Science Roadmap ā 2025 Edition
Ready to start or upgrade your Data Science journey? Hereās your quick guide from basics to Gen AI š
š§® 1ļøā£ Math & Stats ā Master algebra, probability & calculus ā the core of ML & AI.
š» 2ļøā£ Python & SQL ā Learn Python (NumPy, APIs, OOPs) & SQL for data wrangling.
š 3ļøā£ Excel ā Still key for quick analysis, pivot tables & data cleaning.
š 4ļøā£ Data Analysis ā Do EDA, build dashboards (Power BI/Tableau), and visualize with Pandas.
š¤ 5ļøā£ Machine Learning ā Start with regression, classification & model tuning.
š§ 6ļøā£ Deep Learning ā Learn CNNs, RNNs & model deployment for CV & NLP.
āļø 7ļøā£ Generative AI & LLMs ā Explore RAG, AutoGPT & reasoning frameworks.
š¤Æ 8ļøā£ Agentic AI ā Dive into LangChain, OpenAI APIs & intelligent agents.
šÆ Pro Tip:
Donāt rush. Be consistent. Build projects, join Kaggle, and solve real problems ā thatās where real learning happens.
51 827
š Greetings from PVR Cloud Tech!! š
š” From Beginner to Pro in Azure Data Engineering ā Start Your Journey the Smart Way in 2025
š Start Date: 10th November 2025
ā° Time: 08 PM ā 09 PM IST | Monday
š¹ Course Content:
https://drive.google.com/file/d/1YufWV0Ru6SyYt-oNf5Mi5H8mmeV_kfP-/view
š± Join WhatsApp Group:
https://chat.whatsapp.com/D0i5h9Vrq4FLLMfVKCny7u
š„ Register Now:
https://forms.gle/FuiBxFAaC8TgFXZo8
šŗ WhatsApp Channel:
https://www.whatsapp.com/channel/0029Vb60rGU8V0thkpbFFW2n
Team
PVR Cloud Tech:)
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51 827
Free Data Analytics Courses With Certificate
šš
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51 827
ā
How Much Python is Enough to Crack a Data Analyst Interview? šš
Python is a must-have for data analyst roles in 2025āinterviewers 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:
š Basic Syntax & Data Types
ā¦ Variables, strings, integers, floats
ā¦ Lists, tuples, dictionaries, sets
š Conditions & Loops
ā¦ if, elif, else
ā¦ for and while loops
š§° Functions & Scope
ā¦ def, parameters, return values
ā¦ Lambda functions, *args, **kwargs
š¦ Pandas Foundation
ā¦ DataFrame, Series
ā¦ read_csv(), head(), info(), describe()
ā¦ Filtering, sorting, indexing
š§® Data Analysis
ā¦ groupby(), agg(), pivot_table()
ā¦ Handling missing values: isnull(), fillna()
ā¦ Duplicates & outliers
š Visualization
ā¦ matplotlib.pyplot & seaborn
ā¦ Line, bar, scatter, histogram
ā¦ Styling and labeling charts
šļø Working with Files
ā¦ Reading/writing CSV, Excel
ā¦ JSON basics
ā¦ Using with open() for text files
š
Date & Time
ā¦ datetime, pd.to_datetime()
ā¦ Extracting day, month, year
ā¦ Time-based filtering
ā
Must-Have Strengths:
ā¦ Writing clean, readable Python code
ā¦ Analyzing DataFrames confidently
ā¦ Explaining logic behind analysis
ā¦ 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 edgeāmany jobs test Python via coding challenges on datasets.
Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
š¬ Tap ā¤ļø for more!
51 827
š» Python Programming Roadmap
š¹ Stage 1: Python Basics (Syntax, Variables, Data Types)
š¹ Stage 2: Control Flow (if/else, loops)
š¹ Stage 3: Functions & Modules
š¹ Stage 4: Data Structures (Lists, Tuples, Sets, Dicts)
š¹ Stage 5: File Handling (Read/Write, CSV, JSON)
š¹ Stage 6: Error Handling (try/except, custom exceptions)
š¹ Stage 7: Object-Oriented Programming (Classes, Inheritance)
š¹ Stage 8: Standard Libraries (os, datetime, math)
š¹ Stage 9: Virtual Environments & pip package management
š¹ Stage 10: Working with APIs (Requests, JSON data)
š¹ Stage 11: Web Development Basics (Flask/Django)
š¹ Stage 12: Databases (SQLite, PostgreSQL, SQLAlchemy ORM)
š¹ Stage 13: Testing (unittest, pytest frameworks)
š¹ Stage 14: Version Control with Git & GitHub
š¹ Stage 15: Package Development (setup.py, publishing on PyPI)
š¹ Stage 16: Data Analysis (Pandas, NumPy libraries)
š¹ Stage 17: Data Visualization (Matplotlib, Seaborn)
š¹ Stage 18: Web Scraping (BeautifulSoup, Selenium)
š¹ Stage 19: Automation & Scripting projects
š¹ Stage 20: Advanced Topics (AsyncIO, Type Hints, Design Patterns)
š” Tip: Master one stage before moving to the next. Build mini-projects to solidify your learning.
You can find detailed explanation here: š https://whatsapp.com/channel/0029VbBDoisBvvscrno41d1l
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51 827
šGreetings from PVR Cloud Tech!! š
š” From Beginner to Pro in Azure Data Engineering ā Start Your Journey the Smart Way in 2025
š Start Date: 25th October 2025
ā° Time: 10 AM ā 11 AM IST | Saturday
š¹ Course Content:
https://drive.google.com/file/d/1YufWV0Ru6SyYt-oNf5Mi5H8mmeV_kfP-/view
š± Join WhatsApp Group:
https://chat.whatsapp.com/CONhbkkRrnB8MK7GjXbXS4
š„ Register Now:
https://forms.gle/gvDyHekgq2TWc2619
šŗ WhatsApp Channel:
https://www.whatsapp.com/channel/0029Vb60rGU8V0thkpbFFW2n
Team
PVR Cloud Tech :)
+91-9346060794
51 827
ā
Python Checklist for Data Analysts š§
1. Python Basics
āŖ Variables, data types (int, float, str, bool)
āŖ Control flow: if-else, loops (for, while)
āŖ Functions and lambda expressions
āŖ List, dict, tuple, set basics
2. Data Handling & Manipulation
āŖ NumPy: arrays, vectorized operations, broadcasting
āŖ Pandas: Series & DataFrame, reading/writing CSV, Excel
āŖ Data inspection:
head(), info(), describe()
āŖ Filtering, sorting, grouping (groupby), merging/joining datasets
āŖ Handling missing data (isnull(), fillna(), dropna())
3. Data Visualization
āŖ Matplotlib basics: plots, histograms, scatter plots
āŖ Seaborn: statistical visualizations (heatmaps, boxplots)
āŖ Plotly (optional): interactive charts
4. Statistics & Probability
āŖ Descriptive stats (mean, median, std)
āŖ Probability distributions, hypothesis testing (SciPy, statsmodels)
āŖ Correlation, covariance
5. Working with APIs & Data Sources
āŖ Fetching data via APIs (requests library)
āŖ Reading JSON, XML
āŖ Web scraping basics (BeautifulSoup, Scrapy)
6. Automation & Scripting
āŖ Automate repetitive data tasks using loops, functions
āŖ Excel automation (openpyxl, xlrd)
āŖ File handling and regular expressions
7. Machine Learning Basics (Optional starting point)
āŖ Scikit-learn for basic models (regression, classification)
āŖ Train-test split, evaluation metrics
8. Version Control & Collaboration
āŖ Git basics: init, commit, push, pull
āŖ Sharing notebooks or scripts via GitHub
9. Environment & Tools
āŖ Jupyter Notebook / JupyterLab for interactive analysis
āŖ Python IDEs (VSCode, PyCharm)
āŖ Virtual environments (venv, conda)
10. Projects & Portfolio
āŖ Analyze real datasets (Kaggle, UCI)
āŖ Document insights in notebooks or blogs
āŖ Showcase code & analysis on GitHub
š” Tips:
ā¦ Practice coding daily with mini-projects and challenges
ā¦ Use interactive platforms like Kaggle, DataCamp, or LeetCode (Python)
ā¦ Combine SQL + Python skills for powerful data querying & analysis
Python Programming Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L
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