Telegram RegisterThe public register of Telegram

Channel

Python Programming

@pythonpundit

On this record: Growth · Engagement · Posts · Telegram's recommendations · Cite this entry

8,883subscribers

+1 since we began measuring on 12 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001405035303
TypeChannel
Username@pythonpundit
CreatedBetween 1 March 2019 and 30 September 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded12 August 2026
Last confirmed live12 August 2026
Measurements held2
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/pythonpundit

Growth

8,8828,8838,882.512 Aug 2026, 16:31 — 8,882 subscribers12 Aug 2026, 17:45 — 8,883 subscribers12 Aug 2026, 16:3112 Aug 2026, 17:45
2 measurements taken within a single day, net +1. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 8,882–8,883 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 17:458,883+1
12 Aug 2026, 16:318,882first reading

Engagement

20 posts held, back to 3 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
7.31%
avg views ÷ 8,883 subscribers
Avg views / post
650
9 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
9
of 20 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 11 August 2026
Posts held20 (3 June 202611 August 2026)
Views total5,847
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 16:31 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Recent posts

11 Aug 2026, 13:16 UTC187 viewsread 12 August 2026
Photo

🐍 Python Roadmap for Beginners Want to start your programming journey with Python? Follow this structured path: 🔹 1. Python Basics • Variables, Data Types, Operators • Input/Output & Comments 🔹 2. Control Flow • if-else • for & while loops • break, continue, pass 🔹 3. Data Structures • Lists, Tuples, Sets, Dictionaries 🔹 4. Functions • Parameters & Return • *args & **kwargs 🔹 5. Modules & File Handling • Import

8 Aug 2026, 13:31 UTC384 viewsread 12 August 2026
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🐍 FREE PYTHON DEMO SESSION Start your Python journey with practical, industry-focused learning. 📅 Date:-10,11.12 Aug ⏰ Time: 6:30PM IST 💻 Zoom:-https://us06web.zoom.us/meeting/register/shA5Kv5qQZezcVbV6HKt1w 📞 Call/WhatsApp:- 84510-97879 Limited Seats — Register Now!

4 Aug 2026, 13:50 UTC577 viewsread 12 August 2026
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🚀 Python Methods & Functions Every Developer Should Know 🐍 Mastering Python isn't just about syntax—it's about knowing the right function for the right task. 📌 Key Areas to Learn: 🔢 Numeric: abs(), round(), min(), max(), sum() 📝 Strings: split(), join(), replace(), upper(), lower() 📋 Lists: append(), extend(), remove(), sort() 📚 Dictionaries: get(), keys(), values(), items() ⚙️ Functions: def, lambda, map(), f

1 Aug 2026, 13:33 UTC667 viewsread 12 August 2026
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🐍 Python Cheat Sheet 🚀 Mastering Python fundamentals is the foundation for careers in: ✅ Data Analysis ✅ Automation ✅ Web Development ✅ AI & Machine Learning ✅ Backend Development 📌 This cheat sheet covers: • Variables & Data Types • Lists & Dictionaries • Conditionals & Loops • Functions • File Handling • OOP Basics • Exception Handling • Modules • List Comprehensions • Built-in Functions & Methods 💡 Learn the fu

28 Jul 2026, 13:49 UTC697 viewsread 12 August 2026
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🚀 Top 10 Python Tricks Every Beginner Should Know 🐍 Boost your Python skills with these time-saving tricks: ✅ Swap variables: a, b = b, a ✅ Reverse a list: my_list[::-1] ✅ Join strings: " ".join(my_list) ✅ Use in for cleaner conditions ✅ List comprehensions ✅ enumerate() for indexing ✅ zip() for parallel iteration ✅ Remove duplicates with set() ✅ Master *args & **kwargs ✅ Use lambda for quick functions 💡

25 Jul 2026, 13:34 UTC770 viewsread 12 August 2026
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🚀 Evolution of Python DSA 🐍 Python makes learning Data Structures & Algorithms simple, practical, and interview-ready. 💡 Master these concepts: ✅ Arrays, Linked Lists, Stacks & Queues ✅ Trees, Graphs & Hash Tables ✅ Sorting, Binary Search, Recursion ✅ Dynamic Programming, BFS & DFS 🎯 Learning Path: 1️⃣ Python Basics 2️⃣ Data Structures 3️⃣ Algorithms 4️⃣ Solve Problems Daily 5️⃣ Build Logic & Consistency DSA isn'

21 Jul 2026, 13:48 UTC810 viewsread 12 August 2026
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🚀 Pandas The Backbone of Data Analysis in Python If you work with data, Pandas is a must-have skill. With Pandas, you can: ✅ Read CSV, Excel, JSON & SQL data ✅ Clean and preprocess datasets ✅ Filter, sort, group & aggregate data ✅ Handle missing values ✅ Transform raw data into meaningful insights 📌 Master these essentials: • DataFrames & Series • head(), info(), describe() • Filtering & grouping • Missing value h

18 Jul 2026, 13:33 UTC852 viewsread 12 August 2026
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🚀 Python Cheat Sheet Every Developer Should Bookmark 🐍 Master the Python fundamentals that power real-world development: ✅ Data Types ✅ Operators ✅ Control Flow ✅ Data Structures ✅ Built-in Functions ✅ Strings ✅ List Comprehensions ✅ Functions ✅ File Handling ✅ Exception Handling ✅ Productivity Tips 💡 Strong Python fundamentals are essential for Data Analytics, AI/ML, Web Development, and Automation. Don't just m

14 Jul 2026, 14:15 UTC903 viewsread 12 August 2026
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📊 Data Cleaning Cheat Sheet (SQL + Python) Clean data is the foundation of accurate analysis. Master these essential techniques: 🔹 Missing Values • SQL: IS NULL, COALESCE() • Python: isnull(), fillna() 🔹 Remove Duplicates • SQL: SELECT DISTINCT • Python: drop_duplicates() 🔹 Data Formatting • Fix data types, standardize dates, trim & clean text 🔹 Outlier Detection • Use the IQR method to identify extreme values

11 Jul 2026, 13:33 UTC943 viewsread 12 August 2026
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📊 Pandas Cheat Sheet Every Data Analyst Should Know Master these essential Pandas operations to analyze data faster and more efficiently: 🔹 Read & Inspect: read_csv(), .shape, .dtypes, .describe() 🔹 Filter Data: Select columns and apply boolean conditions 🔹 Select Rows: Use .loc and .iloc 🔹 Handle Missing Values: .isnull(), .dropna(), .fillna() 🔹 Group & Aggregate: .groupby(), mean(), count(), etc. 🔹 Merge Dat

7 Jul 2026, 13:29 UTC989 viewsread 12 August 2026
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🚀 Graph Algorithms in Python – A Must-Know for Developers & Data Professionals Graph algorithms power recommendation systems, navigation, fraud detection, network analysis, and AI applications. 📌 Key algorithms to learn: 🔹 BFS & DFS 🔹 Dijkstra's Algorithm 🔹 Bellman-Ford 🔹 Floyd-Warshall 🔹 A* Search 🔹 Prim's & Kruskal's (MST) 🔹 Topological Sort 🔹 Tarjan's Algorithm 💡 Learning these algorithms improves problem-solvi

4 Jul 2026, 12:56 UTC999 viewsread 12 August 2026
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🚀 Master Python List Methods – A Must-Know for Every Python Developer Python lists are one of the most commonly used data structures. Mastering their methods helps you write cleaner, faster, and more efficient code. Key methods to know: ✅ Sort & Organize: sort(), reverse() ✅ Add Elements: append(), extend(), insert() ✅ Remove Elements: remove(), pop(), clear() ✅ Search: index(), count() ✅ Utilities: len(), min(), m

Showing the 12 most recent of 20 posts we hold for @pythonpundit. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Certified Free Courses - MindLuster
@mindluster · 225,001
Telegram ranks this channel #31 of 61 here — alongside 60 others — read 12 August 2026
UPSC Civil Services Upsc Prelims Mains Exam Current Affairs GS Gk Tricks SSC CGL IAS IFS IPS EPFO PCS UPPCS MPPCS Bihar PCS
@cseupscnotes · 152,501
Telegram ranks this channel #75 of 89 here — alongside 88 others — read 12 August 2026

This channel appears in 2 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Python Programming” (@pythonpundit), 8,883 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/pythonpundit.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.