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📚Python Books

📚Python Books

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📚Python библиотека admin - @workakkk @ai_machinelearning_big_data - машинное обучение @programming_books_it - бесплатные it книги @pythonl - 🐍 @ArtificialIntelligencedl - AI @datascienceiot - ml РКН: clck.ru/3FmsTi

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📈 Analytical overview of Telegram channel 📚Python Books

Channel 📚Python Books (@pythonlbooks) is an active participant. Currently, the community unites 33 549 subscribers, ranking 3 874 in the Technologies & Applications category and 19 070 in the Russia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 33 549 subscribers.

According to the latest data from 31 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -205 over the last 30 days and by 2 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 6.73%. Within the first 24 hours after publication, content typically collects 2.56% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 257 views. Within the first day, a publication typically gains 859 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 0.
  • Thematic interests: Content is focused on key topics such as сотрудников, курса, инструменты, использовать, docker.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
📚Python библиотека admin - @workakkk @ai_machinelearning_big_data - машинное обучение @programming_books_it - бесплатные it книги @pythonl - 🐍 @ArtificialIntelligencedl - AI @datascienceiot - ml РКН: clck.ru/3FmsTi

Thanks to the high frequency of updates (latest data received on 01 September, 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.

33 549
Subscribers
+224 hours
-527 days
-20530 days
Posts Archive
Изучение робототехники с использованием Python, 2е издание Book @pythonlbooks
Изучение робототехники с использованием Python, 2е издание Book @pythonlbooks

Intro to Python for Computer Science and Data Science - 2020 Book @pythonlbooks
Intro to Python for Computer Science and Data Science - 2020 Book @pythonlbooks

Python Data Analytics: With Pandas, NumPy, and Matplotlib Book @pythonlbooks
Python Data Analytics: With Pandas, NumPy, and Matplotlib Book @pythonlbooks

Applied Machine Learning with Python Book @pythonlbooks
Applied Machine Learning with Python Book @pythonlbooks

Hands-On Data Analysis with Pandas - 2019 @datascienceiot

Учим Python, делая крутые игры, 4-е издание Book @pythonlbooks
Учим Python, делая крутые игры, 4-е издание Book @pythonlbooks

Invent Your Own Computer Games with Python @pythonlbooks

Automate the boring stuff with Python (2019) @pythonlbooks

Data Science and Analytics with Python @pythonlbooks

Designing Machine Learning Systems with Python @pythonlbooks

The Practice of Computing Using Python, 3rd Edition @pythonlbooks

Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python @pythonlbooks

The Python 3 Standard Library by Example @pythonlbooks

How to Tango with Django @pythonlbooks

Python 3 и PyQt 5. Разработка приложений - 2020 @pythonlbooks

Теоретический минимум по Big Data. Всё, что нужно знать о больших данных @datascienceiot

Mastering OpenCV 4 with Python - 2019 Github @pythonlbooks
Mastering OpenCV 4 with Python - 2019 Github @pythonlbooks

Learn Data Analysis with Python: Lessons in Coding Book @pythonlbooks
Learn Data Analysis with Python: Lessons in Coding Book @pythonlbooks

Serious Python - 2019 Book @pythonlbooks
Serious Python - 2019 Book @pythonlbooks

Generative Adversarial Networks with Python Book @pythonlbooks
Generative Adversarial Networks with Python Book @pythonlbooks