uz
Feedback
Python for Data Analysts

Python for Data Analysts

Kanalga Telegram’da o‘tish

Find top Python resources from global universities, cool projects, and learning materials for data analytics. For promotions: @coderfun Useful links: heylink.me/DataAnalytics

Ko'proq ko'rsatish

📈 Telegram kanali Python for Data Analysts analitikasi

Python for Data Analysts (@pythonanalyst) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 51 853 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 495-o'rinni va Hindiston mintaqasida 6 790-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 51 853 obunachiga ega bo‘ldi.

30 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 94 ga, so‘nggi 24 soatda esa 10 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 3.85% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.96% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 1 994 marta ko‘riladi; birinchi sutkada odatda 499 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 6 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent visualization, panda, analyst, sql, analytic kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Find top Python resources from global universities, cool projects, and learning materials for data analytics. For promotions: @coderfun Useful links: heylink.me/DataAnalytics

Yuqori yangilanish chastotasi (oxirgi ma’lumot 31 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

51 853
Obunachilar
+1024 soatlar
+77 kunlar
+9430 kunlar
Postlar arxiv
02 - Setup the Programming Environment

01 - Course Introduction

🔰 Python Programming: The Complete Python Bootcamp 2023 https://t.me/pythonanalyst/59 🌟 4.4 - 1838 votes 💰 Original Price:
🔰 Python Programming: The Complete Python Bootcamp 2023 https://t.me/pythonanalyst/59 🌟 4.4 - 1838 votes 💰 Original Price: $74.99 Python from Scratch. Learn Data Science and Visualization, Automation, Excel, SQL and Scraping with Python.100% Hands-On Taught By: Andrei Dumitrescu, Crystal Mind Academy Download Full Course: https://t.me/pythonanalyst/59 Download All Courses: https://t.me/pythonfreebootcamp

📈 Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide The process of building a stock price predicti
+8
📈 Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide The process of building a stock price prediction model using Python. 1. Import required modules 2. Obtaining historical data on stock prices 3. Selection of features. 4. Definition of features and target variable 5. Preparing data for training 6. Separation of data into training and test sets 7. Building and training the model 8. Making forecasts 9. Trading Strategy Testing

Intermediate Python.pdf3.58 MB

Big Data Analytics_ A Hands-On Approach ( PDFDrive ).pdf

Python Variables: How to Define/Declare String Variable Types What is a Variable in Python? A Python variable is a reserved memory location to store values. In other words, a variable in a python program gives data to the computer for processing. Python Variable Types Every value in Python has a datatype. Different data types in Python are Numbers, List, Tuple, Strings, Dictionary, etc. Variables in Python can be declared by any name or even alphabets like a, aa, abc, etc. How to Declare and use a Variable Let see an example. We will define variable in Python and declare it as “a” and print it. 1 a=100 2 print (a)

🔹 Statistics in Python

📚 Title: Statistics and Data Visualisation with Python (2023)

14. Appendix Python Special Offers

13. Appendix Web Scraping with Python

12. Appendix SQL and Python

11. Appendix Statistics Overview

10. Machine Learning - Part 03

10. Machine Learning - Part 02

10. Machine Learning - Part 01

9. Example Projects - Part 02

9. Example Projects - Part 01

8. Data Visualization

7. Working with Data Part 3