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

Network:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert India7 356 Technologies & Applications2 607...

📈 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 51 492 subscribers, ranking 2 607 in the Technologies & Applications category and 7 356 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 51 492 subscribers.

According to the latest data from 08 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 204 over the last 30 days and by -16 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 5.19%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
Post reach: On average, each post receives 2 670 views. Within the first day, a publication typically gains 0 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 9.
Thematic interests: Content is focused on key topics such as visualization, panda, analyst, sql, analytic.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Find top Python resources from global universities, cool projects, and learning materials for data analytics. For promotions: @coderfun Useful links: heylink.me/DataAnalytics”

Thanks to the high frequency of updates (latest data received on 09 June, 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.

51 492

Subscribers

-1624 hours

+447 days

+20430 days

2 670

Post views

No data24 hours

No data48 hours

5.19%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

51 485

Natural Language Processing - 2024 #python #en

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Python Most Important Interview Questions Question 1: Calculate the average stock price for Company X over the last 6 months. Question 2: Identify the month with the highest total sales for Company Y using their monthly sales data. Question 3: Find the maximum and minimum stock price for Company Z on any given day in the last year. Question 4: Create a column in the DataFrame showing the percentage change in stock price from the previous day for Company X. Question 5: Determine the number of days when the stock price of Company Y was above its 30-day moving average. Question 6: Compare the average stock price of Companies X and Z in the first quarter of the year. #Data# ---------------------------------------------- import pandas as pd data = { 'Date': pd.date_range(start='2023-01-01', periods=180, freq='D'), 'CompanyX_StockPrice': pd.np.random.randint(50, 150, 180), 'CompanyY_Sales': pd.np.random.randint(20000, 50000, 180), 'CompanyZ_StockPrice': pd.np.random.randint(70, 200, 180) } df = pd.DataFrame(data)

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PythonCrashCourse.pdf5.38 MB

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150 SQL Queries for Practice 👇👇 https://t.me/DataAnalystInterview/170

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I'm earning real cash from DigiWards, the HIGH PAYING Reward App! You can also earn money by entering my invitation code AQCBFJ to get free 1,000 points. Download DigiWards now to earn big rewards! https://play.google.com/store/apps/details?id=com.digiwards.app

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https://www.linkedin.com/posts/sql-analysts_python-dataanalytics-activity-7135473022206889984-XUxd

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Data Visualization with Python Dr. Pooja, 2023

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Python Data Cleaning Cookbook Michael Walker, 2023

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Python Interview Questions for data analyst interview Question 1: Find the top 5 dates when the percentage change in Company A's stock price was the highest. Question 2: Calculate the annualized volatility of Company B's stock price. (Hint: Annualized volatility is the standard deviation of daily returns multiplied by the square root of the number of trading days in a year.) Question 3: Identify the longest streaks of consecutive days when the stock price of Company A was either increasing or decreasing continuously. Question 4: Create a new column that represents the cumulative returns of Company A's stock price over the year. Question 5: Calculate the 7-day rolling average of both Company A's and Company B's stock prices and find the date when the two rolling averages were closest to each other. Question 6: Create a new DataFrame that contains only the dates when Company A's stock price was above its 50-day moving average, and Company B's stock price was below its 50-day moving average

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Learning Professional Python✅ https://www.linkedin.com/posts/sql-analysts_learn-python-activity-7129340888232714240-ZuMM Like for more 👍❤️

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Python for Everybody Charles R. Severance, 2023

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Profound Python Libraries Onder Teker, 2022

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Building Python Microservices with FastAPI.pdf6.62 MB

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Which of the following is/are immutable in Python?

Anonymous voting

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Python Data Science Handbook Python Data Science Handbook: full text in Jupyter Notebooks. This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. Creator: Jake Vanderplas Stars⭐️: 39k Fork: 17.1K Repo: https://github.com/jakevdp/PythonDataScienceHandbook For more, join https://t.me/pythonanalyst

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Python for Data Analysts - Quick Summary (1).pdf0.64 KB

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Python for Data Analysis Free Resources: Free Course: https://www.freecodecamp.org/learn/data-analysis-with-python/ Practice: https://www.kaggle.com/learn/python

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Master Arrays in 14 days.pdf4.98 MB

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Python for JavaScript Developers.zip233.77 MB

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37 - Building Concurrent Applications Using Async IO