Stock Market Case Study: Analyzing Sales Data with Python [Tutorial] | Data Analysis with Python

Welcome to our comprehensive tutorial on analyzing sales data in the stock market using Python! In this video, we delve into real-world case studies and demonstrate how to leverage Python's powerful data analysis libraries to gain valuable insights.

🔎 Boost your data analysis skills: Follow along as we tackle challenging problem statements and provide step-by-step solutions, empowering you to make informed decisions when it comes to stock market investments.

⭐ Key Topics Covered ⭐
-- Importing and preprocessing sales data
-- Exploratory data analysis techniques
-- Visualizing sales trends and patterns
-- Performing statistical analysis on stock market data
-- Implementing forecasting models for predictive insights
💡 Whether you're a beginner or an experienced analyst, this tutorial is designed to cater to all skill levels. Gain hands-on experience and learn how to use popular Python libraries like Pandas, Matplotlib, and NumPy to efficiently process and analyze sales data.

📈 Unlock the potential of your investment strategies with actionable insights derived from data-driven analysis. Join us on this exciting journey and discover how Python can revolutionize your approach to the stock market.

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🔗 Helpful resources mentioned in the video:

0:00 Intro
4:12 Import Data
5:47 Analyzing closing price of all the stocks
11:25 Visualization
28:45 Analyze daily price change in stock
32:22 Analyze daily stock returns
39:22 Analyze monthly mean of close column
43:32 Visualization
46:09 Resampling close column Month/year wise
51:50 Checking if the Stock prices of these tech companies are correlated
54:52 Visualization
1:02:34 Recap

[ashutoshanand]

Hi
Hi team

I was trying to get the names of stocks that hit a new high on a particular day listed in NSE or BSE, but it didn't work. If you know how to get the result, it would be really helpful if you could share it