Project Name: Implement Data Cleaning on Time Series Data (Stock Prices) with a Project

Project Name: Implement Data Cleaning on Time Series Data (Stock Prices) with a Project

Description: This project involves working with real-world stock market price data: the Stock Market Dataset by Jackson Crow on Kaggle. The dataset contains daily historical price information for all currently traded stocks on the NASDAQ exchange. Each CSV file corresponds to a different company (e.g., AAPL.csv for Apple Inc.).

Table of Contents:
Clean missing timestamps
Handle nontrading days
Smooth out anomalies in the data using rolling window methods

Goal:
The goal of this project is to clean and prepare stock market price data for time series analysis. We will do this by adding missing calendar dates to reveal gaps in the data (e.g., weekends, holidays), filling in stock prices on non-trading days, and detecting anomalies in stock prices using rolling window methods

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