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1
Intro
2
Installing Libraries
3
DataFrames
4
Columns
5
Stock Tickers
6
Save to CSV
7
Test
8
Stocks not downloaded
9
Getting all the stocks
10
Plotting the stocks
11
Daily return
12
Merge Data Frames
13
Cumulative Returns
14
Volume Data
Description:
Dive into a comprehensive 45-minute tutorial on getting started with Technical Analysis using Python and various data science libraries. Learn how to download stock data, perform calculations, and create customizable charts for stock market predictions. Master essential skills including working with libraries, converting CSV files to DataFrames, plotting price changes, calculating daily and cumulative returns, and visualizing return on investment and volume data. Gain hands-on experience with real-time data analysis and chart pattern recognition to enhance your understanding of financial markets and technical analysis techniques.

Getting Started with Technical Analysis Using Python

Derek Banas
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