choiiljoo4342

投資講義ではありません。証券データを通じたデータ収集、分析、可視化を扱います。多様なデータフォーマットを扱い、様々なテキスト前処理技法を習得します。時系列データの可視化技法やスケールの表現方法、株価データを解釈するためのいくつかの技法を扱います。この講義は、データ分析を通じてインサイトを得る方法を学んでいく講座です。株価データを通じて学んだ内容を、時系列が活用される需要量、在庫量、販売量、トラフィック量などのデータの収集、分析、可視化に活用できるように構成されています。

todaycode

2026 새해 복 마🐴니 할인

Pythonによる証券データの収集と分析でシグナルとノイズを見分ける

This is not an investment lecture. It covers data collection, analysis, and visualization using stock market data. You will work with various data formats and learn various text preprocessing techniques. It covers visualization techniques for time-series data, methods for representing scales, and several techniques for interpreting stock price data. This course is about learning how to gain insights through data analysis. It is structured so that the concepts learned through stock price data can be applied to collecting, analyzing, and visualizing other time-series data such as demand, inventory, sales, and traffic volume.

입문

초급

중급이상

파이썬

Python

플로틀리

Plotly

판다스

Pandas

넘파이

Numpy

씨본

Seaborn

Finding Signals and Noise through Python Stock Data Collection and Analysis

(1) Finding Signals and Noise with Securities Data

(2.1) Collect all KRX stocks

(2.2) Analysis of All KRX Listed Stocks

(3.1) Collecting daily quotes with FinanceDataReader

(3.2) Comparing Returns of Multiple Stocks

(3.3) Web Crawling? Web Scraping! Collecting Stock Prices Directly with a Few Lines of Code

(3.4) Visualization of daily prices using plotly

(4.1) Collecting all ETF items

(4.2) Data Preprocessing for All ETF Items Collected

(4.3) Analysis of All ETF Items

(5.1) Sector/Theme Collection

(5.2) Industry/Theme Preprocessing

(5.3) Industry Theme Analysis

(6.1) Technical Analysis and Auxiliary Indicators

(6.2) Volatility Indicators - Bollinger Bands

(6.3) Momentum Indicator - RSI

(6.4) Trend Indicators - MACD

(6.5) Increasing productivity with pandas and plotly through cufflinks

Congratulations on making it this far!