臺灣職業籃球聯盟 P. LEAGUE+

爬蟲數據分析與視覺化

    專案簡介： 

開發一個以 Python 和 Flask 為基礎的 Web 應用，實現對 P. LEAGUE+ 球員數據的爬蟲、分析和視覺化展示。 

    主要功能：

• 使用 Python 實現網頁爬蟲，從 P. LEAGUE+ 官方網站抓取球員數據。 
• 對爬取的數據進行整理、分析，找出球員表現的關鍵指標。 
• 運用資料視覺化工具 (此處使用chart.js) 將分析結果製作成圖表，以直觀展示球員表現。 
• 使用 Flask 開發 Web 應用，將爬蟲、分析和視覺化功能整合到一個網站平台。

    成果與影響：

• 開發出一個具有爬蟲、資料分析和視覺化功能的 Web 應用，為 P. LEAGUE+ 籃球迷提供了一個便捷的數據查詢工具。 
• 通過實踐，熟練掌握了 Python 網頁爬蟲、資料分析和視覺化技巧，提升自己在資料科學領域的技能。 
• 學習了如何使用 Flask 框架開發 Web 應用，為未來類似項目的開發奠定了基礎。

    專案簡介：

• 在碩士論文中使用Python進行資料分析和視覺化處理。
• 應用Pandas套件對數據進行分析和探索，並將資料視覺化。
• 完成三種樣品的吸收光譜分析、振動頻率與半徑隨時間的變化分析，以及三種樣品波長在波長627.5 nm之振動頻率強度隨時間變化的分析。

    主要功能：

• 使用Python和Pandas套件，對大量數據進行快速和準確的分析和探索。
• 能夠利用視覺化工具將數據呈現出來，幫助更容易地理解和應用數據。
• 能夠進行吸收光譜、振動頻率和強度等數據的分析，以及對數據中的趨勢和變化進行詳細的探索。

    成果與影響：

• 在碩士論文中，我使用Python和Pandas套件成功地完成了資料分析和視覺化處理，並得出了有意義的結論和發現。
• 培養獨立研究、解決問題、理解數據、學習和應用新技術能力。

Taiwan Professional Basketball League P. LEAGUE+ Web Scraping

Data Analysis, and Visualization 

Project Description:

Develop a web application based on Python and Flask to crawl, analyze and visualize player data for P. LEAGUE+.

Main functions:

1. Use Python to implement web crawling, fetching player data from P. LEAGUE+ official website.
2. Organize and analyze the collected data to identify key performance indicators for each player.
3. Use data visualization tools (such as chart.js) to create charts that provide an intuitive display of player performance.
4. Use Flask to develop the web application and integrate crawling, analysis, and visualization functions into one platform.

Results and Impact:

1. Developed a web application with web crawling, data analysis, and visualization functions, providing a convenient data query tool for P. LEAGUE+ basketball fans.
2. Through practice, gained proficiency in Python web crawling, data analysis, and visualization techniques, improving skills in the field of data science.
3. Learned how to use the Flask framework to develop web applications, laying a foundation for future similar projects.

Project Description:

• Conducted data analysis and visualization using Python in a master's thesis.
• Utilized the Pandas package for data analysis and exploration, and visualized the data.
• Completed absorption spectrum analysis, frequency and radius changes over time analysis for three samples, as well as analysis of frequency intensity changes over time for three samples at a wavelength of 627.5 nm.

Main Responsibilities:

• Utilize Python and the Pandas package to perform fast and accurate analysis and exploration of large amounts of data.
• Utilize visualization tools to present data in a way that is easier to understand and apply.
• Perform analysis of data including absorbance spectra, vibration frequency, intensity, and detailed exploration of trends and changes within the data.

Results and Impact:

• In my master's thesis, I successfully completed data analysis and visualization using Python and Pandas, and drew meaningful conclusions and findings.
• Cultivated abilities in independent research, problem-solving, understanding data, learning and applying new technologies.