Data Structures for Statistical Computing in Python

# Data Structures for Statistical Computing in Python > OpenAlex Metadata Hub · https://openalex.org/W2342249984 ## Bibliographic - **DOI:** 10.25080/majora-92bf1922-00a - **Year:** 2010 - **Citations:** 11335 - **Open Access:** Yes (hybrid) - **License:** cc-by - **Source:** http://conference.scipy.org/proceedings/scipy2010/pdfs/mckinney.pdf ## Authors - Wes McKinney ## Abstract In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets and to provide a set of fundamental building blocks for implementing statistical models. We will discuss specific design issues encountered in the course of developing pandas with relevant examples and some comparisons with the R language. We conclude by discussing possible future directions for statistical computing and data analysis using Python. ## Keywords Python (programming language), Computer science, Data science, Data exploration, Statistical analysis, Data structure, Computational statistics, Theoretical computer science, Data mining, Software engineering, Programming language, Machine learning, Statistics, Visualization, Mathematics ## Concepts - Python (programming language) - Computer science - Data science - Data exploration - Statistical analysis - Data structure - Computational statistics - Theoretical computer science - Data mining - Software engineering - Programming language - Machine learning - Statistics - Visualization - Mathematics --- *Metadata only — full text not imported unless Open Access license permits.*

Bài “Data Structures for Statistical Computing in Python” được TradingBase chuyển thành Knowledge Product cho trader — không phải trang đọc abstract OpenAlex. Tóm lược học thuật (đã diễn giải): In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets and to provide a set of fundamental building blocks for implementing statistical models. We will discuss specific design issues encountered in the course of developing pandas with relevant examples and some comparisons with the R language. We conclude by discussing possible future directions for statistical computing and data analysis using Python. Phần Trading Insights bên dưới nối nghiên cứu với Forex, vàng, USD, lãi suất và risk regime — để bạn đưa vào journal và playbook. Metadata DOI/OA chỉ là rail tham chiếu; nội dung chính là summary, takeaways và ứng dụng thị trường do Content Factory sinh.