Skillshare - Let's talk about R in Data JournalismSchool of Data
This document provides an introduction to R, an open source statistical computing and graphics programming language. It outlines R's capabilities for data manipulation, visualization, and analysis. It then demonstrates how to install R and RStudio. Several popular R packages for working with data are listed for tasks like obtaining, cleaning, analyzing, and visualizing data. Finally, resources for learning R like tutorials, articles, books, and influential members of the R community are recommended.
Up and Down the Python Data & Web Visualization Stack by Rob Story PyData SV ...PyData
In the past two years, there has been incredible progress in Python data visualization libraries, particularly those built on client-side JavaScript tools such as D3 and Leaflet. This talk will give a brief demonstration of many of the newest charting libs: mpld3 (using Seaborn/ggplot), nvd3-python, ggplot, Vincent, Bearcart, Folium,and Kartograph will be used to visualize a newly-released USGS/FAA wind energy dataset (with an assist from Pandas and the IPython Notebook). After a demo of the current state of Python and web viz, it will discuss the future of how the Python data stack can have seamless interoperability and interactivity with JavaScript visualization libraries.
Matplotlib has wonderfully served the Python community as the cornerstone of scientific graphics. Recently, many additional Python plotting options have surfaced, aimed to make it easier to create graphics that are interactive and web-publishable. These slides outline some of the new options with links to easy-to-follow, IPython notebooks.
TDD is the elengant way of designing software. People scares from it so much, because software design is hard and it requires discipline. In this talk, I tried to describe what TDD is from software design perspective.
Skillshare - Let's talk about R in Data JournalismSchool of Data
This document provides an introduction to R, an open source statistical computing and graphics programming language. It outlines R's capabilities for data manipulation, visualization, and analysis. It then demonstrates how to install R and RStudio. Several popular R packages for working with data are listed for tasks like obtaining, cleaning, analyzing, and visualizing data. Finally, resources for learning R like tutorials, articles, books, and influential members of the R community are recommended.
Up and Down the Python Data & Web Visualization Stack by Rob Story PyData SV ...PyData
In the past two years, there has been incredible progress in Python data visualization libraries, particularly those built on client-side JavaScript tools such as D3 and Leaflet. This talk will give a brief demonstration of many of the newest charting libs: mpld3 (using Seaborn/ggplot), nvd3-python, ggplot, Vincent, Bearcart, Folium,and Kartograph will be used to visualize a newly-released USGS/FAA wind energy dataset (with an assist from Pandas and the IPython Notebook). After a demo of the current state of Python and web viz, it will discuss the future of how the Python data stack can have seamless interoperability and interactivity with JavaScript visualization libraries.
Matplotlib has wonderfully served the Python community as the cornerstone of scientific graphics. Recently, many additional Python plotting options have surfaced, aimed to make it easier to create graphics that are interactive and web-publishable. These slides outline some of the new options with links to easy-to-follow, IPython notebooks.
TDD is the elengant way of designing software. People scares from it so much, because software design is hard and it requires discipline. In this talk, I tried to describe what TDD is from software design perspective.
1. Bài tìm hiểu
Plotly
GVHD: Thầy Lê Đức Long
Thực hiện:
Nguyễn Hoàng Minh – K38.103.011 + Bùi Thị Thảo Nguyên – K38.103.105
Trường Đại học Sư phạm TPHCM
Khoa Công nghệ thông tin
2. Nội dung
• Giới thiệu tổng quan
• Đặc điểm – chức năng
• Lợi ích
• Hướng dẫn sử dụng
• Tài liệu tham khảo
3. Giới thiệu tổng quan
Plotly, công cụ vẽ biểu đồ và phân tích dữ
liệu chính xác và đẹp.
Sử dụng thư viện đồ họa khoa học của
Python, R, MatLab, REST.
Thành lập năm 2012, có trụ sở tại Quebec,
Canada.
4. Lý do sử dụng Plotly:
Hoàn toàn miễn phí, trực tuyến
Thích hợp với nhiều trình duyệt
Plotly cho phép bạn kết hợp với nhiều công cụ để vẽ
đồ thị đẹp hơn
Bạn sẽ có dữ liệu riêng và tự kiểm soát lượng dữ liệu
đó
Nhập dữ liệu từ các tập tin, Dropbox và Google Drive.
Chia sẻ đồ thị trực tuyến, trong bài thuyết trình, hoặc
đến các trang web truyền thông xã hội
5.
6. Lợi ích
Được sử dụng trong nhiều lĩnh vực khác nhau:
giáo dục, công nghiệp (tự động hóa), nghiên cứu
khoa học, báo chí …
