| 000 | 00970camuu2200277 a 4500 | |
| 001 | 000045561404 | |
| 005 | 20091125110105 | |
| 008 | 090406s2009 caua b 001 0 eng d | |
| 020 | ▼a 9781430218432 (pbk.) | |
| 020 | ▼a 1430218436 (pbk.) | |
| 020 | ▼a 9781430218449 (electronic) | |
| 035 | ▼a (KERIS)BIB000011622612 | |
| 040 | ▼a 211032 ▼c 211032 ▼d 211009 | |
| 082 | 0 4 | ▼a 005.13/3 ▼2 22 |
| 090 | ▼a 005.133 ▼b V131b | |
| 100 | 1 | ▼a Vaingast, Shai. |
| 245 | 1 0 | ▼a Beginning Python visualization : ▼b crafting visual transformation scripts / ▼c Shai Vaingast. |
| 260 | ▼a Berkeley, CA : ▼b Apress , ▼c c2009. | |
| 300 | ▼a xx, 363 p. : ▼b ill. ; ▼c 24 cm. | |
| 490 | 1 | ▼a Expert's voice in open source |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Python (Computer program language) |
| 650 | 0 | ▼a Object-oriented programming (Computer science) |
| 830 | 0 | ▼a Expert's voice in open source. |
| 945 | ▼a KINS |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 005.133 V131b | 등록번호 121187109 (6회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
We are visual animals. But before we can see the world in its true splendor, our brains, just like our computers, have to sort and organize raw data, and then transform that data to produce new images of the world. Beginning Python Visualization: Crafting Visual Transformation Scripts discusses turning many types of small data sources into useful visual data. And, you will learn Python as part of the bargain.
Data visualization is one of the sleeping giants of computer book publishing. This book teaches data visualization without academic or theoretical baggage. It is a practical book aimed at IT personnel, programmers, engineers, economists and hobbyists.
I was always drawn to math and computers, ever since I was a kid playing computer games on my Sinclair ZX81. When I attended university, I had a special interest in numerical ana- sis, a field that I felt combines math and computers ideally. During my career, I learned of MATLAB, widely popular for digital signal processing, numerical analysis, and feedback and control. MATLAB’s strong suits include a high-level programming language, excellent gra- ing capabilities, and numerous packages from almost every imaginable engineering field. But I found that MATLAB wasn’t enough. I worked with very large files and needed the ability to manipulate both text and data. So I combined Perl, AWK, and Bash scripts to write programs that automate data analysis and visualization. And along the way, I’ve developed practices and ideas involving the organization of data?for example, ways to ensure file names are unique and self-explanatory. With the increasing popularity of the Internet, I learned of GNU/Linux and the open source movement. I made an effort to use open source software whenever possible, and so I’ve learned of GNU-Octave and gnuplot, which together provide excellent scientific computing functionality. That fit well on my Linux machine: Bash scripts, Perl and AWK, GNU-Octave and gnuplot. Knowing I was interested in programming languages and open source software, a friend suggested I give Python a try.
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