/
bibliography.bib
91 lines (82 loc) · 2.72 KB
/
bibliography.bib
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
@article{perkel2020,
title = {Streamline your writing {\textemdash} and collaborations {\textemdash} with these reference managers},
author = {{Perkel}, {Jeffrey M.}},
year = {2020},
month = {09},
date = {2020-09-01},
journal = {Nature},
pages = {149--150},
volume = {585},
number = {7823},
doi = {10.1038/d41586-020-02491-2},
url = {http://dx.doi.org/10.1038/d41586-020-02491-2},
langid = {en}
}
@article{perkel2018,
title = {Why Jupyter is data scientists{\textquoteright} computational notebook of choice},
author = {{Perkel}, {Jeffrey M.}},
year = {2018},
month = {10},
date = {2018-10-30},
journal = {Nature},
pages = {145--146},
volume = {563},
number = {7729},
doi = {10.1038/d41586-018-07196-1},
url = {http://dx.doi.org/10.1038/d41586-018-07196-1},
langid = {en}
}
@article{perkel2018a,
title = {A toolkit for data transparency takes shape},
author = {{Perkel}, {Jeffrey M.}},
year = {2018},
month = {08},
date = {2018-08},
journal = {Nature},
pages = {513--515},
volume = {560},
number = {7719},
doi = {10.1038/d41586-018-05990-5},
url = {http://dx.doi.org/10.1038/d41586-018-05990-5},
langid = {en}
}
@article{perkel2021,
title = {Reactive, reproducible, collaborative: computational notebooks evolve},
author = {{Perkel}, {Jeffrey M.}},
year = {2021},
month = {05},
date = {2021-05-03},
journal = {Nature},
pages = {156--157},
volume = {593},
number = {7857},
doi = {10.1038/d41586-021-01174-w},
url = {http://dx.doi.org/10.1038/d41586-021-01174-w},
langid = {en}
}
@article{shen2014,
title = {Interactive notebooks: Sharing the code},
author = {{Shen}, {Helen}},
year = {2014},
month = {11},
date = {2014-11},
journal = {Nature},
pages = {151--152},
volume = {515},
number = {7525},
doi = {10.1038/515151a},
url = {http://dx.doi.org/10.1038/515151a},
langid = {en}
}
@book{xieMarkdownCookbook2020,
title = {R {{Markdown Cookbook}}},
author = {Xie, Yihui and Dervieux, Christophe and Riederer, Emily},
year = {2020},
month = oct,
series = {The {{R Series}}},
publisher = {{Chapman and Hall/CRC}},
abstract = {This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other documents or chunks, control the formatting with customer templates, fine-tune how your code is processed, and incorporate multiple languages into your analysis.},
isbn = {978-0-367-56383-7},
langid = {english},
file = {/Users/jpn8428/Zotero/storage/SL4UARXZ/rmarkdown-cookbook.html}
}