Term Coverage of Dietary Supplements in Product Labels

Wang, Yefeng
2016-07-07
Thumbnail Image

Persistent link to this item

http://doi.org/10.13020/D6GW2G
 https://hdl.handle.net/11299/181275
Statistics
View Statistics

Keywords

Collection period

2016-02-01
2016-03-10

Date completed

2016-07-07

Date updated

Time period coverage

Geographic coverage

Source information

Dietary Supplement Label Database (DSLD)

Journal Title

Journal ISSN

Volume Title

Title

Term Coverage of Dietary Supplements in Product Labels

Published Date

2016-07-07

Authors

Group

Author Contact

Wang, Yefeng
wang4688@umn.edu

Type

Dataset
Programming Software Code

Abstract

The data includes the Python source code for downloading, extracting and normalizing the dietary supplement ingredients information in Dietary Supplement Label Database (DSLD). Moreover, the output of the normalizing results is also included.

Description

Includes lstProducts.csv, Python scripts (version 3), and output text files. See Readme.txt for more detail.

Referenced by

Term Coverage of Dietary Supplements in Product Labels - AMIA 2016 Manuscript
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5333301/

Related to

Replaces

item.page.isreplacedby

License

Publisher

Collections

Data Repository for U of M (DRUM)

Funding information

item.page.sponsorshipfunderid

item.page.sponsorshipfundingagency

item.page.sponsorshipgrant

Previously Published Citation

Other identifiers

Suggested citation

Wang, Yefeng. (2016). Term Coverage of Dietary Supplements in Product Labels. Retrieved from the Data Repository for the University of Minnesota (DRUM), http://doi.org/10.13020/D6GW2G.

View/Download File

File View/Open
Description
Size
Readme.txt
Text file describing the scripts and other files included in this dataset
(2.64 KB)

InfoDownload.py
Python source code for downloading information from DSLD
(1.85 KB)

type_stat.py
Code for counting the ingredient number under each LanguaL(TM) category
(1.34 KB)

ingrTypeStat.py
Code for retrieving the ingredient category, and counting ingredients under each category
(1.87 KB)

type_print.py
Code that uses output from InfoDownload.py to create SupType.csv.
(1.95 KB)

new_suptypelist.py
Code that defines regular expression filters and performs normalization.
(5.61 KB)

lstProducts.csv
CSV needed to execute the Python scripts
(17.39 MB)

amino acid.txt
Normalized ingredients - Amino Acid
(21.26 KB)

amino acid_new.txt
Comparison between original and normalized ingredients - amino acid
(1.03 MB)

animal part or source.txt
Normalized ingredients - Animal Source or Parts
(6.2 KB)

animal part or source_new.txt
Comparison between original and normalized ingredients - animal part or source
(83.38 KB)

bacteria.txt
Normalized ingredients - Bacteria
(11.26 KB)

bacteria_new.txt
Comparison between original and normalized ingredients - bacteria
(503.06 KB)

blend.txt
Normalized ingredients - Blend
(3.43 KB)

blend_new.txt
Comparison between original and normalized ingredients - blend
(41.84 KB)

botanical.txt
Normalized ingredients - Botanical
(125.32 KB)

botanical_new.txt
Comparison between original and normalized ingredients - botanical
(4.74 MB)

carbohydrate.txt
Normalized ingredients - Carbohydrate
(1.84 KB)

carbohydrate_new.txt
Comparison between original and normalized ingredients - carbohydrate
(529.58 KB)

chemical_new.txt
Comparison between original and normalized ingredients - chemical
(1.01 MB)

chemical.txt
Normalized ingredients - Chemical
(28.31 KB)

element.txt
Normalized ingredients - Element
(1.57 KB)

element_new.txt
Comparison between original and normalized ingredients - element
(404.15 KB)

enzyme.txt
Normalized ingredients - Enzyme
(8.55 KB)

enzyme_new.txt
Comparison between original and normalized ingredients - enzyme
(357.43 KB)

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.