lisc.data.ArticlesAll

class lisc.data.ArticlesAll(articles, exclusions=None)[source]

An object to hold term data, aggregated across articles.

Attributes
labelstr

The label for the current term.

termTerm

Definition of the search term, with inclusion and exclusion words.

has_databool

Whether the current object contains data.

n_articlesint

The number of articles included in the object.

idslist of int

Article ids for all articles included in object.

journalscollections.Counter

Frequency distribution for each journal.

authorscollections.Counter

Frequency distribution for each author.

first_authorscollections.Counter

Frequency distribution for each first author.

last_authorscollections.Counter

Frequency distribution for each last author.

wordscollections.Counter

Frequency distribution of all words.

keywordscollections.Counter

Frequency distribution of all keywords.

yearscollections.Counter

Frequency distribution for each year of publication.

doislist of str

DOIs of each article included in object.

summarydict

A summary of the data associated with the current object.

__init__(articles, exclusions=None)[source]

Initialize ArticlesAll object.

Parameters
articlesArticles

Data for all articles from a given search term.

exclusionslist of str, optional

Words to exclude from the word collections.

Examples

Create an ArticlesAll object from an Articles object:

>>> from lisc.data import Articles
>>> articles = Articles('frontal lobe')
>>> articles_all = ArticlesAll(articles)

Methods

__init__(articles[, exclusions])

Initialize ArticlesAll object.

check_frequencies([data_type, n_check])

Prints out the most common items in a frequency distribution.

clear()

Clear all data attached to object.

create_summary()

Fill the summary dictionary of the current terms Words data.

print_summary()

Print out a summary of the collected words data.

save_summary([directory])

Save out a summary of the collected words data.

Attributes

has_data

Whether the current object contains data.

label

The label for the current term.

n_articles

The number of articles included in the object.

check_frequencies(data_type='words', n_check=20)[source]

Prints out the most common items in a frequency distribution.

Parameters
data_type{‘words’, ‘keywords’}

Which frequency distribution to check.

n_checkint, optional, default: 20

Number of most common items to print out.

Examples

Print the most frequent words, assuming an initialized ArticlesAll object with data:

>>> articles_all.check_frequencies() 
clear()

Clear all data attached to object.

create_summary()[source]

Fill the summary dictionary of the current terms Words data.

Examples

Create a summary for a term, assuming an initialized ArticlesAll object with collected Words data:

>>> articles_all.create_summary() 
property has_data

Whether the current object contains data.

property label

The label for the current term.

property n_articles

The number of articles included in the object.

print_summary()[source]

Print out a summary of the collected words data.

Examples

Print a summary for a term, assuming an initialized ArticlesAll object with data:

>>> articles_all.create_summary() 
>>> articles_all.print_summary() 
save_summary(directory=None)[source]

Save out a summary of the collected words data.

Parameters
directorystr or SCDB or None, optional

Folder or database object specifying the save location.

Examples

Save a summary for a term, assuming an initialized ArticlesAll object with data:

>>> articles_all.create_summary() 
>>> articles_all.save_summary() 

Examples using lisc.data.ArticlesAll

Tutorial 02: Words Analysis

Tutorial 02: Words Analysis