text_plain_output_1.png
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

TABLEFORMAT = pd.read_csv('../input/CORD-19-research-challenge/Kaggle/list_of_tables_and_table_formats.csv')
t = TABLEFORMAT[0:5]

df1 = pd.read_csv('../input/CORD-19-research-challenge/metadata.csv')
df1.shape

journals = df1[['title', 'abstract', 'publish_time', 'url', 'authors']]
journals['words'] = journals.abstract.str.strip().str.split('[\\W_]+')

abstracts = journals[journals.words.str.len() > 0]
abstracts.to_csv('COVID19_Journal_Abrstracts.csv')

abstracts.shape

Q1A = abstracts[abstracts['abstract'].str.contains('communicating')]
Q1A.shape

Q1B = abstracts[abstracts['abstract'].str.contains('reaching out')]
Q1B

Q1C = abstracts[abstracts['abstract'].str.contains('contacting')]
Q1C.shape

Q1D = abstracts[abstracts['abstract'].str.contains('elderly')]
Q1D.shape

Q1D = abstracts[abstracts['abstract'].str.contains('health care workers')]
Q1D.shape

Q1E = abstracts[abstracts['abstract'].str.contains('risk population')]
Q1E.shape

Question1 = pd.concat([Q1A, Q1B, Q1C, Q1D, Q1E])
Question1.dropna(inplace=True)
Question1.shape

q5a = abstracts[abstracts['abstract'].str.contains('not reach')]
q5a.shape

q5b = abstracts[abstracts['abstract'].str.contains('improve access')]
q5b.shape

q5c = abstracts[abstracts['abstract'].str.contains('access to resource')]
q5c.shape

q5e = abstracts[abstracts['abstract'].str.contains('faulty')]
q5e.shape

q5f = abstracts[abstracts['abstract'].str.contains('meet demand')]
q5f.shape

q5g = abstracts[abstracts['abstract'].str.contains('waste')]
q5g.shape

Question5 = pd.concat([q5a, q5b, q5c, q5b, q5e, q5f, q5g])
Question5.dropna(inplace=True)
Question5.shape

StudiesDictionary = {'url': ['https://www.cdc.gov/coronavirus/2019-ncov/covid-data/serology-surveillance/index.html', 'https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30854-0/fulltext', 'https://iussp.org/fr/node/11297', 'https://www.nejm.org/doi/full/10.1056/NEJMp2006761', 'https://www.vox.com/2020/4/24/21229415/coronavirus-antibody-testing-covid-19-california-survey', 'https://www.statnews.com/2020/04/04/cdc-launches-studies-to-get-more-precise-count-of-undetected-covid-19-cases/', 'https://ourworldindata.org/coronavirus', 'https://www.360dx.com/infectious-disease/new-york-california-serology-studies-give-early-estimates-covid-19-prevalence', 'https://www.popcouncil.org/research/responding-to-the-COVID-19-pandemic', 'https://www.nature.com/articles/s41591-020-0883-7']}

StudiesDF = pd.DataFrame.from_dict(StudiesDictionary)
StudiesDF