The goal of this paper is to match Table 1 papers and publications with Table 2 publications and their indicators.
Use pandas merge function to realize left outer join of table. Left outer join is the outer join of the left table, the left table remains unchanged, matching the rows of the right table (after merging the right table can exist null values).
paperPublicationIndicator = (paperPublication,publicationIndicator,
how='left',left_on='Publications',right_on='Name',sort=False)
It was found that there were 13 more rows in the linked table than in Table 1 for paper publications. Exploration reveals that there are duplicate rows for publications such as Publication A-Indicator 1 and Publication A-Indicator 2 in Table 2 Publication Indicator Information. This occurs after matching:
publications name (of a thing) norm publicationsA publicationsA norm1 publicationsA publicationsA norm2 # Redundant lines
The option is to pre-delete the duplicate publication information in Table 2, Publication Indicators.
publicationIndicator.drop_duplicates(subset=['Name'], keep='first',inplace=True)
That way the result is not a problem.
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