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Every Antibiotic

A CodeSights flagship for the medical crowd: 540 antimicrobial drugs with their drug class, discovery and introduction years, discoverers, administration routes, ATC codes, trade names and a WHO Essential Medicines flag. The story the columns tell is the antibiotic discovery void every pharmacology lecture mourns: among the drugs whose articles state a discovery year, the golden age of the 1940s through 1970s outnumbers everything since 1980 by more than two to one, by test. Penicillin anchors the era at 1928, discovered by Alexander Fleming; streptomycin follows in 1943. Class comes from the drug's own lead, the self-naming phrase (a macrolide antibiotic, the cephalosporin class) rather than a passing mention, so erythromycin reads as a macrolide and not a penicillin despite the penicillin allergy note in its own first paragraph, by test. Beta-lactams resolve to their specific subclass wherever the lead names one, so cefalexin is a cephalosporin rather than the umbrella term. ATC codes come from the {{Infobox drug}} template, prefix and suffix joined, and every one validates against the WHO ATC grammar by test. The WHO flag is set by membership in the published Essential Medicines list. The roster is the antibiotic category tree crawled to depth, so the famous drugs are all present (penicillin, ciprofloxacin and vancomycin by test), the class vocabulary is a closed set of eighteen families, and no introduction year precedes its discovery year. Eleven acceptance tests.
540 rows 1 file last pulled 2026-10-14
Antibiotics 540 rows × 11 columns
AntibioticAntibiotic_IDClassATC_CodeDiscovered_YearIntroduced_YearDiscovered_ByAdmin_RouteTrade_NamesWHO_EssentialAntibiotic_URL

Questions and answers

What is the Every Antibiotic dataset?

A CodeSights flagship for the medical crowd: 540 antimicrobial drugs with their drug class, discovery and introduction years, discoverers, administration routes, ATC codes, trade names and a WHO Essential Medicines flag. The story the columns tell is the antibiotic discovery void every pharmacology lecture mourns: among the drugs whose articles state a discovery year, the golden age of the 1940s through 1970s outnumbers everything since 1980 by more than two to one, by test. Penicillin anchors the era at 1928, discovered by Alexander Fleming; streptomycin follows in 1943. Class comes from the drug's own lead, the self-naming phrase (a macrolide antibiotic, the cephalosporin class) rather than a passing mention, so erythromycin reads as a macrolide and not a penicillin despite the penicillin allergy note in its own first paragraph, by test. Beta-lactams resolve to their specific subclass wherever the lead names one, so cefalexin is a cephalosporin rather than the umbrella term. ATC codes come from the {{Infobox drug}} template, prefix and suffix joined, and every one validates against the WHO ATC grammar by test. The WHO flag is set by membership in the published Essential Medicines list. The roster is the antibiotic category tree crawled to depth, so the famous drugs are all present (penicillin, ciprofloxacin and vancomycin by test), the class vocabulary is a closed set of eighteen families, and no introduction year precedes its discovery year. Eleven acceptance tests.

How big is the Every Antibiotic dataset?

540 rows in one CSV file, with 11 columns in total: Antibiotic, Antibiotic_ID, Class, ATC_Code, Discovered_Year, Introduced_Year, Discovered_By, Admin_Route, Trade_Names, WHO_Essential, Antibiotic_URL.

Where does the data come from?

It is built by programmatically scraping en.wikipedia.org, last pulled on 2026-10-14. Datasets are versioned; older versions stay downloadable.

Is the dataset free to download?

Yes. Every CodeSights dataset is completely free as a CSV download; a free account is all it takes. Anyone can preview the data without signing in.

Can I see the code that built this dataset?

Yes. The exact Python scraper that built it is viewable on the dataset page by any signed-in member, so every number is reproducible.

Can the data contain errors?

Automated scraping leaves room for error and the underlying sources change over time, so no version is guaranteed accurate or complete. If a number matters, verify it against the original source.

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