{"id":"https://openalex.org/W2342249984","doi":"https://doi.org/10.25080/majora-92bf1922-00a","title":"Data Structures for Statistical Computing in Python","display_name":"Data Structures for Statistical Computing in Python","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2342249984","doi":"https://doi.org/10.25080/majora-92bf1922-00a","mag":"2342249984"},"language":"en","primary_location":{"id":"doi:10.25080/majora-92bf1922-00a","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-92bf1922-00a","pdf_url":"http://conference.scipy.org/proceedings/scipy2010/pdfs/mckinney.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"http://conference.scipy.org/proceedings/scipy2010/pdfs/mckinney.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067080427","display_name":"Wes McKinney","orcid":null},"institutions":[{"id":"https://openalex.org/I139787848","display_name":"Capital University","ror":"https://ror.org/00jy9e726","country_code":"US","type":"education","lineage":["https://openalex.org/I139787848"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wes McKinney","raw_affiliation_strings":["AQR Capital Management, LLC"],"affiliations":[{"raw_affiliation_string":"AQR Capital Management, LLC","institution_ids":["https://openalex.org/I139787848"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5067080427"],"corresponding_institution_ids":["https://openalex.org/I139787848"],"apc_list":null,"apc_paid":null,"fwci":0.4664,"has_fulltext":true,"cited_by_count":10898,"citation_normalized_percentile":{"value":0.7639931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"56","last_page":"61"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.9194616675376892},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8150767087936401},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5058676600456238},{"id":"https://openalex.org/keywords/data-exploration","display_name":"Data exploration","score":0.5004072189331055},{"id":"https://openalex.org/keywords/statistical-analysis","display_name":"Statistical analysis","score":0.4935344457626343},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.4334874749183655},{"id":"https://openalex.org/keywords/computational-statistics","display_name":"Computational statistics","score":0.42341333627700806},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38464733958244324},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3778475522994995},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.3555530905723572},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.3114299476146698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2478111982345581},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09578320384025574},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.08662164211273193},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08034166693687439}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.9194616675376892},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8150767087936401},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5058676600456238},{"id":"https://openalex.org/C2780977526","wikidata":"https://www.wikidata.org/wiki/Q42417149","display_name":"Data exploration","level":3,"score":0.5004072189331055},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.4935344457626343},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.4334874749183655},{"id":"https://openalex.org/C176222170","wikidata":"https://www.wikidata.org/wiki/Q5157340","display_name":"Computational statistics","level":2,"score":0.42341333627700806},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38464733958244324},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3778475522994995},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3555530905723572},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.3114299476146698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2478111982345581},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09578320384025574},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.08662164211273193},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08034166693687439}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.25080/majora-92bf1922-00a","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-92bf1922-00a","pdf_url":"http://conference.scipy.org/proceedings/scipy2010/pdfs/mckinney.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.25080/majora-92bf1922-00a","is_oa":true,"landing_page_url":"https://doi.org/10.25080/majora-92bf1922-00a","pdf_url":"http://conference.scipy.org/proceedings/scipy2010/pdfs/mckinney.pdf","source":{"id":"https://openalex.org/S4220651651","display_name":"Proceedings of the Python in Science Conferences","issn_l":"2575-9752","issn":["2575-9752"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Python in Science Conference","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2342249984.pdf","grobid_xml":"https://content.openalex.org/works/W2342249984.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W2318935314","https://openalex.org/W2582743722"],"related_works":["https://openalex.org/W2012207548","https://openalex.org/W102383008","https://openalex.org/W2023740799","https://openalex.org/W2319685803","https://openalex.org/W3145895147","https://openalex.org/W4200282234","https://openalex.org/W2048297633","https://openalex.org/W2006526444","https://openalex.org/W2369846593","https://openalex.org/W2013803548"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"are":[4],"concerned":[5],"with":[6,12,33,63,69],"the":[7,58,70],"practical":[8],"issues":[9,55],"of":[10,42,60],"working":[11,32],"data":[13,35,84],"sets":[14,36],"common":[15],"to":[16,30,38],"finance,":[17],"statistics,":[18],"and":[19,37,66,83],"other":[20],"related":[21],"fields.":[22],"pandas":[23,62],"is":[24],"a":[25,40],"new":[26],"library":[27],"which":[28],"aims":[29],"facilitate":[31],"these":[34],"provide":[39],"set":[41],"fundamental":[43],"building":[44],"blocks":[45],"for":[46,80],"implementing":[47],"statistical":[48,81],"models.":[49],"We":[50,73],"will":[51],"discuss":[52],"specific":[53],"design":[54],"encountered":[56],"in":[57],"course":[59],"developing":[61],"relevant":[64],"examples":[65],"some":[67],"comparisons":[68],"R":[71],"language.":[72],"conclude":[74],"by":[75],"discussing":[76],"possible":[77],"future":[78],"directions":[79],"computing":[82],"analysis":[85],"using":[86],"Python.":[87]},"counts_by_year":[{"year":2026,"cited_by_count":468},{"year":2025,"cited_by_count":1861},{"year":2024,"cited_by_count":1672},{"year":2023,"cited_by_count":1611},{"year":2022,"cited_by_count":1471},{"year":2021,"cited_by_count":1405},{"year":2020,"cited_by_count":1074},{"year":2019,"cited_by_count":571},{"year":2018,"cited_by_count":361},{"year":2017,"cited_by_count":184},{"year":2016,"cited_by_count":123},{"year":2015,"cited_by_count":80},{"year":2014,"cited_by_count":14},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}