{"data":{"id":1689,"title":"Introduction to Data Science Using Python","edition_statement":null,"volume":null,"copyright_year":2024,"isbn10":null,"isbn13":null,"license":"Attribution-NonCommercial","language":"eng","accessibility_statement":null,"accessibility_features":["unknown"],"description":"This book contains two parts, the first is designed to be used in an introductory programming course for students looking to learn Python, without having any prior experience with programming. Basic programming concepts are discussed, explained, and illustrated with a Python program. Ample programming questions are provided for practice. The second part of the book utilizes machine-learning concepts and statistics to accomplish data-driven resolutions. Python programs are provided to apply scientific computing to conclude statistically driven results.","contributors":[{"id":7161,"contribution":"Author","primary":true,"corporate":false,"title":null,"first_name":"Afrand","middle_name":null,"last_name":"Agah","location":"West Chester University","background_text":""}],"subjects":[{"id":3,"name":"Computer Science","parent_subject_id":null,"call_number":"QA76","visible_textbooks_count":137,"url":"https://open.umn.edu/opentextbooks/subjects/computer-science-information-systems"}],"publishers":[{"id":1663,"url":null,"year":null,"created_at":"2024-07-14T22:43:10.000-05:00","updated_at":"2026-06-23T14:21:11.000-05:00","name":"The Pennsylvania Alliance for Design of Open Textbooks (PA-ADOPT)"}],"formats":[{"id":4314,"type":"PDF","url":"https://paadopt.org/bookshelf/introduction-to-data-science-using-python/","price":{"cents":0,"currency_iso":"USD"},"isbn":null},{"id":4315,"type":"eBook","url":"https://paadopt.org/bookshelf/introduction-to-data-science-using-python/","price":{"cents":0,"currency_iso":"USD"},"isbn":null}],"rating":"2.5","textbook_reviews_count":1,"reviews":[{"id":35845,"first_name":"Kim","last_name":"Mandery","position":"Computer Scientist in Residence","institution_name":"St. Olaf College","comprehensiveness_rating":1,"comprehensiveness_review":"This book is written more akin to personal notes rather than a complete textbook. I would recommend this to someone wanting additional practice problems, or short tutorials on how to use some building blocks of the Python programming language. Dictionaries are not mentioned, but used later on in the graph theory section. No glossary of terms are included, and the depth of the content is very shallow (more showing rather than explaining how it works).","accuracy_rating":4,"accuracy_review":"No glaring issues in the code presented.","relevance_rating":2,"relevance_review":"While able to add in new content easily, this is moreso because the text is quite short and shallow.","clarity_rating":2,"clarity_review":"While currently written in accessible prose, additional narrative is needed to explain the \"why\" behind the concepts and code given.","consistency_rating":3,"consistency_review":"No issues with terminology used.","modularity_rating":3,"modularity_review":"There are a couple of sections that rely on earlier material (i.e. the section on lists has a few examples using content from files section).","organization_rating":3,"organization_review":"The ordering of concepts makes sense. Personally I would prefer lists after strings (both are sequences) but before files. Content provided (while narrow) does flow well.","interface_rating":4,"interface_review":"No navigation issues. I appreciate that the practice questions and solutions for each section are linked together as this makes navigating through the pdf easier for learners.","grammatical_rating":3,"grammatical_review":"No issues with grammar.","cultural_rating":2,"cultural_review":"Not insensitive, but include no examples of real-world application.","overall_rating":5,"overall_review":null,"created_at":"2026-04-02T12:42:44.000-05:00","updated_at":"2026-04-02T12:42:44.000-05:00"}],"url":"https://open.umn.edu/opentextbooks/textbooks/introduction-to-data-science-using-python","updated_at":"2026-05-18T02:02:17.000-05:00"}}