Marco cremonini (49 risultati)

Rilegato. Condizione: new. A cura di Foschi P., Paltrinieri G. e Tampellini A.Bologna, 2025; ril., pp. 344, cm 17x24. La rivista "Strada Maestra" è la storica rivista della Biblioteca comunale "G. C. Croce" di San Giovanni in Persiceto fondata nel 1968 dal professor Mario Gandini. Gli articoli in questo numero: - I Pepoli e i loro mulini. Un approfondimento sui mulini di Valbona, macchine protoindustriali strategicamente collocate in posizione centrale fra i territori e le comunità di Crevalcore, Sant'Agata e San Giovanni in Persiceto (secoli XIII-XIX) (Paola Foschi) -La emptio Melchioris Bencevenni, fabro lignario di San Giovanni in Persiceto. 'Frammenti' di vita persicetana in un atto di compravendita del 31 ottobre 1583 (Alberto Tampellini) - Il Tempo in piazza a San Giovanni in Persiceto segnato dall'orologio solare più grande del mondo entrato nel Guinness World Records (2023) (Giovanni Paltrinieri, Romano Serra) - I muri raccontano. Alcune riflessioni ispirate dai murali dell'Istituto di istruzione superiore 'Archimede' di San Giovanni in Persiceto (Monica Mazzacori) - Di Bertoldo e di altro. Breve rassegna delle manifestazioni culturali per il 150° anniversario del carnevale storico persicetano (1874-2024) (Pierangelo Pancaldi) - Il patrimonio culturale della moda: l'Archivio Renato Manzoni (Silvia Monfredini) -Introduzione allo studio di Silvia Monfredini dedicato al più antico e consistente caso di archivio calzaturiero presente nella regione Emilia-Romagna (Elisa Tosi Brandi). Libro.…

hardcover. Condizione: Very Good. Cover and edges may have some wear.

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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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Condizione: As New. Unread book in perfect condition.

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hardcover. Condizione: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Condizione: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.…

Condizione: New. 1st edition NO-PA16APR2015-KAP.

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Hardcover. Condizione: New.

Condizione: New.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: new.

Condizione: As New. Unread book in perfect condition.

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Condizione: New.

Condizione: As New. Unread book in perfect condition.

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Hardback. Condizione: New. Data Science Fundamentals with R, Python, and Open Data Introduction to essential concepts and techniques of the fundamentals of R and Python needed to start data science projects Organized with a strong focus on open data, Data Science Fundamentals with R, Python, and Open Data discusses concepts, techniques, tools, and first steps to carry out data science projects, with a focus on Python and RStudio, reflecting a clear industry trend emerging towards the integration of the two. The text examines intricacies and inconsistencies often found in real data, explaining how to recognize them and guiding readers through possible solutions, and enables readers to handle real data confidently and apply transformations to reorganize, indexing, aggregate, and elaborate. This book is full of reader interactivity, with a companion website hosting supplementary material including datasets used in the examples and complete running code (R scripts and Jupyter notebooks) of all examples. Exam-style questions are implemented and multiple choice questions to support the readers' active learning. Each chapter presents one or more case studies. Written by a highly qualified academic, Data Science Fundamentals with R, Python, and Open Data discuss sample topics such as: Data organization and operations on data frames, covering reading CSV dataset and common errors, and slicing, creating, and deleting columns in R Logical conditions and row selection, covering selection of rows with logical condition and operations on dates, strings, and missing values Pivoting operations and wide form-long form transformations, indexing by groups with multiple variables, and indexing by group and aggregations Conditional statements and iterations, multicolumn functions and operations, data frame joins, and handling data in list/dictionary format Data Science Fundamentals with R, Python, and Open Data is a highly accessible learning resource for students from heterogeneous disciplines where Data Science and quantitative, computational methods are gaining popularity, along with hard sciences not closely related to computer science, and medical fields using stochastic and quantitative models.…

Condizione: New. In English.

Condizione: As New. Unread book in perfect condition.

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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Hardback. Condizione: New. Data Science Fundamentals with R, Python, and Open Data Introduction to essential concepts and techniques of the fundamentals of R and Python needed to start data science projects Organized with a strong focus on open data, Data Science Fundamentals with R, Python, and Open Data discusses concepts, techniques, tools, and first steps to carry out data science projects, with a focus on Python and RStudio, reflecting a clear industry trend emerging towards the integration of the two. The text examines intricacies and inconsistencies often found in real data, explaining how to recognize them and guiding readers through possible solutions, and enables readers to handle real data confidently and apply transformations to reorganize, indexing, aggregate, and elaborate. This book is full of reader interactivity, with a companion website hosting supplementary material including datasets used in the examples and complete running code (R scripts and Jupyter notebooks) of all examples. Exam-style questions are implemented and multiple choice questions to support the readers' active learning. Each chapter presents one or more case studies. Written by a highly qualified academic, Data Science Fundamentals with R, Python, and Open Data discuss sample topics such as: Data organization and operations on data frames, covering reading CSV dataset and common errors, and slicing, creating, and deleting columns in R Logical conditions and row selection, covering selection of rows with logical condition and operations on dates, strings, and missing values Pivoting operations and wide form-long form transformations, indexing by groups with multiple variables, and indexing by group and aggregations Conditional statements and iterations, multicolumn functions and operations, data frame joins, and handling data in list/dictionary format Data Science Fundamentals with R, Python, and Open Data is a highly accessible learning resource for students from heterogeneous disciplines where Data Science and quantitative, computational methods are gaining popularity, along with hard sciences not closely related to computer science, and medical fields using stochastic and quantitative models.…

Condizione: New. In English.

Condizione: New. 2024. 1st Edition. hardcover. . . . . .