Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/604
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dc.contributor.authorNelli, Fabio. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:19:27Z-
dc.date.available2020-05-17T08:19:27Z-
dc.date.issued2018en_US
dc.identifier.isbn9781484239131 ;en_US
dc.identifier.isbn9781484239124 (print) ;en_US
dc.identifier.isbn9781484239148 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/604-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484239124. ;en_US
dc.descriptionPrinted edition: ; 9781484239148. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractExplore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data. ;en_US
dc.description.statementofresponsibilityby Fabio Nelli.en_US
dc.description.tableofcontents1. An Introduction to Data Analysis -- 2. Introduction to the Python's World -- 3. The NumPy Library -- 4. The pandas Library-- An Introduction -- 5. pandas: Reading and Writing Data -- 6. pandas in Depth: Data Manipulation -- 7. Data Visualization with matplotlib -- 8. Machine Learning with scikit-learn -- 9. Deep Learning with TensorFlow -- 10. An Example - Meteorological Data -- 11. Embedding the JavaScript D3 Library in IPython Notebook -- 12. Recognizing Handwritten Digits -- 13. Textual data Analysis with NLTK -- 14. Image Analysis and Computer Vision with OpenCV -- Appendix A -- Appendix B. ;en_US
dc.format.extentXIX, 569 p. 648 illus. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484239124.pdfen_US
dc.subjectPython (Computer program language). ;en_US
dc.subjectBig data. ;en_US
dc.subjectElectronic data processing. ;en_US
dc.subjectPython. ; http://scigraph.springernature.com/things/product-market-codes/I29080. ;en_US
dc.subjectBig Data. ; http://scigraph.springernature.com/things/product-market-codes/I29120. ;en_US
dc.subjectComputing Methodologies. ; http://scigraph.springernature.com/things/product-market-codes/I21009. ;en_US
dc.subject.ddc005.133 ; 23 ;en_US
dc.subject.lccQA76.73.P98 ;en_US
dc.titlePython Data Analyticsen_US
dc.title.alternativeWith Pandas, NumPy, and Matplotlib /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.date.edition2nd ed. ;en_US
Appears in Collections:مدیریت فناوری اطلاعات

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9781484239124.pdf14.28 MBAdobe PDFThumbnail
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Full metadata record
DC FieldValueLanguage
dc.contributor.authorNelli, Fabio. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:19:27Z-
dc.date.available2020-05-17T08:19:27Z-
dc.date.issued2018en_US
dc.identifier.isbn9781484239131 ;en_US
dc.identifier.isbn9781484239124 (print) ;en_US
dc.identifier.isbn9781484239148 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/604-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484239124. ;en_US
dc.descriptionPrinted edition: ; 9781484239148. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractExplore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data. ;en_US
dc.description.statementofresponsibilityby Fabio Nelli.en_US
dc.description.tableofcontents1. An Introduction to Data Analysis -- 2. Introduction to the Python's World -- 3. The NumPy Library -- 4. The pandas Library-- An Introduction -- 5. pandas: Reading and Writing Data -- 6. pandas in Depth: Data Manipulation -- 7. Data Visualization with matplotlib -- 8. Machine Learning with scikit-learn -- 9. Deep Learning with TensorFlow -- 10. An Example - Meteorological Data -- 11. Embedding the JavaScript D3 Library in IPython Notebook -- 12. Recognizing Handwritten Digits -- 13. Textual data Analysis with NLTK -- 14. Image Analysis and Computer Vision with OpenCV -- Appendix A -- Appendix B. ;en_US
dc.format.extentXIX, 569 p. 648 illus. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484239124.pdfen_US
dc.subjectPython (Computer program language). ;en_US
dc.subjectBig data. ;en_US
dc.subjectElectronic data processing. ;en_US
dc.subjectPython. ; http://scigraph.springernature.com/things/product-market-codes/I29080. ;en_US
dc.subjectBig Data. ; http://scigraph.springernature.com/things/product-market-codes/I29120. ;en_US
dc.subjectComputing Methodologies. ; http://scigraph.springernature.com/things/product-market-codes/I21009. ;en_US
dc.subject.ddc005.133 ; 23 ;en_US
dc.subject.lccQA76.73.P98 ;en_US
dc.titlePython Data Analyticsen_US
dc.title.alternativeWith Pandas, NumPy, and Matplotlib /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.date.edition2nd ed. ;en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484239124.pdf14.28 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorNelli, Fabio. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:19:27Z-
dc.date.available2020-05-17T08:19:27Z-
dc.date.issued2018en_US
dc.identifier.isbn9781484239131 ;en_US
dc.identifier.isbn9781484239124 (print) ;en_US
dc.identifier.isbn9781484239148 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/604-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9781484239124. ;en_US
dc.descriptionPrinted edition: ; 9781484239148. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractExplore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data. ;en_US
dc.description.statementofresponsibilityby Fabio Nelli.en_US
dc.description.tableofcontents1. An Introduction to Data Analysis -- 2. Introduction to the Python's World -- 3. The NumPy Library -- 4. The pandas Library-- An Introduction -- 5. pandas: Reading and Writing Data -- 6. pandas in Depth: Data Manipulation -- 7. Data Visualization with matplotlib -- 8. Machine Learning with scikit-learn -- 9. Deep Learning with TensorFlow -- 10. An Example - Meteorological Data -- 11. Embedding the JavaScript D3 Library in IPython Notebook -- 12. Recognizing Handwritten Digits -- 13. Textual data Analysis with NLTK -- 14. Image Analysis and Computer Vision with OpenCV -- Appendix A -- Appendix B. ;en_US
dc.format.extentXIX, 569 p. 648 illus. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484239124.pdfen_US
dc.subjectPython (Computer program language). ;en_US
dc.subjectBig data. ;en_US
dc.subjectElectronic data processing. ;en_US
dc.subjectPython. ; http://scigraph.springernature.com/things/product-market-codes/I29080. ;en_US
dc.subjectBig Data. ; http://scigraph.springernature.com/things/product-market-codes/I29120. ;en_US
dc.subjectComputing Methodologies. ; http://scigraph.springernature.com/things/product-market-codes/I21009. ;en_US
dc.subject.ddc005.133 ; 23 ;en_US
dc.subject.lccQA76.73.P98 ;en_US
dc.titlePython Data Analyticsen_US
dc.title.alternativeWith Pandas, NumPy, and Matplotlib /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.date.edition2nd ed. ;en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484239124.pdf14.28 MBAdobe PDFThumbnail
Preview File