國立虎尾科技大學 |

Python Data Analytics = With Pandas, NumPy, and Matplotlib /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Python Data Analytics/ by Fabio Nelli.
Reminder of title:	With Pandas, NumPy, and Matplotlib /
Author:	Nelli, Fabio.
Description:	XIX, 569 p. 648 illus.online resource. :
Contained By:	Springer Nature eBook
Subject:	Python (Computer program language). -
Online resource:	https://doi.org/10.1007/978-1-4842-3913-1
ISBN:	9781484239131

Python Data Analytics = With Pandas, NumPy, and Matplotlib /
Nelli, Fabio.

Python Data AnalyticsWith Pandas, NumPy, and Matplotlib /[electronic resource] :by Fabio Nelli. - 2nd ed. 2018. - XIX, 569 p. 648 illus.online resource.

1. 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.

Explore 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.

ISBN: 9781484239131

Standard No.: 10.1007/978-1-4842-3913-1doiSubjects--Topical Terms:

1127623
Python (Computer program language).

LC Class. No.: QA76.73.P98

Dewey Class. No.: 005.133

Python Data Analytics = With Pandas, NumPy, and Matplotlib /
LDR:03009nam a22003975i 4500 001 988946
003 DE-He213
005 20200703060920.0
007 cr nn 008mamaa
008 201225s2018 xxu| s |||| 0|eng d
020 $a 9781484239131 $9 978-1-4842-3913-1
024 7 $a 10.1007/978-1-4842-3913-1 $2 doi
035 $a 978-1-4842-3913-1
050 4 $a QA76.73.P98
072 7 $a UMX $2 bicssc
072 7 $a COM051360 $2 bisacsh
072 7 $a UMX $2 thema
082 0 4 $a 005.133 $2 23
100 1 $a Nelli, Fabio. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1068168
245 1 0 $a Python Data Analytics $h [electronic resource] : $b With Pandas, NumPy, and Matplotlib / $c by Fabio Nelli.
250 $a 2nd ed. 2018.
264 1 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2018.
300 $a XIX, 569 p. 648 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a 1. 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.
520 $a Explore 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.
650 0 $a Python (Computer program language). $3 1127623
650 0 $a Big data. $3 981821
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a Python. $3 1115944
650 2 4 $a Big Data. $3 1017136
650 2 4 $a Artificial Intelligence. $3 646849
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484239124
776 0 8 $i Printed edition: $z 9781484239148
776 0 8 $i Printed edition: $z 9781484247372
856 4 0 $u https://doi.org/10.1007/978-1-4842-3913-1
912 $a ZDB-2-CWD
912 $a ZDB-2-SXPC
950 $a Professional and Applied Computing (SpringerNature-12059)
950 $a Professional and Applied Computing (R0) (SpringerNature-43716)