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Data Analysis and Visualization Using Python : Analyze Data to Create Visualizations for BI Systems / Ossama Embarak
Apress, 2018
394 p. : illustration ; 25 cm.
Ký hiệu phân loại (DDC): 006
Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python.
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3
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Hands-On Data Analysis with Pandas : A Python data science handbook for data collection, wrangling, analysis, and visualization / Stefanie Molin
UK : Packt, 2021
788 p. : illustration ; 25 cm.
Ký hiệu phân loại (DDC): 006
Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data.
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4
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Healthcare service management : a data-driven systems approach / Li Tao, Jiming Liu
Cham, Switzerland : Springer, 2019
xvii, 168 pages. : illustrations ; 25 cm.
Ký hiệu phân loại (DDC): 362.1068
Healthcare service systems are of profound importance in promoting the public health and wellness of people. This book introduces a data-driven complex systems modeling approach (D2CSM) to systematically understand and improve the essence of healthcare service systems. In particular, this data-driven approach provides new perspectives on health service performance by unveiling the causes for service disparity, such as spatio-temporal variations in wait times across different hospitals.
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5
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Introductory biological statistics / John Edward Havel, Raymond E. Hampton, Scott J. Meiners
Long Grove, Illinois : Waveland Press, Inc., 2019
x, 252 pages. : illustrations ; 28 cm.
Ký hiệu phân loại (DDC): 570.1
A thorough understanding of biology, no matter which subfield, requires a thorough understanding of statistics. As in previous editions, Havel and Hampton (with new co-author Scott Meiners) ground students in all essential methods of descriptive and inferential statistics, using examples from different biological sciences. The authors have retained the readable, accessible writing style popular with both students and instructors. Pedagogical improvements new to this edition include concept checks in all chapters to assist students in active learning and code samples showing how to solve many of the book’s examples using R. Each chapter features numerous practice and homework exercises, with larger data sets available for download.
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