Biological Data Exploration with Python, Pandas and Seaborn

Biological Data Exploration with Python, Pandas and Seaborn PDF Author: Martin Jones
Publisher:
ISBN:
Category :
Languages : en
Pages : 398

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Book Description
In biological research, we''re currently in a golden age of data. It''s never been easier to assemble large datasets to probe biological questions. But these large datasets come with their own problems. How to clean and validate data? How to combine datasets from multiple sources? And how to look for patterns in large, complex datasets and display your findings? The solution to these problems comes in the form of Python''s scientific software stack. The combination of a friendly, expressive language and high quality packages makes a fantastic set of tools for data exploration. But the packages themselves can be hard to get to grips with. It''s difficult to know where to get started, or which sets of tools will be most useful. Learning to use Python effectively for data exploration is a superpower that you can learn. With a basic knowledge of Python, pandas (for data manipulation) and seaborn (for data visualization) you''ll be able to understand complex datasets quickly and mine them for biological insight. You''ll be able to make beautiful, informative charts for posters, papers and presentations, and rapidly update them to reflect new data or test new hypotheses. You''ll be able to quickly make sense of datasets from other projects and publications - millions of rows of data will no longer be a scary prospect! In this book, Dr. Jones draws on years of teaching experience to give you the tools you need to answer your research questions. Starting with the basics, you''ll learn how to use Python, pandas, seaborn and matplotlib effectively using biological examples throughout. Rather than overwhelm you with information, the book concentrates on the tools most useful for biological data. Full color illustrations show hundreds of examples covering dozens of different chart types, with complete code samples that you can tweak and use for your own work. This book will help you get over the most common obstacles when getting started with data exploration in Python. You''ll learn about pandas'' data model; how to deal with errors in input files and how to fit large datasets in memory. The chapters on visualization will show you how to make sophisticated charts with minimal code; how to best use color to make clear charts, and how to deal with visualization problems involving large numbers of data points. Chapters include: Getting data into pandas: series and dataframes, CSV and Excel files, missing data, renaming columns Working with series: descriptive statistics, string methods, indexing and broadcasting Filtering and selecting: boolean masks, selecting in a list, complex conditions, aggregation Plotting distributions: histograms, scatterplots, custom columns, using size and color Special scatter plots: using alpha, hexbin plots, regressions, pairwise plots Conditioning on categories: using color, size and marker, small multiples Categorical axes:strip/swarm plots, box and violin plots, bar plots and line charts Styling figures: aspect, labels, styles and contexts, plotting keywords Working with color: choosing palettes, redundancy, highlighting categories Working with groups: groupby, types of categories, filtering and transforming Binning data: creating categories, quantiles, reindexing Long and wide form: tidying input datasets, making summaries, pivoting data Matrix charts: summary tables, heatmaps, scales and normalization, clustering Complex data files: cleaning data, merging and concatenating, reducing memory FacetGrids: laying out multiple charts, custom charts, multiple heat maps Unexpected behaviours: bugs and missing groups, fixing odd scales High performance pandas: vectorization, timing and sampling Further reading: dates and times, alternative syntax

Biological Data Exploration with Python, Pandas and Seaborn

Biological Data Exploration with Python, Pandas and Seaborn PDF Author: Martin Jones
Publisher:
ISBN:
Category :
Languages : en
Pages : 398

Get Book Here

Book Description
In biological research, we''re currently in a golden age of data. It''s never been easier to assemble large datasets to probe biological questions. But these large datasets come with their own problems. How to clean and validate data? How to combine datasets from multiple sources? And how to look for patterns in large, complex datasets and display your findings? The solution to these problems comes in the form of Python''s scientific software stack. The combination of a friendly, expressive language and high quality packages makes a fantastic set of tools for data exploration. But the packages themselves can be hard to get to grips with. It''s difficult to know where to get started, or which sets of tools will be most useful. Learning to use Python effectively for data exploration is a superpower that you can learn. With a basic knowledge of Python, pandas (for data manipulation) and seaborn (for data visualization) you''ll be able to understand complex datasets quickly and mine them for biological insight. You''ll be able to make beautiful, informative charts for posters, papers and presentations, and rapidly update them to reflect new data or test new hypotheses. You''ll be able to quickly make sense of datasets from other projects and publications - millions of rows of data will no longer be a scary prospect! In this book, Dr. Jones draws on years of teaching experience to give you the tools you need to answer your research questions. Starting with the basics, you''ll learn how to use Python, pandas, seaborn and matplotlib effectively using biological examples throughout. Rather than overwhelm you with information, the book concentrates on the tools most useful for biological data. Full color illustrations show hundreds of examples covering dozens of different chart types, with complete code samples that you can tweak and use for your own work. This book will help you get over the most common obstacles when getting started with data exploration in Python. You''ll learn about pandas'' data model; how to deal with errors in input files and how to fit large datasets in memory. The chapters on visualization will show you how to make sophisticated charts with minimal code; how to best use color to make clear charts, and how to deal with visualization problems involving large numbers of data points. Chapters include: Getting data into pandas: series and dataframes, CSV and Excel files, missing data, renaming columns Working with series: descriptive statistics, string methods, indexing and broadcasting Filtering and selecting: boolean masks, selecting in a list, complex conditions, aggregation Plotting distributions: histograms, scatterplots, custom columns, using size and color Special scatter plots: using alpha, hexbin plots, regressions, pairwise plots Conditioning on categories: using color, size and marker, small multiples Categorical axes:strip/swarm plots, box and violin plots, bar plots and line charts Styling figures: aspect, labels, styles and contexts, plotting keywords Working with color: choosing palettes, redundancy, highlighting categories Working with groups: groupby, types of categories, filtering and transforming Binning data: creating categories, quantiles, reindexing Long and wide form: tidying input datasets, making summaries, pivoting data Matrix charts: summary tables, heatmaps, scales and normalization, clustering Complex data files: cleaning data, merging and concatenating, reducing memory FacetGrids: laying out multiple charts, custom charts, multiple heat maps Unexpected behaviours: bugs and missing groups, fixing odd scales High performance pandas: vectorization, timing and sampling Further reading: dates and times, alternative syntax

Proteomics for Biological Discovery

Proteomics for Biological Discovery PDF Author: Timothy D. Veenstra
Publisher: John Wiley & Sons
ISBN: 0470007737
Category : Science
Languages : en
Pages : 361

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Book Description
Written by recognized experts in the study of proteins, Proteomics for Biological Discovery begins by discussing the emergence of proteomics from genome sequencing projects and a summary of potential answers to be gained from proteome-level research. The tools of proteomics, from conventional to novel techniques, are then dealt with in terms of underlying concepts, limitations and future directions. An invaluable source of information, this title also provides a thorough overview of the current developments in post-translational modification studies, structural proteomics, biochemical proteomics, microfabrication, applied proteomics, and bioinformatics relevant to proteomics. Presents a comprehensive and coherent review of the major issues faced in terms of technology development, bioinformatics, strategic approaches, and applications Chapters offer a rigorous overview with summary of limitations, emerging approaches, questions, and realistic future industry and basic science applications Discusses higher level integrative aspects, including technical challenges and applications for drug discovery Accessible to the novice while providing experienced investigators essential information Proteomics for Biological Discovery is an essential resource for students, postdoctoral fellows, and researchers across all fields of biomedical research, including biochemistry, protein chemistry, molecular genetics, cell/developmental biology, and bioinformatics.

Python for Biologists

Python for Biologists PDF Author: Martin Jones
Publisher: Createspace Independent Publishing Platform
ISBN:
Category : Computers
Languages : en
Pages : 248

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Book Description
Python for biologists is a complete programming course for beginners that will give you the skills you need to tackle common biological and bioinformatics problems.

Parallel Algorithms for Regular Architectures

Parallel Algorithms for Regular Architectures PDF Author: Russ Miller
Publisher: MIT Press
ISBN: 9780262132336
Category : Architecture
Languages : en
Pages : 336

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Book Description
Parallel-Algorithms for Regular Architectures is the first book to concentrate exclusively on algorithms and paradigms for programming parallel computers such as the hypercube, mesh, pyramid, and mesh-of-trees.

Advanced Python for Biologists

Advanced Python for Biologists PDF Author: Martin O. Jones
Publisher: Createspace Independent Publishing Platform
ISBN: 9781495244377
Category : Biology
Languages : en
Pages : 0

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Book Description
Advanced Python for Biologists is a programming course for workers in biology and bioinformatics who want to develop their programming skills. It starts with the basic Python knowledge outlined in Python for Biologists and introduces advanced Python tools and techniques with biological examples. You'll learn: - How to use object-oriented programming to model biological entities - How to write more robust code and programs by using Python's exception system - How to test your code using the unit testing framework - How to transform data using Python's comprehensions - How to write flexible functions and applications using functional programming - How to use Python's iteration framework to extend your own object and functions Advanced Python for Biologists is written with an emphasis on practical problem-solving and uses everyday biological examples throughout. Each section contains exercises along with solutions and detailed discussion.

Data Sharing Using A Common Data Architecture

Data Sharing Using A Common Data Architecture PDF Author: Michael H. Brackett
Publisher: Wiley
ISBN: 9780471309932
Category : Computers
Languages : en
Pages : 508

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Book Description
Data Sharing Using a Common Data Architecture Wouldn’t it be a pleasure to know and understand all the data in your organization? Wouldn’t it be great to easily identify and readily share those data to develop information that supports business strategies? Wouldn’t it be wonderful to have a formal data resource that provides just-in-time data for developing just-in-time information to support just-in-time decision making? Data Sharing Using a Common Data Architecture shows you how by: Defining a common data architecture, its contents, and its uses Refining data to a common data architecture Discussing disparate data, its structure, quality, and how to identify it Describing how Data Sharing Reality is achieved Focusing on the importance of people and creating a win-win situation Providing a data lexicon and extensive glossary Data Sharing Using a Common Data Architecture is must reading for data administrators, database administrators, MIS project leaders, application programmers, systems analysts, MIS trainers and instructors, and graduate students.

Applied Subsurface Geological Mapping with Structural Methods

Applied Subsurface Geological Mapping with Structural Methods PDF Author: Daniel J. Tearpock
Publisher: Pearson Education
ISBN: 0132441683
Category : Technology & Engineering
Languages : en
Pages : 1414

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Book Description
Applied Subsurface Geological Mapping, With Structural Methods, 2nd Edition is the practical, up-to-the-minute guide to the use of subsurface interpretation, mapping, and structural techniques in the search for oil and gas resources. Two of the industry's leading consultants present systematic coverage of the field's key principles and newest advances, offering guidance that is valuable for both exploration and development activities, as well as for "detailed" projects in maturely developed areas. Fully updated and expanded, this edition combines extensive information from the published literature with significant material never before published. The authors introduce superior techniques for every major petroleum-related tectonic setting in the world. Coverage includes: A systematic, ten-step philosophy for subsurface interpretation and mapping The latest computer-based contouring concepts and applications Advanced manual and computer-based log correlation Integration of geophysical data into subsurface interpretations and mapping Cross-section construction: structural, stratigraphic, and problem-solving Interpretation and generation of valid fault, structure, and isochore maps New coverage of 3D seismic interpretation, from project setup through documentation Compressional and extensional structures: balancing and interpretation In-depth new coverage of strike-slip faulting and related structures Growth and correlation consistency techniques: expansion indices, Multiple Bischke Plot Analysis, vertical separation versus depth, and more Numerous field examples from around the world Whatever your role in the adventure of finding and developing oil or gas resources–as a geologist, geophysicist, engineer, technologist, manager or investor–the tools presented in this book can make you significantly more effective in your daily technical or decision-oriented activities.

Radial Basis Function Neural Networks with Sequential Learning

Radial Basis Function Neural Networks with Sequential Learning PDF Author: N. Sundararajan
Publisher: World Scientific
ISBN: 9789810237714
Category : Science
Languages : en
Pages : 236

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Book Description
A review of radial basis founction (RBF) neural networks. A novel sequential learning algorithm for minimal resource allocation neural networks (MRAN). MRAN for function approximation & pattern classification problems; MRAN for nonlinear dynamic systems; MRAN for communication channel equalization; Concluding remarks; A outline source code for MRAN in MATLAB; Bibliography; Index.

Designing Efficient Algorithms for Parallel Computers

Designing Efficient Algorithms for Parallel Computers PDF Author: Michael Jay Quinn
Publisher: McGraw-Hill Companies
ISBN:
Category : Computers
Languages : en
Pages : 312

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Book Description
Mathematics of Computing -- Parallelism.

Modern Python Bio Informatics

Modern Python Bio Informatics PDF Author: Dr. Amarendra Alluri
Publisher: RK Publication
ISBN: 9348020072
Category : Computers
Languages : en
Pages : 303

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Book Description
Modern Python Bioinformatics is an insightful guide merging Python programming with bioinformatics, designed for both beginners and seasoned professionals in computational biology. This book covers essential Python skills and advanced bioinformatics concepts, including DNA/RNA sequencing, protein structure analysis, and data visualization. It emphasizes practical applications with examples and projects that demonstrate how to handle biological data, perform statistical analyses, and develop efficient bioinformatics workflows. With accessible explanations and code snippets, it equips readers to tackle real-world challenges in bioinformatics research and development.