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.

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.

Pandas for Everyone

Pandas for Everyone PDF Author: Daniel Y. Chen
Publisher: Addison-Wesley Professional
ISBN: 0134547055
Category : Computers
Languages : en
Pages : 1093

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Book Description
The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems. Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes. Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability, and introduces you to the wider Python data analysis ecosystem. Work with DataFrames and Series, and import or export data Create plots with matplotlib, seaborn, and pandas Combine datasets and handle missing data Reshape, tidy, and clean datasets so they’re easier to work with Convert data types and manipulate text strings Apply functions to scale data manipulations Aggregate, transform, and filter large datasets with groupby Leverage Pandas’ advanced date and time capabilities Fit linear models using statsmodels and scikit-learn libraries Use generalized linear modeling to fit models with different response variables Compare multiple models to select the “best” Regularize to overcome overfitting and improve performance Use clustering in unsupervised machine learning

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.

Managing Your Biological Data with Python

Managing Your Biological Data with Python PDF Author: Allegra Via
Publisher: CRC Press
ISBN: 1439880948
Category : Computers
Languages : en
Pages : 560

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Book Description
Take Control of Your Data and Use Python with ConfidenceRequiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how

Python Data Science Handbook

Python Data Science Handbook PDF Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 609

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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Introduction to Data Science

Introduction to Data Science PDF Author: Laura Igual
Publisher: Springer
ISBN: 3319500171
Category : Computers
Languages : en
Pages : 227

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Book Description
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.

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.