The third edition of this practical introduction to Python has been thoroughly updated, with all code migrated to Jupyter notebooks. The notebooks are available online with executable versions of all of the book's content (and more). The text starts with a detailed introduction to the basics of the Python language, without assuming any prior knowledge. Building upon each other, the most important Python packages for numerical math (NumPy), symbolic math (SymPy), and plotting (Matplotlib) are introduced, with brand new chapters covering numerical methods (SciPy) and data handling (Pandas). Further new material includes guidelines for writing efficient Python code and publishing code for other users. Simple and concise code examples, revised for compatibility with Python 3, guide the reader and support the learning process throughout the book. Readers from all of the quantitative sciences, whatever their background, will be able to quickly acquire the skills needed for using Python effectively.

Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language''s capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python effectively.

Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language''s capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python effectively.

Python is a free, open source, easy-to-use software tool that offers a significant alternative to proprietary packages such as MATLAB® and Mathematica®. This book covers everything the working scientist needs to know to start using Python effectively. The author explains scientific Python from scratch, showing how easy it is to implement and test non-trivial mathematical algorithms and guiding the reader through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the program''s capabilities. In particular, readers are shown how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. Instead of exercises the book contains useful snippets of tested code which the reader can adapt to handle problems in their own field, allowing students and researchers with little computer expertise to get up and running as soon as possible.

Molecular diagnostics are increasingly used to help guide targeted therapy in solid organ tumors and hematologic malignancies. A large proportion of molecular testing is performed on limited-volume samples obtained via minimally invasive techniques, such as fine needle aspiration. Increasingly, cytopathologists play an essential role in this process, both in the triage of specimens during rapid on-site evaluation and in the evaluation of archival samples to determine suitability for ancillary testing. Therefore, it is imperative that practicing cytopathologists stay abreast of up-to-date diagnostic, prognostic, and predictive ancillary tests that can be used on limited cytologic material. This is a challenge since the landscape of known genomic alterations is constantly evolving and the subsequent set of testing options is ever expanding.The proposed text will provide a user-friendly quick-reference handbook to serve as a useful resource for practicing pathologistsand laboratory personnel dealing with, and interested in, this evolving field of molecular cytopathology. Essential components to be presented include: 1) pre-analytic factors that affect sample selection and evaluation; 2) specimen preparation to maximize confidence in results; 3) interpretation of results; 4) potential limitations; and 5) workflow algorithms.  In addition, specific disease specific molecular testing details will be outlined to provide the reader with resources for quick reference. All chapters will be written by experts in their fields and will include the most up-to-date scientific and clinical information.Molecular Diagnostics in Cytopathology will be of value to Cytopathologists, Cytotechnologists, Cytotechnology students, Cytopathology fellows, Surgical pathologists, Pathology residents and fellows, Molecular Pathologists, Molecular pathology fellows, Molecular technologists, as well as  Translational researchers with an interest in molecular cytopathology.

Molecular diagnostics are increasingly used to help guide targeted therapy in solid organ tumors and hematologic malignancies. A large proportion of molecular testing is performed on limited-volume samples obtained via minimally invasive techniques, such as fine needle aspiration. Increasingly, cytopathologists play an essential role in this process, both in the triage of specimens during rapid on-site evaluation and in the evaluation of archival samples to determine suitability for ancillary testing. Therefore, it is imperative that practicing cytopathologists stay abreast of up-to-date diagnostic, prognostic, and predictive ancillary tests that can be used on limited cytologic material. This is a challenge since the landscape of known genomic alterations is constantly evolving and the subsequent set of testing options is ever expanding.The proposed text will provide a user-friendly quick-reference handbook to serve as a useful resource for practicing pathologistsand laboratory personnel dealing with, and interested in, this evolving field of molecular cytopathology. Essential components to be presented include: 1) pre-analytic factors that affect sample selection and evaluation; 2) specimen preparation to maximize confidence in results; 3) interpretation of results; 4) potential limitations; and 5) workflow algorithms.  In addition, specific disease specific molecular testing details will be outlined to provide the reader with resources for quick reference. All chapters will be written by experts in their fields and will include the most up-to-date scientific and clinical information.Molecular Diagnostics in Cytopathology will be of value to Cytopathologists, Cytotechnologists, Cytotechnology students, Cytopathology fellows, Surgical pathologists, Pathology residents and fellows, Molecular Pathologists, Molecular pathology fellows, Molecular technologists, as well as  Translational researchers with an interest in molecular cytopathology.

The third edition of this practical introduction to Python has been thoroughly updated, with all code migrated to Jupyter notebooks. The notebooks are available online with executable versions of all of the book's content (and more). The text starts with a detailed introduction to the basics of the Python language, without assuming any prior knowledge. Building upon each other, the most important Python packages for numerical math (NumPy), symbolic math (SymPy), and plotting (Matplotlib) are introduced, with brand new chapters covering numerical methods (SciPy) and data handling (Pandas). Further new material includes guidelines for writing efficient Python code and publishing code for other users. Simple and concise code examples, revised for compatibility with Python 3, guide the reader and support the learning process throughout the book. Readers from all of the quantitative sciences, whatever their background, will be able to quickly acquire the skills needed for using Python effectively.

Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language''s capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python effectively.

Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language''s capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python effectively.

Python is a free, open source, easy-to-use software tool that offers a significant alternative to proprietary packages such as MATLAB® and Mathematica®. This book covers everything the working scientist needs to know to start using Python effectively. The author explains scientific Python from scratch, showing how easy it is to implement and test non-trivial mathematical algorithms and guiding the reader through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the program''s capabilities. In particular, readers are shown how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. Instead of exercises the book contains useful snippets of tested code which the reader can adapt to handle problems in their own field, allowing students and researchers with little computer expertise to get up and running as soon as possible.

Molecular diagnostics are increasingly used to help guide targeted therapy in solid organ tumors and hematologic malignancies. A large proportion of molecular testing is performed on limited-volume samples obtained via minimally invasive techniques, such as fine needle aspiration. Increasingly, cytopathologists play an essential role in this process, both in the triage of specimens during rapid on-site evaluation and in the evaluation of archival samples to determine suitability for ancillary testing. Therefore, it is imperative that practicing cytopathologists stay abreast of up-to-date diagnostic, prognostic, and predictive ancillary tests that can be used on limited cytologic material. This is a challenge since the landscape of known genomic alterations is constantly evolving and the subsequent set of testing options is ever expanding.The proposed text will provide a user-friendly quick-reference handbook to serve as a useful resource for practicing pathologistsand laboratory personnel dealing with, and interested in, this evolving field of molecular cytopathology. Essential components to be presented include: 1) pre-analytic factors that affect sample selection and evaluation; 2) specimen preparation to maximize confidence in results; 3) interpretation of results; 4) potential limitations; and 5) workflow algorithms.  In addition, specific disease specific molecular testing details will be outlined to provide the reader with resources for quick reference. All chapters will be written by experts in their fields and will include the most up-to-date scientific and clinical information.Molecular Diagnostics in Cytopathology will be of value to Cytopathologists, Cytotechnologists, Cytotechnology students, Cytopathology fellows, Surgical pathologists, Pathology residents and fellows, Molecular Pathologists, Molecular pathology fellows, Molecular technologists, as well as  Translational researchers with an interest in molecular cytopathology.

Molecular diagnostics are increasingly used to help guide targeted therapy in solid organ tumors and hematologic malignancies. A large proportion of molecular testing is performed on limited-volume samples obtained via minimally invasive techniques, such as fine needle aspiration. Increasingly, cytopathologists play an essential role in this process, both in the triage of specimens during rapid on-site evaluation and in the evaluation of archival samples to determine suitability for ancillary testing. Therefore, it is imperative that practicing cytopathologists stay abreast of up-to-date diagnostic, prognostic, and predictive ancillary tests that can be used on limited cytologic material. This is a challenge since the landscape of known genomic alterations is constantly evolving and the subsequent set of testing options is ever expanding.The proposed text will provide a user-friendly quick-reference handbook to serve as a useful resource for practicing pathologistsand laboratory personnel dealing with, and interested in, this evolving field of molecular cytopathology. Essential components to be presented include: 1) pre-analytic factors that affect sample selection and evaluation; 2) specimen preparation to maximize confidence in results; 3) interpretation of results; 4) potential limitations; and 5) workflow algorithms.  In addition, specific disease specific molecular testing details will be outlined to provide the reader with resources for quick reference. All chapters will be written by experts in their fields and will include the most up-to-date scientific and clinical information.Molecular Diagnostics in Cytopathology will be of value to Cytopathologists, Cytotechnologists, Cytotechnology students, Cytopathology fellows, Surgical pathologists, Pathology residents and fellows, Molecular Pathologists, Molecular pathology fellows, Molecular technologists, as well as  Translational researchers with an interest in molecular cytopathology.