Isbn: 9780134546933 - pandas for everyone: python data analysis: python data analysis (addison-wesley data & analytics series) (27 resultados)

Condición: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

Condición: Good. Item in good condition and has highlighting/writing on text. Used texts may not contain supplemental items such as CDs, info-trac etc.

paperback. Condición: Very Good. Fast shipping and order satisfaction guaranteed. A portion of your purchase benefits Non-Profit Organizations, First Aid and Fire Stations.

Paperback. Condición: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Paperback. Condición: Good. No Jacket. Former library book; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condición: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

paperback. Condición: Good. Used books may not include access codes or one time use codes. Proven Seller with Excellent Customer Service. Choose expedited shipping and get it FAST.

Condición: acceptable.

Condición: Good. : Este libro es una introducción práctica y completa al análisis de datos con Python utilizando la biblioteca Pandas. Daniel Y. Chen presenta los conceptos clave a través de ejemplos sencillos pero prácticos, construyendo sobre ellos para resolver problemas del mundo real. Aprenderás a limpiar, estructurar y visualizar datos, así como a construir modelos para predicción, clustering e inferencia. También se ofrecen consejos sobre rendimiento y escalabilidad, y se introduce el ecosistema más amplio de análisis de datos de Python. EAN: 9780134546933 Tipo: Libros Categoría: Tecnología|Ciencias Título: Pandas for Everyone: Python Data Analysis Autor: Daniel Y. Chen Editorial: Addison-Wesley Professional Idioma: en Páginas: 416 Formato: tapa blanda. …

Paperback. Condición: new. New Copy. Customer Service Guaranteed.

Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Condición: As New. Unread book in perfect condition.

Condición: New.

Paperback. Condición: new. Paperback. Today, analysts must manage data characterised 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, visualise 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 youre 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 visualisation. 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 theyre 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 generalised linear modeling to fit models with different response variables Compare multiple models to select the best Regularise to overcome overfitting and improve performance Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: New.

Condición: As New. Unread book in perfect condition.

paperback. Condición: Fair.

Paperback. Condición: Brand New. 400 pages. 9.25x7.00x1.00 inches. In Stock.

Condición: New.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Taschenbuch. Condición: Neu. Neuware - 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 dataCreate plots with matplotlib, seaborn, and pandasCombine datasets and handle missing dataReshape, tidy, and clean datasets so they re easier to work withConvert data types and manipulate text stringsApply functions to scale data manipulationsAggregate, transform, and filter large datasets with groupbyLeverage Pandas advanced date and time capabilitiesFit linear models using statsmodels and scikit-learn librariesUse generalized linear modeling to fit models with different response variablesCompare multiple models to select the best Regularize to overcome overfitting and improve performanceUse clustering in unsupervised machine learning.…

Condición: New. This tutorial teaches students everything they need to get started with Python programming for the fast-growing field of data analysis. Daniel Chen tightly links each new concept with easy-to-apply, relevant examples from modern data analysis.

Paperback. Condición: new. Paperback. Today, analysts must manage data characterised 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, visualise 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 youre 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 visualisation. 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 theyre 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 generalised linear modeling to fit models with different response variables Compare multiple models to select the best Regularise to overcome overfitting and improve performance Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condición: New. Print on Demand pp. 400.

Condición: New. Print on Demand pp. 400.

Condición: New. PRINT ON DEMAND pp. 400.