Isbn: 9781569904954 - numeric python: python data analysis with numpy, pandas, and matplotlib (25 resultados)

Condición: New.

Paperback or Softback. Condición: New. Numeric Python: Python Data Analysis with Numpy, Pandas, and Matplotlib. Book.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New. 1.

Paperback. Condición: New. 1.

Condición: New.

Condición: As New. Unread book in perfect condition.

Buch. Condición: Neu. Neuware -- Numerical computing with NumPy arrays, dtypes, vectorized operations- Data analysis using Pandas DataFrames, grouping, pivoting, and time series- Scientific visualization with Matplotlib plots, layouts, and contour graphics- Real-world data work: files, missing data, binning, and indexing- Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning. The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters.WHAT'S INSIDE //Numerical operations on multidimensional arrays/Broadcasting and universal functions (ufuncs)/Discrete & continuous plots/Bar charts, histograms, and contour plots/Series and DataFrames/Working with Excel, CSV, and JSON files/Handling missing data (NaN)/Data visualization techniques/Image processing funda mentals/Budget tracking and incomeexpenditure analysis 572 pp. Englisch. …

Buch. Condición: Neu. Neuware -- Numerical computing with NumPy arrays, dtypes, vectorized operations- Data analysis using Pandas DataFrames, grouping, pivoting, and time series- Scientific visualization with Matplotlib plots, layouts, and contour graphics- Real-world data work: files, missing data, binning, and indexing- Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning. The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters.WHAT'S INSIDE //Numerical operations on multidimensional arrays/Broadcasting and universal functions (ufuncs)/Discrete & continuous plots/Bar charts, histograms, and contour plots/Series and DataFrames/Working with Excel, CSV, and JSON files/Handling missing data (NaN)/Data visualization techniques/Image processing funda mentals/Budget tracking and incomeexpenditure analysis 572 pp. Englisch. …

Buch. Condición: Neu. Neuware -- Numerical computing with NumPy arrays, dtypes, vectorized operations Data analysis using Pandas DataFrames, grouping, pivoting, and time series Scientific visualization with Matplotlib plots, layouts, and contour graphics Real-world data work: files, missing data, binning, and indexing Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning.The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters.WHAT'S INSIDE //Numerical operations on multidimensional arrays/Broadcasting and universal functions (ufuncs)/Discrete & continuous plots/Bar charts, histograms, and contour plots/Series and DataFrames/Working with Excel, CSV, and JSON files/Handling missing data (NaN)/Data visualization techniques/Image processing funda mentals/Budget tracking and incomeexpenditure analysis. …

Hardcover. Condición: Brand New. 450 pages. 6.69x0.51x9.45 inches. In Stock.

Condición: New.

hardcover. Condición: New.

Paperback. Condición: New. 1.

Buch. Condición: Neu. Neuware -- Numerical computing with NumPy arrays, dtypes, vectorized operations Data analysis using Pandas DataFrames, grouping, pivoting, and time series Scientific visualization with Matplotlib plots, layouts, and contour graphics Real-world data work: files, missing data, binning, and indexing Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning.The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters.WHAT'S INSIDE //Numerical operations on multidimensional arrays/Broadcasting and universal functions (ufuncs)/Discrete & continuous plots/Bar charts, histograms, and contour plots/Series and DataFrames/Working with Excel, CSV, and JSON files/Handling missing data (NaN)/Data visualization techniques/Image processing funda mentals/Budget tracking and incomeexpenditure analysisHanser Fachbuchverlag, Kolberger Str. 22, 81679 München 572 pp. Englisch. …

Buch. Condición: Neu. Numeric Python | Python Data Analysis with NumPy, Pandas, and Matplotlib | Bernd Klein | Buch | 572 S. | Englisch | 2026 | Hanser Publications | EAN 9781569904954 | Verantwortliche Person für die EU: Carl Hanser Verlag GmbH & [.], Vilshofener Str. 10, 81679 München, info[at]hanser[dot]de | Anbieter: preigu. …

Paperback. Condición: New. 1.

Buch. Condición: Neu. Neuware - - Numerical computing with NumPy arrays, dtypes, vectorized operations- Data analysis using Pandas DataFrames, grouping, pivoting, and time series- Scientific visualization with Matplotlib plots, layouts, and contour graphics- Real-world data work: files, missing data, binning, and indexing- Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning. The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters.WHAT'S INSIDE //Numerical operations on multidimensional arrays/Broadcasting and universal functions (ufuncs)/Discrete & continuous plots/Bar charts, histograms, and contour plots/Series and DataFrames/Working with Excel, CSV, and JSON files/Handling missing data (NaN)/Data visualization techniques/Image processing funda mentals/Budget tracking and incomeexpenditure analysis.…

Buch. Condición: Neu. Neuware -- Numerical computing with NumPy arrays, dtypes, vectorized operations- Data analysis using Pandas DataFrames, grouping, pivoting, and time series- Scientific visualization with Matplotlib plots, layouts, and contour graphics- Real-world data work: files, missing data, binning, and indexing- Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning. The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters.WHAT'S INSIDE //Numerical operations on multidimensional arrays/Broadcasting and universal functions (ufuncs)/Discrete & continuous plots/Bar charts, histograms, and contour plots/Series and DataFrames/Working with Excel, CSV, and JSON files/Handling missing data (NaN)/Data visualization techniques/Image processing funda mentals/Budget tracking and incomeexpenditure analysis 572 pp. Englisch. …

Paperback. Condición: new. Paperback. - Numerical computing with NumPy arrays, dtypes, vectorized operations- Data analysis using Pandas DataFrames, grouping, pivoting, and time series- Scientific visualization with Matplotlib plots, layouts, and contour graphics- Real-world data work: files, missing data, binning, and indexing- Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning. The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Hardcover. Condición: Brand New. 450 pages. 6.69x0.51x9.45 inches. In Stock. This item is printed on demand.

Paperback. Condición: new. Paperback. - Numerical computing with NumPy arrays, dtypes, vectorized operations- Data analysis using Pandas DataFrames, grouping, pivoting, and time series- Scientific visualization with Matplotlib plots, layouts, and contour graphics- Real-world data work: files, missing data, binning, and indexing- Applied Python: image processing, probability, and practical projectsThis book teaches the Python fundamentals required to solve numerical problems in data science and machine learning. The first part focuses on NumPy as the foundation of numerical programming, covering arrays as the core data type, numerical operations, broadcasting, and universal functions, as well as statistics, probability, Boolean masking, and file handling.The second part is devoted to data visualization with Matplotlib, ranging from core concepts to line, bar, histogram, and contour plots. The third part introduces Pandas, including Series and DataFrames, importing and exporting Excel, CSV, and JSON files, handling missing data, and visualization directly within Pandas.The fourth part presents practical applications, including a household budget project, an incomeexpenditure analysis, and an introduction to image processing.The book concludes with a fifth part containing solutions to the numerous exercises that accompany almost every one of the 33 chapters. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …