9781098190255 - think stats: exploratory data analysis de downey, allen b (37 resultados)
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Paperback. Condición: new. Paperback. If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you…'ll learn the entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns and testing hypotheses.Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place.Analyze data distributions and visualize patterns using Python librariesImprove predictions and insights with regression modelsDive into specialized topics like time series analysis and survival analysisIntegrate statistical techniques and tools for validation, inference, and moreCommunicate findings with effective data visualizationTroubleshoot common data analysis challengesBoost reproducibility and collaboration in data analysis projects with interactive notebooks This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback or Softback. Condición: New. Think STATS: Exploratory Data Analysis. Book.
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Paperback. Condición: New. If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn t…he entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns and testing hypotheses.Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place.Analyze data distributions and visualize patterns using Python librariesImprove predictions and insights with regression modelsDive into specialized topics like time series analysis and survival analysisIntegrate statistical techniques and tools for validation, inference, and moreCommunicate findings with effective data visualizationTroubleshoot common data analysis challengesBoost reproducibility and collaboration in data analysis projects with interactive notebooks.
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Paperback. Condición: New. If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn t…he entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns and testing hypotheses.Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place.Analyze data distributions and visualize patterns using Python librariesImprove predictions and insights with regression modelsDive into specialized topics like time series analysis and survival analysisIntegrate statistical techniques and tools for validation, inference, and moreCommunicate findings with effective data visualizationTroubleshoot common data analysis challengesBoost reproducibility and collaboration in data analysis projects with interactive notebooks.
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Paperback. Condición: new. Paperback. If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you…'ll learn the entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns and testing hypotheses.Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place.Analyze data distributions and visualize patterns using Python librariesImprove predictions and insights with regression modelsDive into specialized topics like time series analysis and survival analysisIntegrate statistical techniques and tools for validation, inference, and moreCommunicate findings with effective data visualizationTroubleshoot common data analysis challengesBoost reproducibility and collaboration in data analysis projects with interactive notebooks This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Paperback. Condición: New. If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn t…he entire process of exploratory data analysis-from wrangling data and generating statistics to identifying patterns and testing hypotheses.Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place.Analyze data distributions and visualize patterns using Python librariesImprove predictions and insights with regression modelsDive into specialized topics like time series analysis and survival analysisIntegrate statistical techniques and tools for validation, inference, and moreCommunicate findings with effective data visualizationTroubleshoot common data analysis challengesBoost reproducibility and collaboration in data analysis projects with interactive notebooks.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. Neuware -If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you…'ll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter not Elektronisches Buch, so you can read the text, run the code, and work on exercises all in one place. - Analyze data distributions and visualize patterns using Python libraries - Improve predictions and insights with regression models - Dive into specialized topics like time series analysis and survival analysis - Integrate statistical techniques and tools for validation, inference, and more - Communicate findings with effective data visualization - Troubleshoot common data analysis challenges - Boost reproducibility and collaboration in data analysis projects with interactive not Elektronisches Buch Englisch.
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Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AlemaniaRheinberg-Buch Andreas Meier eK
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EUR 80,50
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Taschenbuch. Condición: Neu. Neuware -If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you…'ll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter not Elektronisches Buch, so you can read the text, run the code, and work on exercises all in one place. - Analyze data distributions and visualize patterns using Python libraries - Improve predictions and insights with regression models - Dive into specialized topics like time series analysis and survival analysis - Integrate statistical techniques and tools for validation, inference, and more - Communicate findings with effective data visualization - Troubleshoot common data analysis challenges - Boost reproducibility and collaboration in data analysis projects with interactive not Elektronisches Buch Englisch.
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Librería: Wegmann1855, Zwiesel, AlemaniaWegmann1855
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Taschenbuch. Condición: Neu. Neuware -If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you…'ll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter not Elektronisches Buch, so you can read the text, run the code, and work on exercises all in one place. - Analyze data distributions and visualize patterns using Python libraries - Improve predictions and insights with regression models - Dive into specialized topics like time series analysis and survival analysis - Integrate statistical techniques and tools for validation, inference, and more - Communicate findings with effective data visualization - Troubleshoot common data analysis challenges - Boost reproducibility and collaboration in data analysis projects with interactive not Elektronisches Buch.
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