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Data analysis crash course for beginners : Pandas + Python /
Take your first step toward data analysis with Pandas - Learn about DataFrames, Jupyter Notebook, iPython, and Pandas commands. Pandas is an open-source library providing you with high-performance, easy-to-use data structures and data analysis tools for Python. Pandas provide a powerful and comprehe...
| Clasificación: | Libro Electrónico |
|---|---|
| Formato: | Electrónico Video |
| Idioma: | Inglés |
| Publicado: |
[Birmingham, United Kingdom] :
Packt Publishing,
[2021]
|
| Edición: | [First edition]. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 300 | |a 1 online resource (1 video file (1 hr., 1 min.)) : |b sound, color. | ||
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| 520 | |a Take your first step toward data analysis with Pandas - Learn about DataFrames, Jupyter Notebook, iPython, and Pandas commands. Pandas is an open-source library providing you with high-performance, easy-to-use data structures and data analysis tools for Python. Pandas provide a powerful and comprehensive toolset for working with data, including tools for reading and writing diverse files, data cleaning and wrangling, analysis and modeling, and visualization. Fields with the widespread use of Pandas include data science, finance, neuroscience, economics, advertising, web analytics, statistics, social science, and many areas of engineering. This course covers fundamentals of data analysis with Python, predominantly using Pandas library. This course starts with covering the fundamentals of data analysis. You will be then working with Pandas, iPython, Jupyter Notebook. After that, you will explore important Jupyter Notebook commands. Post that, you will be working with CSV, Excel, TXT, JSON files, and API responses. Finally, you will be working with DataFrames (indexing, slicing, adding, and deleting). By the end of this course, you will have a good understanding of Pandas and will be ready to explore data analysis in-depth in the future. | ||
| 588 | 0 | |a Online resource; title from title details screen (O’Reilly, viewed March 8, 2022). | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
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| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Exploration de données (Informatique) | |
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