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Show Notes
Python for Data Analysis (Wes McKinney)
- Amazon USA Store: https://www.amazon.com/dp/109810403X?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Python-for-Data-Analysis-Wes-McKinney.html
- Apple Books: https://books.apple.com/us/audiobook/python-for-data-analysis-real-world-projects-and/id1827577561?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Python+for+Data+Analysis+Wes+McKinney+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/109810403X/
#Jupyterexploratorycomputing #NumPyvectorizedarrays #pandasDataFramecleaning #groupbyandreshaping #irregulartimeseries #PythonforDataAnalysis
Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter is a technical, practice-oriented guide to the core Python tools used to prepare, inspect, transform, and summarize structured data. Written by Wes McKinney, the creator of pandas, the third edition centers on the working skills required for data-intensive computing rather than on statistical theory or a survey of analytical methods. It introduces relevant Python language features and interactive work in IPython and Jupyter before developing the numerical foundations supplied by NumPy and the labeled tabular structures supplied by pandas. From there, the book addresses the everyday mechanics of an analysis workflow: importing files and external data, resolving incomplete or inconsistent values, combining datasets, reshaping tables, producing basic plots, and handling dates and time series. Examples and accompanying notebooks make the material executable rather than purely conceptual. Its purpose is to help readers understand not only which library operations exist, but also how those operations fit together into reliable data-wrangling processes.
- Amazon USA Store: https://www.amazon.com/dp/109810403X?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Python-for-Data-Analysis-Wes-McKinney.html
- Apple Books: https://books.apple.com/us/audiobook/python-for-data-analysis-real-world-projects-and/id1827577561?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Python+for+Data+Analysis+Wes+McKinney+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/109810403X/
#Jupyterexploratorycomputing #NumPyvectorizedarrays #pandasDataFramecleaning #groupbyandreshaping #irregulartimeseries #PythonforDataAnalysis
Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter is a technical, practice-oriented guide to the core Python tools used to prepare, inspect, transform, and summarize structured data. Written by Wes McKinney, the creator of pandas, the third edition centers on the working skills required for data-intensive computing rather than on statistical theory or a survey of analytical methods. It introduces relevant Python language features and interactive work in IPython and Jupyter before developing the numerical foundations supplied by NumPy and the labeled tabular structures supplied by pandas. From there, the book addresses the everyday mechanics of an analysis workflow: importing files and external data, resolving incomplete or inconsistent values, combining datasets, reshaping tables, producing basic plots, and handling dates and time series. Examples and accompanying notebooks make the material executable rather than purely conceptual. Its purpose is to help readers understand not only which library operations exist, but also how those operations fit together into reliable data-wrangling processes.
