The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001
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Data Science, Big Data and Data Diversity Data (DATA2001)
Added on 2022-01-21
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DATA2001: Data Science, Big Data and Data Diversity Data Preparation and Exploration with Python Presented by Alan Fekete Material prepared by Uwe Roehm School of Computer Science The University of Sydney Page 1 Jupyter Notebooks: The Python Environment in DATA2001 The University of Sydney Page 2 Jupyter Notebooks support interactive Data Science with Python IPython interactive command shell offers: Introspection Tab completion Command history Jupyter runs in a browser and supports: Sharing and documenting of live
The University of Sydney Page 2 Jupyter Notebooks: The Python Environment in DATA2001
Data Science, Big Data and Data Diversity Data (DATA2001)
Added on 2022-01-21
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The University of SydneyPage1 DATA2001: Data Science, Big Data and Data Diversity Data Cleaning and Exploration with Python Presented by Alan Fekete Material prepared by UweRoehm School of Computer Science
The University of SydneyPage2 JupyterNotebooks: The Python Environment in DATA2001
The University of SydneyPage3 JupyterNotebooks support interactive Data Science with Python –IPythoninteractive command shell offers: –Introspection –Tab completion –Command history –Jupyterruns in a browser and supports: –Sharing and documenting of live code –Data cleaning,visualisation, machine learning,... –Jupyter’sgallery of interesting notebooks: https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks –We provideJupyterservers which run Python 3 https://ucpu0.ug.it.usyd.edu.au/(remember you need to be using VPN, if off campus)
The University of SydneyPage4 1.Click here for file open dialogue 2.Click upload next to file name
The University of SydneyPage5 Installing Python andJupyterusing Anaconda –You can use ourJupyter server –but it can be slow –If you wish, you caninstall Python and Jupyterprivately,eg using Anaconda Distribution, which includes Python, theJupyterNotebook, and other commonly used packages for scientific computing and data science.
The University of SydneyPage6 Python and Data Science Libraries
The University of SydneyPage7 Python background –Students who did data1002: this should mostly be revision –If you didn’t really master pandas, matplotlib before, do so now! –Also note the following key differences •More sophisticated ways to consider the kinds of data (not just numerical/castegorical) –Students who learned Python elsewhere (eginfi1110): you need to learn how to use particular libraries (Pandas, matplotlib etc) from the examples here, and online resources
The University of SydneyPage8 Python general concepts –general program syntax –variables and types –integer and float numbers, string types, type conversion –list, dictionary, tuple and set –condition statements (if/elif/else) –for loops, ranges –functions –print(),len(), lower(), upper(),... –nesting of functions; example:print(len(str.upper() ) )
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