book

Foundational Python for Data Science

by Kennedy Behrman

September 2021

Beginner to intermediate

256 pages

6h 48m

English

Addison-Wesley Professional

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Includes

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Running Python StatementsJupyter NotebooksGoogle ColabSummaryQuestions
Basic Types in PythonPerforming Basic Math OperationsUsing Classes and Objects with Dot NotationSummaryQuestions
Shared OperationsLists and TuplesStringsRangesSummaryQuestions
DictionariesSetsFrozensetsSummaryQuestions
Compound Statementsif Statementswhile Loopsfor Loopsbreak and continue StatementsSummaryQuestions
Defining FunctionsScope in FunctionsDecoratorsAnonymous FunctionsSummaryQuestions
Installing and Importing NumPyCreating ArraysIndexing and SlicingElement-by-Element OperationsFiltering ValuesViews Versus CopiesSome Array MethodsBroadcastingNumPy MathSummaryQuestions
SciPy OverviewThe scipy.misc SubmoduleThe scipy.special SubmoduleThe scipy.stats SubmoduleSummaryQuestions
About DataFramesCreating DataFramesInteracting with DataFrame DataManipulating DataFramesManipulating DataInteractive DisplaySummaryQuestions
matplotlibSeabornPlotlyBokehOther Visualization LibrariesSummaryQuestions
Popular Machine Learning LibrariesHow Machine Learning WorksLearning More About Scikit-learnSummaryQuestions
NLTK Sample TextsFrequency DistributionsText ObjectsClassifying TextSummaryExercises
Introduction to Functional ProgrammingList ComprehensionsGeneratorsSummaryQuestions
Grouping State and FunctionSpecial MethodsInheritanceSummaryQuestions
SortingReading and Writing Filesdatetime ObjectsRegular ExpressionsSummaryQuestions

Content preview from Foundational Python for Data Science

1 Introduction to Notebooks

All animals are equal, but some animals are more equal than others.

George Orwell

In This Chapter

This chapter introduces Google Colab’s Jupyter notebook environment, which is a great way for a beginner to get started in scientific Python development. This chapter begins by looking at traditional ways of running Python code.

Running Python Statements

Historically, Python was invoked either in an interactive Python shell or by supplying text files to the interpreter. If you have Python installed ...