book

SQL for Data Scientists

by Renee M. P. Teate

September 2021

Beginner

288 pages

6h 54m

English

Wiley

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Who I Am and Why I'm Writing About This TopicWho This Book Is ForWhy You Should Learn SQL if You Want to Be a Data ScientistWhat I Hope You Gain from This BookConventionsReader Support for This Book
Data SourcesTools for Connecting to Data Sources and Editing SQLRelational DatabasesDimensional Data WarehousesAsking Questions About the Data SourceIntroduction to the Farmer's Market DatabaseA Note on Machine Learning Dataset TerminologyExercises
The SELECT StatementThe Fundamental Syntax Structure of a SELECT QuerySelecting Columns and Limiting the Number of Rows ReturnedThe ORDER BY Clause: Sorting ResultsIntroduction to Simple Inline CalculationsMore Inline Calculation Examples: RoundingMore Inline Calculation Examples: Concatenating StringsEvaluating Query OutputSELECT Statement SummaryExercises Using the Included Database
The WHERE ClauseFiltering SELECT Statement ResultsFiltering on Multiple ConditionsMulti-Column Conditional FilteringMore Ways to FilterFiltering Using SubqueriesExercises Using the Included Database
CASE Statement SyntaxCreating Binary Flags Using CASEGrouping or Binning Continuous Values Using CASECategorical Encoding Using CASECASE Statement SummaryExercises Using the Included Database
Database Relationships and SQL JOINsA Common Pitfall when Filtering Joined DataJOINs with More than Two TablesExercises Using the Included Database
GROUP BY SyntaxDisplaying Group SummariesPerforming Calculations Inside Aggregate FunctionsMIN and MAXCOUNT and COUNT DISTINCTAverageFiltering with HAVINGCASE Statements Inside Aggregate FunctionsExercises Using the Included Database
ROW NUMBERRANK and DENSE RANKNTILEAggregate Window FunctionsLAG and LEADExercises Using the Included Database

Setting datetime Field ValuesEXTRACT and DATE_PARTDATE_ADD and DATE_SUBDATEDIFFTIMESTAMPDIFFDate Functions in Aggregate Summaries and Window FunctionsExercises
Demonstrating Exploratory Data Analysis with SQLExploring the Products TableExploring Possible Column ValuesExploring Changes Over TimeExploring Multiple Tables SimultaneouslyExploring Inventory vs. SalesExercises
Thinking Through Analytical Dataset RequirementsUsing Custom Analytical Datasets in SQL: CTEs and ViewsTaking SQL Reporting FurtherExercises
UNIONsSelf-Join to Determine To-Date MaximumCounting New vs. Returning Customers by WeekSummaryExercises
Datasets for Time Series ModelsDatasets for Binary ClassificationTaking Things to the Next LevelExercises
What Factors Correlate with Fresh Produce Sales?How Do Sales Vary by Customer Zip Code, Market Distance, and Demographic Data?How Does Product Price Distribution Affect Market Sales?
Storing SQL Datasets as Tables and ViewsAdding a Timestamp ColumnInserting Rows and Updating Values in Database TablesUsing SQL Inside ScriptsIn ClosingExercises
Chapter 1: Data SourcesChapter 2: The SELECT StatementChapter 3: The WHERE ClauseChapter 4: CASE StatementsChapter 5: SQL JOINsChapter 6: Aggregating Results for AnalysisChapter 7: Window Functions and SubqueriesChapter 8: Date and Time FunctionsChapter 9: Exploratory Data Analysis with SQLChapter 10: Building SQL Datasets for Analytical ReportingChapter 11: More Advanced Query StructuresChapter 12: Creating Machine Learning Datasets Using SQLChapter 14: Storing and Modifying Data

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