Osoby które kupowały "DuckDB: Up and Running", wybierały także:

• Windows Media Center. Domowe centrum rozrywki 66,67 zÅ‚, (8,00 zÅ‚ -88%)
• Ruby on Rails. Ćwiczenia 18,75 zÅ‚, (3,00 zÅ‚ -84%)
• Przywództwo w Å›wiecie VUCA. Jak być skutecznym liderem w niepewnym Å›rodowisku 58,64 zÅ‚, (12,90 zÅ‚ -78%)
• Scrum. O zwinnym zarzÄ…dzaniu projektami. Wydanie II rozszerzone 58,64 zÅ‚, (12,90 zÅ‚ -78%)
• Od hierarchii do turkusu, czyli jak zarzÄ…dzać w XXI wieku 58,64 zÅ‚, (12,90 zÅ‚ -78%)

Spis treści

DuckDB: Up and Running eBook -- spis treści

• Preface
  • Conventions Used in This Book
  • Using Code Examples
  • OReilly Online Learning
  • How to Contact Us
  • Acknowledgements
• 1. Getting Started with DuckDB
  • Introduction to DuckDB
    • Why Use DuckDB?
    • High-Performance Analytical Queries
    • Versatile Integration and Ease of Use Across Multiple Programming Languages
    • Open Source
  • A Quick Look at DuckDB
    • Loading Data into DuckDB
    • Inserting a Record
    • Querying a Table
    • Performing Aggregation
    • Joining Tables
    • Reading Data from pandas
  • Why DuckDB Is More Efficient
    • Execution Speed
    • Memory Usage
  • Summary
• 2. Importing Data into DuckDB
  • Creating DuckDB Databases
  • Loading Data from Different Data Sources and Formats
    • Working with CSV Files
      • Loading using the SQL query method
      • Loading using the register() method
      • Exporting a table to CSV
    • Working with Parquet Files
      • Loading Parquet files
      • Exporting Parquet files
    • Working with Excel Files
      • Loading Excel files
      • Exporting tables to Excel
    • Working with MySQL
  • Summary
• 3. A Primer on SQL
  • Using the DuckDB CLI
    • Importing Data into DuckDB
    • Dot Commands
      • .database
      • .open
      • .table
      • .dump
      • .read
    • Persisting the In-Memory Database on Disk
  • DuckDB SQL Primer
    • Creating a Database
    • Creating Tables
    • Viewing the Schemas of Tables
    • Dropping a Table
  • Working with Tables
    • Populating Tables with Rows
    • Updating Rows
    • Deleting Rows
    • Querying Tables
    • Joining Tables
      • Left join
      • Right join
      • Inner join
      • Full join
      • Multiple table joins
    • Aggregating Data
    • Analytics
  • Summary
• 4. Using DuckDB with Polars
  • Introduction to Polars
    • Creating a Polars DataFrame
      • Selecting columns
      • Selecting rows
      • Selecting rows and columns
      • Using SQL on Polars
    • Understanding Lazy Evaluation in Polars
      • Implicit lazy evaluation
      • Explicit lazy evaluation
  • Querying Polars DataFrames Using DuckDB
    • Using the sql() Function
    • Using the DuckDBPyRelation Object
      • Inserting rows
      • Joining tables
      • Filtering rows
      • Aggregating rows
      • Projecting columns
      • Limiting rows
  • Summary
• 5. Performing EDA with DuckDB
  • Our Dataset: The 2015 Flight Delays Dataset
  • Geospatial Analysis
    • Displaying a Map
    • Displaying All Airports on the Map
    • Using the spatial Extension in DuckDB
      • Converting latitude and longitude to the Point data type
      • Converting a pandas DataFrame to a GeoPandas GeoDataFrame
      • Displaying airport locations on the map
      • Finding nearby airports
  • Performing Descriptive Analytics
    • Finding the Airports for Each State and City
    • Aggregating the Total Number of Airports in Each State
    • Obtaining the Flight Counts for Each Pair of Origin and Destination Airports
    • Getting the Canceled Flights from Airlines
    • Getting the Flight Count for Each Day of the Week
    • Finding the Most Common Timeslot for Flight Delays
    • Finding the Airlines with the Most and Fewest Delays
  • Summary
• 6. Using DuckDB with JSON Files
  • Primer on JSON
    • Object
    • String
    • Boolean
    • Number
    • Nested Object
    • Array
    • null
  • Loading JSON Files into DuckDB
    • Using the read_json_auto() Function
    • Using the read_json() Function
      • Array of JSON objects
      • Newline-delimited (ND) JSON
      • Nested JSON
      • Custom JSON file
      • Loading multiple JSON files
    • Using the COPY-FROM Statement
  • Exporting Tables to JSON
  • Summary
• 7. Using DuckDB with JupySQL
  • What Is JupySQL?
    • Installing JupySQL
    • Loading the sql Extension
    • Integrating with DuckDB
    • Performing Queries
    • Storing Snippets
  • Visualization
    • Histograms
    • Box Plots
    • Pie Charts
    • Bar Plots
  • Integrating with MySQL
    • Using Environment Variables
    • Using an .ini File
    • Using keyring
  • Summary
• 8. Accessing Remote Data Using DuckDB
  • DuckDBs httpfs Extension
  • Querying CSV and Parquet Files Remotely
    • Accessing CSV Files
    • Accessing Parquet Files
  • Querying Hugging Face Datasets
    • Using Hugging Face Datasets
    • Reading the Dataset Using hf:// Paths
    • Accessing Files Within a Folder
    • Querying Multiple Files Using the Glob Syntax
    • Working with Private Hugging Face Datasets
      • Uploading a private dataset
      • Creating an access token
      • Performing authentication
  • Summary
• 9. Using DuckDB in the Cloud with MotherDuck
  • Introduction to MotherDuck
    • Signing Up for MotherDuck
    • MotherDuck Plans
  • Getting Started with MotherDuck
    • Adding Tables
    • Creating Schemas
    • Sharing Databases
    • Creating a Database
    • Detaching a Database
  • Using the Databases in MotherDuck
    • Querying Your Database
    • Writing SQL Using AI
  • Using MotherDuck Through the DuckDB CLI
    • Connecting to MotherDuck
    • Querying Databases on MotherDuck
    • Creating Databases on MotherDuck
    • Performing Hybrid Queries
  • Summary
• Index