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Illustration of DuckDB querying a CSV file, a Parquet file, and a Pandas DataFrame simultaneously, with SQL arrows connecting them.
Python

Query CSV, Parquet, and DataFrames with DuckDB in Python

Use DuckDB in Python to run SQL queries directly on CSV, Parquet, and Pandas DataFrames. This guide covers core query patterns, combining sources, and performance tradeoffs.

DuckDBPythonParquetCSV
Side-by-side illustration of PyArrow's columnar memory layout and pandas' row-column DataFrame structure, highlighting their different data representations.
Python

Python PyArrow vs Pandas: A Practical Comparison

python pyarrow vs pandas: Compare Python PyArrow and pandas for data processing: memory layout, API differences, performance tradeoffs, and when to use each.

PyArrowPandasData ProcessingPerformance
A pandas DataFrame with a PyArrow arrow symbol representing the backend integration, emphasizing speed and memory efficiency.
Python

pandas PyArrow Backend: A Practical Guide

Learn how to enable the pandas PyArrow backend, understand the data type changes, and decide when it improves performance and memory use.

pandaspyarrowdataframeperformance
Illustration of Parquet file blocks being compressed by a press, with a balance scale showing the tradeoff between speed and file size.
Python

PyArrow Parquet Compression for Files and Datasets

Configure PyArrow Parquet compression for single files and datasets, compare snappy, zstd, and gzip codecs, and choose the right codec for your workload.

pyarrowparquetcompressiondatasets
A visual representation of reading and writing Parquet files with PyArrow in Python, showing a columnar table and file I/O arrows.
Python

Python PyArrow: Read and Write Parquet Files

A practical guide to reading and writing Parquet files with PyArrow in Python, covering schema control, row group access, partitioning, compression, and memory considerations.

pyarrowparquetdata engineeringcolumnar storage
Diagram comparing PyArrow Table and pandas DataFrame memory layouts, showing shared buffers and copied columns.
Python

PyArrow Tables and pandas: Memory and Integration

How PyArrow Tables and pandas DataFrames convert to each other, when conversion copies memory, and how to structure pipelines to avoid repeated allocation.

pyarrowpandasdataframesmemory management
A split illustration comparing the Python libraries xlsxwriter and openpyxl for Excel file generation, showing a stream of data on one side and an editable workbook on the other.
Python

python xlsxwriter vs openpyxl: Choosing the Right Excel Library

python xlsxwriter vs openpyxl: Compare xlsxwriter and openpyxl for Python Excel workflows: API design, performance, formatting, and when to use each.

xlsxwriteropenpyxlExcelPython
Stylized spreadsheet with green and red highlighted cells next to a blue column chart, representing XlsxWriter conditional formatting and charts.
Python

Python XlsxWriter Charts and Conditional Formatting

Use Python XlsxWriter to add Excel charts and conditional formatting to reports. Covers cell rules, data bars, formula rules, chart series, and combining both features.

XlsxWriterExcel automationconditional formattingdata visualization
Python XlsxWriter workbook with multiple sheets, formatted cells, and formula bar visible
Python

Python XlsxWriter Formatting Formulas and Multiple Sheets

python xlsxwriter formatting formulas and multiple sheets: Learn to combine formatting, formulas, and multiple sheets in Python XlsxWriter to build professional Excel...

xlsxwriterexcelpythonspreadsheet
Illustration of a pandas DataFrame being written into an Excel spreadsheet using XlsxWriter, with a gear icon representing the engine.
Python

Python XlsxWriter: Create Excel and Write Pandas DataFrame

How to use XlsxWriter with pandas to write DataFrames to Excel, format columns and cells, create multi-sheet workbooks, and avoid common export pitfalls.

XlsxWriterpandasExcelDataFrame