A practical guide to using pandas `read_excel` for loading Excel files (.xlsx, .xls, .xlsb, OpenDocument) into DataFrames. Covers engine selection (openpyxl, xlrd, pyxlsb, calamine), key parameters like sheet_name, usecols, dtype, parse_dates, and na_values, reading single or multiple sheets, handling remote URLs, exporting to dict/JSON/CSV, performance tips, and common error fixes.
Table of contents
IntroductionKey takeawaysPrerequisitesStep 1: Inspect a workbook before you parse itStep 2: Read a single sheet with read_excelStep 3: Core parameters at a glanceStep 4: Select columns and skip noiseStep 5: Handle workbooks without a clean header rowStep 6: Read multiple sheets in one callStep 7: Control types, missing tokens, and datesStep 8: Choose the right engineStep 9: Read files hosted at a HTTPS URLStep 10: Export to dict, JSON, or CSVStep 11: Practical performance habitsStep 12: Compare read_excel with other toolsTroubleshootingFAQsConclusionContinue building on DigitalOceanSort: