Excel to DataFrame in Python — pandas Tutorial

Excel to data frame in Python, the most common analyst handoff starts here. One library, one line. Pandas reads XLSX in a single call. Most finance data lives in spreadsheets. Pricing sheets, contract terms, fund holdings. Excel is the lingua franca of business data. Pandas reads XLSX with read_excel. The output is a data frame. The same rows, the same columns, ready for everything that comes next. Today, read a 420 row prices sheet from a two-sheet workbook three different ways. Single sheet, all sheets at once, and the Excel file context manager. Reading rows from a spreadsheet into a Python data frame. Three methods, one workbook, one library. First, confirm stock_summary.xlsx exists. Two sheets inside prices with 14 tickers of OHLCV and tickers with sector labels. Open NVIM. Save it as excel_to_dataframe.py. One import, pandas. Hold the file name in a constant. Method one. Pandas read underscore excel pass the path and a sheet name. You get the prices sheet as a single data frame. Method two. Pass sheet underscore name equals none and pandas returns a dictionary. Keys are sheet names, values are data frames. The whole workbook in one call. Notice the print line spreads each sheets shape side by side. Prices at 420 by 8, tickers at 14 by 2. One dictionary, two data frames. Method three. The excel file context manager. Open the workbook once, parse each sheet by name. The file handle stays open across reads. Faster than calling read underscore excel three times. The with block guarantees the file closes even if parsing raises. And excel dot parse takes the same arguments as read underscore excel. Sheet name, header, use equals, all of them. Save and run with python. All three reads land on the same shapes. Prices comes in at 420 rows by 8 columns. Tickers at 14 by 2. Three things to take away. First, p dash d dot read underscore excel is the canonical Excel to data frame in Python. One line per sheet, works on any modern xlsx. Second, when you pass sheet_name equals none, you get every sheet at once as a dictionary. No looping, no file names, no glob. The whole workbook in a single call. Third, the Excel file context manager opens the workbook once and lets you parse multiple sheets without reopening the file. Use it when you need different slices of the same book. Like, subscribe, comment, and share if this helped. Subscribe to the playlist for more Python answers.