Excel Analysis

Analyzing Excel data with multiple sheets involves using pandas and openpyxl to read, normalize, and merge data across sheets, then aggregating it to produce a consolidated summary report. This skill automates that workflow to output cleaned data ready for pivoting.

Yes, generating charts from an Excel spreadsheet requires reading the data with pandas and openpyxl, then using matplotlib to render bar, line, and pie charts. This skill visualizes trends directly from your spreadsheet data to produce graphical outputs.

Cleaning and normalizing Excel data for analysis involves filtering, standardizing, and merging datasets across sheets for consistent formatting. This skill handles data prep by transforming raw spreadsheets into structured outputs ready for pivot tables and chart generation.

Yes, analyzing Excel files with numeric and categorical data involves reading mixed column types with pandas, aggregating dimensions appropriately, and producing pivot tables. This skill processes both data types to generate summarized reports and visualizations.

Yes, analyzing Excel spreadsheets requires pandas, openpyxl, and matplotlib to read files, manipulate tabular data, and render charts. These dependencies are necessary to execute the data reading, aggregation, and visualization processes.