pivot-table-cross-analysis

To create a crosstab pivot table from Excel data with merged cells, the skill cleans missing values by restructuring target columns, then builds pandas-based cross tables for multi-dimensional categorical cross-analysis. It resolves merged-cell issues automatically before computing frequencies.

To visualize a crosstab percentage distribution as a heatmap in Python, the skill generates Seaborn heatmaps with built-in Chinese font support. It converts raw frequency counts into proportion distributions to help you quickly spot category differences visually.

Yes, you can extract Top-N ranking insights and export them to a multi-sheet Excel report. The skill extracts top performers per category and overall rankings, then outputs all crosstab tables and heatmap insights into a single multi-sheet Excel file.

Yes, this crosstab analysis tool works for award distribution, performance evaluation, and market-share style datasets. It processes structured categorical data to generate crosstab frequency and percentage reporting, making it ideal for multi-dimensional categorical cross-analysis.

The best way to clean messy Excel categorical data for cross-analysis is to fix merged-cell missing values and restructure target columns. The skill handles this preparation automatically, enabling accurate multi-dimensional categorical cross-analysis without manual data cleaning.