Example 1: A cell-level manipulation example question involves manipulating a non-standard relational table (missing header on column D and column E).

This example shows a cell-level manipulation data example which aims to extract a specific part of a text string from a column of cells. The instruction contains the demand of the user and an example manipulating action of the question, which rarely occur in synthetic instructions of the previous benchmarks. Furthermore, the table within the spreadsheet file is a non-standard relational table that lacks a complete table header. The final result is required to be filled in the cells from B3 to B14, which ensure the uniqueness of the answer.

Example 2: A sheet-level manipulation example question involves manipulating multiple tables in one sheet (first table from A1 to B22; second table from E1 to T22).

This example shows a sheet-level manipulation data example aimed at creating a grid for a duty assignment schedule. The instruction contains the demand of the user, the current formula solution and the error encountered by the user. Besides, the spreadsheet file contains two relational tables in one sheet. The final result should be filled in a two dimensional position (i.e., F2 to T22).

Example 3: A sheet-level manipulation example question involves manipulating multiple tables on multiple sheets.

This example shows a sheet-level manipulation data example aims to search across sheets based on a sheet name and two dates (i.e., first date and last date). The instruction contains a complex requirements, a detailed explanation, a manipulation example and the error encountered by the user. Moreover, the spreadsheet file contains multiple sheets, including the table to be manipulated (e.g., sheets named BUYING or SALES) and examples of possible answers (e.g., sheets named CASE1 or CASE2). The final result should be inserted into a two-dimensional location on the sheet named SH2.

Example 4: A test case modified from the question in Example 3.

This example shows a test case modified from the question in Example 3. This test case is constructed following the user's requirements in the instruction. The user expects to obtain a result that will search within a specific sheet name (cell G2). Only the rows with a date falling between the first date (cell C2) and last date (Cell E2) should be returned. Therefore, we modify the value of the sheet name (cell G2) to construct a new test case, as highlighted in yellow. This test case yields search results in the SALES sheet, rather than the original case that searches in the BUYING sheet. The values in the answer position also change, as highlighted in red. By modifying the sheet name, we can alter the sheet that is being searched, enabling a more comprehensive assessment of the solution's effectiveness.

Instruction: Complete the financial model based on the provided assumptions. Ensure the existing structure, layout, and formatting of the model are preserved throughout the process. In the Financials sheet, calculate CAGR for both historical and forecast periods for Revenue, EBITDA, EBIT, PAT, and Total Assets. In the Assumptions sheet, calculate Average Days Inventory for 2014F–2018F based on prior two years' average, reducing by 0.5 days from 2015F–2018F, then derive forecasted inventories. In the Ratio Analysis sheet, calculate Total Asset Turnover, then calculate EV/EBITDA. In the Valuation sheet, calculate Terminal Value.

Example 1: Financial Modeling.

Instruction: Please audit and fix this file thoroughly. Errors may include but are not limited to: formula logic errors or inconsistencies, hardcoded values that should be formulas, broken cell references, data validation issues, potential calculation errors, inconsistent formatting or naming conventions, best practice violations, and any other issues that could affect accuracy or maintainability.

Example 2: Debugging.

Instruction: Create 2 Earnings Per Share charts using the provided dataset in the Surprise sheet (rows 50-71). The first chart is a multi-series combo chart shown by quarter. The primary Y-axis tracks EPS values and the secondary Y-axis tracks Price. Title the chart "Quarterly Price Impact Analysis" at the top center. Display 4 series: Differential (as overlay floating bars spanning from Mean to After Event for each period), After Event (line), Mean (Estimated Value) (markers only), and Price (line on secondary axis). The second chart is a diverging vertical column chart showing Price Impact (%) by quarter, titled "Earnings Per Share: Actual vs. Estimated Performance" at the top center. Both charts should display quarters from Q3 2020 to Q3 2025 on the X-axis.

Example 3: Visualization.