In cross-industry data processing scenarios, importing data from CSV and PDF files into Excel is one of the most common and error-prone tasks — finance teams reconcile CSV bank statements, e-commerce teams organize order files exported from multiple platforms, and administrative staff handle PDF statements from suppliers. These files come in all shapes and formats: inconsistent CSV delimiters, fields containing commas, dates appearing in various forms, phone numbers and ID numbers that start with 0 are treated as numbers and lose their leading zeros; PDF tables cannot be edited directly, and copying them into Excel misaligns rows, columns, and merged cells.

The traditional approach is to split columns manually, set formats column by column, and hunt for erroneous cells by eye. A CSV file with a few hundred rows often takes half an hour of repeated adjustment; PDF tables can only be copied and pasted row by row. Traditional methods are also prone to misaligned columns, misplaced dates, and numbers turning into text. As data volume grows, manual processing becomes nearly impossible.

Take a finance team reconciling bank statements, for example: after receiving a CSV, the usual routine is to confirm the encoding in a text editor first, split the columns in Excel, set date and amount formats column by column, and then hunt for anomalous values by eye. A field containing a comma shifts the whole row, accounts starting with 0 lose their leading zeros, and only after repeated adjustment does the table become usable. PDF statements can only be copied and pasted row by row — rows, columns, and merged cells are almost all misaligned, and reconstructing a single statement often eats up half a day.

Comparison with Traditional SDK API Processing

This article introduces how to use the Excel AI capabilities of Spire.Agent.Office to implement CSV smart column splitting import and PDF table import, automatically completing data type detection and highlighting erroneous formats in red, with just a single natural language instruction.

• CSV Smart Column Splitting Import
• PDF Table Import to Excel

For product installation and SpireToken configuration, please refer to Integrating Spire.Agent.Office in a .NET Project. The following examples assume Spire.Agent.Office is already installed and SpireToken is configured.

CSV Smart Column Splitting Import

CSV is the most common format for data exchange, yet also the least "controllable": the delimiter may be a comma, a tab, or a semicolon; fields may contain commas or line breaks wrapped in quotes; dates, numbers, and text are mixed in the same table; values starting with 0, such as phone numbers and codes, are treated as numbers by default and lose their leading zeros. Import quality directly determines the accuracy of subsequent analysis and reports.

The following example uses the Spire.Agent.Office agent to automatically import a CSV through natural language instructions, completing smart column splitting, data type detection, and highlighting erroneous formats in red:

using Spire.Agent.Office.AI;
using Spire.Agent.Office.Extensions;
using Spire.Xls;

// CSV source file to be imported (passed as an attachment)
string[] attachmentPaths = new string[] { @"C:\DataImport\employee_sales_data.csv" };
// Save path of the import result document
string savePath = @"C:\DataImport\ToXLSX.xlsx";
// SpireToken Key (apply on the official website)
string key = "sk-TF***************************r";
// Natural language instruction
string instruction = "Process as follows:\n" +
    "1. Convert the attached CSV file to an Excel document and apply appropriate formatting to improve readability\n" +
    "2. Unify the formats of dates/sales amounts/phone numbers in the file\n" +
    "3. Mark erroneous and missing data with a red background";

// AI generation
AIResult result = ImportCsvData(instruction, savePath, key, attachmentPaths);

// AI-assisted CSV import
static AIResult ImportCsvData(string instruction, string savePath, string key, string[] attachmentPaths)
{
    // Configure the AI processing options
    AIOptions options = new AIOptions();
    options.SpireToken = key;

    using (Workbook wb = new Workbook())
    {
        AIDocumentProcessor processor = wb.AI(options);
        return processor.ExecuteInstruction(wb, instruction, savePath, attachmentPaths);
    }
}

Original CSV data and smart column splitting import result

PDF Table Import to Excel

PDF is the universal format for distribution and archiving, but the table data inside it cannot be edited directly: copying it into Excel misaligns rows and columns, loses merged cells, and turns numbers and dates into text. When suppliers, banks, or government agencies deliver reports in PDF, accurately restoring the table data into editable Excel is an essential step in moving from fixed-layout documents to electronic processing.

The following example uses the Spire.Agent.Office agent to automatically extract table data from a PDF and write it into Excel through natural language instructions:

using Spire.Agent.Office.AI;
using Spire.Agent.Office.Extensions;
using Spire.Xls;

// PDF source file to be imported (passed as an attachment)
string[] attachmentPaths = new string[] { @"C:\DataImport\PurchaseOrder.pdf" };

// Save path of the import result document
string savePath = @"C:\DataImport\PurchaseOrderData.xlsx";
// SpireToken Key
string key = "sk-TF***************************r";
// Natural language instruction
string instruction =
    "Process as follows:\n" +
    "1. Convert the attached PDF file to an Excel document and apply appropriate formatting to improve readability\n" +
    "2. Unify the formats of dates/sales amounts/phone numbers in the file\n" +
    "3. Mark erroneous and missing data with a red background";
// AI generation
AIResult result = ImportPdfData(instruction, savePath, key, attachmentPaths);

// AI-assisted PDF import
static AIResult ImportPdfData(string instruction, string savePath, string key, string[] attachmentPaths)
{
    // Configure the AI processing options
    AIOptions options = new AIOptions();
    options.SpireToken = key;

    using (Workbook wb = new Workbook())
    {
        AIDocumentProcessor processor = wb.AI(options);
        return processor.ExecuteInstruction(wb, instruction, savePath, attachmentPaths);
    }
}

Original PDF data and table data extracted into Excel

Frequently Asked Questions

Inconsistent CSV delimiters / commas within fields cause column misalignment

Cause: The CSV delimiter may be a semicolon or a tab, or a field may contain a quoted comma or newline, which causes the whole row to shift when columns are split automatically.

Solution: Specify the delimiter in the instruction, or let the AI identify it automatically and correctly handle the quoted fields.

Numbers starting with 0 lose their leading zeros

Cause: Values starting with 0, such as phone numbers, ID numbers, and account numbers, are imported as numeric values, and the leading zeros are dropped.

Solution: Specify the relevant columns as text type in the instruction, such as "set the phone number and ID number columns to text format and preserve the leading zeros".

Obtaining a SpireToken Key

• Contact sales@e-iceblue.com or visit https://www.e-iceblue.com/TemLicense.html to obtain a trial/commercial API key

Configure it in code:

AIOptions options = new AIOptions();
options.SpireToken = key;

In finance and tax scenarios, invoice data entry is one of the most common and time-consuming tasks. The invoice number, date, amount, tax amount and buyer on every invoice must be manually checked and entered into Excel or a financial system one by one. During mid-month reconciliation, month-end tax filing or reimbursement peak periods, the backlog of invoices often numbers in the hundreds, and manual entry speed becomes the bottleneck. The traditional approach is to open each invoice PDF page by page, find the corresponding fields, copy and paste — which is not only inefficient but also highly prone to omissions, misalignments and mistyped amounts. Any single error directly affects the accuracy of reconciliation and tax filing. Invoice layouts also vary widely, with fields in all sorts of positions, further increasing the risk of errors in manual processing. Automating the repetitive work of "reading each invoice and copying its fields" is therefore one of the pain points financial teams most urgently want to solve.

Traditional SDK API vs. Spire.Agent.Office

For "extracting fields from a PDF invoice and exporting to Excel", the traditional SDK and Spire.Agent.Office take two completely different paths. With the traditional approach, you must first figure out the field positions and page structure of every invoice, then write locating and extraction code for each field — change the layout and you must change the code. With the agent approach, you only need to describe in natural language "what to extract and what to export as"; the AI understands and orchestrates the rest:

From the comparison, when invoice layouts, extracted fields or export structures change frequently, the agent only needs a change of one sentence, while the traditional approach requires changing code and redeploying.

This article explains how to use the Spire.Agent.Office PDF AI capability to automatically extract the invoice number, date, amount, tax amount and buyer name from each page of a PDF invoice and export them to Excel, digitalizing your financial documents in one step.

• Automatic Invoice Information Extraction

For product installation and SpireToken configuration, please refer to Integrating Spire.Agent.Office in a .NET Project. The examples below assume Spire.Agent.Office is installed and SpireToken is configured.

Automatic Invoice Information Extraction

The core idea of automatic invoice information extraction is: pass multiple invoice PDFs to the AI agent as attachments; the agent reads each invoice, understands the layout page by page, recognizes fields such as invoice number, issue date, amount, tax ID, tax amount, buyer name and title, and aggregates them into a structured Excel. The whole process is roughly divided into three steps — first the agent reads each invoice PDF and locates the invoice fields on every page; second, it aligns the fields recognized on each page by semantics; finally, it aggregates the results into Excel and beautifies them as requested (auto-fitting column widths, adding borders, keeping numeric values with two decimal places and right-aligned). The whole "page-by-page parsing → field recognition → aggregation & beautification" process is completed automatically by the AI from a natural language instruction, without writing a separate parsing routine for each invoice or worrying about layout differences between suppliers.

For invoice PDFs with dozens or hundreds of pages, the traditional approach requires a set of locating rules for each layout, whereas with the agent approach you always maintain just one natural language instruction no matter how the invoice source or layout changes. Requirements such as the amount basis (tax-inclusive vs. tax-exclusive), column order, or whether to flag anomalies can also be written directly into the instruction and take effect immediately.

The following example uses the Spire.Agent.Office agent to automatically extract invoice information from each page of PDFs and export it to Excel through a natural language instruction:

using Spire.Agent.Office.AI;
using Spire.Agent.Office.Extensions;
using Spire.Pdf;

// PDF processing configuration
string key = "**************************";  // Apply for a SpireToken Key on the official website

string inputDir = @"E:\invoices";  // Directory containing invoice PDFs (multiple allowed)
string[] pdfFiles = Directory.GetFiles(inputDir, "*.pdf", SearchOption.TopDirectoryOnly);
string savePath = @"E:\output\merged.xlsx";  // Output file path (null -> auto-generated to the output directory)

string instruction =
    "Read the attachment files and identify the information of each invoice, extracting the invoice number, issue date, amount, tax ID, tax amount, buyer name and title.\n" +
    "Put each invoice as one row and summarize them into a single Excel table.\n" +
    "When exporting to Excel, please beautify the table appropriately:\n" +
    "auto-fit the column widths so that text is fully displayed; add borders to the whole data area to make rows and columns clear and readable;\n" +
    "keep numeric columns such as amount and tax amount with two decimal places and right-aligned. Finally save as a well-formatted, easy-to-read Excel file.";

// Call the PDF processing function (attachments are the invoice PDFs)
AIResult result = ExecuteDemoPDF(instruction, savePath, key, pdfFiles);

// Execute PDF document AI processing
static AIResult ExecuteDemoPDF(string instruction, string savePath, string key, string[] attachments)
{
    // Create an AIOptions configuration object
    AIOptions options = new AIOptions();
    options.SpireToken = key;  // Set SpireToken Key

    // Process the PDF document with a PdfDocument object
    using (PdfDocument pdf = new PdfDocument())
    {
        // Create the AI document processor; attachments are the invoice PDFs
        AIDocumentProcessor processor = pdf.AI(options);
        return processor.ExecuteInstruction(pdf, instruction, savePath, attachments);
    }
}

Original invoice PDF Extracted and exported Excel

FAQ

The extracted amount or tax amount is incorrect

Reason: The invoice amount has both uppercase and lowercase forms, or the tax-inclusive/tax-exclusive basis is inconsistent.

Solution: Specify the extraction basis clearly in the instruction (e.g., "extract the total amount including tax", "extract the amount excluding tax"); the AI agent will extract according to the specified basis. If the invoice has two forms of amount, it is also recommended to state which one takes precedence to avoid ambiguity.

How are invoices with different layouts recognized?

Reason: Invoices from different suppliers have different layouts and field positions.

Solution: The AI agent can automatically understand the invoice layout and locate fields; for unusual layouts, you can add field hints in the instruction (e.g., "the invoice number is located in the upper-right corner") to help the agent locate more accurately.

The column order / field names of the result don't match expectations

Reason: By default the AI outputs fields in the order it recognizes them.

Solution: Specify the field names and order clearly in the instruction (e.g., "export in the order: invoice number, date, amount, tax amount, buyer"), and the agent will arrange the output columns as requested.

Getting a SpireToken Key

• Contact sales@e-iceblue.com or visit https://www.e-iceblue.com/TemLicense.html to obtain a trial/commercial API key

Configure it in code:

AIOptions options = new AIOptions();
options.SpireToken = key;

In daily office work, data often needs to be exchanged between Excel spreadsheets and OpenDocument spreadsheets (ODS). ODS is an open-standard spreadsheet format widely used in open-source office software such as LibreOffice and OpenOffice. Spire.XLS for JavaScript runs entirely in the browser via WebAssembly, using a virtual file system (VFS) to manage input and output files — no backend server is required. It provides simple, easy-to-use APIs that make format conversion more convenient.

With Spire.XLS for JavaScript, you can save an Excel workbook as ODS format to work seamlessly with open-source office software, or import an ODS file to create a fully formatted Excel workbook. This makes data migration between different applications more convenient and efficient.

This article covers two core features:

• Convert Excel Workbook to ODS File
• Convert ODS File to Excel Workbook

For installation and project setup, refer to Integrating Spire.XLS for JavaScript in a React Project. The examples below assume Spire.XLS is installed and the WebAssembly module is initialized.

Convert Excel Workbook to ODS File

Exporting Excel data as ODS format makes it easy to open and edit directly in open-source office software such as LibreOffice and OpenOffice. With Spire.XLS for JavaScript, you can save an entire workbook as an ODS file, preserving table structure, styles, and data while enabling cross-platform data sharing. The steps are as follows:

• Create a Workbook object and load an existing Excel file.
• Call the workbook's SaveToFile() method, specifying the output filename and the FileFormat.ODS file format.
• Dispose of the workbook resources, read the result file from VFS, and trigger the download.

Below is a complete code example demonstrating how to convert Excel to ODS in React:

function App() {
  const convertToODS = async () => {
    // Get the Spire.XLS WASM module
    const xlsModule = window.wasmModule?.spirexls;

    // Check if the module is ready
    if (!xlsModule) {
      alert('Spire.Xls is not ready yet');
      return;
    }

    // Load the font file to ensure proper text rendering
    await window.spire.FetchFileToVFS('ARIAL.TTF', '/Library/Fonts/', `${process.env.PUBLIC_URL}font/`);

    // Load the sample Excel file into VFS
    await window.spire.FetchFileToVFS('Sample.xlsx', '', `${process.env.PUBLIC_URL}data/`);

    // Create a workbook object and load the Excel file
    const workbook = new xlsModule.Workbook();
    workbook.LoadFromFile({ fileName: 'Sample.xlsx' });

    // Save the workbook as an ODS file
    const outputFileName = 'ExcelToODS.ods';
    workbook.SaveToFile({ fileName: outputFileName, fileFormat: xlsModule.FileFormat.ODS });
    workbook.Dispose();

    // Read the file from VFS and trigger download
    const fileArray = window.dotnetRuntime.Module.FS.readFile(outputFileName);
    const blob = new Blob([fileArray], { type: 'application/vnd.oasis.opendocument.spreadsheet' });
    const url = URL.createObjectURL(blob);
    const a = document.createElement('a');
    a.href = url;
    a.download = outputFileName;
    a.click();
    URL.revokeObjectURL(url);
  };

  return (
    <div style={{ textAlign: 'center', height: '300px' }}>
      <h1>Convert Excel to ODS</h1>
      <button onClick={convertToODS}>
        Generate
      </button>
    </div>
  );
}

export default App;

Excel converted to ODS with Spire.XLS for JavaScript

Convert ODS File to Excel Workbook

Importing an ODS file into an Excel spreadsheet allows you to take full advantage of Excel's powerful formatting, calculation, and charting capabilities. Spire.XLS for JavaScript supports loading an ODS file directly via the LoadFromFile() method, which automatically detects its file format, and then you can save the workbook as an Excel file. The steps are as follows:

• Load the font file and ODS sample file into the VFS.
• Create a Workbook object and load the ODS file via the LoadFromFile() method.
• Save the workbook as an Excel file and trigger the download.

Below is a complete code example demonstrating how to convert ODS to Excel in React:

function App() {
  const convertToExcel = async () => {
    // Get the Spire.XLS WASM module
    const xlsModule = window.wasmModule?.spirexls;

    // Check if the module is ready
    if (!xlsModule) {
      alert('Spire.Xls is not ready yet');
      return;
    }

    // Load the font file to ensure proper text rendering
    await window.spire.FetchFileToVFS('ARIAL.TTF', '/Library/Fonts/', `${process.env.PUBLIC_URL}font/`);

    // Load the ODS sample file into VFS
    await window.spire.FetchFileToVFS('Sample.ods', '', `${process.env.PUBLIC_URL}data/`);

    // Create a workbook object and load the ODS file
    const workbook = new xlsModule.Workbook();
    workbook.LoadFromFile({ fileName: 'Sample.ods' });

    // Save the workbook and release resources
    const outputFileName = 'ODSToExcel.xlsx';
    workbook.SaveToFile({ fileName: outputFileName, version: xlsModule.ExcelVersion.Version2010 });
    workbook.Dispose();

    // Read the file from VFS and trigger download
    const fileArray = window.dotnetRuntime.Module.FS.readFile(outputFileName);
    const blob = new Blob([fileArray], { type: 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet' });
    const url = URL.createObjectURL(blob);
    const a = document.createElement('a');
    a.href = url;
    a.download = outputFileName;
    a.click();
    URL.revokeObjectURL(url);
  };

  return (
    <div style={{ textAlign: 'center', height: '300px' }}>
      <h1>Convert ODS to Excel</h1>
      <button onClick={convertToExcel}>
        Generate
      </button>
    </div>
  );
}

export default App;

ODS converted to Excel with Spire.XLS for JavaScript

FAQ

Why can't the generated ODS file be opened properly?

Cause: When saving the workbook with the SaveToFile() method, if the correct output file format is not specified via the fileFormat parameter, the generated file format may not match the extension, causing it to fail to open.

Solution: Specify the specific file format enum value xlsModule.FileFormat.ODS when saving as ODS:

const outputFileName = 'ExcelToODS.ods';
workbook.SaveToFile({ fileName: outputFileName, fileFormat: xlsModule.FileFormat.ODS });

How to handle the downloaded ODS file being opened as another type or unrecognized?

Cause: The MIME type is not set correctly when creating the Blob, so the browser cannot recognize the downloaded file as an ODS document, which may cause it to open as another type or display garbled text.

Solution: Specify the correct MIME type when downloading and make sure the download filename ends with .ods:

const blob = new Blob([fileArray], { type: 'application/vnd.oasis.opendocument.spreadsheet' });
const a = document.createElement('a');
a.href = URL.createObjectURL(blob);
a.download = 'ExcelToODS.ods';
a.click();

Get a Free License

Spire.XLS for JavaScript offers a 30-day full-featured free trial license with no functional limitations. Apply here to evaluate before purchasing.