When a folder accumulates a large number of txt Notepad files, opening each one individually to check the path, line count, character count, and text encoding is very time-consuming and prone to missed statistics. This article introduces how to use the file information statistics function of the office software " HeSoft Doc Batch Tool " to batch summarize the names, paths, extensions, sizes, creation times, modification times, text encodings, text line counts, and text character counts of multiple TXT files into an Excel spreadsheet, suitable for scenarios such as data inventory, content auditing, text data organizing, and archival handover.
In daily office work, organization of teaching materials, content operations, data archiving, or project handovers, we often encounter a seemingly simple but very time-consuming problem: a folder contains many txt notepad files, and we need to count the full path, file name, number of lines, character count, and text encoding for each file. If it's just one or two files, manually opening Notepad to check is acceptable; but when the number of files reaches dozens, hundreds, or even more, opening them one by one, copying paths, and recording line and character counts is not only inefficient but also prone to omissions or input errors due to repetitive work.
Especially regarding text encoding, many users don't usually pay special attention to it. However, during batch system imports, data migration, programmatic text reading, or troubleshooting garbled characters, encoding differences like utf-8, gb18030, windows-1252, utf-16, us-ascii can directly affect subsequent processing results. Therefore, exporting the basic and detailed text information of TXT files to a unified Excel spreadsheet can make subsequent filtering, verification, archiving, and analysis much clearer.
This article will combine screenshots to introduce how to use the "File Information Statistics" function in the office software HeSoft Doc Batch Tool to perform batch statistics on multiple TXT files and summarize the statistical results into Excel. The entire process does not require opening files individually, making it suitable for office users looking to reduce repetitive operations and improve file organization efficiency.
Applicable Scenarios: When is batch statistics for TXT file information suitable
Batch statistics of TXT file paths, line counts, character counts, and text encoding is not just about "seeing how many files there are." In many practical tasks, such statistical tables can directly serve as a material list, handover document, or basis for troubleshooting.
1. Text Material Archiving and File List Creation
For example, training institutions, schools, data administrators, or project members need to organize a batch of TXT documents like study notes, course summaries, reading lists, and review materials. Through batch statistics, you can quickly obtain the name, folder path, creation time, modification time, and file size for each file, facilitating future archiving and retrieval.
2. Content Operations or Editorial Teams Counting Text Workload
If a team has a large number of copywriting drafts, scripts, notes, and materials saved in txt format, counting text lines and characters can help determine the content scale. Compared to manually opening each file to check, after batch exporting to Excel, you can sort directly by character count to quickly find text files that are too short, too long, or abnormal.
3. Checking Text Encoding Before Program Import
Many business systems have specific encoding format requirements when importing TXT, CSV, or log text files. If file encodings are inconsistent, garbled characters, import failures, or abnormal field recognition may occur. By running a one-time statistic of text encodings, you can discover in advance which files are utf-8, and which are gb18030, utf-16, or windows-1252, allowing for targeted processing.
4. Verification Before File Migration, Backup, and Handover
Before file migration or handover, it is usually necessary to generate a file directory list. An Excel spreadsheet can record paths, sizes, creation times, modification times, and other information, making it easy to compare completeness after migration and allowing the receiving party to quickly understand the data structure.
5. Preparatory Work Before Batch Text Data Analysis
If you plan to perform segmentation, statistics, cleaning, or import the TXT text into other analysis tools later, knowing the line count, character count, and encoding of each file in advance helps assess data quality. For instance, if the character count for some files is 0 or significantly smaller than others, they might need individual inspection.
Result Preview: A batch of scattered TXT files before processing becomes an Excel summary table after processing
Before Processing: Many TXT notepad files in the folder
As seen in the pre-processing screenshot, the folder contains multiple txt files, such as ReadingJournalNotes.txt, VocabularyPracticeText.txt, GrammarReviewLines.txt, StudyPlanningNotes.txt, CourseSummaryText.txt, etc. At this point, we can only see the file names and some time information in File Explorer; we cannot directly view the text encoding, number of text lines, or number of text characters for each file.
If you need to collect this information for each file individually, the traditional method usually involves opening the file, checking its content, copying the file path, and then manually filling it into Excel. The more files there are, the more noticeable the time consumption becomes.
After Processing: All TXT file information summarized into an Excel spreadsheet
After processing is complete, the software outputs the statistical results as an Excel spreadsheet. As seen in the post-processing screenshot, the table has generated multiple columns of information, including: Path, Name, Name (without extension), Extension, Size (Bytes), Size, Parent Folder Name, Parent Folder Path, Creation Time, Modification Time, and text-file-related items like "Text - Text Encoding," "Text - Line Count," and "Text - Character Count."
This result is very suitable for subsequent filtering and analysis. For example, you can sort by "Text - Line Count" in Excel to find the file with the most lines; filter by "Text - Text Encoding" to quickly locate files with inconsistent encoding; or categorize by "Parent Folder Path" to view file situations in different directories.
Operating Steps: Using HeSoft Doc Batch Tool to Batch Statistics TXT File Information
The following steps, aligned with the screenshot order, explain how to complete the batch statistics. This article uses HeSoft Doc Batch Tool , a batch document processing software designed for office scenarios, suitable for handling large volumes of repetitive tasks like file organization, statistics, classification, and conversion. This operation focuses on using the "File Information Statistics" function within it.
Step 1: Enter "File Organization" and select the "File Information Statistics" function
Upon opening the software, you can see multiple function categories in the left navigation bar, such as Home, Task Flow, All Tools, File Name, Folder Name, File Organization, Word Tools, Excel Tools, PowerPoint Tools, PDF Tools, Text Tools, Image Tools, Video Tools, Audio Tools, etc.
This time, we need to count the paths, sizes, times, and detailed text information of TXT files, so we need to enter the File Organization category on the left. In the function cards on the right, find and click "3. File Information Statistics." The prompt in the screenshot explains that this function is for "batch statistics of various files' names, paths, sizes, times, and metadata information," which aligns with our requirement to export a TXT file list and text statistical results.
The purpose of this step is to select the correct entry point for batch processing. After selecting this function, the software enters a step-by-step wizard page, and the subsequent operation follows the process of "Select records to process," "Set processing options," "Set save location," and "Start processing."
Step 2: Import the TXT files to be counted
After entering the "File Information Statistics" page, you can see operation buttons at the top, including Add Files, Import Files from Folder, Clear, and More. If there are few TXT files scattered in different locations, you can use "Add Files" to select specific files; if these txt notepad files are centrally stored in the same folder, it is recommended to use "Import Files from Folder," which allows importing files from a folder into the list in one go.
As seen in the screenshot, multiple records appear in the list after import, containing fields like Index, Name, Path, Extension, Creation Time, Modification Time, etc. For example, files like ClassNotesArchive.txt, CourseSummaryText.txt, ExamPreparationText.txt have been added to the pending list, with paths showing them as corresponding txt files under D:\test\folders\.
The key to this step is confirming the file list is complete. The bottom of the screenshot shows "Record Count: 20," indicating that 20 files have been imported. Users can check the list to verify if the file names and paths are correct. If files were mistakenly selected, they can be removed using the delete operation on the right side of the list; if a reselection is desired, you can also use "Clear" and then re-import.
After importing and confirming everything is correct, click the Next button at the bottom of the page to enter the processing option settings.
Step 3: Check "Text File Details" in the additional information options
After entering the second step "Set Processing Options," the "Additional Information" options appear on the page. In the screenshot, you can see multiple checkable options, including Word File Details, Excel File Details, PPT File Details, PDF File Details, Text File Details, Image File Details, etc.
Since the objects being processed this time are TXT text files, and the goal is to count text encoding, text line count, and text character count, you need to check "Text File Details." This option is already checked in the screenshot, meaning that when the software generates the statistical results, it will not only export basic file information but also additionally analyze the detailed properties of text files.
This step is very important. If you only count regular file information, usually you can only get basic fields like file name, path, size, and time; after checking "Text File Details," the exported Excel will include columns related to TXT content, such as "Text - Text Encoding," "Text - Line Count," and "Text - Character Count."
After confirming the checkbox is selected, click Next to continue.
Step 4: Set the save location and start processing
As seen from the wizard's top section, the subsequent steps are "Set Save Location" and "Start Processing." Although the screenshot does not expand the save location page, based on the page flow, it is reasonable to infer that the user needs to specify a save location for the statistical results in the next step. It is recommended to choose an easy-to-find directory, such as the current project folder, a temporary directory on the desktop, or a folder specifically designated for report output.
After setting the save location, proceed to "Start Processing." The software will, according to the previously imported file list, batch-read the basic attributes and detailed text information of each TXT file and generate a summary result. Once processing is complete, open the exported Excel file to see the statistical table similar to the one in the result preview.
It is recommended to check the following items after processing: whether the file count matches the imported record count; whether the "Text - Text Encoding" column has empty or abnormal values; whether the "Text - Line Count" and "Text - Character Count" match expectations; and whether the path column points to the correct source file locations.
How to Interpret the Excel Result: Focus on these fields
The exported Excel is not just a file list; it can help users examine TXT files from multiple dimensions. The significance of several common fields is explained below.
Path
The Path indicates the complete location of each file on the disk. It is very useful for material handover, backup verification, and locating abnormal files. Later, if a specific text file is found to have incorrect encoding or an abnormal character count, the original file can be found quickly via the path.
Name and Name (without extension)
"Name" typically includes the .txt extension, while "Name (without extension)" keeps only the primary filename. The former is suitable for verifying the actual file, while the latter suits creating directories, labels, or conducting naming convention analysis.
Extension
In this example, the extensions are all txt. If the batch-imported folder contains other types of files mixed in, this column can help quickly filter out the txt files or check for mistakenly imported doc, docx, xlsx, pdf, etc., files.
Size (Bytes) and Size
File size can indirectly reflect the scale of text content. Character count and file size are usually correlated, but not perfectly identical, because different text encodings occupy different numbers of bytes. For example, the byte occupation rules differ for utf-8, utf-16, and gb18030.
Creation Time and Modification Time
These two columns are suitable for file lifecycle analysis, such as checking which files were recently updated and which have not been modified for a long time. In data archiving scenarios, modification time is also often used to judge file versions.
Text - Text Encoding
This is a critical column in TXT batch statistics. The screenshot shows that different files might be identified as having utf-8, gb18030, windows-1252, utf-16, us-ascii, etc., encoding. If there is a need to import them uniformly into a system later, you can first filter out files with inconsistent encoding based on this column to avoid garbled text imports.
Text - Line Count
The line count is suitable for counting text structure. For example, for a TXT data file with one record per line, the line count can estimate the number of records; for teaching notes, study lists, and log files, the line count can also be used to judge the content scale.
Text - Character Count
Character count is suitable for counting the volume of text content. For content like copywriting, explanations, scripts, and notes, character count is more intuitive than file size. After exporting to Excel, functions like sorting, filtering, and summarization can be used for further analysis.
Common Questions and Considerations
1. Why is it essential to check "Text File Details"?
Because text encoding, line count, and character count are additional information related to the text content, not regular file properties. If this option is not checked, the exported result might only contain basic information like name, path, extension, size, and time, failing to meet the need for counting TXT text content.
2. Can TXT files in multiple subfolder levels be counted?
The screenshot shows file import via a folder. Whether subfolders are included depends on the actual options and rules of the software during import. To ensure accurate results, it is recommended to review the pending file list after import to confirm all files intended for statistical processing are present in the list.
3. What to do if the time column displays "#######" in Excel?
The post-processing screenshot shows some time columns displaying hash symbols, which is typically a display issue in Excel caused by insufficient column width, not necessarily indicating data errors. You can appropriately widen the corresponding column in Excel or adjust the cell format to view the complete time information.
4. What is the use of text encoding recognition results?
Text encoding can help determine if a file is likely to display garbled characters. For example, if some files are utf-8, others are gb18030 or utf-16, and the subsequent system only supports one encoding, advance conversion or group processing is needed. Counting the encoding first, then processing the files, is more efficient than troubleshooting after garbled characters appear.
5. Can the statistical results be further filtered and sorted?
Yes. After exporting to Excel, users can continue analysis using Excel's filtering, sorting, conditional formatting, pivot tables, and other features. For example, sort by character count from largest to smallest, group by encoding, filter by folder path, or find recently updated files by modification time.
6. Is it necessary to back up source files before batch statistics?
File information statistics typically involve reading file information and generating a report, not modifying the source file content. However, before any batch operation, especially when vital materials are involved, it is still recommended to keep backups of the original files and first test the process with a small number of samples to confirm the exported fields meet the requirements before processing all files.
Summary: Replace manual registration with batch statistics for more efficient TXT file management
When the number of TXT files is large, manually counting paths, line counts, character counts, and text encodings not only consumes time but is also prone to missing fields, filling errors, and duplicate statistics. With the "File Information Statistics" function of HeSoft Doc Batch Tool , the basic attributes and detailed text information of multiple txt notepad files can be summarized into an Excel spreadsheet at once.
The entire process can be summarized as: enter "File Information Statistics" within "File Organization," import the TXT files needing processing, check "Text File Details," set the save location, and start processing. The resulting Excel report can serve as a file list, as well as a basis for text encoding checking, content scale analysis, data archiving, and project handover.
If you are organizing a large number of txt files, text logs, study notes, or material files, it is recommended to first run a trial with a small number of files. After confirming the result fields meet the requirements, then batch-import all files for statistical analysis. This can significantly reduce repetitive labor, transforming work that originally required opening files one by one into a one-time batch processing and Excel analysis session.