How one can convert textual content recordsdata to Excel (TXT to XLSX): 8 strategies

For those who use textual content recordsdata to retailer and handle knowledge, you have in all probability confronted the problem of changing these recordsdata into CSV, XLSX, or different Excel-compatible codecs.

Excel is a strong software for automation, knowledge evaluation, modeling, reporting, and extra. It will possibly even deal with giant quantities of information effectively.

Nonetheless, you should first deliver your knowledge into Excel to profit from these capabilities. Copying and pasting the information manually from a TXT file to Excel isn’t possible.

The information would possibly find yourself pasted in a single column or the mistaken cells, and it may be time-consuming, particularly with bigger recordsdata. Plus, you danger shedding or misplacing necessary info.

This text will cowl learn how to convert textual content to Excel utilizing on-line and offline instruments and strategies.

Additionally learn: How one can convert Phrase to Excel?

Here is a fast overview of the totally different strategies:

1. Open the textual content file utilizing Excel

This can be a easy technique to transform textual content to Excel. No extra software program or on-line instruments are required.

Simply observe the steps beneath:

1. Open Excel and choose the ‘File’ choice from the menu
2. Click on on ‘Open’ and navigate to the situation of your file
3. Choose ‘All Recordsdata (*.*)’ from the drop-down menu within the decrease proper nook
4. Find and choose your textual content file, then click on ‘Open’ (Notice that Excel can deal with numerous textual content file codecs, together with .txt, .csv (comma-separated values), and .tsv (tab-separated values))
5. Excel’s Textual content Import Wizard will seem — specify how Excel ought to interpret the information in your textual content file
6. Select the suitable Delimiter (comma, tab, or different) that separates your knowledge
7. Preview your knowledge and modify any settings as wanted, then click on ‘End’. (Use Excel’s formatting choices to appropriate knowledge formatting errors with dates or numbers)
8. Your textual content knowledge will now seem in an Excel spreadsheet

Whereas this technique is quick and easy, it could battle with poorly formatted content material, knowledge containing a mixture of numbers, textual content, and dates, or utilization of non-standard delimiters. Excel might not parse and interpret such recordsdata accurately, leading to inconsistencies.

Greatest fitted to: Importing knowledge from sources like exported experiences, log recordsdata, or easy knowledge backups.

2. Copy-paste the tables from Notepad to Excel

One other easy solution to convert textual content to Excel is to repeat the information from a textual content editor like Notepad and paste it into an Excel worksheet. Excel’s Textual content Import Wizard helps you to simply copy and paste tabular knowledge from textual content recordsdata whereas sustaining the construction.

To repeat a textual content desk from Notepad to Excel utilizing the Textual content Import Wizard:

1. Open the textual content file in Notepad or some other textual content editor
2. Choose and replica the tabular knowledge you need to convert
3. Hold a word of how the values are separated (comma, tab, house, and many others.) — the delimiter used
4. Open a brand new Excel workbook and choose the cell the place you need to paste the desk
5. Paste and Choose the Contents. As soon as chosen go to Information -> Textual content to Columns.
6. The Textual content to Columns dialog field will open — choose ‘Delimited‘ and click on ‘Subsequent’
7. Choose the delimiter utilized in your textual content file (comma, tab, house, and many others.) and click on ‘Subsequent’
8. Specify the information format for every column or use the default ‘Normal’ format
9. Click on ‘End’, and the copied knowledge will seem within the Excel worksheet, sustaining the unique tabular construction.

This technique works nicely for small tables, however the knowledge have to be cleanly formatted, with correct delimiters and no lacking or further values. The output Excel desk will not be structured accurately if it comprises inconsistencies or irregular formatting. Additionally, it’s not ideally suited for big datasets as a result of it’s a must to manually copy and paste knowledge, which may be time-consuming and vulnerable to errors.

Greatest fitted to: Transferring knowledge from easy lists or tables with a restricted variety of rows and columns like stock information and buyer lists.

3. Use Excel’s ‘Get Information’ Characteristic

Excel’s ‘Get Information’ function is extra environment friendly for importing and changing textual content to Excel. This function helps a wide range of knowledge sources, together with textual content recordsdata.

Listed below are the steps to observe:

1. Open Excel and choose the ‘Information’ tab from the menu bar
2. Click on on the ‘Get Information’ choice and navigate to ‘From Textual content/CSV’
3. Find and choose your textual content file, then click on ‘Import’
4. Excel will preview your knowledge — select the suitable delimiter, file origin, and knowledge sort detection setting, then click on ‘Load‘
5. Get the textual content knowledge in an Excel window, prepared for additional evaluation and reporting

Nonetheless, Get Information might misread fields like string dates on account of inconsistent codecs, zeros, or regional settings, resulting in incorrect knowledge imports or conversion errors. So, the information might require some pre-processing earlier than conversion.

It is very important word that the ‘Get Information’ function is just out there in more moderen variations of Excel (2016 and later). For those who’re utilizing an older model, it’s possible you’ll have to improve or attempt a unique technique.

Greatest fitted to: Importing knowledge from gross sales experiences, transaction logs, financial institution statements or stock experiences, and log recordsdata from net servers or functions.

4. Convert Textual content to Excel with on-line convertors

These on-line converters can present output in numerous Excel-compatible codecs, equivalent to CSV, XLS, and XLSX, in a matter of clicks. No technical experience or software program set up is required.

A few of the in style on-line converters embody:

These instruments are easy to make use of. Usually, you want to:

1. Go to the converter’s web site
2. Add your textual content file
3. Choose the specified output format (e.g., CSV, XLS, or XLSX)
4. Click on ‘Convert’ or an identical command
5. Obtain the transformed file and open it in Excel for additional use

Whereas on-line converters are helpful, they will not be the only option for delicate or confidential knowledge. As these instruments require you to add and course of your recordsdata on third-party servers, there’s a danger that they could not adhere to knowledge privateness and safety requirements. Plus, some instruments might have constraints on file sizes and lack customization choices.

Greatest fitted to: Changing small to medium-sized textual content recordsdata (up to a couple thousand rows) with easy, constant constructions containing contact lists, product catalogs, or survey responses.

5. Batch processing a number of textual content recordsdata utilizing VBA

When you’ve got a number of textual content recordsdata that you want to convert to Excel format, manually opening and importing every file may be time-consuming. Fortuitously, Excel gives a solution to automate this course of utilizing VBA (Visible Fundamental for Functions) scripts.

By making a VBA macro, you’ll be able to loop by means of all of the textual content recordsdata in a specified folder and import the information from every file into a brand new worksheet inside your lively Excel workbook. This automation can considerably velocity up your workflow when coping with a number of textual content recordsdata.

To create a VBA macro for batch processing textual content recordsdata, you will have to:

1. Open the Visible Fundamental Editor in Excel (press Alt+F11)
2. Create a brand new module and write a VBA script that does the next:

• Specifies the folder path the place your textual content recordsdata are situated
• Loops by means of every textual content file within the folder
• Creates a brand new worksheet for every file and units the worksheet identify based mostly on the file identify
• Imports the information from every textual content file into the corresponding worksheet

3. Run the macro (Press Alt + F8) to import all of the textual content recordsdata into your Excel workbook mechanically

Sub ImportTextFileToExcel()
    Dim FilePath As String
    Dim FileNum As Integer
    Dim FileContent As String
    Dim LineItems() As String
    Dim RowNumber As Lengthy
    Dim ColNumber As Integer
    Dim Delimiter As String
    
    ' Set the file path
    FilePath = "C:pathtoyourfile.txt"  ' Replace this to the trail of your textual content file

    ' Set the delimiter (e.g., "," for CSV, "|" for pipe-separated, vbTab for tab-separated)
    Delimiter = "|"
    
    ' Open the file
    FileNum = FreeFile
    Open FilePath For Enter As FileNum
    
    ' Begin studying the file line by line
    RowNumber = 1
    Do Whereas Not EOF(FileNum)
        Line Enter #FileNum, FileContent  ' Learn a line from the file
        LineItems = Break up(FileContent, Delimiter)  ' Break up the road into gadgets based mostly on the delimiter
        
        ' Write the gadgets to the worksheet
        For ColNumber = LBound(LineItems) To UBound(LineItems)
            Cells(RowNumber, ColNumber + 1).Worth = Trim(LineItems(ColNumber))
        Subsequent ColNumber
        
        ' Transfer to the subsequent row within the worksheet
        RowNumber = RowNumber + 1
    Loop
    
    ' Shut the file
    Shut FileNum
    
    ' Notify the consumer
    MsgBox "Textual content file has been efficiently imported to Excel!", vbInformation
Finish Sub

VBA helps you automate the conversion course of and lets you tailor the import course of to particular wants, equivalent to defining how knowledge is parsed and formatted. Nonetheless, it has a steep studying curve for these unfamiliar with programming or its particular syntax, making it tough for novice customers to create and preserve macros. Chances are you’ll not need to spend effort and time debugging and troubleshooting advanced macros, particularly with their restricted error dealing with and reporting capabilities.

Greatest fitted to: Automating repetitive imports of a lot of textual content recordsdata, equivalent to day by day gross sales experiences, stock updates, or log recordsdata generated by inner programs.

6. Convert textual content to Excel utilizing Python libraries

For those who’re comfy with coding and like a extra programmatic method to changing textual content recordsdata to Excel, Python gives a number of highly effective libraries that may enable you to automate the method. One of the vital in style and versatile libraries for this activity is pandas.

Utilizing pandas, you’ll be able to simply learn textual content recordsdata right into a DataFrame, a two-dimensional knowledge construction much like an Excel spreadsheet. The library helps numerous textual content file codecs, equivalent to CSV (comma-separated values), TSV (tab-separated values), and fixed-width recordsdata. As soon as your knowledge is in a DataFrame, you’ll be able to carry out a variety of information cleansing, manipulation, and evaluation duties utilizing pandas‘ built-in capabilities and strategies.

pip set up pandas openpyxl

To transform a textual content file to Excel utilizing pandas, you should first set up the library and its dependencies (openpyxl for Excel help). Then, you should use capabilities like read_csv() or read_fwf() to load your textual content file right into a DataFrame, specifying the suitable delimiter or column widths. If wanted, you’ll be able to clear and remodel your knowledge throughout the DataFrame, equivalent to renaming columns, filtering rows, or changing knowledge varieties.

Lastly, you’ll be able to export the DataFrame to an Excel file utilizing the to_excel() perform. You’ll be able to specify the output file identify, sheet identify, and different choices like writing to a number of sheets or utilizing an ExcelWriter for extra management over the output.

import pandas as pd

# Load the textual content file right into a DataFrame
df = pd.read_csv('yourfile.txt', delimiter="|")

# Clear and manipulate the information (non-compulsory)
df.columns = ['Product Name', 'Quantity', 'Price', 'Total']
df['Quantity'] = df['Quantity'].astype(int)
df['Price'] = df['Price'].astype(float)
df['Total'] = df['Total'].astype(float)

# Export the DataFrame to Excel
df.to_excel('output.xlsx', index=False)
print("Information efficiently transformed and saved to output.xlsx")

Python gives higher flexibility, customization, and automation than handbook strategies. Nonetheless, the higher computing necessities and steep studying curve of Python syntax and knowledge manipulation libraries can decelerate non-programmers. You might also should cope with compatibility points between totally different variations of Python or dependencies, which might result in script failures or surprising conduct.

Greatest fitted to: Dealing with giant, advanced, or unstructured textual content recordsdata, equivalent to net server logs, social media knowledge exports, or scientific knowledge with tens of millions of information.

To keep away from writing scripts to automate the extraction course of, you’ll be able to leverage the ability of Massive Language Fashions (LLMs) like ChatGPT and Claude to transform your textual content recordsdata to Excel format. LLMs can perceive and course of pure language, making them able to dealing with structured and unstructured knowledge.

For easy text-to-Excel conversions, you’ll be able to immediately use an LLM like ChatGPT.

Here is how:

1. Add the textual content file(s) to ChatGPT.
2. Present ChatGPT with clear directions on changing the textual content knowledge right into a structured format appropriate for Excel. For instance: “Please convert the next textual content knowledge right into a comma-separated format appropriate for Excel”.
3. The LLM will generate a structured output based mostly in your immediate. Evaluation the output and make any obligatory changes to make sure it aligns together with your desired Excel format.
4. You’ll be able to copy-paste the structured output into Excel and specify the delimiter or request ChatGPT to generate a downloadable Excel file.

Now in case you want to totally automate the workflow, you are able to do so by creating Zapier zaps that combine with ChatGPT and your most well-liked cloud storage service. Here is how:

1. Select a set off occasion in Zapier based mostly on the place your textual content recordsdata are saved (e.g., Google Drive, Dropbox, or e mail).
2. Use the ChatGPT motion in Zapier to ship the textual content file content material to the LLM for processing. Present a transparent immediate instructing ChatGPT to transform the information right into a structured format.
3. ChatGPT will generate a structured output based mostly in your immediate. Zapier will mechanically go this output to the subsequent motion in your workflow.
4. Use a Zapier motion to ship the structured knowledge to Excel. This may be finished by creating a brand new row in Google Sheets or saving the information as a CSV file in a cloud storage service like Dropbox.

Utilizing LLMs like ChatGPT or Claude can considerably cut back the effort and time required for text-to-Excel conversions. These AI fashions can perceive the context and construction of your knowledge, making the method extra environment friendly and correct in comparison with conventional strategies.

Nonetheless, these AI fashions might sometimes generate inaccurate or inconsistent output. Hallucination is a typical problem with generative fashions, the place the AI might confidently current false info as truth. Moreover, the price of utilizing LLMs can add up rapidly for bigger volumes of information.

Greatest fitted to: Extract particular knowledge factors from small to medium-sized unstructured or semi-structured textual content knowledge datasets, equivalent to buyer opinions or social media posts. They are perfect for exploratory evaluation, prototyping, or conditions the place non-technical customers have to carry out ad-hoc conversions.

Whereas LLMs and Zapier present a strong mixture for automating text-to-Excel conversion, typically you want extra superior capabilities to extract structured knowledge from advanced paperwork. As a result of LLMs haven’t got a built-in understanding of your particular knowledge extraction necessities, their accuracy is dependent upon the type of prompts you give.

This isn’t ideally suited when it’s a must to course of a big quantity of paperwork with various codecs and constructions. Crafting the right immediate for every doc sort may be difficult. That is the place specialised Clever Doc Processing platforms like Nanonets turn out to be useful.

These instruments use AI fashions which might be skilled to know the construction and structure of various kinds of paperwork, to allow them to precisely find and extract the information you want with out counting on advanced prompts. This protects you effort and time and ensures extra constant and dependable outcomes, even for difficult paperwork.

For the aim of this text, let’s take into account log recordsdata from a big e-commerce web site for example. These log recordsdata may be large, containing tens of millions of traces of textual content knowledge, with every line representing a consumer motion or system occasion.

Now think about you’ve gotten tens of millions of traces like this, and you want to extract particular knowledge factors (like User_ID, Motion, Product_ID, and Worth) and convert them right into a structured Excel format for additional evaluation.

Here is how you should use a software like Nanonets to effectively course of these giant, advanced log recordsdata:

1. Add your log recordsdata to Nanonets or join them to your cloud storage service the place the recordsdata are saved.
2. Practice the AI mannequin by annotating a number of pattern traces, highlighting the information factors you need to extract (User_ID, Motion, Product_ID, Worth).
3. Configure the workflow to mechanically course of incoming log recordsdata, specifying the file format, knowledge fields to extract, and any validation or transformation guidelines wanted.
4. Let Nanonets extract the desired knowledge fields out of your log recordsdata, changing the semi-structured textual content knowledge right into a structured format prepared for export.
5. Validate the extracted knowledge in opposition to predefined guidelines or ship it for human overview if wanted.
6. Export the extracted and validated knowledge to an Excel file, utilizing Nanonets’ numerous export choices and integrations.

This workflow ought to enable you to map fields from the log recordsdata to the suitable columns in your Excel sheet, making certain a clear and structured output. Additionally, you’d be capable to auto-populate the Excel sheet with new knowledge as extra log recordsdata are processed, retaining your evaluation up-to-date.

IDP instruments can deal with a variety of file codecs, together with textual content recordsdata, photographs, PDFs, and Excel sheets, and precisely extract structured knowledge from each structured and unstructured paperwork.

These options allow companies to automate doc processing with out worrying about readability of prompts or workflow errors. In addition they supply options like knowledge validation, error dealing with, and integration with different enterprise programs, making your entire course of extra sturdy and scalable.

Greatest fitted to: Extracting structured knowledge from giant volumes of advanced, unstructured paperwork like invoices, receipts, or log recordsdata. They guarantee excessive accuracy and consistency in knowledge extraction, making them ideally suited for automating crucial enterprise processes and gaining beneficial insights from textual content knowledge.

Last ideas

Keep in mind, getting your knowledge into Excel is simply step one. With instruments like Nanonets, you’ll be able to automate the subsequent steps in your knowledge processing workflow, saving time, bettering accuracy, and enhancing your total productiveness.

Whether or not you are an IT admin, a enterprise proprietor, or an information analyst, having the proper instruments and strategies at your disposal could make a major distinction. Greater than getting your palms on the information, the main target must be on managing, processing, and utilizing that knowledge to drive insights and choices. 

Scale your doc knowledge extraction now!

Learn how Nanonets may be custom-made to your particular doc varieties and knowledge necessities. Schedule a demo to see how one can prepare customized OCR fashions and arrange workflows that match your corporation completely.

📅 E-book a Demo