Text Data Cleansing Assistant

@tmoi06

Hello Sir, I specialize in web research, data mining, cleaning, and admin support. I am 100% confident I can execute the project well. ✅ Why Me: ✔ 500+ projects completed on Freelancer.com ✔ 5.0-star rating and repeat international clients ✔ Fast turnaround and responsive communication For better clarification, you can also look at the 500+ excellent 5-star reviews I have earned on the Freelancer site. Looking forward to working with you. Thanks Ayan

@ashiruddin

I can work with large and multiple Excel/CSV data sources and transform them into a clean, management-ready database

@pvsysgroupinc

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@waleedsheeraz06

Let’s get your text-based records cleaned, standardized, and ready for database import with a consistent, repeatable workflow. I’ve handled similar data-entry, transcription, document-cleanup, and spreadsheet projects where accuracy and consistency were more important than complex formulas. I’m comfortable reviewing records manually, identifying duplicate or inconsistent entries, standardizing spelling, punctuation, capitalization, spacing, and formatting, and applying a defined style guide consistently across large batches. For tools, I can work directly with Excel, Google Sheets, CSV files, Word documents, and text-processing tools depending on the source format. I’ll preserve the original meaning while correcting clear quality issues and flagging anything that requires your decision rather than making assumptions. You’ll receive the cleaned dataset in the agreed format along with a concise change log covering the rules applied, significant corrections, duplicates removed, and ambiguous records flagged for review. I’m happy to start with your sample batch so we can establish the exact cleansing rules before scaling up.

@linhitdcn

Hello, I can help clean and standardize your text-based records while preserving the original meaning and following your style guidelines consistently. I have experience working with data processing and cleanup using Python, Pandas, Regex, CSV/Excel, and structured validation workflows. My approach includes normalizing text and formatting, detecting duplicate records, applying consistent naming/style rules, and flagging ambiguous entries rather than making assumptions. For each batch, I can deliver: • A clean CSV or Google Sheet ready for database import • Consistently formatted text records • Duplicate and inconsistency checks • A concise change log of corrections and rules applied • A separate list of ambiguous items requiring review I’m comfortable starting with your sample dataset so we can agree on the exact cleaning rules and expected output before processing the full batch. I’m available to start immediately and can support ongoing batches if the initial sample meets your expectations.

@YordanZeng

Hello, I’d be happy to help with your text data cleansing and standardization project. I have experience working with large text-based datasets where the main tasks involve checking inconsistent entries, standardizing text formats, identifying duplicates, correcting errors, and preparing clean data for further use. For similar data-processing work, I use Excel for reviewing, filtering, duplicate detection, and consistency checks, and Python when larger batches require more efficient text cleaning or repetitive processing. I am also comfortable working with CSV files and structured spreadsheets. I can follow your style guidelines carefully and will keep a clear change log of the rules applied, corrections made, and any ambiguous entries that require your review rather than making assumptions. I’m also familiar with transcription-related workflows, so adapting to annotation or additional text-processing tasks should be straightforward. Please send me the sample dataset and your formatting guidelines. I can complete the sample first so you can evaluate the accuracy and approach before moving forward with the full batch. Thank you.

@CCdeChenzai

Hello, I am interested in assisting with your text data cleansing project. I have experience organizing and reviewing structured records, identifying inconsistencies, standardizing text formats, removing duplicate entries, and checking data against defined rules. I can work with CSV, Excel, and Google Sheets, and I am also able to use automated checking methods for larger datasets while manually reviewing ambiguous text to maintain accuracy. I will provide both the cleaned dataset and a concise change log documenting the rules applied, corrections made, and any uncertain items requiring your review. I am happy to complete a small sample first so you can evaluate my accuracy, approach, and turnaround time before proceeding with the full batch.

@Toshiyuki724

Hello, I can clean and standardize your text records with a careful, sample-first workflow. I will apply your formatting rules consistently, identify duplicates and inconsistencies, flag ambiguous entries instead of guessing, and provide a concise change log of the edits made. I can also run before/after checks for duplicates, blanks, and formatting consistency. I can start with the small sample and return it within 1 business day after receiving the sample and guidelines. My rate is ₹800 INR per hour. Best regards

@kec05

I can clean and standardize your text records in Excel or CSV, removing duplicates, correcting formatting, and flagging ambiguous entries for review. I will follow your style guide, provide a concise change log, and review a sample first to confirm the workflow and turnaround. My rate is INR 1,000 per hour.

@ericm612

I can take the first sample batch and clean it in a controlled way: standardize text formatting, remove or flag duplicates, apply your style rules, and return the cleaned CSV/Sheet plus a short change log with any ambiguous rows called out. For a low-risk first step I can do up to 2 hours at ₹750/hour within 1 day. My current proof is a synthetic Excel/data-cleaning demo on my profile, not a paid client case yet; I will keep the first pass small and reviewable.

@MorrisNorris

I would turn your style guide into explicit cleanup rules, preserve the source records, and return a cleaned CSV plus an edit log and a short list of ambiguous cases. Exact duplicates and similar-but-distinct text would be handled separately so meaningful entries are not lost. To answer your experience question honestly: I am new on Freelancer, and my portfolio currently shows a labeled demonstration rather than past client jobs. It demonstrates preserved originals, duplicate lineage, field-level changes and validation: https://www.freelancer.com/portfolio-items/11594162-excel-cleanup-with-change-log. My proposed tools are Python for repeatable rules and structured review for exceptions. I suggest a one-off paid pilot at INR 1,000/hour, capped at two actual hours (INR 2,000 maximum), with no ongoing commitment. After your anonymized sample and style guide, we can agree a realistic batch of up to 500 short English records and five fields. Target turnaround is two business days after agreement and payment arrangements. Only actual work time would be billed; any expansion needs agreement. I use AI-assisted coding and review, so we would agree permitted storage and processing before the full dataset. Which text rules are mandatory, and should duplicate matching be case-sensitive?

@KenTsaiTW

Your sample-first approach is a good fit for text cleansing: I would return a before/after sample with the applied rules and ambiguous items clearly separated before we expand the batch. I would use Python/pandas for repeatable whitespace, encoding and approved case-format rules, with Excel or CSV review for exceptions. Duplicate removal would follow your chosen key and keep-record rule; similar-looking names or phrases would be flagged, not silently merged. Each changed record would retain a source identifier, old/new values and a reason, alongside a short rule summary. I do not have a completed text-cleansing client case on this profile to cite. You can assess the actual sample output instead of an unsupported experience claim. My INR1,250/hour rate has an initial five-hour ceiling. Please share the sample, style guide, language, total row count and preferred output type; I will confirm a complete bounded batch and the expected hours before acceptance. Start date, turnaround and billing depend on sample review and confirmed Windows production and independent QA availability. Ongoing batches would need an agreed schedule rather than an assumed daily commitment.

@richap5

Hi, I can help clean and standardize your text-based datasets with strong attention to detail. I have experience working with Excel, CSV, data cleaning, formatting, and data-quality tasks through my Power BI/data analytics work. I can identify duplicates, formatting inconsistencies, spelling issues, and apply your style guidelines consistently. I’ll also provide a brief change log and flag any unclear entries instead of guessing. I’m happy to start with your sample file and follow your preferred workflow. Thanks, Richa.

@sahil41623

Hi, I can review, standardize, and clean your text-based records so they are ready for your main database. My approach focuses on careful language and detail work: spotting inconsistencies, correcting formatting, removing duplicates, and applying your style guidelines consistently across entries. I work comfortably in Excel, Google Sheets, and CSV. For similar cleanup work I have prepared Excel/data-quality samples with before/after cleaning and a documented change log so edits stay transparent. Deliverables for each batch: • Cleaned, well-formatted dataset (CSV or Google Sheet as agreed) • Brief change log of edits, rules applied, and ambiguous items flagged for your review (I will not guess on unclear cases) I am happy to start with your small sample so we can confirm approach and turnaround before expanding. Familiarity with transcription and careful text review will also help if the project later includes annotation-style tasks. Rate: ₹750/hour. I can return the sample within 1 day after receiving the file and style guidelines. Best regards, Sahil

@ProcureTraceEU

I can handle this text-data cleansing work with a repeatable and careful workflow focused on consistency, traceability, and accuracy. My approach would be: - review the sample and your style guidelines first, - standardize formatting, spacing, capitalization, and approved text conventions, - identify and remove exact duplicates while flagging ambiguous near-duplicates for review, - preserve the original meaning and avoid guessing, - return the cleaned CSV or Google Sheet, - provide a concise change log describing the rules applied and any items that need your decision. For larger batches, I can use Python-assisted checks for repeatable rules and duplicate detection, while manually reviewing exceptions. I am comfortable starting with your sample batch so we can confirm the exact cleanup rules and turnaround before scaling.