Excel Files Merge & Dedup

@asifdwan

I’ll consolidate your Excel files into a clean master dataset using Python (pandas) or Power Query—whichever you prefer. I recommend preserving all columns (union schema), aligning shared fields, and flagging gaps for clarity. I’ll remove duplicates (incl. “Do Not Contact”), append seed records, and deliver a spotless file plus a clear process log and reusable script. Ready to start as soon as I receive the files.

@vano101

Hello I have several years of experience with automated processing Excel spreadsheets I work with Python (pandas/openpyxl), and I am able to use it for your project. Could you share files to process, I would like to review in order to get what is best approach to treat those extra or missing fields

@Tanmoy236

Warm greetings! I specialize in Excel data consolidation and deduplication, delivering clean, structured master files with full transparency. With 9+ years of experience in Power Query, VBA, and Python (pandas), I’ll merge your datasets accurately and make the process repeatable. Here's how I can help: * Merge all workbooks into one structured master file * Remove duplicates (incl. “Do Not Contact” exclusions) * Align mismatched columns with a clear, scalable approach * Add “Seed” records correctly into the dataset * Provide log + reusable script/steps (Power Query/VBA/Python) I recommend a unified schema preserving all fields Can you confirm the unique identifier for deduplication (email, name, or both)?

@usmanbashir12100

Hi, I can consolidate your Excel workbooks into one clean, deduplicated master file with full accuracy. I’ll: Merge the 5,542-record main file Remove matches from the 306-record “Do Not Contact” file Add the 7 records from the seed file Handle mismatched columns using the most practical structure and provide recommendations Deliver a clean master Excel file plus a process log/instructions I’m experienced with Microsoft Excel, Power Query, VBA, and Python (pandas/openpyxl) for accurate data cleanup. Once you send the files, I can confirm completion timeline immediately.

@ayazakhtar75

Hello, I can consolidate your Excel workbooks into one clean master file with full deduplication and clear documentation. I’ll merge the main file (5,542 records), remove the “Do Not Contact” entries (306 records), and add the 7 records from the seed file while ensuring the final workbook contains only valid, unique entries. For files with different column structures, I’ll recommend the best approach—usually a clean master schema while preserving important extra fields where needed. Using Power Query or Python (based on your preference), I’ll ensure the process is accurate, repeatable, and easy to understand. You’ll receive: • One fully cleaned and deduplicated master Excel file • Removed restricted contacts + added seed records • Clear notes explaining duplicate handling and column mapping • Reusable process (Power Query/Python steps if needed) Quick question: which field should define duplicates—email, full name, or a combination? Best Regards, Ayaz Akhtar

@HiraMahmood4072

Hello, With over 7 years of experience in Data Processing, Excel, Excel Macros, and Data Entry, I have carefully reviewed your project requirements. To accomplish this task, I will first consolidate all the Excel workbooks into a single master file while removing any duplicate records to ensure the final spreadsheet contains only unique entries. For spreadsheets with varying column structures, I will provide recommendations on the best approach, whether to preserve all columns, align common fields, or suggest another method for optimal results. The deliverables will include a fully deduplicated master Excel file, a detailed note on how column differences and duplicates were handled, and any necessary scripts, macros, or instructions for future reference. I prioritize accuracy and transparency in my work, utilizing tools such as Power Query, VBA, Python (pandas/openpyxl), to ensure a clean and easily understandable output. I invite you to connect in chat for further discussion on the project details. You can visit my profile at https://www.freelancer.com/u/HiraMahmood4072 Thank you.

@AmazingEngr76386

Hi, happy to consolidate your workbooks into a single clean master file with full deduplication. For the column mismatch question, my recommendation is to preserve every column using a union approach (Power Query handles this cleanly): records keep their original fields, missing columns show blank for files that didn't have them, and you don't lose any data. If later you want a tighter view, we can hide or drop the rarely-used columns, but you'll always have the full record. Trimming columns up front is hard to undo. My plan once I have the files: 1. Load main file (5,542 records), do-not-contact file (306), and seed file (7) in Power Query. 2. Apply your business rules: remove the 306 do-not-contact names from the main file, append the 7 seed records, then deduplicate. 3. Run dedup against the key field (email or name + another identifier, your call) so we don't accidentally drop legitimate near-duplicates. 4. Deliver the master Excel file plus a short log explaining column handling, the dedup key used, and counts at every stage (in: X, removed: Y, added: Z, final: N). 5. Include the Power Query M code or a step-by-step doc so you can rerun the whole thing yourself when new files come in. I work with Power Query, VBA, and Python (pandas) regularly, recently merged and reconciled a 3,500+ row pharmaceutical pricing dataset and built repeatable consolidation flows for client lists. Thanks, Adnan

@belarjsoufiane20

Hello, I can merge your Excel files into a single clean master dataset using Python (pandas), handling different column structures, standardizing fields, and removing duplicates to ensure only unique records remain. You will receive a final cleaned Excel file, a brief explanation of the logic used for merging and deduplication, and a reusable Python script so the process can be repeated anytime. Once you share the files, I can start immediately.

@suganyav12

Hi there, Myself suganya hope you are doing good. I am clear with the instructions and ready to work on this straightforward project. Good in excel data cleansing smd merging I cam easily navigate any type of source quickly And also i will remove 306 names and add 7 names. Waiting for your message. Thanks

@quan9824

Hi, I can consolidate your Excel workbooks into one clean master file and ensure the final output is fully deduplicated. My recommended approach is to preserve all useful columns, align matching fields by header, and clearly flag any source-specific columns rather than dropping data too early. I’ll also remove the approx. 306 “Do Not Contact” records from the main file and add the 7 seed records, then deduplicate the final dataset. I typically use Python with pandas/openpyxl or Power Query, depending on the file structure. This allows the process to be accurate, repeatable, and easy to audit. Deliverables: • Final master Excel file • Duplicate-free cleaned records • Do-not-contact names removed • Seed records added • Short processing log explaining column handling and deduplication rules • Script or repeatable steps for future merges Once I receive the files, I can review the structure and confirm the exact completion time. For the record volume you mentioned, this should be straightforward and can usually be completed quickly.

@muneeb6767

I’ll merge your Excel files into a clean master dataset, remove duplicates, and smartly align columns (keeping all fields with proper mapping) using Power Query or Python—fully documented and reusable. Ready to start once files are shared.

@SamirBanna

Hello, I’m a Senior Software Engineer with extensive experience in Python automation and web scraping & C# WindowFormApp and WFP. I’ve carefully reviewed your requirements and I can deliver a reliable, production-ready solution — not a quick workaround. ✅ Clean and maintainable code ✅ Clear communication ✅ On-time delivery I’d be happy to discuss your project details and propose the best technical approach. Best regards, Samir

@rosscarter1011

Merging multiple Excel files with mismatched columns — while ensuring zero duplicate leakage — requires a structured, auditable process, not just copy‑paste consolidation. You need one clean master file (5,542+ records plus 7 seed entries), with 306 “Do Not Contact” names fully excluded, and a transparent method you can rerun later. Since column structures differ, the key decision is whether to normalize into a unified schema or preserve all fields without losing data integrity. With strong technical experience and backend data handling through Django-based workflows, I regularly structure, clean, and validate datasets using Python (pandas) and Excel tools to ensure repeatable, error‑free outputs. Before starting, I’d like to confirm: • Is there a reliable unique identifier (email, phone, ID), or should we define duplicate logic across multiple fields? • Should the “Do Not Contact” list override both the main and seed files automatically? Once you share the files, I can review the structures and confirm completion time the same day.

@SmartCodeDev

Hey, I can do this. I’ll merge all your Excel files into one clean master sheet, deduplicate using a proper matching rule (not just basic row drop), and keep column mismatches handled safely by aligning shared fields while preserving extra data. I’ll use a Python/pandas workflow so it’s fully repeatable, and you’ll also get the script + a short log explaining how duplicates and column differences were handled. Final output: one spotless master Excel file with all updates applied (including removals + new entries). Send the files and I can start right away

@moustafa1

Hello, I understand your need to consolidate multiple Excel workbooks into one clean master file while removing duplicates and handling column differences with clarity. I can merge all records accurately, ensure only unique entries remain, and provide a transparent log of how column variations and duplicates were managed. With my experience using tools like Power Query, Formulas, I will deliver a spotless, well-structured file along with clear instructions for repeatability. Please send me a message through chat to discuss this task so we can get started. Best Regards, Moustafa

@besho87

Hello, I’d be happy to help consolidate and clean your Excel files. I have strong experience with Excel data merging, deduplication, Power Query, VBA, Python/pandas, and openpyxl, and I can deliver a clean master file with a clear process log. What I will do: • Merge the main file with 5,542 records • Remove names from the Do Not Contact file (~306 records) • Add the seed file records (7 names) • Remove duplicates and keep only valid unique entries • Review column differences and recommend the cleanest structure before finalizing Deliverables: • Final master Excel file • Short log explaining: – how duplicates were handled – how column differences were treated – what records were removed/added • Script or repeatable steps if needed My recommendation is usually to preserve all useful columns, align common fields, and clearly mark any unmatched/extra fields so no data is lost. Once I receive the files, I can confirm the exact turnaround and complete the project accurately. Best regards.

@SAHINUR2

Consolidating messy Excel files without losing a single record is exactly the kind of work I do every day — and your setup is straightforward enough that I can turn this around cleanly and quickly. Here is my read on the column mismatch question before you even send the files: the safest and most transparent approach is a full outer merge — every column from every workbook is preserved in the master file, with blank cells where a source file had no matching field. This keeps the data lossless and gives you a complete audit trail. If some columns turn out to be redundant or trivially named differently, I will flag them in the log and suggest whether to consolidate or drop them. You make the final call, but you will have all the information in front of you. For the actual work: I will use Python with pandas to merge all source workbooks, remove duplicates based on the key identifier fields, subtract the 306 Do Not Contact records from the master, and append the 7 seed records. The output will be one clean Excel file with roughly 5,249 unique, verified records. You will also receive a plain-English process log and the annotated script so you can rerun the entire merge yourself if the source files ever change. I work precisely and document everything. Send the files when you are ready and I will confirm a completion timeline the same day I receive them.

@zhens2

As a seasoned Full-Stack Developer with over 8 years of experience and specialized skills in Python and Visual Basic, I guarantee you a seamless and efficient solution for your Excel files merging and deduplication project. My extensive experience in handling large datasets with meticulous attention to detail will come in handy to ensure maximum accuracy in merging your workbooks and eliminating any duplicate records. My familiarity and expertise with powerful data manipulation libraries such as pandas in Python, make me well-equipped for complex data challenges like aligning non-identical column structures. I can provide you with clear options on how to handle these differences and the necessary scripts or macros to replicate the process later if needed. Given that you value precision over velocity, I assure you a result-oriented approach with zero compromise on quality. Responsiveness throughout collaboration is essential for me, so I'll ensure constant communication regarding the progress of the project. Rest assured, by hiring me, you're investing in an experienced professional dedicated to delivering a flawless final product that perfectly caters to your needs.

@seandinwiddie

✨✨✨ ✨✨✨ ✨✨✨ ✨✨✨✨✨✨ ✨✨✨ ✨✨✨ ✨✨✨✨✨ Hi, Dear. Portfolio : https://www.freelancer.com/u/seandinwiddie I can consolidate your Excel files into a clean, fully deduplicated master dataset with a transparent, repeatable process. I’ve handled similar data merges using Power Query and Python (pandas) for accuracy and clarity. I will start by analyzing all files and proposing a column strategy (recommended: unified schema with all columns preserved + standardized naming, while aligning core fields for deduplication). Next, I will merge the datasets, remove duplicates based on agreed keys (e.g., name/email), exclude the “Do Not Contact” list, and include the seed records. Finally, I will deliver a clean master Excel file plus a clear log and either a Power Query workflow or Python script so you can rerun the process anytime. The result will be accurate, structured, and easy to maintain going forward. Best Regards. Sean D.