A clean order CSV with a reconciled exclusion count
Excel Data Cleanup
Clean and reshape messy sales data for a reliable handoff.
beginner · About 95 minutes · 4 lessons · 8 exercises + 1 project
Your finished work
A clean order CSV with a reconciled exclusion count
Completion requires every output check to pass. Exact columns, types, values, missing values and duplicate counts all matter. A diagnostic score helps you revise your work.
All examples use original, fictional business data. Your final project starts with 68 source records.
Try data preparation before choosing a course
Work through four original lessons, check your own output, then hand off a clean order file.
Selected public objectives from DataCamp: Data Preparation in Excel: selected skill trial. This independent trial uses original lessons and fictional practice data.
Read a small table and edit a cell. No Excel installation is needed for this CSV trial.
4 lessons · Eight exercises · One final project · About 95 minutes
What this trial covers
- Import and inspect tabular data: Quoted CSV, stable headers and empty records; no Excel import dialogs.
- Prepare missing data: Explicit defaults and preservation of zero; no Flash Fill or inferred values.
- Remove duplicates: Declared business keys and a keep-first policy.
- Prepare text and dates: Whitespace and declared date formats; no full Excel text/date function library.
Where native Excel practice continues
- Native Excel import dialogs, Flash Fill and workbook protection
- Nested logical formulas and the full Excel text/date function library
- VLOOKUP, HLOOKUP and PivotTable creation
- The complete provider course, its exercises, instructor support and credentials
This browser trial checks CSV preparation and a limited set of formulas. Use Microsoft Excel to practice its import tools, workbook features and full function library.
Your final handoff
A checked order CSV with 59 output records, declared date formats, unique business keys and explicit rules for missing values. Work from 68 source records. Download your output and the report of its checks.
Final project checklist
- Return order_id, date, region, name, amount in that order, sorted by numeric order_id. Amounts are integer whole dollars.
- For each order_id, collapse byte-for-byte identical records to one. If any source field disagrees within an ID, exclude every record for that ID; never choose a maximum amount.
- Accept only real calendar dates written YYYY/MM/DD. Exclude ambiguous or impossible dates. Convert accepted dates to YYYY-MM-DD.
- An empty region becomes Unknown. Trim outer spaces and collapse repeated spaces in names. Preserve numeric zero amounts.
Completion requires every output check to pass: columns, row count, types, missing values and duplicate counts.
The course
- Start lesson →
1. Import without losing data
Keep quoted text and stable headers when importing CSV.
- Start lesson →
2. Handle missing values
Fill only fields with an explicit business default.
- Start lesson →
3. Deduplicate by a business key
Keep the first record for each order ID.
- Start lesson →
4. Standardize dates and whitespace
Normalize declared date formats without guessing.
Put it together
Handoff a clean order file
68 source records. Apply the business rules, check your output and download a handoff report with your source, answer and results.
Preview your first input
order_id,customer,note 1,Avery,"Desk, blue" ,, 2,Morgan,"He said ""ship"""