Data Review¶
The Data Review tab provides visual comparison between your fetched/entered data and the existing database, helping you identify what's new and what already exists.
Purpose¶
- Visual Comparison: See database vs. new data overlaid on the same chart
- Duplicate Identification: Quickly spot records that already exist
- Quality Check: Verify new data aligns with historical trends
- Regional Analysis: Compare national and subnational data
How to Use¶
Step 1: Load the Database¶
Click "Load Database from GitHub" to fetch the current database for comparison.
Note
The database is filtered to only include countries present in your cleaned data.
Step 2: Select Filters¶
- Country: Choose the country to review
- Regions: Select specific regions or check "Include NATIONAL" for country-level data
- Indicator: Select the indicator to visualize
Step 3: Generate Plot¶
Click "Generate Plot" to create the comparison chart.
Reading the Chart¶
Database Data (Existing)¶
| Level | Line Style | Marker |
|---|---|---|
| National | Solid line (thick) | Circle |
| Subnational | Dotted line (thin) | Triangle |
Colors indicate source: - DHS: Teal (#0f706d) - MICS: Blue (#3498db) - WUENIC: Purple (#9b59b6) - UNWPP: Orange (#f39c12) - WHO: Green (#1abc9c)
New/Fetched Data¶
| Level | Line Style | Marker | Color |
|---|---|---|---|
| National | Dashed | Diamond | Red |
| Subnational | Dash-dot | Square | Orange |
Duplicate Summary¶
Below the filters, a summary shows:
- X already in database: Records that match existing entries
- Y are new: Records not found in database
This helps you understand how much of your fetched data is new vs. duplicate.
Summary Tables¶
Two tables show the breakdown:
Database Records Table¶
Shows existing records for your selection, including: - Region, Year, Value, Source
New Data Table¶
Shows your fetched/entered data for comparison
Workflow Integration¶
The Data Review tab fits into the workflow between cleaning and database integration:
Fetch/Enter → Clean → **Review** → Validate → Deduplicate → Push
Use this step to:
- Verify data quality before integration
- Identify gaps in existing coverage
- Spot anomalies in new data
- Plan updates - decide which records to replace
Tips¶
- Review data before running duplicate check
- Use to verify manual entries match expected patterns
- Compare multiple regions to spot inconsistencies
- National data (solid lines) should generally be visible above subnational (dotted lines)