WHO Malawi AIR_16
Annual WHO Global Health Observatory time series for Malawi covering 'AIR_16' (AIR_16).
Filename
who_malawi_air_16_AIR_16.csv
Preview
Schema
Coverage
Source Linked
1
Downloads
0
Views
3
Rows Parsed
386.0 B
File Size
09 May 2026
Updated
WHO Malawi AIR_16 is a CSV dataset from World Health Organization, ingested into the Kafukufuku Data Hub with 3 parsed rows.
Annual WHO Global Health Observatory time series for Malawi covering 'AIR_16' (AIR_16). The source is catalogued as who gho indicator timeseries. Spatial granularity is national. It belongs to the who malawi health indicators collection. Geographic scope is MWI.
| Source | World Health Organization |
| Format | CSV |
| Rows Parsed | 3 |
| Country | MWI |
| Spatial Granularity | National |
| Dataset Type | Who Gho Indicator Timeseries |
Filename
who_malawi_air_16_AIR_16.csv
| Source | World Health Organization |
| Format | CSV |
| Filename |
who_malawi_air_16_AIR_16.csv
|
| Rows Parsed | 3 |
| Dataset Type | Who Gho Indicator Timeseries |
| Indicators | 0 |
| File Size | 386.0 B |
| Status | completed |
| Spatial Granularity | National |
| Hosted by Kafukufuku | Yes |
| Checksum MD5 |
abfcf635dda37343a4756e23c840d6f8
|
| Last Updated | 09 May 2026 |
Coverage Summary
| Country | MWI |
| Spatial Granularity | National |
| Years Covered | Not identified |
| Distinct Years | 1 |
| Districts Identified | 0 |
| Regions Identified | 0 |
No district or region labels were identified from the parsed rows.
Pipeline Lineage
Raw file
Completed
CSV · who_malawi_air_16_AIR_16.csv
Parse
Not run
No parse job recorded
Bronze
Created
3 bronze record(s)
Silver
Reviewed
3 silver record(s)
Published
Published
885 datamart record(s)
| Latest Parse Job | Not recorded |
| Latest Crawler Job | Not linked |
| Bronze Records | 3 |
| Silver Records | 3 |
| Published Records | 885 |
| Validation Issues | 0 errors, 3 warnings, 0 info |
Published Domains
Health · 885
Terms & Citation
| Access Level | Unspecified |
| License | License not specified |
| Source URL | https://ghoapi.azureedge.net/api/AIR_16 |
Suggested Citation
World Health Organization. WHO Malawi AIR_16. Kafukufuku Data Hub, coverage n.d.. Source: https://ghoapi.azureedge.net/api/AIR_16.
No explicit license was captured during ingestion. Reuse should be checked against the original publisher terms.
The canonical source URL points to the upstream publisher or download location.
Schema
| Field | Type | Profile | Coverage | Missing | Distinct | Examples | Notes |
|---|---|---|---|---|---|---|---|
_domain |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
health
|
Two-level field best treated as a yes/no or flag variable. |
_domain_confidence |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
1.0
|
Two-level field best treated as a yes/no or flag variable. |
country |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
MWI
|
Two-level field best treated as a yes/no or flag variable. |
country_code |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
MWI
|
Two-level field best treated as a yes/no or flag variable. |
dataset_name |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
WHO GHO Malawi AIR_16
|
Two-level field best treated as a yes/no or flag variable. |
high |
Text | Categorical | 100.0% present | 0.0% | 3 |
80752.08594
58269.17578
139021.2656
|
Field is best read as a label/category rather than a numeric measure. |
indicator_code |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
AIR_16
|
Two-level field best treated as a yes/no or flag variable. |
indicator_name |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
AIR_16
|
Two-level field best treated as a yes/no or flag variable. |
low |
Text | Categorical | 100.0% present | 0.0% | 3 |
55972.87109
40388.96094
96361.83594
|
Field is best read as a label/category rather than a numeric measure. |
value |
Text | Categorical | 100.0% present | 0.0% | 3 |
70202.94531
50657.11719
120860.0625
|
Field is best read as a label/category rather than a numeric measure. |
year |
Year | Temporal | 100.0% present | 0.0% | 1 |
2019
|
Interpreted as a reporting period rather than a measure. |
Sample Rows (3)
| Low | High | Year | Value | Country | Comments | Datasource | Country_Code | Dataset_Name | Display_Value | Indicator_Code | Indicator_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 55972.87109 | 80752.08594 | 2019 | 70202.94531 | MWI | - | - | MWI | WHO GHO Malawi AIR_16 | - | AIR_16 | AIR_16 |
| 40388.96094 | 58269.17578 | 2019 | 50657.11719 | MWI | - | - | MWI | WHO GHO Malawi AIR_16 | - | AIR_16 | AIR_16 |
| 96361.83594 | 139021.2656 | 2019 | 120860.0625 | MWI | - | - | MWI | WHO GHO Malawi AIR_16 | - | AIR_16 | AIR_16 |
Data Quality Summary
| Rows Analysed | 3 |
| Columns With Data | 11 |
| Cell Completeness | 78.6% |
| Continuous Columns | 0 |
| Categorical Columns | 11 |
| Identifier-Like Columns | 3 |
| Temporal Columns | 1 |
| District Recognition | 0.0% recognised · 3 unresolved rows |
| Domain Recognition | 100.0% classified · 0 unresolved rows |
| Duplicate Rows | 0 |
| Mixed-Type Columns | 0 |
| Empty Columns | 3 · comments, datasource, display_value |
These checks summarize coverage, consistency, and variable structure from parsed rows. Identifier-like columns and year/code fields are treated as categorical so averages are not shown where they would be misleading. Malawi-specific district/domain recognition rates are included to show how much of the file the pipeline can place and classify reliably.
Categorical Variables
| Column | Profile | Coverage | Distinct | Most Common Share | Top Values | Interpretation |
|---|---|---|---|---|---|---|
_domain |
Binary | 100.0% present | 1 | 100.0% |
health - 3 (100.0%)
|
Two-level field; best read as a flag or yes/no split. |
country |
Binary | 100.0% present | 1 | 100.0% |
MWI - 3 (100.0%)
|
Two-level field; best read as a flag or yes/no split. |
dataset_name |
Binary | 100.0% present | 1 | 100.0% |
WHO GHO Malawi AIR_16 - 3 (100.0%)
|
Two-level field; best read as a flag or yes/no split. |
indicator_name |
Binary | 100.0% present | 1 | 100.0% |
AIR_16 - 3 (100.0%)
|
Two-level field; best read as a flag or yes/no split. |
high |
Categorical | 100.0% present | 3 | 33.3% |
139021.2656 - 1 (33.3%)
58269.17578 - 1 (33.3%)
80752.08594 - 1 (33.3%)
|
Nominal field summarised by the most frequent values. |
low |
Categorical | 100.0% present | 3 | 33.3% |
40388.96094 - 1 (33.3%)
55972.87109 - 1 (33.3%)
96361.83594 - 1 (33.3%)
|
Nominal field summarised by the most frequent values. |
value |
Categorical | 100.0% present | 3 | 33.3% |
120860.0625 - 1 (33.3%)
50657.11719 - 1 (33.3%)
70202.94531 - 1 (33.3%)
|
Nominal field summarised by the most frequent values. |
_domain_confidence |
Identifier | 100.0% present | 1 | 100.0% |
1.0 - 3 (100.0%)
|
High-cardinality identifier-like field; category frequencies are less informative. |
country_code |
Identifier | 100.0% present | 1 | 100.0% |
MWI - 3 (100.0%)
|
High-cardinality identifier-like field; category frequencies are less informative. |
indicator_code |
Identifier | 100.0% present | 1 | 100.0% |
AIR_16 - 3 (100.0%)
|
High-cardinality identifier-like field; category frequencies are less informative. |
year |
Temporal | 100.0% present | 1 | 100.0% |
2019 - 3 (100.0%)
|
Time-like field; values are better read as reporting periods than categories. |