WHO Malawi NUT_CF_ISSSF
Annual WHO Global Health Observatory time series for Malawi covering 'NUT_CF_ISSSF' (NUT_CF_ISSSF).
Preview
Schema
Coverage
Source Linked
28
Downloads
2
Views
175
Rows Parsed
36.4 KB
File Size
09 May 2026
Updated
WHO Malawi NUT_CF_ISSSF is a CSV dataset from World Health Organization, ingested into the Kafukufuku Data Hub with 175 parsed rows.
Annual WHO Global Health Observatory time series for Malawi covering 'NUT_CF_ISSSF' (NUT_CF_ISSSF). 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 | 175 |
| Country | MWI |
| Spatial Granularity | National |
| Dataset Type | Who Gho Indicator Timeseries |
Filename
who_malawi_nut_cf_isssf_NUT_CF_ISSSF.csv
| Source | World Health Organization |
| Format | CSV |
| Filename |
who_malawi_nut_cf_isssf_NUT_CF_ISSSF.csv
|
| Rows Parsed | 175 |
| Dataset Type | Who Gho Indicator Timeseries |
| Indicators | 0 |
| File Size | 36.4 KB |
| Status | completed |
| Spatial Granularity | National |
| Hosted by Kafukufuku | Yes |
| Checksum MD5 |
025ae21b6943989f8571c8cd6dc206e1
|
| Last Updated | 09 May 2026 |
Coverage Summary
| Country | MWI |
| Spatial Granularity | National |
| Years Covered | Not identified |
| Distinct Years | 7 |
| Districts Identified | 2 |
| Regions Identified | 2 |
District Coverage
lilongwe
zomba
Region Coverage
central
southern
2 districts were identified during normalization.
Pipeline Lineage
Raw file
Completed
CSV · who_malawi_nut_cf_isssf_NUT_CF_ISSSF.csv
Parse
Completed
175 rows parsed
Bronze
Created
175 bronze record(s)
Silver
Reviewed
175 silver record(s)
Published
Published
1,750 datamart record(s)
| Latest Parse Job | Completed · csv · 175 rows |
| Latest Crawler Job | Not linked |
| Bronze Records | 175 |
| Silver Records | 175 |
| Published Records | 1,750 |
| Validation Issues | 0 errors, 25 warnings, 0 info |
Published Domains
Health · 1,750
Recent Parse Jobs
| Started | Parser | Status | Rows |
|---|---|---|---|
| 09 May 2026 10:29 | csv | Completed | 175 |
Terms & Citation
| Access Level | Unspecified |
| License | License not specified |
| Source URL | https://ghoapi.azureedge.net/api/NUT_CF_ISSSF |
Suggested Citation
World Health Organization. WHO Malawi NUT_CF_ISSSF. Kafukufuku Data Hub, coverage n.d.. Source: https://ghoapi.azureedge.net/api/NUT_CF_ISSSF.
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 |
Text / Code | Identifier | 100.0% present | 0.0% | 4 |
0.5
0.6666666666666666
1.0
|
High-cardinality field that looks like an ID or code. |
comments |
Text | Categorical | 100.0% present | 0.0% | 8 |
Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office
Malawi Demographic and Health Survey 2015-16. Zomba, Malawi, and Rockville, Maryland, USA. NSO and ICF.
Malawi MDG endline survey 2014. Final Report. Zomba, Malawi: National Statistical Office, 2014.
|
Field is best read as a label/category rather than a numeric measure. |
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 NUT_CF_ISSSF
|
Two-level field best treated as a yes/no or flag variable. |
high |
Decimal | Measure | 100.0% present | 0.0% | 96 |
91.9
92.2
94.6
|
Mostly numeric with enough variation to summarize as a measure. |
indicator_code |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
NUT_CF_ISSSF
|
Two-level field best treated as a yes/no or flag variable. |
indicator_name |
Boolean / Flag | Binary | 100.0% present | 0.0% | 1 |
NUT_CF_ISSSF
|
Two-level field best treated as a yes/no or flag variable. |
low |
Decimal | Measure | 100.0% present | 0.0% | 98 |
83.5
55.6
83.8
|
Mostly numeric with enough variation to summarize as a measure. |
value |
Decimal | Measure | 100.0% present | 0.0% | 99 |
88.3
79.4
90.5
|
Mostly numeric with enough variation to summarize as a measure. |
year |
Year | Temporal | 100.0% present | 0.0% | 7 |
2020
2015
2014
|
Interpreted as a reporting period rather than a measure. |
Sample Rows (8)
| Low | High | Year | Value | Country | Comments | Datasource | Country_Code | Dataset_Name | Display_Value | Indicator_Code | Indicator_Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 83.5 | 91.9 | 2020 | 88.3 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
| 55.6 | 92.2 | 2020 | 79.4 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
| 83.8 | 94.6 | 2020 | 90.5 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
| 84.0 | 91.1 | 2020 | 88.0 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
| 81.1 | 90.7 | 2020 | 86.6 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
| 83.3 | 92.2 | 2020 | 88.4 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
| 82.3 | 93.7 | 2020 | 89.2 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
| 85.4 | 93.6 | 2020 | 90.3 | MWI | Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office | - | MWI | WHO GHO Malawi NUT_CF_ISSSF | - | NUT_CF_ISSSF | NUT_CF_ISSSF |
Data Quality Summary
| Rows Analysed | 175 |
| Columns With Data | 12 |
| Cell Completeness | 85.7% |
| Continuous Columns | 3 |
| Categorical Columns | 9 |
| Identifier-Like Columns | 3 |
| Temporal Columns | 1 |
| District Recognition | 85.7% recognised · 25 unresolved rows |
| Domain Recognition | 100.0% classified · 0 unresolved rows |
| Duplicate Rows | 31 |
| Mixed-Type Columns | 0 |
| Empty Columns | 2 · 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.
Continuous Variables
| Column | Coverage | Distinct | Mean | Median | Range | Middle 50% | Std Dev | Shape |
|---|---|---|---|---|---|---|---|---|
high |
100.0% present | 96 | 90.77 | 91.10 | 79.10 to 99.90 | 88.75 to 94.35 | 4.76 | Left-skewed |
low |
100.0% present | 98 | 81.35 | 83.20 | 55.60 to 96.60 | 79.25 to 85.50 | 7.11 | Left-skewed |
value |
100.0% present | 99 | 86.90 | 88 | 71.50 to 99.50 | 84.90 to 90.35 | 5.68 | Left-skewed |
Categorical Variables
| Column | Profile | Coverage | Distinct | Most Common Share | Top Values | Interpretation |
|---|---|---|---|---|---|---|
_domain |
Binary | 100.0% present | 1 | 100.0% |
health - 175 (100.0%)
|
Two-level field; best read as a flag or yes/no split. |
country |
Binary | 100.0% present | 1 | 100.0% |
MWI - 175 (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 NUT_CF_ISSSF - 175 (100.0%)
|
Two-level field; best read as a flag or yes/no split. |
indicator_name |
Binary | 100.0% present | 1 | 100.0% |
NUT_CF_ISSSF - 175 (100.0%)
|
Two-level field; best read as a flag or yes/no split. |
comments |
Categorical | 100.0% present | 8 | 14.3% |
Malawi Demographic and Health Survey 2015-16. Zomba, Malawi, and Rockville, Maryland, USA. NSO and ICF. - 25 (14.3%)
Malawi MDG endline survey 2014. Final Report. Zomba, Malawi: National Statistical Office, 2014. - 25 (14.3%)
Malawi Multiple Indicator Cluster Survey 2019-20, Survey Findings Report. Zomba, Malawi: National Statistical Office - 25 (14.3%)
Malawi demographic and health survey 2004. Demographic and Health Surveys. Calverton, Maryland: NSO and ORC Macro, 2005 - 25 (14.3%)
Malawi demographic and health survey 2010. Demographic and Health Surveys. Zomba, Malawi, and Calverton, Maryland, USA: NSO and ICF Macro. 2011 - 25 (14.3%)
|
Nominal field summarised by the most frequent values. |
_domain_confidence |
Identifier | 100.0% present | 4 | 42.9% |
0.6 - 75 (42.9%)
0.5 - 50 (28.6%)
0.6666666666666666 - 25 (14.3%)
1.0 - 25 (14.3%)
|
High-cardinality identifier-like field; category frequencies are less informative. |
country_code |
Identifier | 100.0% present | 1 | 100.0% |
MWI - 175 (100.0%)
|
High-cardinality identifier-like field; category frequencies are less informative. |
indicator_code |
Identifier | 100.0% present | 1 | 100.0% |
NUT_CF_ISSSF - 175 (100.0%)
|
High-cardinality identifier-like field; category frequencies are less informative. |
year |
Temporal | 100.0% present | 7 | 14.3% |
2000 - 25 (14.3%)
2004 - 25 (14.3%)
2006 - 25 (14.3%)
2010 - 25 (14.3%)
2014 - 25 (14.3%)
|
Time-like field; values are better read as reporting periods than categories. |