# EDCOM II early-childhood dashboard data, cleaned (version 1) Data behind the NASH Reviewer series on the CRLA at the end of SY 2025-26. It was extracted from the public EDCOM II early-childhood care and development dashboard (), checked and cleaned, and joined to DepEd's public school data. NASH Reviewer is not affiliated with EDCOM II or the Department of Education. - **Every file, with the report and charts:** [EDCOM II CRLA data](https://nash.com.ph/edcom-data) - **How it was made:** [How the EDCOM Dashboard Data Was Cleaned](https://nash.com.ph/blog/edcom-eccd-dashboard-data-cleaned) - **What it shows:** [CRLA Results at the End of SY 2025-26](https://nash.com.ph/blog/crla-end-of-year-results-sy-2025-2026) - **Reading school results fairly:** [How to Read a School's CRLA Results](https://nash.com.ph/blog/how-to-read-school-crla-results) ## Files | File | Contents | Rows | Size | |---|---|---:|---:| | [`edcom_raw_extract_csv.zip`](https://data.nash.com.ph/edcom-data/v1/edcom_raw_extract_csv.zip) | The six tables as recovered from the dashboard workbook, unchanged, with the field dictionary and metadata | | 8.9 MB | | [`schools_literacy_clean.csv.gz`](https://data.nash.com.ph/edcom-data/v1/schools_literacy_clean.csv.gz) | One row per school: CRLA results by grade and language, barangay link, coordinates, flags | 38,679 | 4.2 MB | | [`school_locations_clean.csv.gz`](https://data.nash.com.ph/edcom-data/v1/school_locations_clean.csv.gz) | All school location records with geography and coordinate quality | 48,254 | 3.4 MB | | [`barangays_clean.csv.gz`](https://data.nash.com.ph/edcom-data/v1/barangays_clean.csv.gz) | PSGC barangay reference with match keys and centroids | 42,010 | 1.6 MB | | [`barangays_without_cdc_clean.csv.gz`](https://data.nash.com.ph/edcom-data/v1/barangays_without_cdc_clean.csv.gz) | Barangays with no child development center (DILG CBMS, 17 Sep 2025) | 4,604 | 35 KB | | [`stunting_2025_clean.csv.gz`](https://data.nash.com.ph/edcom-data/v1/stunting_2025_clean.csv.gz) | OPT Plus 2025 stunting, ages 0-2, by region, province and municipality (DOH/NNC, 2 Mar 2026) | 1,742 | 126 KB | | [`barangay_programs_clean.csv.gz`](https://data.nash.com.ph/edcom-data/v1/barangay_programs_clean.csv.gz) | Literacy, nutrition and childcare program records (100) | 100 | 6 KB | | [`overview_by_region_clean.csv.gz`](https://data.nash.com.ph/edcom-data/v1/overview_by_region_clean.csv.gz) | The dashboard's regional overview | 19 | 1 KB | | [`region_crosswalk.csv.gz`](https://data.nash.com.ph/edcom-data/v1/region_crosswalk.csv.gz) | Region labels to PSGC regions | 18 | 1 KB | | [`region_reconciliation.csv.gz`](https://data.nash.com.ph/edcom-data/v1/region_reconciliation.csv.gz) | Regional totals reconciled with the national totals | 19 | 1 KB | | [`cleaning_log.csv`](https://data.nash.com.ph/edcom-data/v1/cleaning_log.csv) | Every change the cleaning made: table, record, rule, old and new value, reason | 1,486 | 216 KB | | [`validation.json`](https://data.nash.com.ph/edcom-data/v1/validation.json) | Row counts, reconciliation checks and link summary | | 2 KB | | [`edcom_crla_2026.parquet`](https://data.nash.com.ph/edcom-data/v1/edcom_crla_2026.parquet) | Analysis table: one row per school, CRLA blocks and totals, barangay and municipality codes, SY 2023-24 school inputs (in_ columns), head type | 38,679 | 8.4 MB | | [`division_estimates.csv`](https://data.nash.com.ph/edcom-data/v1/division_estimates.csv) | 232 divisions: share struggling, empirical Bayes estimate and 95% interval, rank interval, funnel and FDR flags | 232 | 46 KB | | [`school_estimates.csv.gz`](https://data.nash.com.ph/edcom-data/v1/school_estimates.csv.gz) | Every school: share struggling, empirical Bayes and hierarchical Bayes estimates with 95% intervals, funnel flag (read the guide before ranking schools) | 38,679 | 2.9 MB | | [`inputs_by_region.csv`](https://data.nash.com.ph/edcom-data/v1/inputs_by_region.csv) | School inputs and struggling readers: odds ratios with 95% intervals from a separate model for each region | 230 | 27 KB | | [`municipalities.csv`](https://data.nash.com.ph/edcom-data/v1/municipalities.csv) | Municipality or city: learners, struggling readers, estimate, LISA and Gi* results, stunting and CDC gaps | 1,639 | 437 KB | CSV files are UTF-8; `.csv.gz` files are gzip-compressed CSV. Checksums are in [`CHECKSUMS.sha256`](https://data.nash.com.ph/edcom-data/v1/CHECKSUMS.sha256). ## Definitions - **Period.** CRLA results at the end of SY 2025-26, as of 10 May 2026, for 38,679 public schools. - **Learners.** The dashboard's totals are Grade 1 Mother Tongue + Grade 2 Filipino + Grade 3 English: one result per learner, 5,127,670 learners in all. - **Struggling readers.** Low Emerging plus High Emerging: 511,753 learners (9.98%). - **Regions.** The 18 PSGC regions (`region_clean`), with Sulu in Region IX and the Negros Island Region as its own region. ## Sources and credit The data come from the EDCOM II dashboard, which compiles DepEd's CRLA results, DOH/NNC's Operation Timbang Plus 2025, DILG's Community-Based Monitoring System and a list of program records. School inputs come from DepEd's public school files for SY 2023-24. Municipal boundaries used in the analysis are from PSA and NAMRIA via OCHA HDX (CC BY-IGO). Please cite: *Llego, M. A. (2026). EDCOM II early-childhood dashboard data, cleaned, version 1. NASH Reviewer. https://nash.com.ph/edcom-data* ## Cautions - School-level shares from small schools are noisy. Use the estimates and intervals in `school_estimates.csv.gz`, not raw shares, and do not rank individual schools from them. - Links and coordinates added by research are marked in `cleaning_log.csv`; researched coordinates are less precise than DepEd's (a median of 5.2 km from the barangay center against 0.73 km). - Stunting (ages 0-2, 2025) and reading (Grades 1-3, SY 2025-26) describe different children. Comparisons between them are about places, not individual children.