This is a live demo, built on made-up or public data. All demos

Student Enrollment

Total student enrollment counts by school, grade, and year.

rcd_adm
Rows
59,478
Schools & agencies
3,130
Years covered
2005–06 to 2023–24
Clear

This is exactly how the state publishes it — raw column names, raw codes.

Decode this table
id agency_code avg_student_num category_code year
56205 00A000 2421 Unknown 2024
56206 00B000 3015 Unknown 2024
56207 010303 231 Unknown 2024
56208 010304 595 Unknown 2024
56209 010308 583 Unknown 2024
56210 010310 517 Unknown 2024
56211 010312 640 Unknown 2024
56212 010320 296 Unknown 2024
56213 010324 1079 Unknown 2024
56214 010326 534 Unknown 2024
56215 010328 499 Unknown 2024
56216 010340 692 Unknown 2024
56217 010346 349 Unknown 2024
56218 010347 679 Unknown 2024
56219 010348 711 Unknown 2024
56220 010350 476 Unknown 2024
56221 010351 401 Unknown 2024
56222 010353 820 Unknown 2024
56223 010354 498 Unknown 2024
56224 010357 485 Unknown 2024
56225 010358 505 Unknown 2024
56226 010360 788 Unknown 2024
56227 010362 535 Unknown 2024
56228 010364 363 Unknown 2024
56229 010372 280 Unknown 2024
56230 010374 525 Unknown 2024
56231 010378 64 Unknown 2024
56232 010380 455 Unknown 2024
56233 010384 548 Unknown 2024
56234 010388 1134 Unknown 2024
56235 010390 850 Unknown 2024
56236 010392 270 Unknown 2024
56237 010394 688 Unknown 2024
56238 010396 1176 Unknown 2024
56239 010400 1100 Unknown 2024
56240 010403 879 Unknown 2024
56241 010406 741 Unknown 2024
56242 010410 864 Unknown 2024
56243 010450 230 Unknown 2024
56244 010LEA 22080 Unknown 2024
56245 010LEA 230 A 2024
56246 010LEA 487 E 2024
56247 010LEA 885 H 2024
56248 010LEA 710 M 2024
56249 010LEA 64 T 2024
56250 01B000 754 Unknown 2024
56251 01C000 930 Unknown 2024
56252 01D000 582 Unknown 2024
56253 01F000 607 Unknown 2024
56254 020302 1209 Unknown 2024
Column dictionary — the state's own definitions
Shown as State's column Data type State's description Codes
agency_code key agency_code VARCHAR(6) 010303/010LEA/NC-SEA
avg_student_num avg_student_num NUMERIC(38,0) Average number of students
category_code key category_code VARCHAR(1) Grade span category code. See grade_span_cat_code table for detail
6 codes
  • A → Elementary, Middle, High School
  • E → Elementary
  • H → High School
  • I → Elementary, Middle school
  • M → Middle School
  • T → Middle, High School
year key year VARCHAR(4) YYYY (i.e. 2006 for the 2005/06 school year)
About this table

State's description: average daily membership

Listed in the state's table index as rcd_adm (active, 2016)

59,478 rows loaded, covering 3,130 schools and agencies, 2005–06 to 2023–24.

How this table got here
  1. The state publishes an Excel data dictionary. This demo reads it: 66 table definitions, 525 column definitions, and 181 code definitions — the same ones behind the Decoded view above.
  2. From those definitions it writes a Django database model for each table, so nobody has to type the columns in by hand. This table's model came out like this:
class RcdAdm(SRCBaseModel):
    agency_code = models.CharField(max_length=6)
    avg_student_num = models.DecimalField(max_digits=38, decimal_places=0, null=True, blank=True)
    category_code = models.CharField(
        max_length=31,
        choices=[
            ("E", "Elementary"),
            ("M", "Middle School"),
            ("H", "High School"),
            ("A", "Elementary, Middle, High School"),
            ("T", "Middle, High School"),
            ("I", "Elementary, Middle school"),
        ],
    )
    year = models.CharField(max_length=4)

    class Meta:
        db_table = "rcd_adm"
        managed = True
        unique_together = ("year", "agency_code", "category_code")
  1. 59,478 rows were then loaded from the state's raw data files into RcdAdm.
  2. It also takes a fingerprint (SHA-256) of the dictionary's general-rules sheet. If the state quietly rewrites its rules document, the next rebuild flags the change instead of absorbing it silently.
Want something like this for your program? Schedule a conversation or email matt@mattniksch.com.