Source: /home/coolhand/html/datavis/data_trove/data/policy/executive_orders.json
Saturn profiled 1 rows across 7 columns. The stats below are deterministic and machine-readable; the prose is a language-model interpretation of those stats (opt-in, added after the fact, never sees raw rows).
!pip install saturn-dissect
import subprocess
subprocess.run([
"saturn", "analyze", "/home/coolhand/html/datavis/data_trove/data/policy/executive_orders.json",
"--findings", "data-trove-executive-orders-database.json",
"--llm", "anthropic:default",
])This dataset is a metadata wrapper — a single-row JSON manifest describing a collection of Trump second-term executive orders (EO 14147 through EO 14371) sourced from the Federal Register API. With only 1 row and 7 columns, the file itself is a stub or index record rather than the full underlying data; the actual executive order records are nested inside the 'data', '_sample', '_stats', and '_fields' columns which were skipped during profiling. The most important next step is to unpack those nested columns — particularly 'data' — to access the real executive order records. Until that extraction is done, no meaningful analysis of the orders themselves (topics, signing dates, frequency, etc.) is possible.
citing: row_count · column_count · _description.top_value · _source.top_value · _stub.top_value · _fields.alerts · _sample.alerts · _stats.alerts · data.alerts
saturn.schema() · 7 columns
| column | kind | n | null% | unique | alerts |
|---|---|---|---|---|---|
| _stub | categorical | 1 | 0.0% | 1 | long_tail imbalance |
| _description | categorical | 1 | 0.0% | 1 | long_tail imbalance |
| _source | categorical | 1 | 0.0% | 1 | long_tail imbalance |
| _fields | unknown | 1 | 0.0% | — | skipped |
| _sample | unknown | 1 | 0.0% | — | skipped |
| _stats | unknown | 1 | 0.0% | — | skipped |
| data | unknown | 1 | 0.0% | — | skipped |
| value | count | share |
|---|---|---|
| Trump second term executive orders (EO 14147 - EO 14371) | 1 | 100.0% |
| value | count | share |
|---|---|---|
| Federal Register API: https://www.federalregister.gov/api/v1/documents.json?conditions[presidential_document_type]=executive_order&conditions[president]=donald-trump | 1 | 100.0% |
| value | count | share |
|---|---|---|
| True | 1 | 100.0% |
| column | kind | null % |
|---|---|---|
| _stub | categorical | 0.0% |
| _description | categorical | 0.0% |
| _source | categorical | 0.0% |
| _fields | unknown | 0.0% |
| _sample | unknown | 0.0% |
| _stats | unknown | 0.0% |
| data | unknown | 0.0% |
This column '_stub' is a degenerate constant flag containing a single row with value 'True', making it entirely uninformative. With n=1, cardinality=1, top_rate=1.0, and entropy of 0.0, there is zero variance and no predictive or descriptive utility whatsoever. The alerts for long_tail and imbalance are technically correct but secondary to the fundamental issue: this is a single-observation, single-value column that appears to be a placeholder or scaffold artifact.
Treatment: Drop immediately; zero-variance constant with only 1 row provides no analytical value.
saturn.columns["_stub"].stats
| stat | value |
|---|---|
| n | 1 |
| nulls | 0 (0.0%) |
| unique | 1 |
| top_value | True |
| top_rate | 1 |
| cardinality | 1 |
| entropy | 0 |
| entropy_ratio | 0 |
| alert: long_tail | 1 singleton categories |
| alert: imbalance | top value is 100.0% of rows |
_stub.
| value | count | share |
|---|---|---|
| True | 1 | 100.0% |
This column is a dataset-level description label, not a per-row feature — it contains exactly one value ('Trump second term executive orders (EO 14147 - EO 14371)') repeated across all 1 row(s), giving it zero entropy and 100% top-value rate. With n=1 and cardinality=1, this appears to be a metadata annotation describing the dataset's subject matter rather than any analytical variable. No analytical signal is present.
Treatment: Drop before modelling; retain only as dataset provenance documentation.
saturn.columns["_description"].stats
| stat | value |
|---|---|
| n | 1 |
| nulls | 0 (0.0%) |
| unique | 1 |
| top_value | Trump second term executive orders (EO 14147 - EO 14371) |
| top_rate | 1 |
| cardinality | 1 |
| entropy | 0 |
| entropy_ratio | 0 |
| alert: long_tail | 1 singleton categories |
| alert: imbalance | top value is 100.0% of rows |
_description.
| value | count | share |
|---|---|---|
| Trump second term executive orders (EO 14147 - EO 14371) | 1 | 100.0% |
This column is a data provenance/source tag indicating where the dataset was fetched from — specifically the Federal Register API filtered for Donald Trump executive orders. It contains exactly one unique value appearing in all 1 row(s), making it a constant metadata field with zero informational variance (entropy = 0.0). The 'long_tail' and 'imbalance' alerts are technically correct but trivially explained by the column being perfectly constant. No analytical signal exists here.
Treatment: Drop before modelling; constant column adds no signal and wastes memory.
saturn.columns["_source"].stats
| stat | value |
|---|---|
| n | 1 |
| nulls | 0 (0.0%) |
| unique | 1 |
| top_value | Federal Register API: https://www.federalregister.gov/api/v1/documents.json?conditions[presidential_document_type]=executive_order&conditions[president]=donald-trump |
| top_rate | 1 |
| cardinality | 1 |
| entropy | 0 |
| entropy_ratio | 0 |
| alert: long_tail | 1 singleton categories |
| alert: imbalance | top value is 100.0% of rows |
_source.
| value | count | share |
|---|---|---|
| Federal Register API: https://www.federalregister.gov/api/v1/documents.json?conditions[presidential_document_type]=executive_order&conditions[president]=donald-trump | 1 | 100.0% |
_fields is an internal or system-generated column (likely a struct/array/map type that the profiler could not decompose), with only 1 row observed and no further statistics available. The profiler skipped analysis entirely, so nothing can be said about its distribution, cardinality, or content. Its name pattern ('_fields') suggests a catch-all or schema-overflow field common in Elasticsearch, Protobuf, or similar serialisation systems.
Treatment: Inspect raw schema to determine underlying type; if it contains nested attributes, explode or parse before any modelling or analysis.
saturn.columns["_fields"].stats
| stat | value |
|---|---|
| n | 1 |
| nulls | 0 (0.0%) |
| unique | — |
| alert: skipped | no profiler for kind=unknown |
This column ('_sample') contains only a single row and no computed statistics, indicating it was skipped during profiling. With n=1 and no unique-count or distributional data available, no meaningful inference about its content or role can be made.
Treatment: Investigate whether this is a sentinel/metadata artifact from the sampling process; confirm if it should be dropped or excluded from analysis.
saturn.columns["_sample"].stats
| stat | value |
|---|---|
| n | 1 |
| nulls | 0 (0.0%) |
| unique | — |
| alert: skipped | no profiler for kind=unknown |
This column contains a single row with no computable statistics, flagged as 'skipped' by the profiler. With n=1 and an unknown kind, it is likely a metadata or sentinel row rather than a real data column. No distributional, type, or uniqueness signals are available to characterise it further.
Treatment: Investigate whether this is a spurious row or internal profiler artifact; exclude from modelling until origin is confirmed.
saturn.columns["_stats"].stats
| stat | value |
|---|---|
| n | 1 |
| nulls | 0 (0.0%) |
| unique | — |
| alert: skipped | no profiler for kind=unknown |
This column contains only a single row and was flagged as 'skipped' during profiling, yielding no computable statistics. With n=1 and kind classified as 'unknown', there is effectively no distributional signal available. Nothing meaningful can be inferred about the column's role or content beyond its existence.
Treatment: Investigate data source — single-row column with no stats; determine if this is a parsing artifact or a genuine singleton record before any further use.
saturn.columns["data"].stats
| stat | value |
|---|---|
| n | 1 |
| nulls | 0 (0.0%) |
| unique | — |
| alert: skipped | no profiler for kind=unknown |
click to copy
@misc{saturn-data-trove-executive-orders-database-2026,
author = {Steuber, Luke},
title = {Saturn reading: data trove executive orders database},
year ={2026},
howpublished = {\url{https://dr.eamer.dev/saturn/view/data-trove-executive-orders-database}},
note = {Profiled with saturn-dissect v0.2.0, prompt saturn-insight-v2, model anthropic:default},
}
Steuber, L. (2026). Saturn reading: data trove executive orders database. Source: /home/coolhand/html/datavis/data_trove/data/policy/executive_orders.json. Profiled with saturn-dissect v0.2.0 (saturn-insight-v2, anthropic:default). Retrieved from https://dr.eamer.dev/saturn/view/data-trove-executive-orders-database