data trove executive orders database
Reading
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
Charts the summary said to look at first
Show data table
| value | count | share |
|---|---|---|
| Trump second term executive orders (EO 14147 - EO 14371) | 1 | 100.0% |
Show data table
| 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% |
Show data table
| value | count | share |
|---|---|---|
| True | 1 | 100.0% |
Schema
7 columns| Alerts | ||||
|---|---|---|---|---|
| _stub | categorical | 0.0% | 1 |
long_tail
imbalance
|
| _description | categorical | 0.0% | 1 |
long_tail
imbalance
|
| _source | categorical | 0.0% | 1 |
long_tail
imbalance
|
| _fields | unknown | 0.0% | — |
skipped
|
| _sample | unknown | 0.0% | — |
skipped
|
| _stats | unknown | 0.0% | — |
skipped
|
| data | unknown | 0.0% | — |
skipped
|
_stub
categorical other long_tail imbalanceThis 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.
- n
- 1
- nulls
- 0 (0.0%)
- unique
- 1
- top_value
- True
- top_rate
- 1
- cardinality
- 1
- entropy
- 0
- entropy_ratio
- 0
_description
categorical metadata long_tail imbalanceThis 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.
- 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
_source
categorical metadata long_tail imbalanceThis 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.
- 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
_fields
unknown other skipped_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.
- n
- 1
- nulls
- 0 (0.0%)
- unique
- —
_sample
unknown other skippedThis 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.
- n
- 1
- nulls
- 0 (0.0%)
- unique
- —
_stats
unknown metadata skippedThis 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.
- n
- 1
- nulls
- 0 (0.0%)
- unique
- —
data
unknown other skippedThis 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.
- n
- 1
- nulls
- 0 (0.0%)
- unique
- —