A minimal TypeScript package that profiles arrays of records (data-frame-like) for LLM context.
npm install data-profileA minimal TypeScript package that profiles arrays of records (data-frame-like) for LLM context.
``bash`
npm install data-profile
`typescript
import profile from 'data-profile';
const data = [
{ id: 1, name: 'Alice', age: 30, active: true },
{ id: 2, name: 'Bob', age: 25, active: false },
{ id: 3, name: 'Charlie', age: 35, active: true }
];
// Basic profiling
const summary = profile(data);
// With advanced features
const detailed = profile(data, {
sampleSize: 10,
associationMatrix: true,
keysDependencies: true,
missingnessPatterns: true,
outliers: true,
categoricalEntropy: true
});
`
- Basic Stats: Row count, column types, missing values
- Numeric Analysis: Min/max, mean, median, quartiles, percentiles, standard deviation
- Categorical Analysis: Unique values, top 10 frequencies, HHI index
- Associations: Pearson correlation, Cramér's V, eta-squared
- Data Quality: Primary key candidates, functional dependencies, outlier detection
- Missing Patterns: Per-column rates, co-missing analysis
- Entropy: Information content for categorical variables
- Customizable Sampling: Control number of sample rows returned (default: 5)
`typescript`
type ProfileSummary = {
rowCount: number;
columns: string[];
columnStats: Record
missing: number;
types: string[];
numericStats?: { min, max, mean, median, quartiles, stddev, percentiles };
categoricalStats?: { unique, top10, hhi };
}>;
sampleRows: Array
// Optional advanced features...
};Real Dataset Example
Here's an example using the Titanic dataset:
`typescript`
const basicProfile = profile(titanicSample);
console.log(JSON.stringify(basicProfile, null, 2));
`json
{
"rowCount": 891,
"columns": [
"Age",
"Cabin",
"Embarked",
"Fare",
"Name",
"Parch",
"PassengerId",
"Pclass",
"Sex",
"SibSp",
"Survived",
"Ticket"
],
"columnStats": {
"Age": {
"present": 714,
"missing": 177,
"types": [
"number"
],
"numericStats": {
"min": 0.42,
"max": 80,
"mean": 29.69911764705882,
"median": 28,
"quartiles": [
20.125,
28,
38
],
"stddev": 14.526497332334044,
"percentiles": {
"10": 14,
"90": 50
}
}
},
"Cabin": {
"present": 204,
"missing": 687,
"types": [
"string"
],
"categoricalStats": {
"unique": 147,
"top10": [
{
"value": "G6",
"count": 4
},
{
"value": "C23 C25 C27",
"count": 4
},
{
"value": "B96 B98",
"count": 4
},
{
"value": "F33",
"count": 3
},
{
"value": "E101",
"count": 3
},
{
"value": "F2",
"count": 3
},
{
"value": "D",
"count": 3
},
{
"value": "C22 C26",
"count": 3
},
{
"value": "C123",
"count": 2
},
{
"value": "D33",
"count": 2
}
],
"hhi": 83.14109957708554
}
},
"Embarked": {
"present": 889,
"missing": 2,
"types": [
"string"
],
"categoricalStats": {
"unique": 3,
"top10": [
{
"value": "S",
"count": 644
},
{
"value": "C",
"count": 168
},
{
"value": "Q",
"count": 77
}
],
"hhi": 5679.8313596627195
}
},
"Fare": {
"present": 891,
"missing": 0,
"types": [
"number"
],
"numericStats": {
"min": 0,
"max": 512.3292,
"mean": 32.2042079685746,
"median": 14.4542,
"quartiles": [
7.9104,
14.4542,
31
],
"stddev": 49.693428597180905,
"percentiles": {
"10": 7.55,
"90": 77.9583
}
}
},
"Name": {
"present": 891,
"missing": 0,
"types": [
"string"
],
"categoricalStats": {
"unique": 891,
"top10": [
{
"value": "Braund, Mr. Owen Harris",
"count": 1
},
{
"value": "Cumings, Mrs. John Bradley (Florence Briggs Thayer)",
"count": 1
},
{
"value": "Heikkinen, Miss. Laina",
"count": 1
},
{
"value": "Futrelle, Mrs. Jacques Heath (Lily May Peel)",
"count": 1
},
{
"value": "Allen, Mr. William Henry",
"count": 1
},
{
"value": "Moran, Mr. James",
"count": 1
},
{
"value": "McCarthy, Mr. Timothy J",
"count": 1
},
{
"value": "Palsson, Master. Gosta Leonard",
"count": 1
},
{
"value": "Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",
"count": 1
},
{
"value": "Nasser, Mrs. Nicholas (Adele Achem)",
"count": 1
}
],
"hhi": 11.223344556677977
}
},
"Parch": {
"present": 891,
"missing": 0,
"types": [
"number"
],
"numericStats": {
"min": 0,
"max": 6,
"mean": 0.38159371492704824,
"median": 0,
"quartiles": [
0,
0,
0
],
"stddev": 0.8060572211299559,
"percentiles": {
"10": 0,
"90": 2
}
}
},
"PassengerId": {
"present": 891,
"missing": 0,
"types": [
"number"
],
"numericStats": {
"min": 1,
"max": 891,
"mean": 446,
"median": 446,
"quartiles": [
223.5,
446,
668.5
],
"stddev": 257.3538420152301,
"percentiles": {
"10": 90,
"90": 802
}
}
},
"Pclass": {
"present": 891,
"missing": 0,
"types": [
"number"
],
"numericStats": {
"min": 1,
"max": 3,
"mean": 2.308641975308642,
"median": 3,
"quartiles": [
2,
3,
3
],
"stddev": 0.8360712409770513,
"percentiles": {
"10": 1,
"90": 3
}
}
},
"Sex": {
"present": 891,
"missing": 0,
"types": [
"string"
],
"categoricalStats": {
"unique": 2,
"top10": [
{
"value": "male",
"count": 577
},
{
"value": "female",
"count": 314
}
],
"hhi": 5435.638338743466
}
},
"SibSp": {
"present": 891,
"missing": 0,
"types": [
"number"
],
"numericStats": {
"min": 0,
"max": 8,
"mean": 0.5230078563411896,
"median": 0,
"quartiles": [
0,
0,
1
],
"stddev": 1.1027434322934275,
"percentiles": {
"10": 0,
"90": 1
}
}
},
"Survived": {
"present": 891,
"missing": 0,
"types": [
"number"
],
"numericStats": {
"min": 0,
"max": 1,
"mean": 0.3838383838383838,
"median": 0,
"quartiles": [
0,
0,
1
],
"stddev": 0.4865924542648585,
"percentiles": {
"10": 0,
"90": 1
}
}
},
"Ticket": {
"present": 891,
"missing": 0,
"types": [
"string",
"number"
]
}
},
"sampleRows": [
{
"Age": 22,
"Cabin": null,
"Embarked": "S",
"Fare": 7.25,
"Name": "Braund, Mr. Owen Harris",
"Parch": 0,
"PassengerId": 1,
"Pclass": 3,
"Sex": "male",
"SibSp": 1,
"Survived": 0,
"Ticket": "A/5 21171"
}
....
],
}
`
Advanced Features Output:
`typescript`
const advancedProfile = profile(titanicSample, {
associationMatrix: true,
keysDependencies: true,
missingnessPatterns: true,
outliers: true,
categoricalEntropy: true
});
`json``
{
"associationMatrix": {
"Age": {
"Cabin": 0.84487746358188,
"Embarked": 0.0017926615874587443,
"Fare": 0.09606669176903883,
"Name": 1,
"Parch": -0.18911926263203518,
"PassengerId": 0.03684719786132784,
"Pclass": -0.36922601531551574,
"Sex": 0.008696229596377726,
"SibSp": -0.3082467589236574,
"Survived": -0.07722109457217737
},
"Cabin": {
"Age": 0.84487746358188,
"Embarked": 0.9492663573697424,
"Fare": 0.8853684889490768,
"Name": 0.9999999999998898,
"Parch": 0.9406806543707776,
"PassengerId": 0.8050749169584301,
"Pclass": 1.0000000000000016,
"Sex": 0.85902989670101,
"SibSp": 0.9294261294261293,
"Survived": 0.7904411764705864
},
"Embarked": {
"Age": 0.0017926615874587443,
"Cabin": 0.9492663573697424,
"Fare": 0.07927065096791176,
"Name": 0.9999999999999969,
"Parch": 0.00723127712686622,
"PassengerId": 0.0011747820348445024,
"Pclass": 0.09501742839465667,
"Sex": 0.12256919037251322,
"SibSp": 0.004906413368023388,
"Survived": 0.029796568998017418
},
"Fare": {
"Age": 0.09606669176903883,
"Cabin": 0.8853684889490768,
"Embarked": 0.07927065096791176,
"Name": 1,
"Parch": 0.21622494477076254,
"PassengerId": 0.012658219287491229,
"Pclass": -0.5494996199439062,
"Sex": 0.033245262282584974,
"SibSp": 0.15965104324216106,
"Survived": 0.2573065223849618
},
"Name": {
"Age": 1,
"Cabin": 0.9999999999998898,
"Embarked": 0.9999999999999969,
"Fare": 1,
"Parch": 1,
"PassengerId": 1,
"Pclass": 1,
"Sex": 0.9999999999999973,
"SibSp": 1,
"Survived": 1
},
"Parch": {
"Age": -0.18911926263203518,
"Cabin": 0.9406806543707776,
"Embarked": 0.00723127712686622,
"Fare": 0.21622494477076254,
"Name": 1,
"PassengerId": -0.0016520124027188283,
"Pclass": 0.01844267131074835,
"Sex": 0.06026482952641173,
"SibSp": 0.41483769862015263,
"Survived": 0.08162940708348221
},
"PassengerId": {
"Age": 0.03684719786132784,
"Cabin": 0.8050749169584301,
"Embarked": 0.0011747820348445024,
"Fare": 0.012658219287491229,
"Name": 1,
"Parch": -0.0016520124027188283,
"Pclass": -0.03514399403037966,
"Sex": 0.0018437474224206054,
"SibSp": -0.057526833784441705,
"Survived": -0.005006660767066476
},
"Pclass": {
"Age": -0.36922601531551574,
"Cabin": 1.0000000000000016,
"Embarked": 0.09501742839465667,
"Fare": -0.5494996199439062,
"Name": 1,
"Parch": 0.01844267131074835,
"PassengerId": -0.03514399403037966,
"Sex": 0.017397739421770773,
"SibSp": 0.08308136284568661,
"Survived": -0.3384810359610158
},
"Sex": {
"Age": 0.008696229596377726,
"Cabin": 0.85902989670101,
"Embarked": 0.12256919037251322,
"Fare": 0.033245262282584974,
"Name": 0.9999999999999973,
"Parch": 0.06026482952641173,
"PassengerId": 0.0018437474224206054,
"Pclass": 0.017397739421770773,
"SibSp": 0.013140222690535797,
"Survived": 0.29523072286268753
},
"SibSp": {
"Age": -0.3082467589236574,
"Cabin": 0.9294261294261293,
"Embarked": 0.004906413368023388,
"Fare": 0.15965104324216106,
"Name": 1,
"Parch": 0.41483769862015263,
"PassengerId": -0.057526833784441705,
"Pclass": 0.08308136284568661,
"Sex": 0.013140222690535797,
"Survived": -0.03532249888573588
},
"Survived": {
"Age": -0.07722109457217737,
"Cabin": 0.7904411764705864,
"Embarked": 0.029796568998017418,
"Fare": 0.2573065223849618,
"Name": 1,
"Parch": 0.08162940708348221,
"PassengerId": -0.005006660767066476,
"Pclass": -0.3384810359610158,
"Sex": 0.29523072286268753,
"SibSp": -0.03532249888573588
},
"Ticket": {}
},
"keysAndDependencies": {
"candidatePrimaryKeys": [
[
"Name"
],
[
"PassengerId"
]
],
"functionalDependencies": [
{
"from": [
"Cabin"
],
"to": "Pclass"
},
{
"from": [
"Ticket"
],
"to": "Pclass"
}
]
},
"missingnessPatterns": {
"perColumnRates": {
"Age": 0.19865319865319866,
"Cabin": 0.7710437710437711,
"Embarked": 0.002244668911335578,
"Fare": 0,
"Name": 0,
"Parch": 0,
"PassengerId": 0,
"Pclass": 0,
"Sex": 0,
"SibSp": 0,
"Survived": 0,
"Ticket": 0
},
"topCoMissingPairs": [
{
"pair": [
"Age",
"Cabin"
],
"count": 158
}
]
},
"outliers": {
"Age": {
"tukeyCount": 11,
"zscoreCount": 2
},
"Fare": {
"tukeyCount": 116,
"zscoreCount": 20
},
"Parch": {
"tukeyCount": 213,
"zscoreCount": 15
},
"PassengerId": {
"tukeyCount": 0,
"zscoreCount": 0
},
"Pclass": {
"tukeyCount": 0,
"zscoreCount": 0
},
"SibSp": {
"tukeyCount": 46,
"zscoreCount": 30
},
"Survived": {
"tukeyCount": 0,
"zscoreCount": 0
}
},
"categoricalEntropy": {
"Cabin": {
"entropy": 7.065687903192981,
"tailShareOutsideTop10": 0.8480392156862745
},
"Embarked": {
"entropy": 1.0968693499252113,
"tailShareOutsideTop10": 0
},
"Name": {
"entropy": 9.79928162152199,
"tailShareOutsideTop10": 0.9887766554433222
},
"Sex": {
"entropy": 0.9362046432498521,
"tailShareOutsideTop10": 0
}
}
}
- Association matrix: Capped at 50 columns
- Key detection: Capped at 20 columns
- Missing patterns: Optimized for large datasets
MIT