files/arthur-docs-markdown/user-guide/api-query-guide/index.md.txt

# API Query Guide


This selection of guides and references covers the basics of querying data using the Arthur Query API Endpoints. 
The complete reference for the full Arthur API documentation can be found 
[here](https://docs.arthur.ai/api-documentation/v3-api-docs.html), 
and the reference to the Query Endpoint can be found
[here](https://docs.arthur.ai/api-documentation/v3-api-docs.html#tag/query).

## {doc}`Query Quickstart <query_quickstart>`
For beginners to the Arthur Query API, see the {doc}`query_quickstart`
for a basic walkthrough on querying data about your model's performance.

## References:

### {doc}`Endpoint Overview <endpoint_overview>`
The {doc}`endpoint_overview` covers the structure and parameters of queries 
and provides more examples to get started.

### {doc}`Model Evaluation Functions <model_evaluation_functions>`
This reference shows the basic metrics needed to evaluate the performance of models (accuracy, confusion matrix, MSE, etc)

### {doc}`Data Drift <data_drift>`
This reference shows querying data drift over time, 
which is needed to diagnose which changes in data could explain a change in model performance.

### {doc}`Explainability </user-guide/api-query-guide/explainability>`
This reference shows how to query explanations for inferences. Whether in terms of features in tabular models, 
words in NLP models, or regions of pixels in CV models, explainability offers a rough approximation of 
the _how_ and _why_ behind a model's inferences.

### {doc}`Aggregation Functions <aggregation_functions>`
This reference shows  how to apply aggregators like an _average_ (`avg`) or a _maximum_ (`max`) to a query.

### {doc}`Transformation Functions <transformation_functions>`
This reference shows the transformations available within an Arthur query (numerical operations, binning variables, 
grouping by time resolution, etc)

### {doc}`Composing Functions <composing_functions>`
This reference shows composing functions to fit complex transformations into a single query

### {doc}`Subqueries <subqueries>`
This reference shows how to embed queries within queries.

## {doc}`Grouped Inference Queries <grouped_inference_queries>`
This guide shows how to query information pertaining to individual instances of data over time.

```{toctree}
:maxdepth: 2
:hidden:

Query Quickstart <query_quickstart>
Endpoint Overview <endpoint_overview>
Model Evaluation Functions <model_evaluation_functions>
Data Drift <data_drift>
Explainability <explainability>
Aggregation <aggregation_functions>
Transformations <transformation_functions>
Composition <composing_functions>
Subqueries <subqueries>
Advanced Example: Unique Identifiers <grouped_inference_queries>

```