---
layout: default
title: How to use
nav_order: 1
parent: Key Patient Characteristics
grand_parent: Curated Assets
permalink: /curated_assets/kpcs/how_to_use
---

# How to use

All kpc tables will be curated [**quarterly**]({% link docs/curated_assets/curated_assets.md %}#available-versions), following the NHS Data Wranglers provisioning runs. 

All tables are saved to the DSA schema **dsa_391419_j3w9t_collab**.

The archived_on_date is in the format **YYYY_MM_DD**.


{: .highlight-title }
> Table Names
>
> 
> **Demographics table**
> >
> hds_curated_assets__demographics_archived_on_date
>
> **Multisource tables**
> >
> hds_curated_assets__date_of_birth_multisource_archived_on_date
> hds_curated_assets__sex_multisource_archived_on_date
> hds_curated_assets__ethnicity_multisource_archived_on_date
> hds_curated_assets__lsoa_multisource_archived_on_date
>
> **Individual tables**
> >
> hds_curated_assets__date_of_birth_individual_archived_on_date
> hds_curated_assets__sex_individual_archived_on_date
> hds_curated_assets__ethnicity_individual_archived_on_date
> hds_curated_assets__lsoa_individual_archived_on_date


The example below will load the demographics table as at April 2024 using PySpark:

{% highlight markdown %}
```python
import pyspark.sql.functions as f
dsa = f'dsa_391419_j3w9t_collab'
demographics_table = spark.table(f'{dsa}.hds_curated_assets__demographics_2024_04_25')
```
{% endhighlight %}