Tutorial 7: Setting up data export

In this tutorial, you will learn how to set up a data export. Each export si defined in the export object.

What you'll create

This is the export window, where you can download the export in a CSV file.

Customers export

Let's have a look at our customers dataset one more time. We will identify the properties that will be included in our export. Note that all active filters and the map selection are counted in the exports.

The requirement is to export customers, who have made a transaction bigger than 3000 CZK, to give them a special voucher.

The properties we want to include are: customer_id, address, sex and age_group.

Name	Title	Data type
`customer_id`	Customer ID	integer
`neighborhood_code`	Neighborhood code	string
`city`	Customer's city	string
`address`	Customer's address	string
`sex`	Customer's sex	string
`age_group`	Customer's age group	string
`lat`	Address latitude	latitude
`lng`	Address longitude	longitude

The export object will look like this:
Customers export syntax

CODE

{
    "name": "customers_export",
    "type": "export",
    "title": "Customers export",
    "content": {
        "properties": [
            "customers.customer_id",
            "customers.address",
            "customers.sex",
            "customers.age_group"
        ]
    }
}

Create customers_export.json and add this export object to the project using addMetadata. Now we just need to add the export reference to the business_overview_view object.

Business overview view excerpt

CODE

      ...
            "mapOptions": {
                "center": {
                    "lat": 49.203,
                    "lng": 16.606
                },
                "zoom": 12,
                "tileLayer": "mapbox"
            },
            "exports": [
                {
                    "export": "/rest/projects/$projectId/md/exports?name=customers_export"
                }
            ]
        },
        "accessInfo": {
      ...

Before we perform the export, we have to apply the required filter first.

Applied `histogram` filter on the `transaction_size` property

Also, don't forget that the map window should contain all available areas.

The export is available after clicking the Menu button in the top left corner (), and selecting Export.

Select Customers export and hit Export.

The selected columns, as well as metric results, will be present in the customers_export.csv file.

Stores export

This is the stores dataset we've added in the previous tutorial.

Identifier	Title	Data type
`store_id`	Store ID	integer
`address`	Store address	string
`store_type`	Store type	string
`opening_hours`	Opening hours	string
`monthly_rent`	Monthly rent	integer
`contact`	Contact email	string
`link`	Store web link	string
`parking`	Designated parking lot	string
`employees`	Number of employees	integer
`lat`	Store's latitude	latitude
`lng`	Store's longitude	longitude

We won't put any filters on this export and we'll export these properties: store_id, address, store_type, contact.

It is possible to include properties from other datasets in an export. We will include some properties from datasets of the Administrative units dimension we've added in one of the previous tutorials.

cast_obec_dwh.nazev - the city district where the store is located
okres_dwh.nazev - name of the county
kraj_dwh.nazev - name of the region

Stores export syntax

CODE

{
    "name": "stores_export",
    "type": "export",
    "title": "Stores export",
    "content": {
        "properties": [
            "stores.store_id",
            "stores.address",
            "stores.store_type",
            "stores.contact",
            "cast_obec_dwh.nazev",
            "okres_dwh.nazev",
            "kraj_dwh.nazev"
        ]
    }
}

Create stores_export.json and add the object using addMetadata and add the export reference to the business_overview_view object.

Business overview view excerpt

CODE

      ...
            "mapOptions": {
                "center": {
                    "lat": 49.203,
                    "lng": 16.606
                },
                "zoom": 12,
                "tileLayer": "mapbox"
            },
            "exports": [
                {
                    "export": "/rest/projects/$projectId/md/exports?name=customers_export"
                },
                {
                    "export": "/rest/projects/$projectId/md/exports?name=stores_export"
                }
            ]
        },
        "accessInfo": {
      ...

Push the object using pushProject. Then repeat the export process, but select Stores export and hit Export.

You can see that the stores_export.csv contains all six stores, with respective results of all metrics in all city districts.

That's it! In the next tutorial, we will learn how to use AreaMapper and use a new visualization - grid.

What you'll create

Customers export

Business overview view excerpt

Applied histogram filter on the transaction_size property

Stores export

Stores export syntax

Business overview view excerpt

Applied `histogram` filter on the `transaction_size` property