Let's have a look at the available data before we define the corresponding dataset object.
Customers table
The data we will visualize in this tutorial represent our customers. The anonymized table contains each customer's internal ID, city, address, sex, age group and most importantly - latitude and longitude of the address. The table also contains code of the neighborhood to which the address belongs, which we'll use later.
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| 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 |
Download the CSV file and put it in the /data folder of your dump.
Creating a dataset
Now, we will create the corresponding dataset. Dataset object has some specifics which differ it from other metadata objects:
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| Info | ||
|---|---|---|
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That's it! In the ...