When a file is imported to your account, your data is transformed into a table that can be processed by CARTO. The Data View of a connected dataset includes formatted columns and indexes required for rendering your visualization.
You can manage connected datasets through Your datasets dashboard, which enables you to add rows, add columns, edit cell values, change the data type of a column, export your dataset, and even use SQL to modify your data.
For this guide, let's look at tech companies in Brooklyn, NY and learn how a basic table schema is created. There are no files to download for this guide, as we are building data from scratch by connecting an empty dataset and adding data manually.
If you prefer to create a new dataset from scratch, create an empty dataset and add metadata by adding row and column values.
Login to CARTO and navigate to Your datasets dashboard.
Click NEW DATASET.
The Connect dataset options appear.
Click CREATE EMPTY DATASET.
An empty dataset containing the default CARTO columns and indexes is created.
Double-click on the untitled table name to rename it to
Tech Co. You can also change the privacy settings, if applicable.
Let's start adding data!
In this section, we will rename some of the existing columns, add new columns, and add row values.
Rename the following columns:
Double-click on the column heading
name and enter
You will get confirmation message before renaming a column. The column is created using the string data type by default.
Double-click on the column heading
description and change it to
zip code, and
Add a column for
Add Row values:
Each row represents unique entries defined by the
cartodb_id column. Any cell without data entered will be shown as null.
Double-click in a row to add a value. For this example, enter the company location of
201 Moore Street, Brooklyn, NY 11206 in each of the respective columns.
Since certain map options are rendered based on the column data type, it is a good practice to confirm that the correct data type is assigned to the column.
Select Change data type from the column name context menu and select from the available options. (Options may vary, depending on your data).
For this example, keep the default String data type for all columns.
Now that we have confirmed that the column data type is correct, let's create a map from the dataset.
Click CREATE MAP to create a map directly from the dataset.
The connected dataset appears as the first map layer in Builder. Notice that there is no geometry since
the_geom column of our dataset contains null values. No problem! We can georeference our data to convert text to geometries.
By default, CARTO stores geospatial data using
the_geom column. This column displays the latitude and longitude in a single projection, using the WGS84 cartographic method. For this example, let's visualize location data by using the
zip_code column to georeference postal code points.
Click on the tech co map layer.
The STYLE tab indicates that there is no geometry data and provides a shortcut to georeference your data. If you switch to the Data View, you will notice that
the_geom column contains null values, even though there is an address, city, state, and zip code column.
The ANALYSIS tab opens and Georeference is automatically selected.
Change the georeference TYPE to Postal Codes and apply the following parameters:
zip_codecolumn from our dataset.
If you check the Data View, you will notice that
the_geom indicates the geometry is a polygon.
Suppose you want to edit data and add another row, you can access your dataset directly from Builder.
When the tech co map layer is selected, the name of the connected dataset appears underneath the layer name as a link.
Click on the
The connected dataset opens in a new window, enabling you to add rows and columns.
Any changes applied to your dataset are automatically reflected in your map. For example, if I add a row of data, the next time I refresh the map in Builder, the analysis will rerun since my dataset was updated!
We would love to hear from you! Was it easy to understand? Do you need more information? Let us know.