Data Sources

Add data from files or external sources, then chat with Plotly Studio to query and transform it to build your app.

Note

The data source chat interface is available for projects created in Plotly Studio version 0.0.46 and later. As of version 0.0.52, you can migrate projects created using the legacy data module when you open them.

Adding data

To get started, select + New project from the Projects page.

New project button

You can upload a file directly or use the chat to connect to an external data source.

Choose a data source

Uploading a file or using sample data

Drag and drop a file into the chat or select the attach icon to upload a file (up to 200 MB). For structured data files like .csv, .tsv, .xlsx, and others that it can parse, Plotly Studio displays a preview.

Upload a file or use sample data

If you upload a file Plotly Studio can't parse as structured data (like .txt or .md), it will ask how you'd like to work with it, or you can tell it directly (for example, "Count the frequency of words in this file").

Once your data is loaded, you can query and transform it. See Querying and transforming data.

Tip

You can also ask the chat to generate sample data for your industry or use case (for example, "Create a sample dataset for a retail sales dashboard").

Connecting to external data sources

To connect to an external data source, for example, Snowflake, PostgreSQL, AWS S3, and more:

Request a connection in the chat by selecting one of the quick action buttons:

Or describe the data source you want to connect to. For example:
```
Connect to my PostgreSQL database
```
```
Connect to my S3 bucket
```
```
Fetch data from the GitHub API
```
See Example data prompts for more examples.

Tip

If you need to start over, for example to change the data source, select Reset Conversation () in the top right corner of the chat.
Select the Credentials tab, enter the required information for your data source, and select Save Credentials.

Note

When you add credentials, they are securely stored in your computer's keychain. When you publish your app, they are stored as secrets on Plotly Cloud or environment variables on Dash Enterprise, and used to connect to your data source when the app loads.

Tip

Some data sources support multiple authentication methods. If the credential fields don't match your setup, ask in the chat for a different method (e.g., "Connect using an API key" or "Connect using username and password").
After entering your credentials, Plotly Studio automatically switches to the Preview tab.
- If you requested a specific table or file, your data displays immediately.
- If not, you'll see a list of available tables, schemas, or files. Use the chat to specify which one to load:
```
Load the orders table from my database
```

Once you have the dataset you want to work with, you can query and transform it. See Querying and transforming data.

Tip

View the Code tab to see the Python code, or the Specification tab for a plain-language description of how your data is loaded.

Using data from multiple sources

You can add multiple files or connect to additional data sources and tell the chat how to combine them.

Use the attach icon in the chat to upload additional files, or ask the chat to connect to another source. Then tell the chat how to work with your data. Files don't need to be of the same type. For example, if you upload a CSV with survey results and a JSON file with the survey schema, you could ask:

Merge the survey results with the schema

Example data prompts

Connecting to a database:

Connect to my PostgreSQL database

Loading a specific table from a database:

Connect to my MySQL database
Show me the customers table

Loading data from cloud storage:

Connect to my S3 bucket and load the sales data CSV

Fetching data from an API:

Get daily high and low temperatures for New York for the past 30 days from the Open-Meteo API

Loading data from a public Google Sheet:

Load data from this Google Sheet (no API key required): https://docs.google.com/spreadsheets/d/your-sheet-id

Loading a file from a URL:

Load the CSV file from this URL: https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv

Combining files with identical schemas:

Combine the contents of both output_001.csv and output_002.csv into a single output. The schemas are identical between them.

Querying and transforming data

Once your data is loaded, you can query and transform it through natural language in the data sources chat. Some common tasks include filtering rows, creating calculated columns, cleaning data, and aggregating and grouping.

Here are some examples with the built-in dataset:

Filtering:

Show only shipments with defects

Filter to show only items from the Osaka factory

Show shipments created in June 2022

Creating calculated columns:

Add a column for shipping days (difference between shipped_date and created_date)

Create a column for weight category: light if weight < 0.5, medium if 0.5-1.5, heavy if > 1.5

Add a column called 'delayed' showing if shipping took more than 30 days

Cleaning data:

Remove rows with missing delivery locations

Fill missing weight values with the average

Aggregating and grouping:

Count the number of shipments by factory location

Calculate average shipping days by delivery location

Tip

You can also use SQL queries directly to select and transform your data. For example: SELECT * FROM table_name LIMIT 20

Scheduling automatic data refresh

By default, data does not refresh automatically. You can configure your data to refresh on a schedule by asking in the chat, for example:

Refresh my data every hour

Update the data daily at 6am

Refresh the data every 30 minutes

Once your app is generated, you can manually refresh your data at any time by selecting the refresh button next to the Data Updated timestamp. This is available in the app preview in Plotly Studio and, if published, in the published app.

Note

Data can be refreshed at most once per minute.

Generating your app from a data source

As you query and transform your data, Plotly Studio saves versions as separate data sources. Use the dropdown to switch between versions.

Data source dropdown

When you're happy with your data, select Continue to start building your app.

Generate app button

This takes you to the App tab where you can select Generate charts to generate a first draft with six charts and supporting components based on your data. Alternatively, you can Create a new visualization from scratch or explore suggestions.

Editing an existing data source

You can return to the Data tab at any time to modify your data source, queries, or transformations. You can also add new files using the attach icon or ask the chat to connect to new external data sources. Once you've made your changes, select Update to apply them.

Editing your data source

Tip

The current and previously uploaded datasets are available in the dropdown in the upper right corner of the screen. The purple dot indicates which dataset is currently in use.

Troubleshooting

If you encounter connection issues, check the Logs tab for error messages. Common issues include:

Incorrect credentials - Go back to the Credentials tab to update your username, password, or access keys.
Network connectivity - Ensure your data source is accessible from your network.
Permission errors - Confirm your credentials have the necessary permissions.

Tip

If you encounter an issue, try asking in the chat for help. You can provide the error logs from the Logs tab, or ask the chat for the next step to resolve the problem.